Innovationsin Food Analysis

Innovations in Food AnalysisTable of contentsTOC

CO

NTE

NTS

Welcome

Advances in LCndashMS for Food Analysis

Advances in GCndashMS for Food Analysis

Determination of Phenylurea Herbicidesin Tap Water and Soft Drink Samplesby HPLCndashUV and Solid-Phase Extraction

Data Handling amp Validation in Automated Detection of Food Toxicants Using Full Scan GCndashMS and LCndashMS

Video IntroductionLaura Bush

LC-MSFrancesco Cacciola

Paola Donato Marco Beccaria Paola Dugo and Luigi Mondello

GC-MSPeter Quinto Tranchida

Paola Dugo and Luigi Mondello

HPLCManpreet Kaur Ashok Kumar Malik

and Baldev Singh

Data HandlingHans Mol Arjen Lommen

Paul Zomer Henk van der KampMartijn van der Lee and Arjen Gerssen

INTR

OD

UC

TIO

NWelcome

1

Advances in LCndashMS for Food Analysis

By Francesco Cacciola Paola Donato Marco Beccaria Paola Dugo and Luigi Mondello

LC-M

S

Food products are complex mixtures containing both organic and inorganic constituents The analysis of food products is generally directed towards the assessment of food safety and authenticity the control of a technological process the

determination of nutritional values and the detection of molecules with a possible beneficial or toxic effect on human health

Consequently one of the most stringent demands of food chemistry is directed towards the continuous improvement and development of powerful analytical techniques (1) to analyse the major and minor components of food samples

Liquid chromatographyndashmass spectrometry (LCndashMS) is an increasingly valuable tool in food analysis and has been widely applied to the analysis of many food products (2) Recent achievements in instrumentation and data processing have allowed LCndashMS to play a central role in food-related analysis However when dealing with the extreme complexity of many real-world samples one-dimensional chromatography may not provide sufficient analytical results As a consequence considerable research has recently been devoted to the development of multidimensional LC techniques (MDLC) with enhanced resolving power (3)

Within the wide range of hyphenated techniques liquid chromatographyndashmass spectrometry (LCndashMS) has recently emerged to a central role in different fields including food analysis In this review the most recent LCndashMS approaches are discussed as well as the technical requirements for linking an LC system to a mass spectrometer The advantages of on-line two-dimensional liquid chromatography (2DLC) in the ldquocomprehensiverdquo mode are also illustrated and selected applications for the analysis of common foodstuffs such as triacylglycerols carotenoids and polyphenols are described Finally future trends for LCndashMS in food analysis are reported

2

The purpose of this review is to acquaint the reader with some of the existing recent applications of LCndashMS-based techniques in food analysis Topics covered will include MS analysis of LC-amenable food compounds namely triacylglycerols carotenoids and polyphenols Technical sections will briefly introduce both theoretical and practical concerns of this hyphenated technique also in the multidimensional ldquocomprehensiverdquo mode (LCtimesLCndashMS)

Liquid ChromatographyndashMass Spectrometry (LCndashMS)The potential benefits arising from the hyphenation of LC to MS become clear if the limitations of the two independent techniques are considered and to what extent such a combination may alleviate them Peak overlapping sometimes precludes unambiguous identification even if disposing of reference standard material Even the most widely used ultra-violet (UV) detector can rarely provide unambiguous data on the separated analytes regardless of the degree of chromatographic separation obtained the situation is further complicated if quantitative determination is also desired

On the other hand mass spectral data are in many instances specific enough to support positive identification and in discriminating non-isobaric compounds providing the analyst with structural information in addition to the molecular weight

MS systems can also be used with non-UV absorbing analytes and can be operated in the full scan mode viz total ion current (TIC) or more specifically in tandem MS (MSndashMS) experiments or in the selected ion monitoring (SIM) mode SIM operation is preferred for the development of selective and sensitive quantitative assays while tandem MS data generated by using soft ionization techniques provide structural information which can help in the identification of unknown analytes

Mass spectrometry allows for quantitative determination to be performed accurately precisely and with high sensitivity (at the picogram level) using isotopically-labeled compounds as internal standards (ISs) Whenever the quantification or even the detection of a target trace component in SIM mode is hampered by the presence of high background ions with the same mz values constant neutral loss or precursor ion scanning techniques help in distinguishing the ions of interest from unspecific matrix components The so-called selected reaction monitoring (SRM) mode enhances selectivity and lowers detection limits therefore reducing sample consumption analysis times and the need for clean-up procedures (4)

Detection of Pharmaceuticals in Water by LC-MS-MS

SPOnSORED

Detection of Pharmaceuticals Personal CareProducts and Pesticides in Water Resources byAPCI-LC-MSMSLiza Viglino1 Khadija Aboulfald1 Michegravele Preacutevost2 and Seacutebastien Sauveacute1

1Department of Chemistry Universiteacute de Montreacuteal Montreacuteal QC Canada 2Deacutepartement of Civil Geological and MiningEngineering Eacutecole Polytechnique de Montreacuteal Montreacuteal QC Canada

IntroductionPharmaceuticals (PhACs) personal care productcompounds (PCPs) and endocrine disruptors (EDCs)such as pesticides detected in surface and drinking watersare an issue of increasing international attention due topotential environmental impacts12 These compounds aredistributed widely in surface waters from human andanimal urine as well as improper disposal posing apotential health concern to humans via the consumptionof drinking water This presents a major challenge towater treatment facilities

Collectively referred to as organic wastewatercontaminants (OWCs) the distribution of these emergingcontaminants near sewage treatment plants (STP) iscurrently an area of investigation in Canada andelsewhere34 More specifically some of these compoundshave been detected in most effluent-receiving rivers ofOntario and Queacutebec56 However it is not clear whethercontamination is localized to areas a few meters from STPdischarges or whether these compounds are distributedwidely in surface waters potentially contaminatingsources of drinking water

A research project at the University of MontrealrsquosChemistry Department and Civil Geological and MiningEngineering Department was undertaken to establish theoccurrence and identify the major sources of thesecompounds in drinking water intakes in surface waters inthe Montreal region The identification and quantificationof PhACs PCPs and EDCs is critical to determine theneed for advanced processes such as ozonation andadsorption in treatment upgrades

The establishment of occurrence data is challengingbecause of (1) the large number and chemical diversity ofthe compounds of interest (2) the need to quantify lowlevels in an organic matrix and (3) the complexity ofsample concentration techniques To address these issuesscientists traditionally use a solid phase extraction (SPE)method to concentrate the analytes and remove matrixcomponents

After extraction several different analytical techniquesmay perform the actual detection such as GC-MSMS andmore recently LC-MSMS78 Another analytical challengeresides in the different physicochemical characteristics andwide polarity range of organic compounds ndash makingsimultaneous preconcentration chromatographyseparation and determination difficult Analytical

methods capable of detecting multiple classes of emergingcontaminants would be very useful to any environmentalmonitoring program However up to now it has oftenbeen a necessity to employ a combination of multipleanalytical techniques in order to cover a wide range oftrace contaminants9 This can add significant costs toanalyses including equipment labor and timeinvestments

GoalsTo develop a simple method for the simultaneousdetermination of trace levels of compounds from a diversegroup of pharmaceuticals pesticides and personal careproducts using SPE and liquid chromatography-tandemmass spectrometry (LC-MSMS)

Determine which selected substances are present insignificant quantities in the water resources around theMontreal region

Materials and Method

Analyte selection

Compounds were selected from a list of the most-frequently encountered OWCs in Canada4-6 (Figure 1)

Sample collection

Raw water samples were taken from the Mille Iles desPrairies and St-Laurent rivers Three samples werecollected at the same time from each river in pre-cleanedfour-liter glass bottles and kept on ice while beingtransported to the laboratory These water sources varywidely due to wastewater contamination and seweroverflow discharges

All samples were acidified with H2SO4 for samplepreservation and stored in the dark at 4 degC Immediatelybefore analysis samples were filtered using 07 microm pore-size fiberglass filters followed by 045 microm pore size mixed-cellulose membranes (Millipore MA USA) Samples wereextracted within 24 hours of collection

Key Words

bull TSQ QuantumUltra

bull Water Analysis

bull Solid PhaseExtraction

ApplicationNote 466httpwwwlearnpharmascience

comtablet-appsfood-issue1article1detection_pharma_ in_waterpdf

Innovations in Food AnalysisTable of contentsTOC

CO

NTE

NTS

Welcome

Advances in LCndashMS for Food Analysis

Advances in GCndashMS for Food Analysis

Determination of Phenylurea Herbicidesin Tap Water and Soft Drink Samplesby HPLCndashUV and Solid-Phase Extraction

Data Handling amp Validation in Automated Detection of Food Toxicants Using Full Scan GCndashMS and LCndashMS

Video IntroductionLaura Bush

LC-MSFrancesco Cacciola

Paola Donato Marco Beccaria Paola Dugo and Luigi Mondello

GC-MSPeter Quinto Tranchida

Paola Dugo and Luigi Mondello

HPLCManpreet Kaur Ashok Kumar Malik

and Baldev Singh

Data HandlingHans Mol Arjen Lommen

Paul Zomer Henk van der KampMartijn van der Lee and Arjen Gerssen

INTR

OD

UC

TIO

NWelcome

1

Advances in LCndashMS for Food Analysis

By Francesco Cacciola Paola Donato Marco Beccaria Paola Dugo and Luigi Mondello

LC-M

S

Food products are complex mixtures containing both organic and inorganic constituents The analysis of food products is generally directed towards the assessment of food safety and authenticity the control of a technological process the

determination of nutritional values and the detection of molecules with a possible beneficial or toxic effect on human health

Consequently one of the most stringent demands of food chemistry is directed towards the continuous improvement and development of powerful analytical techniques (1) to analyse the major and minor components of food samples

Liquid chromatographyndashmass spectrometry (LCndashMS) is an increasingly valuable tool in food analysis and has been widely applied to the analysis of many food products (2) Recent achievements in instrumentation and data processing have allowed LCndashMS to play a central role in food-related analysis However when dealing with the extreme complexity of many real-world samples one-dimensional chromatography may not provide sufficient analytical results As a consequence considerable research has recently been devoted to the development of multidimensional LC techniques (MDLC) with enhanced resolving power (3)

Within the wide range of hyphenated techniques liquid chromatographyndashmass spectrometry (LCndashMS) has recently emerged to a central role in different fields including food analysis In this review the most recent LCndashMS approaches are discussed as well as the technical requirements for linking an LC system to a mass spectrometer The advantages of on-line two-dimensional liquid chromatography (2DLC) in the ldquocomprehensiverdquo mode are also illustrated and selected applications for the analysis of common foodstuffs such as triacylglycerols carotenoids and polyphenols are described Finally future trends for LCndashMS in food analysis are reported

2

The purpose of this review is to acquaint the reader with some of the existing recent applications of LCndashMS-based techniques in food analysis Topics covered will include MS analysis of LC-amenable food compounds namely triacylglycerols carotenoids and polyphenols Technical sections will briefly introduce both theoretical and practical concerns of this hyphenated technique also in the multidimensional ldquocomprehensiverdquo mode (LCtimesLCndashMS)

Liquid ChromatographyndashMass Spectrometry (LCndashMS)The potential benefits arising from the hyphenation of LC to MS become clear if the limitations of the two independent techniques are considered and to what extent such a combination may alleviate them Peak overlapping sometimes precludes unambiguous identification even if disposing of reference standard material Even the most widely used ultra-violet (UV) detector can rarely provide unambiguous data on the separated analytes regardless of the degree of chromatographic separation obtained the situation is further complicated if quantitative determination is also desired

On the other hand mass spectral data are in many instances specific enough to support positive identification and in discriminating non-isobaric compounds providing the analyst with structural information in addition to the molecular weight

MS systems can also be used with non-UV absorbing analytes and can be operated in the full scan mode viz total ion current (TIC) or more specifically in tandem MS (MSndashMS) experiments or in the selected ion monitoring (SIM) mode SIM operation is preferred for the development of selective and sensitive quantitative assays while tandem MS data generated by using soft ionization techniques provide structural information which can help in the identification of unknown analytes

Mass spectrometry allows for quantitative determination to be performed accurately precisely and with high sensitivity (at the picogram level) using isotopically-labeled compounds as internal standards (ISs) Whenever the quantification or even the detection of a target trace component in SIM mode is hampered by the presence of high background ions with the same mz values constant neutral loss or precursor ion scanning techniques help in distinguishing the ions of interest from unspecific matrix components The so-called selected reaction monitoring (SRM) mode enhances selectivity and lowers detection limits therefore reducing sample consumption analysis times and the need for clean-up procedures (4)

Detection of Pharmaceuticals in Water by LC-MS-MS

SPOnSORED

Detection of Pharmaceuticals Personal CareProducts and Pesticides in Water Resources byAPCI-LC-MSMSLiza Viglino1 Khadija Aboulfald1 Michegravele Preacutevost2 and Seacutebastien Sauveacute1

1Department of Chemistry Universiteacute de Montreacuteal Montreacuteal QC Canada 2Deacutepartement of Civil Geological and MiningEngineering Eacutecole Polytechnique de Montreacuteal Montreacuteal QC Canada

IntroductionPharmaceuticals (PhACs) personal care productcompounds (PCPs) and endocrine disruptors (EDCs)such as pesticides detected in surface and drinking watersare an issue of increasing international attention due topotential environmental impacts12 These compounds aredistributed widely in surface waters from human andanimal urine as well as improper disposal posing apotential health concern to humans via the consumptionof drinking water This presents a major challenge towater treatment facilities

Collectively referred to as organic wastewatercontaminants (OWCs) the distribution of these emergingcontaminants near sewage treatment plants (STP) iscurrently an area of investigation in Canada andelsewhere34 More specifically some of these compoundshave been detected in most effluent-receiving rivers ofOntario and Queacutebec56 However it is not clear whethercontamination is localized to areas a few meters from STPdischarges or whether these compounds are distributedwidely in surface waters potentially contaminatingsources of drinking water

A research project at the University of MontrealrsquosChemistry Department and Civil Geological and MiningEngineering Department was undertaken to establish theoccurrence and identify the major sources of thesecompounds in drinking water intakes in surface waters inthe Montreal region The identification and quantificationof PhACs PCPs and EDCs is critical to determine theneed for advanced processes such as ozonation andadsorption in treatment upgrades

The establishment of occurrence data is challengingbecause of (1) the large number and chemical diversity ofthe compounds of interest (2) the need to quantify lowlevels in an organic matrix and (3) the complexity ofsample concentration techniques To address these issuesscientists traditionally use a solid phase extraction (SPE)method to concentrate the analytes and remove matrixcomponents

After extraction several different analytical techniquesmay perform the actual detection such as GC-MSMS andmore recently LC-MSMS78 Another analytical challengeresides in the different physicochemical characteristics andwide polarity range of organic compounds ndash makingsimultaneous preconcentration chromatographyseparation and determination difficult Analytical

methods capable of detecting multiple classes of emergingcontaminants would be very useful to any environmentalmonitoring program However up to now it has oftenbeen a necessity to employ a combination of multipleanalytical techniques in order to cover a wide range oftrace contaminants9 This can add significant costs toanalyses including equipment labor and timeinvestments

GoalsTo develop a simple method for the simultaneousdetermination of trace levels of compounds from a diversegroup of pharmaceuticals pesticides and personal careproducts using SPE and liquid chromatography-tandemmass spectrometry (LC-MSMS)

Determine which selected substances are present insignificant quantities in the water resources around theMontreal region

Materials and Method

Analyte selection

Compounds were selected from a list of the most-frequently encountered OWCs in Canada4-6 (Figure 1)

Sample collection

Raw water samples were taken from the Mille Iles desPrairies and St-Laurent rivers Three samples werecollected at the same time from each river in pre-cleanedfour-liter glass bottles and kept on ice while beingtransported to the laboratory These water sources varywidely due to wastewater contamination and seweroverflow discharges

All samples were acidified with H2SO4 for samplepreservation and stored in the dark at 4 degC Immediatelybefore analysis samples were filtered using 07 microm pore-size fiberglass filters followed by 045 microm pore size mixed-cellulose membranes (Millipore MA USA) Samples wereextracted within 24 hours of collection

Key Words

bull TSQ QuantumUltra

bull Water Analysis

bull Solid PhaseExtraction

ApplicationNote 466httpwwwlearnpharmascience

comtablet-appsfood-issue1article1detection_pharma_ in_waterpdf

INTR

OD

UC

TIO

NWelcome

1

Advances in LCndashMS for Food Analysis

By Francesco Cacciola Paola Donato Marco Beccaria Paola Dugo and Luigi Mondello

LC-M

S

Food products are complex mixtures containing both organic and inorganic constituents The analysis of food products is generally directed towards the assessment of food safety and authenticity the control of a technological process the

determination of nutritional values and the detection of molecules with a possible beneficial or toxic effect on human health

Consequently one of the most stringent demands of food chemistry is directed towards the continuous improvement and development of powerful analytical techniques (1) to analyse the major and minor components of food samples

Liquid chromatographyndashmass spectrometry (LCndashMS) is an increasingly valuable tool in food analysis and has been widely applied to the analysis of many food products (2) Recent achievements in instrumentation and data processing have allowed LCndashMS to play a central role in food-related analysis However when dealing with the extreme complexity of many real-world samples one-dimensional chromatography may not provide sufficient analytical results As a consequence considerable research has recently been devoted to the development of multidimensional LC techniques (MDLC) with enhanced resolving power (3)

Within the wide range of hyphenated techniques liquid chromatographyndashmass spectrometry (LCndashMS) has recently emerged to a central role in different fields including food analysis In this review the most recent LCndashMS approaches are discussed as well as the technical requirements for linking an LC system to a mass spectrometer The advantages of on-line two-dimensional liquid chromatography (2DLC) in the ldquocomprehensiverdquo mode are also illustrated and selected applications for the analysis of common foodstuffs such as triacylglycerols carotenoids and polyphenols are described Finally future trends for LCndashMS in food analysis are reported

2

The purpose of this review is to acquaint the reader with some of the existing recent applications of LCndashMS-based techniques in food analysis Topics covered will include MS analysis of LC-amenable food compounds namely triacylglycerols carotenoids and polyphenols Technical sections will briefly introduce both theoretical and practical concerns of this hyphenated technique also in the multidimensional ldquocomprehensiverdquo mode (LCtimesLCndashMS)

Liquid ChromatographyndashMass Spectrometry (LCndashMS)The potential benefits arising from the hyphenation of LC to MS become clear if the limitations of the two independent techniques are considered and to what extent such a combination may alleviate them Peak overlapping sometimes precludes unambiguous identification even if disposing of reference standard material Even the most widely used ultra-violet (UV) detector can rarely provide unambiguous data on the separated analytes regardless of the degree of chromatographic separation obtained the situation is further complicated if quantitative determination is also desired

On the other hand mass spectral data are in many instances specific enough to support positive identification and in discriminating non-isobaric compounds providing the analyst with structural information in addition to the molecular weight

MS systems can also be used with non-UV absorbing analytes and can be operated in the full scan mode viz total ion current (TIC) or more specifically in tandem MS (MSndashMS) experiments or in the selected ion monitoring (SIM) mode SIM operation is preferred for the development of selective and sensitive quantitative assays while tandem MS data generated by using soft ionization techniques provide structural information which can help in the identification of unknown analytes

Mass spectrometry allows for quantitative determination to be performed accurately precisely and with high sensitivity (at the picogram level) using isotopically-labeled compounds as internal standards (ISs) Whenever the quantification or even the detection of a target trace component in SIM mode is hampered by the presence of high background ions with the same mz values constant neutral loss or precursor ion scanning techniques help in distinguishing the ions of interest from unspecific matrix components The so-called selected reaction monitoring (SRM) mode enhances selectivity and lowers detection limits therefore reducing sample consumption analysis times and the need for clean-up procedures (4)

Detection of Pharmaceuticals in Water by LC-MS-MS

SPOnSORED

Detection of Pharmaceuticals Personal CareProducts and Pesticides in Water Resources byAPCI-LC-MSMSLiza Viglino1 Khadija Aboulfald1 Michegravele Preacutevost2 and Seacutebastien Sauveacute1

1Department of Chemistry Universiteacute de Montreacuteal Montreacuteal QC Canada 2Deacutepartement of Civil Geological and MiningEngineering Eacutecole Polytechnique de Montreacuteal Montreacuteal QC Canada

IntroductionPharmaceuticals (PhACs) personal care productcompounds (PCPs) and endocrine disruptors (EDCs)such as pesticides detected in surface and drinking watersare an issue of increasing international attention due topotential environmental impacts12 These compounds aredistributed widely in surface waters from human andanimal urine as well as improper disposal posing apotential health concern to humans via the consumptionof drinking water This presents a major challenge towater treatment facilities

Collectively referred to as organic wastewatercontaminants (OWCs) the distribution of these emergingcontaminants near sewage treatment plants (STP) iscurrently an area of investigation in Canada andelsewhere34 More specifically some of these compoundshave been detected in most effluent-receiving rivers ofOntario and Queacutebec56 However it is not clear whethercontamination is localized to areas a few meters from STPdischarges or whether these compounds are distributedwidely in surface waters potentially contaminatingsources of drinking water

A research project at the University of MontrealrsquosChemistry Department and Civil Geological and MiningEngineering Department was undertaken to establish theoccurrence and identify the major sources of thesecompounds in drinking water intakes in surface waters inthe Montreal region The identification and quantificationof PhACs PCPs and EDCs is critical to determine theneed for advanced processes such as ozonation andadsorption in treatment upgrades

The establishment of occurrence data is challengingbecause of (1) the large number and chemical diversity ofthe compounds of interest (2) the need to quantify lowlevels in an organic matrix and (3) the complexity ofsample concentration techniques To address these issuesscientists traditionally use a solid phase extraction (SPE)method to concentrate the analytes and remove matrixcomponents

After extraction several different analytical techniquesmay perform the actual detection such as GC-MSMS andmore recently LC-MSMS78 Another analytical challengeresides in the different physicochemical characteristics andwide polarity range of organic compounds ndash makingsimultaneous preconcentration chromatographyseparation and determination difficult Analytical

methods capable of detecting multiple classes of emergingcontaminants would be very useful to any environmentalmonitoring program However up to now it has oftenbeen a necessity to employ a combination of multipleanalytical techniques in order to cover a wide range oftrace contaminants9 This can add significant costs toanalyses including equipment labor and timeinvestments

GoalsTo develop a simple method for the simultaneousdetermination of trace levels of compounds from a diversegroup of pharmaceuticals pesticides and personal careproducts using SPE and liquid chromatography-tandemmass spectrometry (LC-MSMS)

Determine which selected substances are present insignificant quantities in the water resources around theMontreal region

Materials and Method

Analyte selection

Compounds were selected from a list of the most-frequently encountered OWCs in Canada4-6 (Figure 1)

Sample collection

Raw water samples were taken from the Mille Iles desPrairies and St-Laurent rivers Three samples werecollected at the same time from each river in pre-cleanedfour-liter glass bottles and kept on ice while beingtransported to the laboratory These water sources varywidely due to wastewater contamination and seweroverflow discharges

All samples were acidified with H2SO4 for samplepreservation and stored in the dark at 4 degC Immediatelybefore analysis samples were filtered using 07 microm pore-size fiberglass filters followed by 045 microm pore size mixed-cellulose membranes (Millipore MA USA) Samples wereextracted within 24 hours of collection

Key Words

bull TSQ QuantumUltra

bull Water Analysis

bull Solid PhaseExtraction

ApplicationNote 466httpwwwlearnpharmascience

comtablet-appsfood-issue1article1detection_pharma_ in_waterpdf

1

Advances in LCndashMS for Food Analysis

By Francesco Cacciola Paola Donato Marco Beccaria Paola Dugo and Luigi Mondello

LC-M

S

Food products are complex mixtures containing both organic and inorganic constituents The analysis of food products is generally directed towards the assessment of food safety and authenticity the control of a technological process the

determination of nutritional values and the detection of molecules with a possible beneficial or toxic effect on human health

Consequently one of the most stringent demands of food chemistry is directed towards the continuous improvement and development of powerful analytical techniques (1) to analyse the major and minor components of food samples

Liquid chromatographyndashmass spectrometry (LCndashMS) is an increasingly valuable tool in food analysis and has been widely applied to the analysis of many food products (2) Recent achievements in instrumentation and data processing have allowed LCndashMS to play a central role in food-related analysis However when dealing with the extreme complexity of many real-world samples one-dimensional chromatography may not provide sufficient analytical results As a consequence considerable research has recently been devoted to the development of multidimensional LC techniques (MDLC) with enhanced resolving power (3)

Within the wide range of hyphenated techniques liquid chromatographyndashmass spectrometry (LCndashMS) has recently emerged to a central role in different fields including food analysis In this review the most recent LCndashMS approaches are discussed as well as the technical requirements for linking an LC system to a mass spectrometer The advantages of on-line two-dimensional liquid chromatography (2DLC) in the ldquocomprehensiverdquo mode are also illustrated and selected applications for the analysis of common foodstuffs such as triacylglycerols carotenoids and polyphenols are described Finally future trends for LCndashMS in food analysis are reported

2

The purpose of this review is to acquaint the reader with some of the existing recent applications of LCndashMS-based techniques in food analysis Topics covered will include MS analysis of LC-amenable food compounds namely triacylglycerols carotenoids and polyphenols Technical sections will briefly introduce both theoretical and practical concerns of this hyphenated technique also in the multidimensional ldquocomprehensiverdquo mode (LCtimesLCndashMS)

Liquid ChromatographyndashMass Spectrometry (LCndashMS)The potential benefits arising from the hyphenation of LC to MS become clear if the limitations of the two independent techniques are considered and to what extent such a combination may alleviate them Peak overlapping sometimes precludes unambiguous identification even if disposing of reference standard material Even the most widely used ultra-violet (UV) detector can rarely provide unambiguous data on the separated analytes regardless of the degree of chromatographic separation obtained the situation is further complicated if quantitative determination is also desired

On the other hand mass spectral data are in many instances specific enough to support positive identification and in discriminating non-isobaric compounds providing the analyst with structural information in addition to the molecular weight

MS systems can also be used with non-UV absorbing analytes and can be operated in the full scan mode viz total ion current (TIC) or more specifically in tandem MS (MSndashMS) experiments or in the selected ion monitoring (SIM) mode SIM operation is preferred for the development of selective and sensitive quantitative assays while tandem MS data generated by using soft ionization techniques provide structural information which can help in the identification of unknown analytes

Mass spectrometry allows for quantitative determination to be performed accurately precisely and with high sensitivity (at the picogram level) using isotopically-labeled compounds as internal standards (ISs) Whenever the quantification or even the detection of a target trace component in SIM mode is hampered by the presence of high background ions with the same mz values constant neutral loss or precursor ion scanning techniques help in distinguishing the ions of interest from unspecific matrix components The so-called selected reaction monitoring (SRM) mode enhances selectivity and lowers detection limits therefore reducing sample consumption analysis times and the need for clean-up procedures (4)

Detection of Pharmaceuticals in Water by LC-MS-MS

SPOnSORED

Detection of Pharmaceuticals Personal CareProducts and Pesticides in Water Resources byAPCI-LC-MSMSLiza Viglino1 Khadija Aboulfald1 Michegravele Preacutevost2 and Seacutebastien Sauveacute1

1Department of Chemistry Universiteacute de Montreacuteal Montreacuteal QC Canada 2Deacutepartement of Civil Geological and MiningEngineering Eacutecole Polytechnique de Montreacuteal Montreacuteal QC Canada

IntroductionPharmaceuticals (PhACs) personal care productcompounds (PCPs) and endocrine disruptors (EDCs)such as pesticides detected in surface and drinking watersare an issue of increasing international attention due topotential environmental impacts12 These compounds aredistributed widely in surface waters from human andanimal urine as well as improper disposal posing apotential health concern to humans via the consumptionof drinking water This presents a major challenge towater treatment facilities

Collectively referred to as organic wastewatercontaminants (OWCs) the distribution of these emergingcontaminants near sewage treatment plants (STP) iscurrently an area of investigation in Canada andelsewhere34 More specifically some of these compoundshave been detected in most effluent-receiving rivers ofOntario and Queacutebec56 However it is not clear whethercontamination is localized to areas a few meters from STPdischarges or whether these compounds are distributedwidely in surface waters potentially contaminatingsources of drinking water

A research project at the University of MontrealrsquosChemistry Department and Civil Geological and MiningEngineering Department was undertaken to establish theoccurrence and identify the major sources of thesecompounds in drinking water intakes in surface waters inthe Montreal region The identification and quantificationof PhACs PCPs and EDCs is critical to determine theneed for advanced processes such as ozonation andadsorption in treatment upgrades

The establishment of occurrence data is challengingbecause of (1) the large number and chemical diversity ofthe compounds of interest (2) the need to quantify lowlevels in an organic matrix and (3) the complexity ofsample concentration techniques To address these issuesscientists traditionally use a solid phase extraction (SPE)method to concentrate the analytes and remove matrixcomponents

After extraction several different analytical techniquesmay perform the actual detection such as GC-MSMS andmore recently LC-MSMS78 Another analytical challengeresides in the different physicochemical characteristics andwide polarity range of organic compounds ndash makingsimultaneous preconcentration chromatographyseparation and determination difficult Analytical

methods capable of detecting multiple classes of emergingcontaminants would be very useful to any environmentalmonitoring program However up to now it has oftenbeen a necessity to employ a combination of multipleanalytical techniques in order to cover a wide range oftrace contaminants9 This can add significant costs toanalyses including equipment labor and timeinvestments

GoalsTo develop a simple method for the simultaneousdetermination of trace levels of compounds from a diversegroup of pharmaceuticals pesticides and personal careproducts using SPE and liquid chromatography-tandemmass spectrometry (LC-MSMS)

Determine which selected substances are present insignificant quantities in the water resources around theMontreal region

Materials and Method

Analyte selection

Compounds were selected from a list of the most-frequently encountered OWCs in Canada4-6 (Figure 1)

Sample collection

Raw water samples were taken from the Mille Iles desPrairies and St-Laurent rivers Three samples werecollected at the same time from each river in pre-cleanedfour-liter glass bottles and kept on ice while beingtransported to the laboratory These water sources varywidely due to wastewater contamination and seweroverflow discharges

All samples were acidified with H2SO4 for samplepreservation and stored in the dark at 4 degC Immediatelybefore analysis samples were filtered using 07 microm pore-size fiberglass filters followed by 045 microm pore size mixed-cellulose membranes (Millipore MA USA) Samples wereextracted within 24 hours of collection

Key Words

bull TSQ QuantumUltra

bull Water Analysis

bull Solid PhaseExtraction

ApplicationNote 466httpwwwlearnpharmascience

comtablet-appsfood-issue1article1detection_pharma_ in_waterpdf

2

The purpose of this review is to acquaint the reader with some of the existing recent applications of LCndashMS-based techniques in food analysis Topics covered will include MS analysis of LC-amenable food compounds namely triacylglycerols carotenoids and polyphenols Technical sections will briefly introduce both theoretical and practical concerns of this hyphenated technique also in the multidimensional ldquocomprehensiverdquo mode (LCtimesLCndashMS)

Liquid ChromatographyndashMass Spectrometry (LCndashMS)The potential benefits arising from the hyphenation of LC to MS become clear if the limitations of the two independent techniques are considered and to what extent such a combination may alleviate them Peak overlapping sometimes precludes unambiguous identification even if disposing of reference standard material Even the most widely used ultra-violet (UV) detector can rarely provide unambiguous data on the separated analytes regardless of the degree of chromatographic separation obtained the situation is further complicated if quantitative determination is also desired

On the other hand mass spectral data are in many instances specific enough to support positive identification and in discriminating non-isobaric compounds providing the analyst with structural information in addition to the molecular weight

MS systems can also be used with non-UV absorbing analytes and can be operated in the full scan mode viz total ion current (TIC) or more specifically in tandem MS (MSndashMS) experiments or in the selected ion monitoring (SIM) mode SIM operation is preferred for the development of selective and sensitive quantitative assays while tandem MS data generated by using soft ionization techniques provide structural information which can help in the identification of unknown analytes

Mass spectrometry allows for quantitative determination to be performed accurately precisely and with high sensitivity (at the picogram level) using isotopically-labeled compounds as internal standards (ISs) Whenever the quantification or even the detection of a target trace component in SIM mode is hampered by the presence of high background ions with the same mz values constant neutral loss or precursor ion scanning techniques help in distinguishing the ions of interest from unspecific matrix components The so-called selected reaction monitoring (SRM) mode enhances selectivity and lowers detection limits therefore reducing sample consumption analysis times and the need for clean-up procedures (4)

Detection of Pharmaceuticals in Water by LC-MS-MS

SPOnSORED

Detection of Pharmaceuticals Personal CareProducts and Pesticides in Water Resources byAPCI-LC-MSMSLiza Viglino1 Khadija Aboulfald1 Michegravele Preacutevost2 and Seacutebastien Sauveacute1

1Department of Chemistry Universiteacute de Montreacuteal Montreacuteal QC Canada 2Deacutepartement of Civil Geological and MiningEngineering Eacutecole Polytechnique de Montreacuteal Montreacuteal QC Canada

IntroductionPharmaceuticals (PhACs) personal care productcompounds (PCPs) and endocrine disruptors (EDCs)such as pesticides detected in surface and drinking watersare an issue of increasing international attention due topotential environmental impacts12 These compounds aredistributed widely in surface waters from human andanimal urine as well as improper disposal posing apotential health concern to humans via the consumptionof drinking water This presents a major challenge towater treatment facilities

Collectively referred to as organic wastewatercontaminants (OWCs) the distribution of these emergingcontaminants near sewage treatment plants (STP) iscurrently an area of investigation in Canada andelsewhere34 More specifically some of these compoundshave been detected in most effluent-receiving rivers ofOntario and Queacutebec56 However it is not clear whethercontamination is localized to areas a few meters from STPdischarges or whether these compounds are distributedwidely in surface waters potentially contaminatingsources of drinking water

A research project at the University of MontrealrsquosChemistry Department and Civil Geological and MiningEngineering Department was undertaken to establish theoccurrence and identify the major sources of thesecompounds in drinking water intakes in surface waters inthe Montreal region The identification and quantificationof PhACs PCPs and EDCs is critical to determine theneed for advanced processes such as ozonation andadsorption in treatment upgrades

The establishment of occurrence data is challengingbecause of (1) the large number and chemical diversity ofthe compounds of interest (2) the need to quantify lowlevels in an organic matrix and (3) the complexity ofsample concentration techniques To address these issuesscientists traditionally use a solid phase extraction (SPE)method to concentrate the analytes and remove matrixcomponents

After extraction several different analytical techniquesmay perform the actual detection such as GC-MSMS andmore recently LC-MSMS78 Another analytical challengeresides in the different physicochemical characteristics andwide polarity range of organic compounds ndash makingsimultaneous preconcentration chromatographyseparation and determination difficult Analytical

methods capable of detecting multiple classes of emergingcontaminants would be very useful to any environmentalmonitoring program However up to now it has oftenbeen a necessity to employ a combination of multipleanalytical techniques in order to cover a wide range oftrace contaminants9 This can add significant costs toanalyses including equipment labor and timeinvestments

GoalsTo develop a simple method for the simultaneousdetermination of trace levels of compounds from a diversegroup of pharmaceuticals pesticides and personal careproducts using SPE and liquid chromatography-tandemmass spectrometry (LC-MSMS)

Determine which selected substances are present insignificant quantities in the water resources around theMontreal region

Materials and Method

Analyte selection

Compounds were selected from a list of the most-frequently encountered OWCs in Canada4-6 (Figure 1)

Sample collection

Raw water samples were taken from the Mille Iles desPrairies and St-Laurent rivers Three samples werecollected at the same time from each river in pre-cleanedfour-liter glass bottles and kept on ice while beingtransported to the laboratory These water sources varywidely due to wastewater contamination and seweroverflow discharges

All samples were acidified with H2SO4 for samplepreservation and stored in the dark at 4 degC Immediatelybefore analysis samples were filtered using 07 microm pore-size fiberglass filters followed by 045 microm pore size mixed-cellulose membranes (Millipore MA USA) Samples wereextracted within 24 hours of collection

Key Words

bull TSQ QuantumUltra

bull Water Analysis

bull Solid PhaseExtraction

ApplicationNote 466httpwwwlearnpharmascience

comtablet-appsfood-issue1article1detection_pharma_ in_waterpdf

3

LCndashMS plays a central role in both basic and applied research because of significant advances in interface technology and ionization techniques and it also has a broad range of applicability and high sensitivity for the analysis of high-polar and high-molecular mass compounds

In addition the replacement of the older sector machines with ion trapping instruments (IT) quadrupoles (Q) time-of-flight (ToF) systems and a variety of hybrid instruments characterized by high resolution enhanced sensitivity as well as increased mass accuracy over a wide dynamic range Among these are the ion mobility time-of-flight (IM-ToF) quadrupole ToF (Q-ToF) ion trap-ToF (IT-ToF) and linear ion trap-Fourier transform ion cyclotron resonance (FT-ICR)

Ultimate generation single-quadrupoles allow for high speed scanning (up to 15000 amusec) and ultrafast polarity switching the small size and the possibility to perform tandem MS make them ideal for benchtop LCndashMS On the other hand ToF instruments present a number of advantages high speed (up to 20000 Hz) high resolution (using a reflectron) virtually no limit on mass range femtogram-level sensitivity sub-ppm mass accuracy improved in-spectrum dynamic range without loss in sensitivity high mass resolution and feasibility to use as a second stage in tandem MS experiments in combination with either an IT-ToF or a Q-ToF

From the quantitative standpoint the linear dynamic range depends on the type of source employed electrospray ionization (ESI) is characterized by a dynamic range over 2ndash3 orders of magnitude and currently represents the most common choice for routine LCndashMS analysis However atmospheric-pressure chemical ionization (APCI) and atmospheric pressure photo-ionization (APPI) techniques offer greater sensitivity and a wider dynamic range (4ndash5 orders of magnitude) though their use for large bio-molecules is precluded (5) Liquid chromatography nano-electrospray ionization (LCndashnano-ESI) operation has become feasible in recent years (6) boosting the sensitivity of LCndashMS techniques The newly developed interfaces are suitable for linkage with capillary-type LC columns operated in the microL-to-nL flow range current configurations using gold-coated capillaries or automated chips allow analyte detection down to the femtomole level

LCndashMS Applications for Triacylglycerol AnalysisPlant oils animal fats and fish oils are natural sources of triacylglycerols (TAGs) in the human diet Since they may contain hundreds of different TAGs which are characterized by the total carbon number (Cn) the number position and configuration (cistrans) of double bonds (DBs) in fatty acids (FA) acyl chains and the stereospecific position of FAs on the glycerol skeleton (sn-1 2 or 3) tremendously complex mixtures may arise (7) Two chromatographic techniques are more widespread in the analysis of TAGs in natural samples namely non-aqueous reversed-phase liquid chromatography (nARP-LC) and silver-ion chromatography (SIC)

4

As shown in Figure 1 in nARP-LC TAG retention times increase with the increasing partition number (Pn) (8) In SIC TAG separation is governed mainly by the number of DBs Double bond positional isomers cis-trans-isomers or regioisomers (R1R1R2 vs R1R2R1) can be also separated (9) APCI-MS coupled to LC represents the most powerful tool for TAG identification because of the full compatibility with common nARP-LC conditions easy ionization of non-polar TAGs and the attainment of both protonated molecules [M+H]+ and fragment ions [M+HminusRiCOOH]+ in addition ESI or matrix-assisted laser desorptionionization (MALDI)

have also been used (1011) LCndashMS offers possibilities for a better determination of minor compounds whose signals might otherwise be suppressed in terms of mass spectrometric analysers TAG analysis has been developed and implemented successfully with tandem quadrupoles and linear ion traps Tandem mass spectrometry (MSndashMS) has proved to be an essential tool for unambiguous structural characterization for mixtures of isobaric species yielding product ions from both positive and negative fragmentation processes Later on the triple quadrupole mass spectrometer was found to be well suited for TAG analysis through MSndashMS operation including product ion scanning and selected reaction monitoring (SRM) High resolution mass analysis of molecular ion species and product ions after collision-induced dissociation (CID) became routinely possible with the second generation ToF analysers FT-ICR and orbitrap mass spectrometer Hybrid mass spectrometers such as the Q-ToF afford superior spectral resolution and mass accuracy also overcoming duty cycle issues typically associated with other scanning instruments the so-called MSE acquisition mode actually allows for many precursor and neutral loss acquisitions within a single experimental run From the LC standpoint recent advances in column technology (sub-2 microm and shell-particles) and hardware (allowing operating pressures up to 15000 psi) have arrived to meet the expected performance in terms of resolution speed and sensitivity with respect to conventional LC analysis UHPLCndashMS platform combining ultra high performance liquid chromatography with an orthogonal-accelerated time-of-flight (oa-ToF) spectrometer offer high-throughput sample analysis providing narrow chromatographic peaks (lt 3 sec) with good ion statistics from accurate mass measurement (lt 2 ppm) (12)

LCndashMS Applications for Carotenoid Analysis Carotenoids are a class of naturally occurring compounds in foods and food products usually characterized by a C40-tetraterpenoid structure with a centrally located extended conjugated double bond system They are usually divided into two groups hydrocarbon (carotenes) and oxygenated carotenoids (xanthophylls) The latter can be found in either a

free form or in a more stable fatty acid esterified form

Figure 1 NARP-LCndashAPCI-MS analysis of plant oils (a) grape seed-red (Vitis vinifera) and (b) avocado (Persea americana) (c) redcurrant (Ribes rubrum) and (d) borage (Borago officinalis) Adapted and reprinted from Journal of Chromatography A 1198ndash1199 115ndash130 (2008) M Lisa and

M Holcapek Triacylglycerols Profiling in Plant Oils Important in Food Industry Dietetics and Cosmetics using High-

performance Liquid Chromatographyndashatmospheric Pressure Chemical Ionization Mass spectrometry Copyright 2008

with permission from Elsevier

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65 70 75 80 85 90 95 65 70 75 80 85 90 95 100

Time (min)50 60 70 80 90 100

Time (min)

Time (min)

Time (min)

5

Several works have highlighted the preventive effect of these molecules against serious health disorders such as cancer heart disease and macular degeneration (13) Most of the studies performed so far have been directed to the analysis of free carotenoids usually after a saponification step to reduce sample complexity Major drawbacks of such a strategy consist of the strong conditions used for hydrolysis

which may lead to carotenoid loss as well as isomerization C18 and C30 stationary phases have been extensively used to achieve the separation of carotenoids differing in hydrophobicity within a given structural class (14)

Although widely used for carotenoid identification photodiode array (PDA) detection nevertheless fails in the situation of analytes that exhibit similar or even identical spectra To circumvent such an issue many researchers have complemented carotenoid identification by using other detection methods (15) Among these mass detection turned out to be a great aid for the analysis of these substances allowing structure elucidation on the basis of both molecular mass and fragmentation pattern Several ionization methods have been reported for MS analysis of carotenoids including electron impact (EI) fast atom bombardment (FAB) MALDI ESI APCI and more recently APPI and atmospheric pressure solids analysis probe (ASAP) The latter can be used for the direct analysis of samples without the need for sample preparation or chromatographic separation thus allowing for a fast detection screen of multiple analytes

Sometimes LCndashMSndashMS or MSn can be advantageously applied to carotenoid analysis through the use of specific transitions and daughter ions for the identification of analytes through precursor ion selection with high mass accuracy (eventually allowing to discriminate between carotenoids having equal molecular masses but different fragmentation patterns) an example is shown in Figure 2 Further advantages are represented by minimal sample clean-up leading to a decrease in overall analysis time and a higher sample throughput (16)

LCndashMS Applications for Polyphenol Analysis Occurring in many food products with enormous structural variability (5000 derivatives are known today) phenols and flavonoids are receiving special interest because of their broad spectrum of pharmacological effects (17) The identification of these polyphenol derivatives in food samples is a difficult task as a result of the complexity of the structures and the limited standards commercially available For this reason the most common separation techniques used to determine these kinds of bioactive compounds in such samples have been capillary electrophoresis (CE) GC and LC

Figure 2 Identification of carotenoid β-Cryptoxanthin by LCMSndashIT-TOF (APCI+) high mass accuracy and resolution is achieved independent of MS mode (unpublished data property of the authors)

20

inten(X1000000)

β-Cryptoxanthin

exact mass 5534404

Selected precursor ion 5534410

Selected precursor ion 5354320

MASS ACCURACY

Expected

MS

MSMS

MS3

5534404

5354303

2692169 2692194

5354320 +317

minus928

5534410 minus108

Found Error

(ppm)

Event1 MS (APCI+)

Event2 MSMS (APCI+)

[M+H-H2O]+

[M+H-H2O-266]+

Event3 MS3 (APCI+)

[M+H]+

HO

5534410

5354320

2692194

inten(X100000)

inten(X100000)

10

00

100

075

050

025

5300

30

20

10

002650 2700 2750 2800 mz

5325 5350 5375 mz

4000

41713844150413

45913274451092

4733743

5191407

5361642

5331626

5501742

4250 4500 4750 5000 5250 5500 5750 6000 6250 6500 6750 mz

6

CE provides high efficiencies in short migration times with small amounts of reagents and sample volumes needed (18) although its main disadvantage is the low concentration sensitivity GC is the least used technique for this purpose because a derivatization step is necessary LC in combination with MS proved to be by far the most useful analytical approach for identification structural characterization and quantitative analysis of these compounds The sensitivity of the MS response is clearly dependent on the interface technology employed As ionization interfaces APCI and ESI under positive and negative ionization modes are usually adopted In general polyphenolic components are detected with a greater sensitivity as negative ions (protonated or not) while significant fragments are obtained in the positive ionization mode in this regard the two modes complement each other to provide useful information for identification purposes

In contrast API typically yields only a single intense ion thus hampering analyte accurate identification Often spectral data from single-stage MS are combined with UV absorbance to afford positive identification of polyphenolic compounds with the support of commercial standards andor reference data when available (Figure 3) (19) The employment of MSndashMS and MSn achievable by ion trap or triple quadruple MS is a very powerful tool since it discriminates between positional isomers as well as elucidates the aglycone and sugar moiety (20)

Comprehensive Two‑Dimensional Liquid ChromatographyndashMass Spectrometry (LCtimesLCndashMS)The enormous complexity of real-world samples including foodstuffsposes high demand both in terms of separation power and sensitivity of detection In the last few decades much effort has been directed to the development of multidimensional LC (MDLC) systems especially in the comprehensive mode (LCtimesLC) aimed at increased resolution through careful selection of independent (orthogonal) separation modes Hyphenation to mass spectrometry represents a third added dimension to an LCtimesLC system generating the most powerful analytical tool today for non-volatile analytes Moreover tandem MS techniques can afford structure elucidation through characteristic fragmentation pattern each MS stage representing an added dimension to the LC or

2DLC system in terms of isolation selectivity or structural information Additional degrees of freedom can be obtained by the unprecedented mass accuracy (lt 1 ppm) and resolution (gt

100000) of modern ToF triple quadrupole and FT-ICR analyzers These high- and ultra-high resolution mass spectrometers used in conjunction with soft ionization methods can help

Figure 3 Comparison of a (a) UV-chromatogram and (b) a MS-chromatogram of the same sample (UV at 330 nm inset at 210 nm) Adapted and reprinted from Journal of Chromatography

B 879(24) 2459ndash2464 (2011) BF Zimmermann SG Walch LN Tinzoh W Stuumlhlinger and D W Lachenmeier Rapid

UHPLC Determination of Polyphenols in Aqueous Infusions of Salvia officinalls L (sage tea) Copyright 2011 with

permission from Elsevier

55e-1

50e-1

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00200

AU

AU

400

542 676 756

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ers

565

7 C

amo

sol-

lso

mer

s

58 C

amo

sic-

Aci

d-l

som

er58

Cam

osi

c A

cid

45 R

cem

arin

ic A

cid

9481022

1176 402

1316UV330nm

MS TIC

UV210nm

1147 153190e-2

1800

1825

1892

2241

2480

2073

1975

1813

AU

2680

2702

2000 2200 2400 2600

95e-2

10e-1

105e-1

11e-1

12e-1

13e-1

14e-1

115e-1

125e-1

135e-1

145e-1

600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600

200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600

Time ( min)

Time ( min)

0

(a)

(b)

7

to resolve highly complex samples (2122) An increased number of spectra and improved mass resolution make ToF analysers the optimum choice for detection in 2DLC

Technical requirements for linkage of an LCtimesLC system to an MS one include the choice of the mobile phase (buffer and salts) flow rate (splitting) type of ionization (interface) and coupling mode (off-line and on-line) The choice of column sets spatial resolution mass resolving power mass accuracy and tandem-MS capabilities are also crucial both from the LC and the MS standpoint Selectivity can be further tuned by adjusting experimental parameters such as mobile phase composition and pH value ion-pairing agents elution (either isocratic or gradient) flow rate and temperature

When designing an on-line LCtimesLCndashMS technique the detector response and the limited dynamic range of the instrument must be considered also Tubing and valves used may cause significant dilution and negatively affect the MS response with the overall dilution factor being multiplicative of the dilution factors in each dimension The use of trapping columns for fraction collection may alleviate such an issue since analyte re-concentration occurs (23) Requirements for the second dimension (2D) which represent the back-end separation prior to the MS system are the same as those for a one-dimensional LCndashMS analysis reversed phase (RP) chromatography is the most common choice since typical mobile phases at the end of an RP separation contain a high percentage of organic solvents and volatile additives which are beneficial for MS ionization With regards to column dimension miniaturization (use of a microbore 10 mm id or capillary 01ndash05 mm id column) is also beneficial as far as dilution and sensitivity are concerned in addition reduced mobile-phase flow rates (microL to the nL range) avoids flow splitting prior to the MS source In LCtimesLCndashMS platforms a fast MS acquisition rate is often necessary since the 2D separation can be very rapid and peak widths characterized by a few seconds or less are not unusual To adequately sample the 2D effluent the mass analyser should be capable of acquiring at least 6ndash10 data points per peak

Maximizing the resolution is beneficial for subsequent MS detection since it alleviates ion suppression effects due to insufficient separation which may cause high abundant species to obscure the detection of the less abundant On the other hand the potential spreading of minor peaks over too many fractions must be considered since high sampling rates may reduce the concentration of low abundant components and therefore hamper their detection

LCtimesLCndashMS Applications for Triacylglycerol Analysis In the last few years comprehensive two-dimensional systems in combination with mass spectrometry have been investigated for TAG separation in various food samples namely

SeC

tio

n 2

LC

-MS

SPOnSORED

Measurement of Chloramphenicol in Honey with LC-MS-MS

Measurement of Chloramphenicol in HoneyUsing Automated Sample Preparation with LC-MSMSCatherine Lafontaine Yang Shi Francois Espourteille Thermo Fisher Scientific Franklin MA USA

IntroductionChloramphenicol (CAP) (Figure 1) is a bacteriostaticantimicrobial previously used in veterinary medicine CAPhas been found to be potentially carcinogenic whichmakes it an unacceptable substance for use with any food-producing animals including honey bees The UnitedStates Canada and the European Union (EU) as well asmany other countries have completely banned the usageof CAP in the production of food The EU has set aminimum required performance level (MRPL) for CAP infood of animal origin at a level of 03 microgkg1

Currently sample preparation for the detection of CAPin honey by liquid chromatography-mass spectrometry(LC-MSMS) involves complex offline extraction methodssuch as solid phase extraction QuEChERS orliquidliquid extraction all of which require additionalsample concentration and reconstitution in an appropriatesolvent These sample preparation methods are time-consuming often taking 2 hours or more per sample andare more vulnerable to variability due to errors in manualpreparation To offer a high sensitivity (low ppbs) CAPdetection method and timely automated analysis ofmultiple samples our approach is to use the ThermoScientific Aria TLX-1 system powered by TurboFlowtrade

automated sample preparation technology coupled to thedetection capabilities of a high-sensitivity ThermoScientific TSQ Vantage triple stage quadrupole massspectrometer

Figure 1 Chemical structure of chloramphenicol

GoalDevelop a quick automated sample preparation LC-MSMS method for chloramphenicol (CAP) in honeyby negative ion heated electrospray ionization (H-ESI)using a deuterated internal standard (CAP-d5)

Experimental

Sample PreparationOrganic wildflower honey used in this analysis for thepreparation of blanks QCs and standards was obtainedfrom a local supermarket CAP was obtained from Sigma-Aldrich US (Fluka) and CAP-d5 (100 microgmL inacetonitrile) from Cambridge Isotope Labs Inc (AndoverMA USA) A CAP working solution was prepared in 11methanolwater at 100 ngmL The honey was diluted byadding 30 mL of purified water to 10 g of honey (13 wv) CAP standards and QC standards were seriallydiluted to the target concentrations with 13 honeywatercontaining 250 pgmL CAP-d5 as an internal standardTarget standard concentrations ranged from 0024 microgkgto 15 microgkg Four samples of honey obtainedinternationally and one sample obtained from a localgrocery store were analyzed as ldquosamplesrdquo and prepared bydissolving 5 g of honey in 15 mL of purified water Theinternal standard was added to a final concentration of250 pgmL The injection volume was 25 microL

MethodThe honey extract clean-up was accomplished using theThermo Scientific TurboFlow method run on an Ariatrade

TLX-1 LC system using a TurboFlow Cyclone polymer-based extraction column Simple sugars were un-retainedand moved to waste during the loading step while theanalyte of interest was retained on the extraction columnThis was followed by organic elution to a ThermoScientific Hypersil GOLD end-capped silica-based C18reversed-phase analytical column and gradient elution to aTSQ Vantagetrade triple stage quadrupole MS with a H-ESIsource CAP precursor mz 321 rarr 257 152 and 194 high resolution selective reaction monitoring (H-SRM) transitions were monitored in the negativeionization mode The 257 mz product ion for CAP wasused for quantitation and the 152 and 194 mz productions were used as confirmation Precursor 326 mz rarr 157mz and 262 mz H-SRM transitions were monitored forCAP-d5 The total LC-MSMS method run time wasabout 5 minutes

Key Words

bull Aria TLX-1

bull TurboFlowtechnology

bull TSQ Vantagemassspectrometer

bull Food safety

ApplicationNote 473

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article1measure_chlorapdf

4

As shown in Figure 1 in nARP-LC TAG retention times increase with the increasing partition number (Pn) (8) In SIC TAG separation is governed mainly by the number of DBs Double bond positional isomers cis-trans-isomers or regioisomers (R1R1R2 vs R1R2R1) can be also separated (9) APCI-MS coupled to LC represents the most powerful tool for TAG identification because of the full compatibility with common nARP-LC conditions easy ionization of non-polar TAGs and the attainment of both protonated molecules [M+H]+ and fragment ions [M+HminusRiCOOH]+ in addition ESI or matrix-assisted laser desorptionionization (MALDI)

have also been used (1011) LCndashMS offers possibilities for a better determination of minor compounds whose signals might otherwise be suppressed in terms of mass spectrometric analysers TAG analysis has been developed and implemented successfully with tandem quadrupoles and linear ion traps Tandem mass spectrometry (MSndashMS) has proved to be an essential tool for unambiguous structural characterization for mixtures of isobaric species yielding product ions from both positive and negative fragmentation processes Later on the triple quadrupole mass spectrometer was found to be well suited for TAG analysis through MSndashMS operation including product ion scanning and selected reaction monitoring (SRM) High resolution mass analysis of molecular ion species and product ions after collision-induced dissociation (CID) became routinely possible with the second generation ToF analysers FT-ICR and orbitrap mass spectrometer Hybrid mass spectrometers such as the Q-ToF afford superior spectral resolution and mass accuracy also overcoming duty cycle issues typically associated with other scanning instruments the so-called MSE acquisition mode actually allows for many precursor and neutral loss acquisitions within a single experimental run From the LC standpoint recent advances in column technology (sub-2 microm and shell-particles) and hardware (allowing operating pressures up to 15000 psi) have arrived to meet the expected performance in terms of resolution speed and sensitivity with respect to conventional LC analysis UHPLCndashMS platform combining ultra high performance liquid chromatography with an orthogonal-accelerated time-of-flight (oa-ToF) spectrometer offer high-throughput sample analysis providing narrow chromatographic peaks (lt 3 sec) with good ion statistics from accurate mass measurement (lt 2 ppm) (12)

LCndashMS Applications for Carotenoid Analysis Carotenoids are a class of naturally occurring compounds in foods and food products usually characterized by a C40-tetraterpenoid structure with a centrally located extended conjugated double bond system They are usually divided into two groups hydrocarbon (carotenes) and oxygenated carotenoids (xanthophylls) The latter can be found in either a

free form or in a more stable fatty acid esterified form

Figure 1 NARP-LCndashAPCI-MS analysis of plant oils (a) grape seed-red (Vitis vinifera) and (b) avocado (Persea americana) (c) redcurrant (Ribes rubrum) and (d) borage (Borago officinalis) Adapted and reprinted from Journal of Chromatography A 1198ndash1199 115ndash130 (2008) M Lisa and

M Holcapek Triacylglycerols Profiling in Plant Oils Important in Food Industry Dietetics and Cosmetics using High-

performance Liquid Chromatographyndashatmospheric Pressure Chemical Ionization Mass spectrometry Copyright 2008

with permission from Elsevier

Intensx103

(a) (b)

(d)(c)

30

20

10

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15

10

05

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Intensx103

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40 50 60 70 80 90

LLLn

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65 70 75 80 85 90 95 65 70 75 80 85 90 95 100

Time (min)50 60 70 80 90 100

Time (min)

Intensx103

(a) (b)

(d)(c)

30

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00

Intensx103

15

10

05

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Intensx103

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nP

OLO

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PoO

LPPO

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LOPL

PM

oOP

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POP

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Ma PP

PG

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C25

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LgO

OLg

OP

C25

0OO

C26

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SLP

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PLP

C19

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C21

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GLS

+BLL

OLM

aG

LO OO

O

65 70 75 80 85 90 95 65 70 75 80 85 90 95 100

Time (min)50 60 70 80 90 100

Time (min)

Time (min)

Time (min)

5

Several works have highlighted the preventive effect of these molecules against serious health disorders such as cancer heart disease and macular degeneration (13) Most of the studies performed so far have been directed to the analysis of free carotenoids usually after a saponification step to reduce sample complexity Major drawbacks of such a strategy consist of the strong conditions used for hydrolysis

which may lead to carotenoid loss as well as isomerization C18 and C30 stationary phases have been extensively used to achieve the separation of carotenoids differing in hydrophobicity within a given structural class (14)

Although widely used for carotenoid identification photodiode array (PDA) detection nevertheless fails in the situation of analytes that exhibit similar or even identical spectra To circumvent such an issue many researchers have complemented carotenoid identification by using other detection methods (15) Among these mass detection turned out to be a great aid for the analysis of these substances allowing structure elucidation on the basis of both molecular mass and fragmentation pattern Several ionization methods have been reported for MS analysis of carotenoids including electron impact (EI) fast atom bombardment (FAB) MALDI ESI APCI and more recently APPI and atmospheric pressure solids analysis probe (ASAP) The latter can be used for the direct analysis of samples without the need for sample preparation or chromatographic separation thus allowing for a fast detection screen of multiple analytes

Sometimes LCndashMSndashMS or MSn can be advantageously applied to carotenoid analysis through the use of specific transitions and daughter ions for the identification of analytes through precursor ion selection with high mass accuracy (eventually allowing to discriminate between carotenoids having equal molecular masses but different fragmentation patterns) an example is shown in Figure 2 Further advantages are represented by minimal sample clean-up leading to a decrease in overall analysis time and a higher sample throughput (16)

LCndashMS Applications for Polyphenol Analysis Occurring in many food products with enormous structural variability (5000 derivatives are known today) phenols and flavonoids are receiving special interest because of their broad spectrum of pharmacological effects (17) The identification of these polyphenol derivatives in food samples is a difficult task as a result of the complexity of the structures and the limited standards commercially available For this reason the most common separation techniques used to determine these kinds of bioactive compounds in such samples have been capillary electrophoresis (CE) GC and LC

Figure 2 Identification of carotenoid β-Cryptoxanthin by LCMSndashIT-TOF (APCI+) high mass accuracy and resolution is achieved independent of MS mode (unpublished data property of the authors)

20

inten(X1000000)

β-Cryptoxanthin

exact mass 5534404

Selected precursor ion 5534410

Selected precursor ion 5354320

MASS ACCURACY

Expected

MS

MSMS

MS3

5534404

5354303

2692169 2692194

5354320 +317

minus928

5534410 minus108

Found Error

(ppm)

Event1 MS (APCI+)

Event2 MSMS (APCI+)

[M+H-H2O]+

[M+H-H2O-266]+

Event3 MS3 (APCI+)

[M+H]+

HO

5534410

5354320

2692194

inten(X100000)

inten(X100000)

10

00

100

075

050

025

5300

30

20

10

002650 2700 2750 2800 mz

5325 5350 5375 mz

4000

41713844150413

45913274451092

4733743

5191407

5361642

5331626

5501742

4250 4500 4750 5000 5250 5500 5750 6000 6250 6500 6750 mz

6

CE provides high efficiencies in short migration times with small amounts of reagents and sample volumes needed (18) although its main disadvantage is the low concentration sensitivity GC is the least used technique for this purpose because a derivatization step is necessary LC in combination with MS proved to be by far the most useful analytical approach for identification structural characterization and quantitative analysis of these compounds The sensitivity of the MS response is clearly dependent on the interface technology employed As ionization interfaces APCI and ESI under positive and negative ionization modes are usually adopted In general polyphenolic components are detected with a greater sensitivity as negative ions (protonated or not) while significant fragments are obtained in the positive ionization mode in this regard the two modes complement each other to provide useful information for identification purposes

In contrast API typically yields only a single intense ion thus hampering analyte accurate identification Often spectral data from single-stage MS are combined with UV absorbance to afford positive identification of polyphenolic compounds with the support of commercial standards andor reference data when available (Figure 3) (19) The employment of MSndashMS and MSn achievable by ion trap or triple quadruple MS is a very powerful tool since it discriminates between positional isomers as well as elucidates the aglycone and sugar moiety (20)

Comprehensive Two‑Dimensional Liquid ChromatographyndashMass Spectrometry (LCtimesLCndashMS)The enormous complexity of real-world samples including foodstuffsposes high demand both in terms of separation power and sensitivity of detection In the last few decades much effort has been directed to the development of multidimensional LC (MDLC) systems especially in the comprehensive mode (LCtimesLC) aimed at increased resolution through careful selection of independent (orthogonal) separation modes Hyphenation to mass spectrometry represents a third added dimension to an LCtimesLC system generating the most powerful analytical tool today for non-volatile analytes Moreover tandem MS techniques can afford structure elucidation through characteristic fragmentation pattern each MS stage representing an added dimension to the LC or

2DLC system in terms of isolation selectivity or structural information Additional degrees of freedom can be obtained by the unprecedented mass accuracy (lt 1 ppm) and resolution (gt

100000) of modern ToF triple quadrupole and FT-ICR analyzers These high- and ultra-high resolution mass spectrometers used in conjunction with soft ionization methods can help

Figure 3 Comparison of a (a) UV-chromatogram and (b) a MS-chromatogram of the same sample (UV at 330 nm inset at 210 nm) Adapted and reprinted from Journal of Chromatography

B 879(24) 2459ndash2464 (2011) BF Zimmermann SG Walch LN Tinzoh W Stuumlhlinger and D W Lachenmeier Rapid

UHPLC Determination of Polyphenols in Aqueous Infusions of Salvia officinalls L (sage tea) Copyright 2011 with

permission from Elsevier

55e-1

50e-1

45e-1

40e-1

35e-1

30e-1

25e-1

20e-1

15e-1

10e-1

50e-2

00200

AU

AU

400

542 676 756

22 S

apo

nar

in

1 D

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23

Pro

toca

tech

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affe

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vian

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Aci

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50 S

alvi

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K

52 S

Cam

oso

l-ls

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535

455

Ro

sman

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565

7 R

Cam

oso

l-ls

om

ers

58 C

amo

sic

Aci

d-l

som

er

59 C

amo

sic

Aci

d

29 L

ute

din

-Dig

lucu

ren

ide

31 H

ydro

xylu

teo

l-G

lucu

ron

id

41 L

ute

olin

-Glu

curo

nid

e

446

Ap

igar

in-G

lucu

ron

ide

50 S

alvi

and

ic A

cid

K

52 C

amo

sol-

lso

mer

535

455

Ro

sman

cl-l

som

ers

565

7 C

amo

sol-

lso

mer

s

58 C

amo

sic-

Aci

d-l

som

er58

Cam

osi

c A

cid

45 R

cem

arin

ic A

cid

9481022

1176 402

1316UV330nm

MS TIC

UV210nm

1147 153190e-2

1800

1825

1892

2241

2480

2073

1975

1813

AU

2680

2702

2000 2200 2400 2600

95e-2

10e-1

105e-1

11e-1

12e-1

13e-1

14e-1

115e-1

125e-1

135e-1

145e-1

600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600

200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600

Time ( min)

Time ( min)

0

(a)

(b)

7

to resolve highly complex samples (2122) An increased number of spectra and improved mass resolution make ToF analysers the optimum choice for detection in 2DLC

Technical requirements for linkage of an LCtimesLC system to an MS one include the choice of the mobile phase (buffer and salts) flow rate (splitting) type of ionization (interface) and coupling mode (off-line and on-line) The choice of column sets spatial resolution mass resolving power mass accuracy and tandem-MS capabilities are also crucial both from the LC and the MS standpoint Selectivity can be further tuned by adjusting experimental parameters such as mobile phase composition and pH value ion-pairing agents elution (either isocratic or gradient) flow rate and temperature

When designing an on-line LCtimesLCndashMS technique the detector response and the limited dynamic range of the instrument must be considered also Tubing and valves used may cause significant dilution and negatively affect the MS response with the overall dilution factor being multiplicative of the dilution factors in each dimension The use of trapping columns for fraction collection may alleviate such an issue since analyte re-concentration occurs (23) Requirements for the second dimension (2D) which represent the back-end separation prior to the MS system are the same as those for a one-dimensional LCndashMS analysis reversed phase (RP) chromatography is the most common choice since typical mobile phases at the end of an RP separation contain a high percentage of organic solvents and volatile additives which are beneficial for MS ionization With regards to column dimension miniaturization (use of a microbore 10 mm id or capillary 01ndash05 mm id column) is also beneficial as far as dilution and sensitivity are concerned in addition reduced mobile-phase flow rates (microL to the nL range) avoids flow splitting prior to the MS source In LCtimesLCndashMS platforms a fast MS acquisition rate is often necessary since the 2D separation can be very rapid and peak widths characterized by a few seconds or less are not unusual To adequately sample the 2D effluent the mass analyser should be capable of acquiring at least 6ndash10 data points per peak

Maximizing the resolution is beneficial for subsequent MS detection since it alleviates ion suppression effects due to insufficient separation which may cause high abundant species to obscure the detection of the less abundant On the other hand the potential spreading of minor peaks over too many fractions must be considered since high sampling rates may reduce the concentration of low abundant components and therefore hamper their detection

LCtimesLCndashMS Applications for Triacylglycerol Analysis In the last few years comprehensive two-dimensional systems in combination with mass spectrometry have been investigated for TAG separation in various food samples namely

SeC

tio

n 2

LC

-MS

SPOnSORED

Measurement of Chloramphenicol in Honey with LC-MS-MS

Measurement of Chloramphenicol in HoneyUsing Automated Sample Preparation with LC-MSMSCatherine Lafontaine Yang Shi Francois Espourteille Thermo Fisher Scientific Franklin MA USA

IntroductionChloramphenicol (CAP) (Figure 1) is a bacteriostaticantimicrobial previously used in veterinary medicine CAPhas been found to be potentially carcinogenic whichmakes it an unacceptable substance for use with any food-producing animals including honey bees The UnitedStates Canada and the European Union (EU) as well asmany other countries have completely banned the usageof CAP in the production of food The EU has set aminimum required performance level (MRPL) for CAP infood of animal origin at a level of 03 microgkg1

Currently sample preparation for the detection of CAPin honey by liquid chromatography-mass spectrometry(LC-MSMS) involves complex offline extraction methodssuch as solid phase extraction QuEChERS orliquidliquid extraction all of which require additionalsample concentration and reconstitution in an appropriatesolvent These sample preparation methods are time-consuming often taking 2 hours or more per sample andare more vulnerable to variability due to errors in manualpreparation To offer a high sensitivity (low ppbs) CAPdetection method and timely automated analysis ofmultiple samples our approach is to use the ThermoScientific Aria TLX-1 system powered by TurboFlowtrade

automated sample preparation technology coupled to thedetection capabilities of a high-sensitivity ThermoScientific TSQ Vantage triple stage quadrupole massspectrometer

Figure 1 Chemical structure of chloramphenicol

GoalDevelop a quick automated sample preparation LC-MSMS method for chloramphenicol (CAP) in honeyby negative ion heated electrospray ionization (H-ESI)using a deuterated internal standard (CAP-d5)

Experimental

Sample PreparationOrganic wildflower honey used in this analysis for thepreparation of blanks QCs and standards was obtainedfrom a local supermarket CAP was obtained from Sigma-Aldrich US (Fluka) and CAP-d5 (100 microgmL inacetonitrile) from Cambridge Isotope Labs Inc (AndoverMA USA) A CAP working solution was prepared in 11methanolwater at 100 ngmL The honey was diluted byadding 30 mL of purified water to 10 g of honey (13 wv) CAP standards and QC standards were seriallydiluted to the target concentrations with 13 honeywatercontaining 250 pgmL CAP-d5 as an internal standardTarget standard concentrations ranged from 0024 microgkgto 15 microgkg Four samples of honey obtainedinternationally and one sample obtained from a localgrocery store were analyzed as ldquosamplesrdquo and prepared bydissolving 5 g of honey in 15 mL of purified water Theinternal standard was added to a final concentration of250 pgmL The injection volume was 25 microL

MethodThe honey extract clean-up was accomplished using theThermo Scientific TurboFlow method run on an Ariatrade

TLX-1 LC system using a TurboFlow Cyclone polymer-based extraction column Simple sugars were un-retainedand moved to waste during the loading step while theanalyte of interest was retained on the extraction columnThis was followed by organic elution to a ThermoScientific Hypersil GOLD end-capped silica-based C18reversed-phase analytical column and gradient elution to aTSQ Vantagetrade triple stage quadrupole MS with a H-ESIsource CAP precursor mz 321 rarr 257 152 and 194 high resolution selective reaction monitoring (H-SRM) transitions were monitored in the negativeionization mode The 257 mz product ion for CAP wasused for quantitation and the 152 and 194 mz productions were used as confirmation Precursor 326 mz rarr 157mz and 262 mz H-SRM transitions were monitored forCAP-d5 The total LC-MSMS method run time wasabout 5 minutes

Key Words

bull Aria TLX-1

bull TurboFlowtechnology

bull TSQ Vantagemassspectrometer

bull Food safety

ApplicationNote 473

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article1measure_chlorapdf

5

Several works have highlighted the preventive effect of these molecules against serious health disorders such as cancer heart disease and macular degeneration (13) Most of the studies performed so far have been directed to the analysis of free carotenoids usually after a saponification step to reduce sample complexity Major drawbacks of such a strategy consist of the strong conditions used for hydrolysis

which may lead to carotenoid loss as well as isomerization C18 and C30 stationary phases have been extensively used to achieve the separation of carotenoids differing in hydrophobicity within a given structural class (14)

Although widely used for carotenoid identification photodiode array (PDA) detection nevertheless fails in the situation of analytes that exhibit similar or even identical spectra To circumvent such an issue many researchers have complemented carotenoid identification by using other detection methods (15) Among these mass detection turned out to be a great aid for the analysis of these substances allowing structure elucidation on the basis of both molecular mass and fragmentation pattern Several ionization methods have been reported for MS analysis of carotenoids including electron impact (EI) fast atom bombardment (FAB) MALDI ESI APCI and more recently APPI and atmospheric pressure solids analysis probe (ASAP) The latter can be used for the direct analysis of samples without the need for sample preparation or chromatographic separation thus allowing for a fast detection screen of multiple analytes

Sometimes LCndashMSndashMS or MSn can be advantageously applied to carotenoid analysis through the use of specific transitions and daughter ions for the identification of analytes through precursor ion selection with high mass accuracy (eventually allowing to discriminate between carotenoids having equal molecular masses but different fragmentation patterns) an example is shown in Figure 2 Further advantages are represented by minimal sample clean-up leading to a decrease in overall analysis time and a higher sample throughput (16)

LCndashMS Applications for Polyphenol Analysis Occurring in many food products with enormous structural variability (5000 derivatives are known today) phenols and flavonoids are receiving special interest because of their broad spectrum of pharmacological effects (17) The identification of these polyphenol derivatives in food samples is a difficult task as a result of the complexity of the structures and the limited standards commercially available For this reason the most common separation techniques used to determine these kinds of bioactive compounds in such samples have been capillary electrophoresis (CE) GC and LC

Figure 2 Identification of carotenoid β-Cryptoxanthin by LCMSndashIT-TOF (APCI+) high mass accuracy and resolution is achieved independent of MS mode (unpublished data property of the authors)

20

inten(X1000000)

β-Cryptoxanthin

exact mass 5534404

Selected precursor ion 5534410

Selected precursor ion 5354320

MASS ACCURACY

Expected

MS

MSMS

MS3

5534404

5354303

2692169 2692194

5354320 +317

minus928

5534410 minus108

Found Error

(ppm)

Event1 MS (APCI+)

Event2 MSMS (APCI+)

[M+H-H2O]+

[M+H-H2O-266]+

Event3 MS3 (APCI+)

[M+H]+

HO

5534410

5354320

2692194

inten(X100000)

inten(X100000)

10

00

100

075

050

025

5300

30

20

10

002650 2700 2750 2800 mz

5325 5350 5375 mz

4000

41713844150413

45913274451092

4733743

5191407

5361642

5331626

5501742

4250 4500 4750 5000 5250 5500 5750 6000 6250 6500 6750 mz

6

CE provides high efficiencies in short migration times with small amounts of reagents and sample volumes needed (18) although its main disadvantage is the low concentration sensitivity GC is the least used technique for this purpose because a derivatization step is necessary LC in combination with MS proved to be by far the most useful analytical approach for identification structural characterization and quantitative analysis of these compounds The sensitivity of the MS response is clearly dependent on the interface technology employed As ionization interfaces APCI and ESI under positive and negative ionization modes are usually adopted In general polyphenolic components are detected with a greater sensitivity as negative ions (protonated or not) while significant fragments are obtained in the positive ionization mode in this regard the two modes complement each other to provide useful information for identification purposes

In contrast API typically yields only a single intense ion thus hampering analyte accurate identification Often spectral data from single-stage MS are combined with UV absorbance to afford positive identification of polyphenolic compounds with the support of commercial standards andor reference data when available (Figure 3) (19) The employment of MSndashMS and MSn achievable by ion trap or triple quadruple MS is a very powerful tool since it discriminates between positional isomers as well as elucidates the aglycone and sugar moiety (20)

Comprehensive Two‑Dimensional Liquid ChromatographyndashMass Spectrometry (LCtimesLCndashMS)The enormous complexity of real-world samples including foodstuffsposes high demand both in terms of separation power and sensitivity of detection In the last few decades much effort has been directed to the development of multidimensional LC (MDLC) systems especially in the comprehensive mode (LCtimesLC) aimed at increased resolution through careful selection of independent (orthogonal) separation modes Hyphenation to mass spectrometry represents a third added dimension to an LCtimesLC system generating the most powerful analytical tool today for non-volatile analytes Moreover tandem MS techniques can afford structure elucidation through characteristic fragmentation pattern each MS stage representing an added dimension to the LC or

2DLC system in terms of isolation selectivity or structural information Additional degrees of freedom can be obtained by the unprecedented mass accuracy (lt 1 ppm) and resolution (gt

100000) of modern ToF triple quadrupole and FT-ICR analyzers These high- and ultra-high resolution mass spectrometers used in conjunction with soft ionization methods can help

Figure 3 Comparison of a (a) UV-chromatogram and (b) a MS-chromatogram of the same sample (UV at 330 nm inset at 210 nm) Adapted and reprinted from Journal of Chromatography

B 879(24) 2459ndash2464 (2011) BF Zimmermann SG Walch LN Tinzoh W Stuumlhlinger and D W Lachenmeier Rapid

UHPLC Determination of Polyphenols in Aqueous Infusions of Salvia officinalls L (sage tea) Copyright 2011 with

permission from Elsevier

55e-1

50e-1

45e-1

40e-1

35e-1

30e-1

25e-1

20e-1

15e-1

10e-1

50e-2

00200

AU

AU

400

542 676 756

22 S

apo

nar

in

1 D

ansh

ensu

23

Pro

toca

tech

uo

yl-H

exo

ses

8 C

om

aro

yl-H

exo

ses

10 M

on

oh

ydro

xyb

enzo

ic A

cid

11 C

ou

mar

ayl-

Ap

iosy

l-G

luco

se10

Ch

loro

gen

ic A

cid

17 C

affe

ic A

cid

22 S

apo

nai

n24

Sal

vian

olic

Aci

d F

-lso

mer

28 S

alvi

ano

lic A

cid

I-ls

om

er

29 L

ute

clin

-Dig

luro

nid

e30

En

oct

rin

31 H

ydro

xylu

teo

lin-G

lucu

ron

id

38 L

ute

olin

-Gly

cosi

de

40 L

ute

olin

-Ru

tin

osi

de

lso

mer

424

4 A

pig

enin

-Ru

tin

osi

de

lso

mer

s45

Ro

smar

inic

Aci

d

41 L

ute

olin

-7-O

-Glu

curo

nid

e

46 A

pig

enin

-Glu

curo

nid

e48

Sal

vian

olic

Aci

d B

50 S

alvi

ano

lic A

cid

K

52 S

Cam

oso

l-ls

om

er

535

455

Ro

sman

ol-

lso

mer

s

565

7 R

Cam

oso

l-ls

om

ers

58 C

amo

sic

Aci

d-l

som

er

59 C

amo

sic

Aci

d

29 L

ute

din

-Dig

lucu

ren

ide

31 H

ydro

xylu

teo

l-G

lucu

ron

id

41 L

ute

olin

-Glu

curo

nid

e

446

Ap

igar

in-G

lucu

ron

ide

50 S

alvi

and

ic A

cid

K

52 C

amo

sol-

lso

mer

535

455

Ro

sman

cl-l

som

ers

565

7 C

amo

sol-

lso

mer

s

58 C

amo

sic-

Aci

d-l

som

er58

Cam

osi

c A

cid

45 R

cem

arin

ic A

cid

9481022

1176 402

1316UV330nm

MS TIC

UV210nm

1147 153190e-2

1800

1825

1892

2241

2480

2073

1975

1813

AU

2680

2702

2000 2200 2400 2600

95e-2

10e-1

105e-1

11e-1

12e-1

13e-1

14e-1

115e-1

125e-1

135e-1

145e-1

600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600

200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600

Time ( min)

Time ( min)

0

(a)

(b)

7

to resolve highly complex samples (2122) An increased number of spectra and improved mass resolution make ToF analysers the optimum choice for detection in 2DLC

Technical requirements for linkage of an LCtimesLC system to an MS one include the choice of the mobile phase (buffer and salts) flow rate (splitting) type of ionization (interface) and coupling mode (off-line and on-line) The choice of column sets spatial resolution mass resolving power mass accuracy and tandem-MS capabilities are also crucial both from the LC and the MS standpoint Selectivity can be further tuned by adjusting experimental parameters such as mobile phase composition and pH value ion-pairing agents elution (either isocratic or gradient) flow rate and temperature

When designing an on-line LCtimesLCndashMS technique the detector response and the limited dynamic range of the instrument must be considered also Tubing and valves used may cause significant dilution and negatively affect the MS response with the overall dilution factor being multiplicative of the dilution factors in each dimension The use of trapping columns for fraction collection may alleviate such an issue since analyte re-concentration occurs (23) Requirements for the second dimension (2D) which represent the back-end separation prior to the MS system are the same as those for a one-dimensional LCndashMS analysis reversed phase (RP) chromatography is the most common choice since typical mobile phases at the end of an RP separation contain a high percentage of organic solvents and volatile additives which are beneficial for MS ionization With regards to column dimension miniaturization (use of a microbore 10 mm id or capillary 01ndash05 mm id column) is also beneficial as far as dilution and sensitivity are concerned in addition reduced mobile-phase flow rates (microL to the nL range) avoids flow splitting prior to the MS source In LCtimesLCndashMS platforms a fast MS acquisition rate is often necessary since the 2D separation can be very rapid and peak widths characterized by a few seconds or less are not unusual To adequately sample the 2D effluent the mass analyser should be capable of acquiring at least 6ndash10 data points per peak

Maximizing the resolution is beneficial for subsequent MS detection since it alleviates ion suppression effects due to insufficient separation which may cause high abundant species to obscure the detection of the less abundant On the other hand the potential spreading of minor peaks over too many fractions must be considered since high sampling rates may reduce the concentration of low abundant components and therefore hamper their detection

LCtimesLCndashMS Applications for Triacylglycerol Analysis In the last few years comprehensive two-dimensional systems in combination with mass spectrometry have been investigated for TAG separation in various food samples namely

SeC

tio

n 2

LC

-MS

SPOnSORED

Measurement of Chloramphenicol in Honey with LC-MS-MS

Measurement of Chloramphenicol in HoneyUsing Automated Sample Preparation with LC-MSMSCatherine Lafontaine Yang Shi Francois Espourteille Thermo Fisher Scientific Franklin MA USA

IntroductionChloramphenicol (CAP) (Figure 1) is a bacteriostaticantimicrobial previously used in veterinary medicine CAPhas been found to be potentially carcinogenic whichmakes it an unacceptable substance for use with any food-producing animals including honey bees The UnitedStates Canada and the European Union (EU) as well asmany other countries have completely banned the usageof CAP in the production of food The EU has set aminimum required performance level (MRPL) for CAP infood of animal origin at a level of 03 microgkg1

Currently sample preparation for the detection of CAPin honey by liquid chromatography-mass spectrometry(LC-MSMS) involves complex offline extraction methodssuch as solid phase extraction QuEChERS orliquidliquid extraction all of which require additionalsample concentration and reconstitution in an appropriatesolvent These sample preparation methods are time-consuming often taking 2 hours or more per sample andare more vulnerable to variability due to errors in manualpreparation To offer a high sensitivity (low ppbs) CAPdetection method and timely automated analysis ofmultiple samples our approach is to use the ThermoScientific Aria TLX-1 system powered by TurboFlowtrade

automated sample preparation technology coupled to thedetection capabilities of a high-sensitivity ThermoScientific TSQ Vantage triple stage quadrupole massspectrometer

Figure 1 Chemical structure of chloramphenicol

GoalDevelop a quick automated sample preparation LC-MSMS method for chloramphenicol (CAP) in honeyby negative ion heated electrospray ionization (H-ESI)using a deuterated internal standard (CAP-d5)

Experimental

Sample PreparationOrganic wildflower honey used in this analysis for thepreparation of blanks QCs and standards was obtainedfrom a local supermarket CAP was obtained from Sigma-Aldrich US (Fluka) and CAP-d5 (100 microgmL inacetonitrile) from Cambridge Isotope Labs Inc (AndoverMA USA) A CAP working solution was prepared in 11methanolwater at 100 ngmL The honey was diluted byadding 30 mL of purified water to 10 g of honey (13 wv) CAP standards and QC standards were seriallydiluted to the target concentrations with 13 honeywatercontaining 250 pgmL CAP-d5 as an internal standardTarget standard concentrations ranged from 0024 microgkgto 15 microgkg Four samples of honey obtainedinternationally and one sample obtained from a localgrocery store were analyzed as ldquosamplesrdquo and prepared bydissolving 5 g of honey in 15 mL of purified water Theinternal standard was added to a final concentration of250 pgmL The injection volume was 25 microL

MethodThe honey extract clean-up was accomplished using theThermo Scientific TurboFlow method run on an Ariatrade

TLX-1 LC system using a TurboFlow Cyclone polymer-based extraction column Simple sugars were un-retainedand moved to waste during the loading step while theanalyte of interest was retained on the extraction columnThis was followed by organic elution to a ThermoScientific Hypersil GOLD end-capped silica-based C18reversed-phase analytical column and gradient elution to aTSQ Vantagetrade triple stage quadrupole MS with a H-ESIsource CAP precursor mz 321 rarr 257 152 and 194 high resolution selective reaction monitoring (H-SRM) transitions were monitored in the negativeionization mode The 257 mz product ion for CAP wasused for quantitation and the 152 and 194 mz productions were used as confirmation Precursor 326 mz rarr 157mz and 262 mz H-SRM transitions were monitored forCAP-d5 The total LC-MSMS method run time wasabout 5 minutes

Key Words

bull Aria TLX-1

bull TurboFlowtechnology

bull TSQ Vantagemassspectrometer

bull Food safety

ApplicationNote 473

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article1measure_chlorapdf

6

CE provides high efficiencies in short migration times with small amounts of reagents and sample volumes needed (18) although its main disadvantage is the low concentration sensitivity GC is the least used technique for this purpose because a derivatization step is necessary LC in combination with MS proved to be by far the most useful analytical approach for identification structural characterization and quantitative analysis of these compounds The sensitivity of the MS response is clearly dependent on the interface technology employed As ionization interfaces APCI and ESI under positive and negative ionization modes are usually adopted In general polyphenolic components are detected with a greater sensitivity as negative ions (protonated or not) while significant fragments are obtained in the positive ionization mode in this regard the two modes complement each other to provide useful information for identification purposes

In contrast API typically yields only a single intense ion thus hampering analyte accurate identification Often spectral data from single-stage MS are combined with UV absorbance to afford positive identification of polyphenolic compounds with the support of commercial standards andor reference data when available (Figure 3) (19) The employment of MSndashMS and MSn achievable by ion trap or triple quadruple MS is a very powerful tool since it discriminates between positional isomers as well as elucidates the aglycone and sugar moiety (20)

Comprehensive Two‑Dimensional Liquid ChromatographyndashMass Spectrometry (LCtimesLCndashMS)The enormous complexity of real-world samples including foodstuffsposes high demand both in terms of separation power and sensitivity of detection In the last few decades much effort has been directed to the development of multidimensional LC (MDLC) systems especially in the comprehensive mode (LCtimesLC) aimed at increased resolution through careful selection of independent (orthogonal) separation modes Hyphenation to mass spectrometry represents a third added dimension to an LCtimesLC system generating the most powerful analytical tool today for non-volatile analytes Moreover tandem MS techniques can afford structure elucidation through characteristic fragmentation pattern each MS stage representing an added dimension to the LC or

2DLC system in terms of isolation selectivity or structural information Additional degrees of freedom can be obtained by the unprecedented mass accuracy (lt 1 ppm) and resolution (gt

100000) of modern ToF triple quadrupole and FT-ICR analyzers These high- and ultra-high resolution mass spectrometers used in conjunction with soft ionization methods can help

Figure 3 Comparison of a (a) UV-chromatogram and (b) a MS-chromatogram of the same sample (UV at 330 nm inset at 210 nm) Adapted and reprinted from Journal of Chromatography

B 879(24) 2459ndash2464 (2011) BF Zimmermann SG Walch LN Tinzoh W Stuumlhlinger and D W Lachenmeier Rapid

UHPLC Determination of Polyphenols in Aqueous Infusions of Salvia officinalls L (sage tea) Copyright 2011 with

permission from Elsevier

55e-1

50e-1

45e-1

40e-1

35e-1

30e-1

25e-1

20e-1

15e-1

10e-1

50e-2

00200

AU

AU

400

542 676 756

22 S

apo

nar

in

1 D

ansh

ensu

23

Pro

toca

tech

uo

yl-H

exo

ses

8 C

om

aro

yl-H

exo

ses

10 M

on

oh

ydro

xyb

enzo

ic A

cid

11 C

ou

mar

ayl-

Ap

iosy

l-G

luco

se10

Ch

loro

gen

ic A

cid

17 C

affe

ic A

cid

22 S

apo

nai

n24

Sal

vian

olic

Aci

d F

-lso

mer

28 S

alvi

ano

lic A

cid

I-ls

om

er

29 L

ute

clin

-Dig

luro

nid

e30

En

oct

rin

31 H

ydro

xylu

teo

lin-G

lucu

ron

id

38 L

ute

olin

-Gly

cosi

de

40 L

ute

olin

-Ru

tin

osi

de

lso

mer

424

4 A

pig

enin

-Ru

tin

osi

de

lso

mer

s45

Ro

smar

inic

Aci

d

41 L

ute

olin

-7-O

-Glu

curo

nid

e

46 A

pig

enin

-Glu

curo

nid

e48

Sal

vian

olic

Aci

d B

50 S

alvi

ano

lic A

cid

K

52 S

Cam

oso

l-ls

om

er

535

455

Ro

sman

ol-

lso

mer

s

565

7 R

Cam

oso

l-ls

om

ers

58 C

amo

sic

Aci

d-l

som

er

59 C

amo

sic

Aci

d

29 L

ute

din

-Dig

lucu

ren

ide

31 H

ydro

xylu

teo

l-G

lucu

ron

id

41 L

ute

olin

-Glu

curo

nid

e

446

Ap

igar

in-G

lucu

ron

ide

50 S

alvi

and

ic A

cid

K

52 C

amo

sol-

lso

mer

535

455

Ro

sman

cl-l

som

ers

565

7 C

amo

sol-

lso

mer

s

58 C

amo

sic-

Aci

d-l

som

er58

Cam

osi

c A

cid

45 R

cem

arin

ic A

cid

9481022

1176 402

1316UV330nm

MS TIC

UV210nm

1147 153190e-2

1800

1825

1892

2241

2480

2073

1975

1813

AU

2680

2702

2000 2200 2400 2600

95e-2

10e-1

105e-1

11e-1

12e-1

13e-1

14e-1

115e-1

125e-1

135e-1

145e-1

600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600

200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600

Time ( min)

Time ( min)

0

(a)

(b)

7

to resolve highly complex samples (2122) An increased number of spectra and improved mass resolution make ToF analysers the optimum choice for detection in 2DLC

Technical requirements for linkage of an LCtimesLC system to an MS one include the choice of the mobile phase (buffer and salts) flow rate (splitting) type of ionization (interface) and coupling mode (off-line and on-line) The choice of column sets spatial resolution mass resolving power mass accuracy and tandem-MS capabilities are also crucial both from the LC and the MS standpoint Selectivity can be further tuned by adjusting experimental parameters such as mobile phase composition and pH value ion-pairing agents elution (either isocratic or gradient) flow rate and temperature

When designing an on-line LCtimesLCndashMS technique the detector response and the limited dynamic range of the instrument must be considered also Tubing and valves used may cause significant dilution and negatively affect the MS response with the overall dilution factor being multiplicative of the dilution factors in each dimension The use of trapping columns for fraction collection may alleviate such an issue since analyte re-concentration occurs (23) Requirements for the second dimension (2D) which represent the back-end separation prior to the MS system are the same as those for a one-dimensional LCndashMS analysis reversed phase (RP) chromatography is the most common choice since typical mobile phases at the end of an RP separation contain a high percentage of organic solvents and volatile additives which are beneficial for MS ionization With regards to column dimension miniaturization (use of a microbore 10 mm id or capillary 01ndash05 mm id column) is also beneficial as far as dilution and sensitivity are concerned in addition reduced mobile-phase flow rates (microL to the nL range) avoids flow splitting prior to the MS source In LCtimesLCndashMS platforms a fast MS acquisition rate is often necessary since the 2D separation can be very rapid and peak widths characterized by a few seconds or less are not unusual To adequately sample the 2D effluent the mass analyser should be capable of acquiring at least 6ndash10 data points per peak

Maximizing the resolution is beneficial for subsequent MS detection since it alleviates ion suppression effects due to insufficient separation which may cause high abundant species to obscure the detection of the less abundant On the other hand the potential spreading of minor peaks over too many fractions must be considered since high sampling rates may reduce the concentration of low abundant components and therefore hamper their detection

LCtimesLCndashMS Applications for Triacylglycerol Analysis In the last few years comprehensive two-dimensional systems in combination with mass spectrometry have been investigated for TAG separation in various food samples namely

SeC

tio

n 2

LC

-MS

SPOnSORED

Measurement of Chloramphenicol in Honey with LC-MS-MS

Measurement of Chloramphenicol in HoneyUsing Automated Sample Preparation with LC-MSMSCatherine Lafontaine Yang Shi Francois Espourteille Thermo Fisher Scientific Franklin MA USA

IntroductionChloramphenicol (CAP) (Figure 1) is a bacteriostaticantimicrobial previously used in veterinary medicine CAPhas been found to be potentially carcinogenic whichmakes it an unacceptable substance for use with any food-producing animals including honey bees The UnitedStates Canada and the European Union (EU) as well asmany other countries have completely banned the usageof CAP in the production of food The EU has set aminimum required performance level (MRPL) for CAP infood of animal origin at a level of 03 microgkg1

Currently sample preparation for the detection of CAPin honey by liquid chromatography-mass spectrometry(LC-MSMS) involves complex offline extraction methodssuch as solid phase extraction QuEChERS orliquidliquid extraction all of which require additionalsample concentration and reconstitution in an appropriatesolvent These sample preparation methods are time-consuming often taking 2 hours or more per sample andare more vulnerable to variability due to errors in manualpreparation To offer a high sensitivity (low ppbs) CAPdetection method and timely automated analysis ofmultiple samples our approach is to use the ThermoScientific Aria TLX-1 system powered by TurboFlowtrade

automated sample preparation technology coupled to thedetection capabilities of a high-sensitivity ThermoScientific TSQ Vantage triple stage quadrupole massspectrometer

Figure 1 Chemical structure of chloramphenicol

GoalDevelop a quick automated sample preparation LC-MSMS method for chloramphenicol (CAP) in honeyby negative ion heated electrospray ionization (H-ESI)using a deuterated internal standard (CAP-d5)

Experimental

Sample PreparationOrganic wildflower honey used in this analysis for thepreparation of blanks QCs and standards was obtainedfrom a local supermarket CAP was obtained from Sigma-Aldrich US (Fluka) and CAP-d5 (100 microgmL inacetonitrile) from Cambridge Isotope Labs Inc (AndoverMA USA) A CAP working solution was prepared in 11methanolwater at 100 ngmL The honey was diluted byadding 30 mL of purified water to 10 g of honey (13 wv) CAP standards and QC standards were seriallydiluted to the target concentrations with 13 honeywatercontaining 250 pgmL CAP-d5 as an internal standardTarget standard concentrations ranged from 0024 microgkgto 15 microgkg Four samples of honey obtainedinternationally and one sample obtained from a localgrocery store were analyzed as ldquosamplesrdquo and prepared bydissolving 5 g of honey in 15 mL of purified water Theinternal standard was added to a final concentration of250 pgmL The injection volume was 25 microL

MethodThe honey extract clean-up was accomplished using theThermo Scientific TurboFlow method run on an Ariatrade

TLX-1 LC system using a TurboFlow Cyclone polymer-based extraction column Simple sugars were un-retainedand moved to waste during the loading step while theanalyte of interest was retained on the extraction columnThis was followed by organic elution to a ThermoScientific Hypersil GOLD end-capped silica-based C18reversed-phase analytical column and gradient elution to aTSQ Vantagetrade triple stage quadrupole MS with a H-ESIsource CAP precursor mz 321 rarr 257 152 and 194 high resolution selective reaction monitoring (H-SRM) transitions were monitored in the negativeionization mode The 257 mz product ion for CAP wasused for quantitation and the 152 and 194 mz productions were used as confirmation Precursor 326 mz rarr 157mz and 262 mz H-SRM transitions were monitored forCAP-d5 The total LC-MSMS method run time wasabout 5 minutes

Key Words

bull Aria TLX-1

bull TurboFlowtechnology

bull TSQ Vantagemassspectrometer

bull Food safety

ApplicationNote 473

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article1measure_chlorapdf

7

to resolve highly complex samples (2122) An increased number of spectra and improved mass resolution make ToF analysers the optimum choice for detection in 2DLC

Technical requirements for linkage of an LCtimesLC system to an MS one include the choice of the mobile phase (buffer and salts) flow rate (splitting) type of ionization (interface) and coupling mode (off-line and on-line) The choice of column sets spatial resolution mass resolving power mass accuracy and tandem-MS capabilities are also crucial both from the LC and the MS standpoint Selectivity can be further tuned by adjusting experimental parameters such as mobile phase composition and pH value ion-pairing agents elution (either isocratic or gradient) flow rate and temperature

When designing an on-line LCtimesLCndashMS technique the detector response and the limited dynamic range of the instrument must be considered also Tubing and valves used may cause significant dilution and negatively affect the MS response with the overall dilution factor being multiplicative of the dilution factors in each dimension The use of trapping columns for fraction collection may alleviate such an issue since analyte re-concentration occurs (23) Requirements for the second dimension (2D) which represent the back-end separation prior to the MS system are the same as those for a one-dimensional LCndashMS analysis reversed phase (RP) chromatography is the most common choice since typical mobile phases at the end of an RP separation contain a high percentage of organic solvents and volatile additives which are beneficial for MS ionization With regards to column dimension miniaturization (use of a microbore 10 mm id or capillary 01ndash05 mm id column) is also beneficial as far as dilution and sensitivity are concerned in addition reduced mobile-phase flow rates (microL to the nL range) avoids flow splitting prior to the MS source In LCtimesLCndashMS platforms a fast MS acquisition rate is often necessary since the 2D separation can be very rapid and peak widths characterized by a few seconds or less are not unusual To adequately sample the 2D effluent the mass analyser should be capable of acquiring at least 6ndash10 data points per peak

Maximizing the resolution is beneficial for subsequent MS detection since it alleviates ion suppression effects due to insufficient separation which may cause high abundant species to obscure the detection of the less abundant On the other hand the potential spreading of minor peaks over too many fractions must be considered since high sampling rates may reduce the concentration of low abundant components and therefore hamper their detection

LCtimesLCndashMS Applications for Triacylglycerol Analysis In the last few years comprehensive two-dimensional systems in combination with mass spectrometry have been investigated for TAG separation in various food samples namely

SeC

tio

n 2

LC

-MS

SPOnSORED

Measurement of Chloramphenicol in Honey with LC-MS-MS

Measurement of Chloramphenicol in HoneyUsing Automated Sample Preparation with LC-MSMSCatherine Lafontaine Yang Shi Francois Espourteille Thermo Fisher Scientific Franklin MA USA

IntroductionChloramphenicol (CAP) (Figure 1) is a bacteriostaticantimicrobial previously used in veterinary medicine CAPhas been found to be potentially carcinogenic whichmakes it an unacceptable substance for use with any food-producing animals including honey bees The UnitedStates Canada and the European Union (EU) as well asmany other countries have completely banned the usageof CAP in the production of food The EU has set aminimum required performance level (MRPL) for CAP infood of animal origin at a level of 03 microgkg1

Currently sample preparation for the detection of CAPin honey by liquid chromatography-mass spectrometry(LC-MSMS) involves complex offline extraction methodssuch as solid phase extraction QuEChERS orliquidliquid extraction all of which require additionalsample concentration and reconstitution in an appropriatesolvent These sample preparation methods are time-consuming often taking 2 hours or more per sample andare more vulnerable to variability due to errors in manualpreparation To offer a high sensitivity (low ppbs) CAPdetection method and timely automated analysis ofmultiple samples our approach is to use the ThermoScientific Aria TLX-1 system powered by TurboFlowtrade

automated sample preparation technology coupled to thedetection capabilities of a high-sensitivity ThermoScientific TSQ Vantage triple stage quadrupole massspectrometer

Figure 1 Chemical structure of chloramphenicol

GoalDevelop a quick automated sample preparation LC-MSMS method for chloramphenicol (CAP) in honeyby negative ion heated electrospray ionization (H-ESI)using a deuterated internal standard (CAP-d5)

Experimental

Sample PreparationOrganic wildflower honey used in this analysis for thepreparation of blanks QCs and standards was obtainedfrom a local supermarket CAP was obtained from Sigma-Aldrich US (Fluka) and CAP-d5 (100 microgmL inacetonitrile) from Cambridge Isotope Labs Inc (AndoverMA USA) A CAP working solution was prepared in 11methanolwater at 100 ngmL The honey was diluted byadding 30 mL of purified water to 10 g of honey (13 wv) CAP standards and QC standards were seriallydiluted to the target concentrations with 13 honeywatercontaining 250 pgmL CAP-d5 as an internal standardTarget standard concentrations ranged from 0024 microgkgto 15 microgkg Four samples of honey obtainedinternationally and one sample obtained from a localgrocery store were analyzed as ldquosamplesrdquo and prepared bydissolving 5 g of honey in 15 mL of purified water Theinternal standard was added to a final concentration of250 pgmL The injection volume was 25 microL

MethodThe honey extract clean-up was accomplished using theThermo Scientific TurboFlow method run on an Ariatrade

TLX-1 LC system using a TurboFlow Cyclone polymer-based extraction column Simple sugars were un-retainedand moved to waste during the loading step while theanalyte of interest was retained on the extraction columnThis was followed by organic elution to a ThermoScientific Hypersil GOLD end-capped silica-based C18reversed-phase analytical column and gradient elution to aTSQ Vantagetrade triple stage quadrupole MS with a H-ESIsource CAP precursor mz 321 rarr 257 152 and 194 high resolution selective reaction monitoring (H-SRM) transitions were monitored in the negativeionization mode The 257 mz product ion for CAP wasused for quantitation and the 152 and 194 mz productions were used as confirmation Precursor 326 mz rarr 157mz and 262 mz H-SRM transitions were monitored forCAP-d5 The total LC-MSMS method run time wasabout 5 minutes

Key Words

bull Aria TLX-1

bull TurboFlowtechnology

bull TSQ Vantagemassspectrometer

bull Food safety

ApplicationNote 473

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article1measure_chlorapdf

8

rice oil (24) soybean and linseed oils (25) donkey milk (26) and corn oil (27) using SIC- in the first dimension (1D) and nARP-LC in 2D respectively The two separation modes are based on different retention mechanisms and hence the column combination can be considered as entirely orthogonal For 1D separation either a microbore (1 mm id) or a narrow-bore column (21 mm id) were employed both lab-silvered using a nucleosil 5-SA (strong cation exchange) column In most cases (24ndash26) n-hexane modified with a small amount of acetonitrile was used in 1D whereas isopropanol and acetonitrile in a gradient programme were used in 2D The issues related to solvent incompatibility and analyte-focusing were solved by using a microbore column with a very low flow rate in the 1D and by decreasing the percentage of the weaker solvent (acetonitrile) in the 2D The 2D chromatograms were characterized by the formation of group-type patterns with TAGs located in characteristic positions in relation to their Pn and DB values With regards to MS conditions a data acquisition rate of 5 Hz and a mass scan range of 400ndash900 amu allowed the acquisition of approximately 10 spectra for peaks of approximately 2 sec duration the spectral production frequency was sufficient for reliable peak identification An innovative LCtimesLC system has recently been investigated by van der Klift et al (27) for the analysis of a corn oil sample In this work TAGs could be rapidly and efficiently separated with a methanol-based solvent on an Ag-coated ion exchanger avoiding the use of hexane and enabling peak focusing at the head of the 2D column In terms of detection the authors compared UV evaporative light scattering detector (ELSD) and APCI-MS with the aim of improving the accuracy and precision of TAG quantitation APCI-MS TIC data were processed both manually and automatically from the untransformed LCtimesLC chromatograms (Figure 4) After correction with literature-derived response factors the quantitative values obtained were compared with values previously reported for corn oil TAGs by GCndashFID analysis The main trend coincided but significant deviations were observed for individual components This was probably caused by the use of correction factors obtained under different experimental conditions (both chromatographic and MS parameters) However in terms of peak overlap the developed LCtimesLC-APCI-MS system showed a remarkable increase in peak capacity with respect to one-dimensional techniques and was of great help in the qualitative and quantitative determination of the TAG fraction in the complex food sample tested

LCtimesLCndashMS Applications for Carotenoid Analysis Different LCtimesLCndashPDAndashAPCI-MS systems were investigated to elucidate the carotenoid

composition of complex food samples either on free carotenoids attained after a saponification step or on the native forms (28ndash31) In the first approach a silica microbore column operated under normal phase (nP) conditions was coupled to a C18 monolithic

Figure 4 Contour plots of a corn oil sample constructed on the basis of the TIC chromatogram (a) total contour plot and (b) expansion of the contour plot in (a) Adapted

and reprinted from Journal of Chomatography A 1178(1ndash2) 43ndash55 (2008) EJC van der Klift G Vivo-Truyols FW

Claassen FL van Holthoon and TA van Beek Comprehensive Two-dimensional Liquid Chromatography with Ultraviolet

Evaporative Light Scattering and Mass Spectrometric Detection of Triacylglycerols in Corn Oil Copyright 2008 with

permission from Elsevier

9

column under RP conditions (28) In the second set-up a cyano microbore column operated under nP conditions was coupled to either a C18 monolithic (2930) or shell-packed column (31) under RP conditions In the 1D n-hexanebutylacetateacetone 80155 (vvv) and n-hexane were used whereas 2-propanol and 20 water in acetonitrile (vv) were employed in the 2D

Under nP-LC conditions free carotenoids are separated into groups of different polarity from the non-polar carotenes up to the polar polyols In the RP-LC mode carotenoids are eluted according to their increasing hydrophobicity and decreasing polarity In all cases the use of two detection systems namely PDA and MS proved to be a mandatory tool for carotenoid identification Concerning MS conditions in three out of four set-ups tested a quadrupole system in the mass range of 250ndash1300 mz was employed while for the most recent application an IT-TOF mass spectrometer in the mass range of 200ndash1200 mz both equipped with an APCI interface In the most recent work special attention was devoted to the elucidation of the epoxycarotenoid fraction whose composition could be a useful parameter to evaluate juice age and freshness (31) In fact re-arrangements from 56- (violaxanthin antheraxanthin) to 58-epoxides (luteoxanthin mutatoxanthin) can occur with time partially due to the natural acidity of the juice which can affect the juice freshness The attained MS and UV spectra were purer as a result of the higher LCtimesLC separation power with respect to conventional LC thus highlighting the power of the LCtimesLC-APCI-MS approach (31)

LCtimesLCndashMS Applications for Polyphenol Analysis Polyphenol content in many food samples is high and highly variable for this reason conventional LC techniques are often insufficient for complete characterization Thus LCtimesLCndashMS techniques were considered for the study of such compounds in beer (32) wine and juices (3334) as well as apple and cocoa extracts (35) Hajek et al optimized an LCtimesLC method for the analysis of polyphenols using UV electrochemical coulometric and MS detection (32) A polyethylene glycol (PEG) column was used in the 1D and different C18 and C8 stationary phases were tested in the 2D The combination of the columns tested under matching gradient profiles provided a high degree of orthogonality for 27 natural antioxidants A similar set-up in combination with PDA and MS (ESI-IT-TOF) detection has been investigated (33) for the separation of polyphenolic antioxidants in a commercial red wine A microphenyl column in the 1D while a partially porous C18 and a monolithic C18 column of identical dimensions (30 times 46 mm 27 microm) were compared for the 2D separation

The high resolution and accuracy of the IT-TOF-MS was beneficial for identification with an ESI source operated under both positive and negative ionization conditions the general MS

10

accuracy was lower than 31 ppm A novel RPLCtimesRPLC system was developed (34) for the quantification of polyphenolic antioxidants in wine and juice In the configuration described the well separated components in the 1D were directed to the detector while the more complex part of the sample was diverted to the 2D via a ten-port valve Two C18 columns the second with an ion-pair reagent (tetrapentylammonium bromide) were used Compound identification was performed using LCndashESI-TOF-MS for primary-column analytes since the ion-pair reagent used in the 2D was not compatible with MS A comprehensive HILICtimesRPLC approach was investigated by Kalili and de Villiers for the analysis of procyanidins in cocoa and apple extracts (35) Depending on the degree of polymerization these structures composed of flavan-3-ol monomeric units can be very complex and their separation challenging Oligomeric procyanidins were separated according to molecular weight using a HILIC and RP-LC columns respectively in the 1D and 2D The combination of the two separation modes provided very high orthogonality and a significant improvement in the resolution of oligomeric procyanidin isomers (Figure 5) Positive confirmation was then achieved by the combination of both MS and fluorescence data dramatically decreasing the probability of false identification

ConclusionsIn recent years there has been a notable increase in the amount of literature pertaining to LCndashMS analysis of several food products Several methodologies have been developed to detect identify and quantify various food-related naturally occurring substances Instrumentation incorporating ESI sources has recently come to dominate many areas of MS Predictably both ESI-MS and MALDI-MS will continue to have expanding roles in the future It is expected that the automation of the entire LCndashMS system (benchtop instrumentation inclusive of on-line sampling treatment) will

favour its diffusion for routine analysis In this scenario scientists involved in producing new analytical instrumentation and developing new analytical methods play a crucial role in order to give a correct answer to these new needs and expectations

Francesco Cacciola12 Paola Donato31 Marco Beccaria1 Paola Dugo13 and Luigi Mondello13

1 Dipartimento Farmaco-chimico Universitagrave degli Studi di Messina Messina Italy2 Chromaleont srl A spin-off of the University of Messina co Dipartimento Farmaco-chimico Universitagrave degli Studi di Messina Messina Italy

3 Centro Integrato di Ricerca (CIR) Universitagrave Campus Bio-Medico Roma Italy

How to Cite this Article

F Cacciola P Donato M Beccaria P Dugo and L Mondello ldquoAdvances in LC-MS for Food Analysisrdquo LCGC Europe 25(s5) ldquoAdvances in Food Analysisrdquo supplement 15ndash24 (2012)

Figure 5 Identification of dimeric and trimeric procyanidins by alignment of RP-LCndashMS extracted ion chromatograms with the relevant section of the fluorescence contour plot Adapted and reprinted from Journal of Chromatography A 1216(35) 6274ndash6284 (2009) KM Kalili and A de Villiers

Off-line comprehensive 2-dimensional hydrophilic interactiontimesreversed phase liquid chromatography analysis of

procyanidins Copyright 2009 with permission from Elsevier

21

18

15

12

100

04613

5773

5773

100

0

9902

900 1000 1100

1153711537

11537

1200 1300 1400

900 1000 1100 1200 1300 1400

1069

8655

8655

8655

4073

5773

11537

57737375

mz = 8655

mz = 5773

Time

Time

57738645

1202 1369

11

References(1) H-D Belitz and W Grosch Food Chemistry Springer-Verlag Berlin (1999)(2) M Careri F Bianchi and C Corradini J Chromatogr A 970(1ndash2) 3ndash64 (2002) (3) P Dugo F Cacciola T Kumm G Dugo and L Mondello J Chromatogr A 1184(1ndash2) 353ndash368 (2008)(4) SH Hoke II KL Morand KD Greis TR Baker KL Harbol and RLM Dobson Int J Mass Spectrom 212(1ndash3)

135ndash196 (2001)(5) SS Cai KA Hanold and JA Syage Anal Chem 79(6) 2491ndash2498 (2007) (6) M Wilm and M Mann Anal Chem 68 1ndash8 (1996) (7) WC Byrdwell EA Emken WE Neff and RO Adlof Lipids 31(9) 919ndash935 (1996) (8) M Lisa and M Holcapek J Chromatogr A 1198ndash1199 115ndash130 (2008)(9) M Lisa H Velinska and M Holcapek Anal Chem 81(10) 3903ndash3910 (2009)(10) NL Leveque S Heron and A Tchapla J Mass Spectrom 45(3) 284ndash296 (2010)(11) M Malone and JJ Evans Lipids 39(3) 273ndash284 (2004)(12) JM Castro-Perez J Kamphorst J DeGroot F Lafeber J Goshawk K Yu JP Shockcor RJ Vreeken and T Hanke-

meier J Proteome Res in press (101021pr901094j) (13) CE Scott and AL Eldridge J Food Comp Anal 18(6) 551ndash559 (2005)(14) F Khachik Analysis of carotenoids in nutritional studies in Carotenoids Nutrition and Health (Vol 5) G Britton S

Liaaen-Jensen and H Pfander Eds (Basel Boston Berlin Birkhauser Verlag) 7ndash44 (2009)(15) Q Su KG Rowley and NDH Balazs J Chromatogr B 781(1ndash2) 393ndash418 (2002) (16) SM Rivera and R Canela-Garayoa J Chromatogr A 1224 1ndash10 (2012)(17) M Ganzera Electrophoresis 29(17) 3489ndash3503 (2008)(18) V Garciacutea-Canas and A Cifuentes Electrophoresis 29(1) 294ndash309 (2008)(19) BF Zimmermann SG Walch LN Tinzoh W Stuumlhlinger and DW Lachenmeier J Chromatogr B 879(24) 2459ndash

2464 (2011)(20) P Dugo F Cacciola P Donato R Assis Jacques E Bastos Caramatildeo and L Mondello J Chromatogr A 1216(43)

7213ndash7221 (2009)(21) FW McLafferty Int J Mass Spectrom 212(1ndash3) 81ndash87 (2001)(22) RW Kondrat Int J Mass Spectrom 212(1ndash3) 89ndash95 (2001)(23) K Horvath J Fairchild and G Guiochon J Chromatogr A 1216(12) 2511ndash2518 (2009)(24) L Mondello PQ Tranchida V Stanek P Jandera G Dugo and P Dugo J Chromatogr A 1086(1ndash2) 91ndash98

(2005) (25) P Dugo T Kumm ML Crupi A Cotroneo and L Mondello J Chromatogr A 1112(1ndash2) 269ndash275 (2006)(26) P Dugo T Kumm B Chiofalo A Cotroneo and L Mondello J Sep Sci 29(8) 1146ndash1154 (2006)(27) EJC van der Klift G Vivo-Truyols FW Claassen FL van Holthoon and TA van Beek J Chromatogr A 1178(1ndash2)

43ndash55 (2008)

12

(28) P Dugo V Skerikova T Kumm A Trozzi P Jandera and L Mondello Anal Chem 78(22) 7743ndash7750 (2006)(29) P Dugo M Herrero T Kumm D Giuffrida G Dugo and L Mondello J Chromatogr A 1189(1ndash2) 196ndash206 (2008)(30) P Dugo M Herrero D Giuffrida T Kumm and L Mondello J Agric Food Chem 56(10) 3478ndash3485 (2008)(31) P Dugo D Giuffrida M Herrero P Donato and L Mondello J Sep Sci 32(7) 973ndash980 (2009)(32) T Hajek V Skerikova P Cesla K Vynuchalova and P Jandera J Sep Sci 31(19) 3309ndash3328 (2008)(33) P Dugo F Cacciola M Herrero P Donato and L Mondello J Sep Sci 31(19) 3297ndash3308 (2008)(34) M Kivilompolo and T Hyotylainen J Chromatogr A 1145(1ndash2) 155ndash164 (2007)(35) KM Kalili and A de Villiers J Chromatogr A 1216(35) 6274ndash6284 (2009)

9

column under RP conditions (28) In the second set-up a cyano microbore column operated under nP conditions was coupled to either a C18 monolithic (2930) or shell-packed column (31) under RP conditions In the 1D n-hexanebutylacetateacetone 80155 (vvv) and n-hexane were used whereas 2-propanol and 20 water in acetonitrile (vv) were employed in the 2D

Under nP-LC conditions free carotenoids are separated into groups of different polarity from the non-polar carotenes up to the polar polyols In the RP-LC mode carotenoids are eluted according to their increasing hydrophobicity and decreasing polarity In all cases the use of two detection systems namely PDA and MS proved to be a mandatory tool for carotenoid identification Concerning MS conditions in three out of four set-ups tested a quadrupole system in the mass range of 250ndash1300 mz was employed while for the most recent application an IT-TOF mass spectrometer in the mass range of 200ndash1200 mz both equipped with an APCI interface In the most recent work special attention was devoted to the elucidation of the epoxycarotenoid fraction whose composition could be a useful parameter to evaluate juice age and freshness (31) In fact re-arrangements from 56- (violaxanthin antheraxanthin) to 58-epoxides (luteoxanthin mutatoxanthin) can occur with time partially due to the natural acidity of the juice which can affect the juice freshness The attained MS and UV spectra were purer as a result of the higher LCtimesLC separation power with respect to conventional LC thus highlighting the power of the LCtimesLC-APCI-MS approach (31)

LCtimesLCndashMS Applications for Polyphenol Analysis Polyphenol content in many food samples is high and highly variable for this reason conventional LC techniques are often insufficient for complete characterization Thus LCtimesLCndashMS techniques were considered for the study of such compounds in beer (32) wine and juices (3334) as well as apple and cocoa extracts (35) Hajek et al optimized an LCtimesLC method for the analysis of polyphenols using UV electrochemical coulometric and MS detection (32) A polyethylene glycol (PEG) column was used in the 1D and different C18 and C8 stationary phases were tested in the 2D The combination of the columns tested under matching gradient profiles provided a high degree of orthogonality for 27 natural antioxidants A similar set-up in combination with PDA and MS (ESI-IT-TOF) detection has been investigated (33) for the separation of polyphenolic antioxidants in a commercial red wine A microphenyl column in the 1D while a partially porous C18 and a monolithic C18 column of identical dimensions (30 times 46 mm 27 microm) were compared for the 2D separation

The high resolution and accuracy of the IT-TOF-MS was beneficial for identification with an ESI source operated under both positive and negative ionization conditions the general MS

10

accuracy was lower than 31 ppm A novel RPLCtimesRPLC system was developed (34) for the quantification of polyphenolic antioxidants in wine and juice In the configuration described the well separated components in the 1D were directed to the detector while the more complex part of the sample was diverted to the 2D via a ten-port valve Two C18 columns the second with an ion-pair reagent (tetrapentylammonium bromide) were used Compound identification was performed using LCndashESI-TOF-MS for primary-column analytes since the ion-pair reagent used in the 2D was not compatible with MS A comprehensive HILICtimesRPLC approach was investigated by Kalili and de Villiers for the analysis of procyanidins in cocoa and apple extracts (35) Depending on the degree of polymerization these structures composed of flavan-3-ol monomeric units can be very complex and their separation challenging Oligomeric procyanidins were separated according to molecular weight using a HILIC and RP-LC columns respectively in the 1D and 2D The combination of the two separation modes provided very high orthogonality and a significant improvement in the resolution of oligomeric procyanidin isomers (Figure 5) Positive confirmation was then achieved by the combination of both MS and fluorescence data dramatically decreasing the probability of false identification

ConclusionsIn recent years there has been a notable increase in the amount of literature pertaining to LCndashMS analysis of several food products Several methodologies have been developed to detect identify and quantify various food-related naturally occurring substances Instrumentation incorporating ESI sources has recently come to dominate many areas of MS Predictably both ESI-MS and MALDI-MS will continue to have expanding roles in the future It is expected that the automation of the entire LCndashMS system (benchtop instrumentation inclusive of on-line sampling treatment) will

favour its diffusion for routine analysis In this scenario scientists involved in producing new analytical instrumentation and developing new analytical methods play a crucial role in order to give a correct answer to these new needs and expectations

Francesco Cacciola12 Paola Donato31 Marco Beccaria1 Paola Dugo13 and Luigi Mondello13

1 Dipartimento Farmaco-chimico Universitagrave degli Studi di Messina Messina Italy2 Chromaleont srl A spin-off of the University of Messina co Dipartimento Farmaco-chimico Universitagrave degli Studi di Messina Messina Italy

3 Centro Integrato di Ricerca (CIR) Universitagrave Campus Bio-Medico Roma Italy

How to Cite this Article

F Cacciola P Donato M Beccaria P Dugo and L Mondello ldquoAdvances in LC-MS for Food Analysisrdquo LCGC Europe 25(s5) ldquoAdvances in Food Analysisrdquo supplement 15ndash24 (2012)

Figure 5 Identification of dimeric and trimeric procyanidins by alignment of RP-LCndashMS extracted ion chromatograms with the relevant section of the fluorescence contour plot Adapted and reprinted from Journal of Chromatography A 1216(35) 6274ndash6284 (2009) KM Kalili and A de Villiers

Off-line comprehensive 2-dimensional hydrophilic interactiontimesreversed phase liquid chromatography analysis of

procyanidins Copyright 2009 with permission from Elsevier

21

18

15

12

100

04613

5773

5773

100

0

9902

900 1000 1100

1153711537

11537

1200 1300 1400

900 1000 1100 1200 1300 1400

1069

8655

8655

8655

4073

5773

11537

57737375

mz = 8655

mz = 5773

Time

Time

57738645

1202 1369

11

References(1) H-D Belitz and W Grosch Food Chemistry Springer-Verlag Berlin (1999)(2) M Careri F Bianchi and C Corradini J Chromatogr A 970(1ndash2) 3ndash64 (2002) (3) P Dugo F Cacciola T Kumm G Dugo and L Mondello J Chromatogr A 1184(1ndash2) 353ndash368 (2008)(4) SH Hoke II KL Morand KD Greis TR Baker KL Harbol and RLM Dobson Int J Mass Spectrom 212(1ndash3)

135ndash196 (2001)(5) SS Cai KA Hanold and JA Syage Anal Chem 79(6) 2491ndash2498 (2007) (6) M Wilm and M Mann Anal Chem 68 1ndash8 (1996) (7) WC Byrdwell EA Emken WE Neff and RO Adlof Lipids 31(9) 919ndash935 (1996) (8) M Lisa and M Holcapek J Chromatogr A 1198ndash1199 115ndash130 (2008)(9) M Lisa H Velinska and M Holcapek Anal Chem 81(10) 3903ndash3910 (2009)(10) NL Leveque S Heron and A Tchapla J Mass Spectrom 45(3) 284ndash296 (2010)(11) M Malone and JJ Evans Lipids 39(3) 273ndash284 (2004)(12) JM Castro-Perez J Kamphorst J DeGroot F Lafeber J Goshawk K Yu JP Shockcor RJ Vreeken and T Hanke-

meier J Proteome Res in press (101021pr901094j) (13) CE Scott and AL Eldridge J Food Comp Anal 18(6) 551ndash559 (2005)(14) F Khachik Analysis of carotenoids in nutritional studies in Carotenoids Nutrition and Health (Vol 5) G Britton S

Liaaen-Jensen and H Pfander Eds (Basel Boston Berlin Birkhauser Verlag) 7ndash44 (2009)(15) Q Su KG Rowley and NDH Balazs J Chromatogr B 781(1ndash2) 393ndash418 (2002) (16) SM Rivera and R Canela-Garayoa J Chromatogr A 1224 1ndash10 (2012)(17) M Ganzera Electrophoresis 29(17) 3489ndash3503 (2008)(18) V Garciacutea-Canas and A Cifuentes Electrophoresis 29(1) 294ndash309 (2008)(19) BF Zimmermann SG Walch LN Tinzoh W Stuumlhlinger and DW Lachenmeier J Chromatogr B 879(24) 2459ndash

2464 (2011)(20) P Dugo F Cacciola P Donato R Assis Jacques E Bastos Caramatildeo and L Mondello J Chromatogr A 1216(43)

7213ndash7221 (2009)(21) FW McLafferty Int J Mass Spectrom 212(1ndash3) 81ndash87 (2001)(22) RW Kondrat Int J Mass Spectrom 212(1ndash3) 89ndash95 (2001)(23) K Horvath J Fairchild and G Guiochon J Chromatogr A 1216(12) 2511ndash2518 (2009)(24) L Mondello PQ Tranchida V Stanek P Jandera G Dugo and P Dugo J Chromatogr A 1086(1ndash2) 91ndash98

(2005) (25) P Dugo T Kumm ML Crupi A Cotroneo and L Mondello J Chromatogr A 1112(1ndash2) 269ndash275 (2006)(26) P Dugo T Kumm B Chiofalo A Cotroneo and L Mondello J Sep Sci 29(8) 1146ndash1154 (2006)(27) EJC van der Klift G Vivo-Truyols FW Claassen FL van Holthoon and TA van Beek J Chromatogr A 1178(1ndash2)

43ndash55 (2008)

12

(28) P Dugo V Skerikova T Kumm A Trozzi P Jandera and L Mondello Anal Chem 78(22) 7743ndash7750 (2006)(29) P Dugo M Herrero T Kumm D Giuffrida G Dugo and L Mondello J Chromatogr A 1189(1ndash2) 196ndash206 (2008)(30) P Dugo M Herrero D Giuffrida T Kumm and L Mondello J Agric Food Chem 56(10) 3478ndash3485 (2008)(31) P Dugo D Giuffrida M Herrero P Donato and L Mondello J Sep Sci 32(7) 973ndash980 (2009)(32) T Hajek V Skerikova P Cesla K Vynuchalova and P Jandera J Sep Sci 31(19) 3309ndash3328 (2008)(33) P Dugo F Cacciola M Herrero P Donato and L Mondello J Sep Sci 31(19) 3297ndash3308 (2008)(34) M Kivilompolo and T Hyotylainen J Chromatogr A 1145(1ndash2) 155ndash164 (2007)(35) KM Kalili and A de Villiers J Chromatogr A 1216(35) 6274ndash6284 (2009)

10

accuracy was lower than 31 ppm A novel RPLCtimesRPLC system was developed (34) for the quantification of polyphenolic antioxidants in wine and juice In the configuration described the well separated components in the 1D were directed to the detector while the more complex part of the sample was diverted to the 2D via a ten-port valve Two C18 columns the second with an ion-pair reagent (tetrapentylammonium bromide) were used Compound identification was performed using LCndashESI-TOF-MS for primary-column analytes since the ion-pair reagent used in the 2D was not compatible with MS A comprehensive HILICtimesRPLC approach was investigated by Kalili and de Villiers for the analysis of procyanidins in cocoa and apple extracts (35) Depending on the degree of polymerization these structures composed of flavan-3-ol monomeric units can be very complex and their separation challenging Oligomeric procyanidins were separated according to molecular weight using a HILIC and RP-LC columns respectively in the 1D and 2D The combination of the two separation modes provided very high orthogonality and a significant improvement in the resolution of oligomeric procyanidin isomers (Figure 5) Positive confirmation was then achieved by the combination of both MS and fluorescence data dramatically decreasing the probability of false identification

ConclusionsIn recent years there has been a notable increase in the amount of literature pertaining to LCndashMS analysis of several food products Several methodologies have been developed to detect identify and quantify various food-related naturally occurring substances Instrumentation incorporating ESI sources has recently come to dominate many areas of MS Predictably both ESI-MS and MALDI-MS will continue to have expanding roles in the future It is expected that the automation of the entire LCndashMS system (benchtop instrumentation inclusive of on-line sampling treatment) will

favour its diffusion for routine analysis In this scenario scientists involved in producing new analytical instrumentation and developing new analytical methods play a crucial role in order to give a correct answer to these new needs and expectations

Francesco Cacciola12 Paola Donato31 Marco Beccaria1 Paola Dugo13 and Luigi Mondello13

1 Dipartimento Farmaco-chimico Universitagrave degli Studi di Messina Messina Italy2 Chromaleont srl A spin-off of the University of Messina co Dipartimento Farmaco-chimico Universitagrave degli Studi di Messina Messina Italy

3 Centro Integrato di Ricerca (CIR) Universitagrave Campus Bio-Medico Roma Italy

How to Cite this Article

F Cacciola P Donato M Beccaria P Dugo and L Mondello ldquoAdvances in LC-MS for Food Analysisrdquo LCGC Europe 25(s5) ldquoAdvances in Food Analysisrdquo supplement 15ndash24 (2012)

Figure 5 Identification of dimeric and trimeric procyanidins by alignment of RP-LCndashMS extracted ion chromatograms with the relevant section of the fluorescence contour plot Adapted and reprinted from Journal of Chromatography A 1216(35) 6274ndash6284 (2009) KM Kalili and A de Villiers

Off-line comprehensive 2-dimensional hydrophilic interactiontimesreversed phase liquid chromatography analysis of

procyanidins Copyright 2009 with permission from Elsevier

21

18

15

12

100

04613

5773

5773

100

0

9902

900 1000 1100

1153711537

11537

1200 1300 1400

900 1000 1100 1200 1300 1400

1069

8655

8655

8655

4073

5773

11537

57737375

mz = 8655

mz = 5773

Time

Time

57738645

1202 1369

11

References(1) H-D Belitz and W Grosch Food Chemistry Springer-Verlag Berlin (1999)(2) M Careri F Bianchi and C Corradini J Chromatogr A 970(1ndash2) 3ndash64 (2002) (3) P Dugo F Cacciola T Kumm G Dugo and L Mondello J Chromatogr A 1184(1ndash2) 353ndash368 (2008)(4) SH Hoke II KL Morand KD Greis TR Baker KL Harbol and RLM Dobson Int J Mass Spectrom 212(1ndash3)

135ndash196 (2001)(5) SS Cai KA Hanold and JA Syage Anal Chem 79(6) 2491ndash2498 (2007) (6) M Wilm and M Mann Anal Chem 68 1ndash8 (1996) (7) WC Byrdwell EA Emken WE Neff and RO Adlof Lipids 31(9) 919ndash935 (1996) (8) M Lisa and M Holcapek J Chromatogr A 1198ndash1199 115ndash130 (2008)(9) M Lisa H Velinska and M Holcapek Anal Chem 81(10) 3903ndash3910 (2009)(10) NL Leveque S Heron and A Tchapla J Mass Spectrom 45(3) 284ndash296 (2010)(11) M Malone and JJ Evans Lipids 39(3) 273ndash284 (2004)(12) JM Castro-Perez J Kamphorst J DeGroot F Lafeber J Goshawk K Yu JP Shockcor RJ Vreeken and T Hanke-

meier J Proteome Res in press (101021pr901094j) (13) CE Scott and AL Eldridge J Food Comp Anal 18(6) 551ndash559 (2005)(14) F Khachik Analysis of carotenoids in nutritional studies in Carotenoids Nutrition and Health (Vol 5) G Britton S

Liaaen-Jensen and H Pfander Eds (Basel Boston Berlin Birkhauser Verlag) 7ndash44 (2009)(15) Q Su KG Rowley and NDH Balazs J Chromatogr B 781(1ndash2) 393ndash418 (2002) (16) SM Rivera and R Canela-Garayoa J Chromatogr A 1224 1ndash10 (2012)(17) M Ganzera Electrophoresis 29(17) 3489ndash3503 (2008)(18) V Garciacutea-Canas and A Cifuentes Electrophoresis 29(1) 294ndash309 (2008)(19) BF Zimmermann SG Walch LN Tinzoh W Stuumlhlinger and DW Lachenmeier J Chromatogr B 879(24) 2459ndash

2464 (2011)(20) P Dugo F Cacciola P Donato R Assis Jacques E Bastos Caramatildeo and L Mondello J Chromatogr A 1216(43)

7213ndash7221 (2009)(21) FW McLafferty Int J Mass Spectrom 212(1ndash3) 81ndash87 (2001)(22) RW Kondrat Int J Mass Spectrom 212(1ndash3) 89ndash95 (2001)(23) K Horvath J Fairchild and G Guiochon J Chromatogr A 1216(12) 2511ndash2518 (2009)(24) L Mondello PQ Tranchida V Stanek P Jandera G Dugo and P Dugo J Chromatogr A 1086(1ndash2) 91ndash98

(2005) (25) P Dugo T Kumm ML Crupi A Cotroneo and L Mondello J Chromatogr A 1112(1ndash2) 269ndash275 (2006)(26) P Dugo T Kumm B Chiofalo A Cotroneo and L Mondello J Sep Sci 29(8) 1146ndash1154 (2006)(27) EJC van der Klift G Vivo-Truyols FW Claassen FL van Holthoon and TA van Beek J Chromatogr A 1178(1ndash2)

43ndash55 (2008)

12

(28) P Dugo V Skerikova T Kumm A Trozzi P Jandera and L Mondello Anal Chem 78(22) 7743ndash7750 (2006)(29) P Dugo M Herrero T Kumm D Giuffrida G Dugo and L Mondello J Chromatogr A 1189(1ndash2) 196ndash206 (2008)(30) P Dugo M Herrero D Giuffrida T Kumm and L Mondello J Agric Food Chem 56(10) 3478ndash3485 (2008)(31) P Dugo D Giuffrida M Herrero P Donato and L Mondello J Sep Sci 32(7) 973ndash980 (2009)(32) T Hajek V Skerikova P Cesla K Vynuchalova and P Jandera J Sep Sci 31(19) 3309ndash3328 (2008)(33) P Dugo F Cacciola M Herrero P Donato and L Mondello J Sep Sci 31(19) 3297ndash3308 (2008)(34) M Kivilompolo and T Hyotylainen J Chromatogr A 1145(1ndash2) 155ndash164 (2007)(35) KM Kalili and A de Villiers J Chromatogr A 1216(35) 6274ndash6284 (2009)

11

References(1) H-D Belitz and W Grosch Food Chemistry Springer-Verlag Berlin (1999)(2) M Careri F Bianchi and C Corradini J Chromatogr A 970(1ndash2) 3ndash64 (2002) (3) P Dugo F Cacciola T Kumm G Dugo and L Mondello J Chromatogr A 1184(1ndash2) 353ndash368 (2008)(4) SH Hoke II KL Morand KD Greis TR Baker KL Harbol and RLM Dobson Int J Mass Spectrom 212(1ndash3)

135ndash196 (2001)(5) SS Cai KA Hanold and JA Syage Anal Chem 79(6) 2491ndash2498 (2007) (6) M Wilm and M Mann Anal Chem 68 1ndash8 (1996) (7) WC Byrdwell EA Emken WE Neff and RO Adlof Lipids 31(9) 919ndash935 (1996) (8) M Lisa and M Holcapek J Chromatogr A 1198ndash1199 115ndash130 (2008)(9) M Lisa H Velinska and M Holcapek Anal Chem 81(10) 3903ndash3910 (2009)(10) NL Leveque S Heron and A Tchapla J Mass Spectrom 45(3) 284ndash296 (2010)(11) M Malone and JJ Evans Lipids 39(3) 273ndash284 (2004)(12) JM Castro-Perez J Kamphorst J DeGroot F Lafeber J Goshawk K Yu JP Shockcor RJ Vreeken and T Hanke-

meier J Proteome Res in press (101021pr901094j) (13) CE Scott and AL Eldridge J Food Comp Anal 18(6) 551ndash559 (2005)(14) F Khachik Analysis of carotenoids in nutritional studies in Carotenoids Nutrition and Health (Vol 5) G Britton S

Liaaen-Jensen and H Pfander Eds (Basel Boston Berlin Birkhauser Verlag) 7ndash44 (2009)(15) Q Su KG Rowley and NDH Balazs J Chromatogr B 781(1ndash2) 393ndash418 (2002) (16) SM Rivera and R Canela-Garayoa J Chromatogr A 1224 1ndash10 (2012)(17) M Ganzera Electrophoresis 29(17) 3489ndash3503 (2008)(18) V Garciacutea-Canas and A Cifuentes Electrophoresis 29(1) 294ndash309 (2008)(19) BF Zimmermann SG Walch LN Tinzoh W Stuumlhlinger and DW Lachenmeier J Chromatogr B 879(24) 2459ndash

2464 (2011)(20) P Dugo F Cacciola P Donato R Assis Jacques E Bastos Caramatildeo and L Mondello J Chromatogr A 1216(43)

7213ndash7221 (2009)(21) FW McLafferty Int J Mass Spectrom 212(1ndash3) 81ndash87 (2001)(22) RW Kondrat Int J Mass Spectrom 212(1ndash3) 89ndash95 (2001)(23) K Horvath J Fairchild and G Guiochon J Chromatogr A 1216(12) 2511ndash2518 (2009)(24) L Mondello PQ Tranchida V Stanek P Jandera G Dugo and P Dugo J Chromatogr A 1086(1ndash2) 91ndash98

(2005) (25) P Dugo T Kumm ML Crupi A Cotroneo and L Mondello J Chromatogr A 1112(1ndash2) 269ndash275 (2006)(26) P Dugo T Kumm B Chiofalo A Cotroneo and L Mondello J Sep Sci 29(8) 1146ndash1154 (2006)(27) EJC van der Klift G Vivo-Truyols FW Claassen FL van Holthoon and TA van Beek J Chromatogr A 1178(1ndash2)

43ndash55 (2008)

12

(28) P Dugo V Skerikova T Kumm A Trozzi P Jandera and L Mondello Anal Chem 78(22) 7743ndash7750 (2006)(29) P Dugo M Herrero T Kumm D Giuffrida G Dugo and L Mondello J Chromatogr A 1189(1ndash2) 196ndash206 (2008)(30) P Dugo M Herrero D Giuffrida T Kumm and L Mondello J Agric Food Chem 56(10) 3478ndash3485 (2008)(31) P Dugo D Giuffrida M Herrero P Donato and L Mondello J Sep Sci 32(7) 973ndash980 (2009)(32) T Hajek V Skerikova P Cesla K Vynuchalova and P Jandera J Sep Sci 31(19) 3309ndash3328 (2008)(33) P Dugo F Cacciola M Herrero P Donato and L Mondello J Sep Sci 31(19) 3297ndash3308 (2008)(34) M Kivilompolo and T Hyotylainen J Chromatogr A 1145(1ndash2) 155ndash164 (2007)(35) KM Kalili and A de Villiers J Chromatogr A 1216(35) 6274ndash6284 (2009)

12

(28) P Dugo V Skerikova T Kumm A Trozzi P Jandera and L Mondello Anal Chem 78(22) 7743ndash7750 (2006)(29) P Dugo M Herrero T Kumm D Giuffrida G Dugo and L Mondello J Chromatogr A 1189(1ndash2) 196ndash206 (2008)(30) P Dugo M Herrero D Giuffrida T Kumm and L Mondello J Agric Food Chem 56(10) 3478ndash3485 (2008)(31) P Dugo D Giuffrida M Herrero P Donato and L Mondello J Sep Sci 32(7) 973ndash980 (2009)(32) T Hajek V Skerikova P Cesla K Vynuchalova and P Jandera J Sep Sci 31(19) 3309ndash3328 (2008)(33) P Dugo F Cacciola M Herrero P Donato and L Mondello J Sep Sci 31(19) 3297ndash3308 (2008)(34) M Kivilompolo and T Hyotylainen J Chromatogr A 1145(1ndash2) 155ndash164 (2007)(35) KM Kalili and A de Villiers J Chromatogr A 1216(35) 6274ndash6284 (2009)

1

Advances in GCndashMS for Food Analysis

By Peter Quinto Tranchida Paola Dugo and Luigi Mondello

GC

-MS

Food products are usually of a highly complex nature and are composed of organic material (fats sugars proteins and vitamins) and inorganic material (water and minerals) Apart from natural constituents foods can contain xenobiotic compounds

deriving from a variety of sources including the environment packaging agrochemical treatments etc Many xenobiotic compounds can have a profound negative effect on human health mdash even at trace concentration levels

A gas chromatography-mass spectrometry (GCndashMS) analysis of a food can vary in scope For example a GCndashMS method can be used for the qualitativequantitative analysis of untargeted volatiles (for example elucidation of an aroma profile) or targeted ones (such as pesticides) Furthermore a GCndashMS method can also be exploited for the generation of a chromatography profile (fingerprinting) with the aim of distinguishing between food samples of the same type (for example to determine geographical origin) In such studies the exploitation of statistical methods is almost obligatory However for almost any purpose a GCndashMS technique must be both sensitive and selective as well as possessing a decent separation power and speed The extent to which one or more of the aforementioned features prevails is dependent on the initial analytical objective

An overview of important gas chromatographyndashmass spectrometry (GCndashMS) techniques currently used in food analysis is described Considerable attention is devoted to the use of the mass spectrometer in relation to its potential for separation and identification The importance of comprehensive two-dimensional GC (GCtimesGC) is also discussed

2

Current one-dimensional GC approaches are generally based on the use of a 30 m times 025 mm times 025 microm column which generates peak capacities in the 400ndash600 range and are the most commonly exploited tools for the separation of food volatiles One can expect to fully-resolve around 80ndash100 analytes using such a capillary column (compound more compound less) However because food samples are generally of moderate-to-high complexity then the occurrence of solute co-elution at the column outlet is common leading to difficulties or possible errors in the identification and quantification of specific components

In the GCndashMS field most analysts are located in one of two groups On the one hand there are the many separation scientists who are mainly GC specialists and devote their time almost entirely to the optimization of the separation step and tend to treat the MS instrument as a simple detector Such an approach is fine if the ion source receives totally-isolated solutes identified commonly by using dedicated MS databases Problems arise when peak overlapping occurs hence demanding a deeper exploitation of the MS step (for example by using peak deconvolution methodologies extracted ions or knowledge of MS fragmentation processes) On the other hand several MS specialists pay little attention to the GC process and prefer to circumvent a poor GC separation by exploiting a mass-analysing second dimension multi-compound bands are transformed into a bunch of ions that are resolved and detected on a mass basis It is obvious however that in the case of extensive co-elution the reliability of the qualitativequantitative results can be hampered In truth both analytical dimensions are complementary and should be pushed to their full capacities

One-Dimensional GC-Based ProcessesIn this section a series of recent GCndashMS food applications will be described in which different types of MS systems have been used Emphasis will be directed to the potential of the MS analytical step which is often exploited to a greater extent in the presence of a single GC dimension Cajka et al used a high resolution time-of-flight mass spectrometer (HR ToF MS) connected to a 10 m times 053 mm times 05 microm ldquo5 phenylrdquo column for the target analysis of 111 pesticides in baby foods (1) The short mega-bore column was used to exploit the low pressure (LP) conditions created by the mass spectrometer increasing the optimum gas linear velocity

A QuEChERS (quick easy cheap effective rugged and safe) method was used for sample preparation while a programmed temperature vaporizor (PTV) was employed as injection system The GC step was a fast (1075 min total run time) and low resolution one hence higher demands were put on the high resolution MS process The HR ToF MS instrument used operated under electron-ionization (EI) conditions was reported to have a mass resolution of approximately

Pesticide Analysis in Green Tea with QuEChERS and GC-MSn

SPOnSOREd

Multi-residue Pesticide Analysis in Green Tea by a Modified QuEChERS Extraction and Ion Trap GCMSn AnalysisDavid Steiniger Guiping Lu Jessie Butler Eric Phillips Yolanda Fintschenko Thermo Fisher Scientific Austin TX USA

Introduction

Recently formulated pesticides are quite different in theirphysical properties from their predecessors such as 44-DDTMost of these newer pesticides are smaller in molecularweight and were designed to break down rapidly in theenvironment Therefore to successfully identify andquantify these compounds in foods more carefulconsideration must be placed on the sample preparationfor extraction and the instrument parameters for analysisThis study will cover the preparation of extracts and theoptimization of the analytical parameters of the splitlessinjection separation and detection

The determination of pesticides in fruits vegetablesgrains and herbs has been simplified by a new samplepreparation method QuEChERS (Quick Easy CheapEffective Rugged and Safe) published recently as AOACMethod 2007011 The sample preparation is simplified byusing a single step buffered acetonitrile (MeCN) extractionand liquid-liquid partitioning from water in the sample bysalting out with sodium acetate and magnesium sulfate(MgSO4)1 QuEChERS can be used to prepare green teasamples for analysis by gas chromatographytandem massspectrometry (GCMSn) on the Thermo Scientific ITQ 700GC-ion trap mass spectrometer

The study was performed to determine the linear rangesquantitation limits and detection limits for a partial list ofpesticides that are commonly used on green tea cropsprepared in matrix using the QuEChERS sample preparationguidelines A splitless injection of 22 pesticides was madein a single injection with detection in electron ionization(EI) MSMS Since the extracts were prepared in MeCN asolvent exchange was made to hexaneacetone (91) priorto conventional splitless injection2 Once the calibrationcurve was constructed multiple matrix spikes were analyzedat levels of 375 75 150 225 600 or 1200 ngg (ppb)and low level spikes of 75 15 375 75 or 300 ngg (ppb)to verify the precision and accuracy of the analyticalmethod These concentrations were chosen based on therequirements of various regulatory agencies

Experimental Conditions

The sample preparation involves careful homogenizationof the sample Extraction solvents must be buffered andthe powdered reagents measured at appropriate amountsfor the size of sample prepared Some reagents cause anexothermic reaction when mixed with water which canadversely affect the recoveries of target compounds Therecommended consumables required for sample

preparation and analysis were rigorously tested (Table 1)A list of the pesticides to be studied was created thatwould address all of the various functional groups anddifferent physical properties of most pesticides MSn

parameters were optimized with the use of variable buffergas the testing of the isolation efficiency and adjustmentof the Collision Induced Dissociation (CID) voltage Asurge splitless injection was made into a Thermo ScientificTRACE TR-Pesticide III 35 diphenyl65 dimethylpolysiloxane column (025 mm x 30 meter and a filmthickness of 025 microm with a 5 m guard column)

Key Words

bull ITQ 700

bull Food Safety

bull GCMSn

bull Green Tea

bull PesticideResidues

bull QuEChERS

Technical Note 10295

Item Descriptions

TRACEtrade TR-Pesticide III 35 diphenyl65 dimethyl polysiloxane column025 mm x 30 meter 025 microm w 5 m guard column

5 mm ID x 105 mm liner (pk of 5)

10 microL syringe

Septa (pk of 50)

Liner graphite seal (pk of 10)

Ion volume EI open

Ion volume holder

Graphite ferrule 01-025 mm (pk of 10)

Ferrule 04 mm ID 116 GV (pk of 10)

Blank vespel ferrule for MS interface (pk of 10)

2 mL amber glass vial silanized glass with write-on patch (pk of 100)

Blue cap with ivory PTFEred rubber seal (pk of 100)

Acetonitrile analytical grade (4L)

Hexane GC Resolv (4L)

Acetone GC Resolv (4L)

Organic bottle top dispenser

HPLC grade glacial acetic acid

50 mL Nalgene FEP centrifuge tubes (pk of 2)

Clean up tube15 mL tube ENVIRO 900 mg MgSO4300 mg PSA 150 mg C18 (pk of 50)

50 mL PP Tubes 6 g MgSO4 15 g CH3CHOONa (anhydrous) (pk of 250)

Clean up tube 2 mL tubes 150 mg MgSO4 50 mg PSA 50 mg C18 (pk of 100)

Table 1 Consumables for QuEChERS sample preparation and GCMS analysis

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article2residue_teapdf

2

Current one-dimensional GC approaches are generally based on the use of a 30 m times 025 mm times 025 microm column which generates peak capacities in the 400ndash600 range and are the most commonly exploited tools for the separation of food volatiles One can expect to fully-resolve around 80ndash100 analytes using such a capillary column (compound more compound less) However because food samples are generally of moderate-to-high complexity then the occurrence of solute co-elution at the column outlet is common leading to difficulties or possible errors in the identification and quantification of specific components

In the GCndashMS field most analysts are located in one of two groups On the one hand there are the many separation scientists who are mainly GC specialists and devote their time almost entirely to the optimization of the separation step and tend to treat the MS instrument as a simple detector Such an approach is fine if the ion source receives totally-isolated solutes identified commonly by using dedicated MS databases Problems arise when peak overlapping occurs hence demanding a deeper exploitation of the MS step (for example by using peak deconvolution methodologies extracted ions or knowledge of MS fragmentation processes) On the other hand several MS specialists pay little attention to the GC process and prefer to circumvent a poor GC separation by exploiting a mass-analysing second dimension multi-compound bands are transformed into a bunch of ions that are resolved and detected on a mass basis It is obvious however that in the case of extensive co-elution the reliability of the qualitativequantitative results can be hampered In truth both analytical dimensions are complementary and should be pushed to their full capacities

One-Dimensional GC-Based ProcessesIn this section a series of recent GCndashMS food applications will be described in which different types of MS systems have been used Emphasis will be directed to the potential of the MS analytical step which is often exploited to a greater extent in the presence of a single GC dimension Cajka et al used a high resolution time-of-flight mass spectrometer (HR ToF MS) connected to a 10 m times 053 mm times 05 microm ldquo5 phenylrdquo column for the target analysis of 111 pesticides in baby foods (1) The short mega-bore column was used to exploit the low pressure (LP) conditions created by the mass spectrometer increasing the optimum gas linear velocity

A QuEChERS (quick easy cheap effective rugged and safe) method was used for sample preparation while a programmed temperature vaporizor (PTV) was employed as injection system The GC step was a fast (1075 min total run time) and low resolution one hence higher demands were put on the high resolution MS process The HR ToF MS instrument used operated under electron-ionization (EI) conditions was reported to have a mass resolution of approximately

Pesticide Analysis in Green Tea with QuEChERS and GC-MSn

SPOnSOREd

Multi-residue Pesticide Analysis in Green Tea by a Modified QuEChERS Extraction and Ion Trap GCMSn AnalysisDavid Steiniger Guiping Lu Jessie Butler Eric Phillips Yolanda Fintschenko Thermo Fisher Scientific Austin TX USA

Introduction

Recently formulated pesticides are quite different in theirphysical properties from their predecessors such as 44-DDTMost of these newer pesticides are smaller in molecularweight and were designed to break down rapidly in theenvironment Therefore to successfully identify andquantify these compounds in foods more carefulconsideration must be placed on the sample preparationfor extraction and the instrument parameters for analysisThis study will cover the preparation of extracts and theoptimization of the analytical parameters of the splitlessinjection separation and detection

The determination of pesticides in fruits vegetablesgrains and herbs has been simplified by a new samplepreparation method QuEChERS (Quick Easy CheapEffective Rugged and Safe) published recently as AOACMethod 2007011 The sample preparation is simplified byusing a single step buffered acetonitrile (MeCN) extractionand liquid-liquid partitioning from water in the sample bysalting out with sodium acetate and magnesium sulfate(MgSO4)1 QuEChERS can be used to prepare green teasamples for analysis by gas chromatographytandem massspectrometry (GCMSn) on the Thermo Scientific ITQ 700GC-ion trap mass spectrometer

The study was performed to determine the linear rangesquantitation limits and detection limits for a partial list ofpesticides that are commonly used on green tea cropsprepared in matrix using the QuEChERS sample preparationguidelines A splitless injection of 22 pesticides was madein a single injection with detection in electron ionization(EI) MSMS Since the extracts were prepared in MeCN asolvent exchange was made to hexaneacetone (91) priorto conventional splitless injection2 Once the calibrationcurve was constructed multiple matrix spikes were analyzedat levels of 375 75 150 225 600 or 1200 ngg (ppb)and low level spikes of 75 15 375 75 or 300 ngg (ppb)to verify the precision and accuracy of the analyticalmethod These concentrations were chosen based on therequirements of various regulatory agencies

Experimental Conditions

The sample preparation involves careful homogenizationof the sample Extraction solvents must be buffered andthe powdered reagents measured at appropriate amountsfor the size of sample prepared Some reagents cause anexothermic reaction when mixed with water which canadversely affect the recoveries of target compounds Therecommended consumables required for sample

preparation and analysis were rigorously tested (Table 1)A list of the pesticides to be studied was created thatwould address all of the various functional groups anddifferent physical properties of most pesticides MSn

parameters were optimized with the use of variable buffergas the testing of the isolation efficiency and adjustmentof the Collision Induced Dissociation (CID) voltage Asurge splitless injection was made into a Thermo ScientificTRACE TR-Pesticide III 35 diphenyl65 dimethylpolysiloxane column (025 mm x 30 meter and a filmthickness of 025 microm with a 5 m guard column)

Key Words

bull ITQ 700

bull Food Safety

bull GCMSn

bull Green Tea

bull PesticideResidues

bull QuEChERS

Technical Note 10295

Item Descriptions

TRACEtrade TR-Pesticide III 35 diphenyl65 dimethyl polysiloxane column025 mm x 30 meter 025 microm w 5 m guard column

5 mm ID x 105 mm liner (pk of 5)

10 microL syringe

Septa (pk of 50)

Liner graphite seal (pk of 10)

Ion volume EI open

Ion volume holder

Graphite ferrule 01-025 mm (pk of 10)

Ferrule 04 mm ID 116 GV (pk of 10)

Blank vespel ferrule for MS interface (pk of 10)

2 mL amber glass vial silanized glass with write-on patch (pk of 100)

Blue cap with ivory PTFEred rubber seal (pk of 100)

Acetonitrile analytical grade (4L)

Hexane GC Resolv (4L)

Acetone GC Resolv (4L)

Organic bottle top dispenser

HPLC grade glacial acetic acid

50 mL Nalgene FEP centrifuge tubes (pk of 2)

Clean up tube15 mL tube ENVIRO 900 mg MgSO4300 mg PSA 150 mg C18 (pk of 50)

50 mL PP Tubes 6 g MgSO4 15 g CH3CHOONa (anhydrous) (pk of 250)

Clean up tube 2 mL tubes 150 mg MgSO4 50 mg PSA 50 mg C18 (pk of 100)

Table 1 Consumables for QuEChERS sample preparation and GCMS analysis

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article2residue_teapdf

3

7000 and was operated at an acquisition frequency of 4 Hz which was considered sufficient for quantification purposes With only a few exceptions the limits of quantification were le 001 mg

Kg Pesticide identification was performed exploiting mass spectral deconvolution while quantification was performed by using extracted ions with a 002 da mass window A disadvantage of the proposed approach appeared in the low resolving power of the capillary column (circa 20000 n) as can be observed in Figure 1(a) which reports extracted-ion chromatogram segments relative to the separations of (mz = 180938) HCH (hexachlorocyclohexane) (mz = 235008) ddd (dichlorodiphenyldichloroethane)ddT (dichlorodiphenyltrichloroethane) and (mz = 323024) difenoconazole isomers a series of co-elutions do occur The use of a conventional GC column (circa 120000 n) with the sacrifice of speed is probably a betterif slower option [Figure 1(b)]

Triple quadrupole MS instrumentation (MSndashMS analysis) can provide greater selectivity and sensitivity than ldquofull-scanrdquo systems with the requisite of prior knowledge on ldquowhat yoursquore looking forrdquo An MSndashMS analysis is comparable to a selected-ion-monitoring (SIM) one performed by using a single quadrupole MS system but with higher selectivity Koesukwiwat et al performed an LP-GCndashMS-MS analysis using a ldquo5 phenylrdquo mega-bore capillary (10 m times 053 mm times 1 microm) on 150 relevant pesticides in four vegetable foods (2) The GC retention time window ranged from 29 min to 62 min and thus the occurrence of compound overlapping at the low-resolution column outlet was inevitable Again high demands were put on the MS process Twenty-six multiple reaction monitoring (MRM) segments (60 transitions for each segment) were set across a brief time space (26ndash67 min) to cover all the target analytes Two ion transitions were monitored for each of the 150 pesticides with the most intense

ion exploited for quantification purposes and the other for qualitative ones The choice of the precursor ion a process which required a substantial amount of preliminary work privileged higher mass ions The triple quadrupole MS system was operated at a cycle time of about 208 msec (48 Hz) and a dwell time of 25 msec was used for each transition The sensitivity of the method was generally sufficient for the requirement of food pesticide analysis with LCL (lowest calibration level) values down to the 5 ppb level

A fast GCndashMS method was developed by Scandinaro et al for the construction of a novel MS database named EI-MS FampF (electron-impact-MS flavour amp fragrance) (3) The authors reported the use of a micro-bore apolar GC column (10 m times 010 mm times 010 microm) and a rapid-scanning quadrupole mass spectrometer (qMS) The qMS system employed was characterized by a scan speed of 10000 amus and a 25 Hz data acquisition frequency under a normal mass range (for example mz = 40ndash360) Such instrumental characteristics are sufficient for the requirements of qualitativequantitative fast GC analysis Single quadrupole MS instruments are the most commonly used in the GC field combining a relatively low cost with robustness and reduced

Figure 1a-b GC separation of isomers of HCH (mz 180938) DDD and DDT (mz 235008) and difenoconazole (mz 323024) at a concentration of 005 mgkg under (a) LP-GC (b) conventional GC conditions A mass window of 002 Da was used in the experiment Adapted and reprinted from Journal of Chromatography A 1186(1ndash2) 281ndash294 (2008) T Cajka J

Hasjlova O Lacina K Mastovska and S Lehotay Rapid Analysis of Multiple Pesticide Residues in Fruit-based

Baby Food using Programmed Temperature Vaporiser Injection-low-pressure Gas Chromatographyndashhigh-resolution

Time-of-flight Mass Spectrometry Copyright 2009 with permission from Elsevier

(a)100

Rela

tive

res

pons

e (

)Re

lati

ve r

espo

nse

()

100279

976

950 1000 1050 Time (min)

270 280 290 380370360Time (min) Time (min) 490 500480470 Time (min)

232023002280 Time (min)175017001650 Time (min)

10501027 1115

291

301289α-HCH

α-HCH

β-HCH

β-HCH

γ-HCH

γ-HCH

δ-HCH

δ-HCH

363

1649

1741

18151746

374 492

2306

2316

388

ρρ-DDDDifenoconazole I

Difeno-conazole I Difenoconazole II

Difenoconazole II

ρρ-DDD

ρρ-DDT

ρρ-DDT

+ ορ-DDT

ορ-DDT

ορ-DDD

ορ-DDD

0 0

100

0

100

0

100

0

100

0

(b)

4

dimensions Furthermore MS databases are normally constructed using qMS spectra and thus peak assignment through database matching is quite reliable To reach sufficient degrees of sensitivity extracted-ion chromatograms must be used or even better (in sensitivity terms) the SIM mode It is clear that in the latter case full-scan spectral information is lost A disadvantage of qMS instrumentation can be mass spectral skewing an effect which can be observed particularly in fast GCndashMS analysis Skewing is related to the change of analyte concentration in the ion source during a scan causing the generation of inconsistent spectral profiles across a peak

during the experiment performed by Scandinaro et al the authors subjected 200 essential oils to fast GC-qMS analysis After a single spectrum was derived from each chromatogram by averaging the spectra relative to all peaks in the chromatogram (apart from the solvent) and was added to the database In principle each spectrum attained can be considered in the same manner as a direct MS injection The EI-MS FampF database was found to be an effective tool to give a reliable name to an unknown essential oil After the GCndashMS chromatogram can be used for compound-to-compound identification

Mass spectrometric systems can be considered in their own right as a second separative dimension However such an analytical characteristic is often masked when using the most common ionization mode namely EI In fact when using such an ionization procedure a great number of fragments are generated in the ion source for each compound thus creating complex spectral profiles On the other hand if a soft ionization method is used [for example chemical ionization (CI) field ionization (FI) or photoionization (PI)] generating a low degree of fragmentation then the separation potential of the mass analyser is exalted

Hejazi et al analysed fatty acid methyl ester (FAME) mixtures by using a highly polar cyanopropyl 60 m times 025 mm times 025 microm column with the latter entering the ion source of an HR-ToF MS instrument (4) Instead of using EI the authors applied FI a soft ionization method with very little or no fragmentation (the TIC is essentially a molecular-ion chromatogram) In the first dimension FAMEs were separated on the basis of increasing polarity while in the second MS dimension separation was dominated by molecular weight

The GC-FI ToF MS data was represented on a 2d plane with mz values located along an x-axis and elution times along a y-axis The GC elution times were manipulated so that the saturated FAMEs were shifted onto a horizontal line relative retention times with respect to the saturated FAME line were then derived for the other FAMEs The 2d plane derived

from the analysis of fish oil is illustrated in Figure 2 As can be seen analyte distribution is highly organized FAMEs with the same C number are located in specific zones while the same can be affirmed for analytes with the same number of double bonds A great amount of information was

20

α io

n 2

08

α io

n 2

36

α io

n 1

50

α io

n 1

08

CO

1Mo

CO

1Mo

Elut

ion

tim

e re

lati

ve t

o sa

tura

ted

FAM

Es

16

12

108

80

Relative elution time ofunbranched saturated FAMEs

Branched saturated FAMEs

120

150 200 250Molecular mz

300 350

OH

Anti-oxidant

140 150 160

161162

163

164

170

241

215

171

180

181

182

183

184

200

201

202

203

204

205

220

221

225

226

208150 236 108 208150 236mz mz

8

4

Figure 2 Bidimensional GC-FI ToF MS data derived from an analysis on fish oil Fragmentation under EI conditions for two positional isomers (C183) is shown on the left-hand side Adapted and reprinted from Analytical Chemistry 81(4)1450ndash1458 (2009) L Hejazi D Ebrahimi

M Guilhaus and DB Hibbert Determination of the Composition of Fatty Acid Mixtures using GCtimesFI-MS A

Comprehensive Two-Dimensional Separation Approach Copyright 2009 with permission from American Chemical

Society

5

obtained through the GC-FI ToF MS experiment (exact masses + 2d plane locations) however the GC-FI ToF MS data was not sufficient to distinguish positional isomers (that is C183ω3 and C183ω6) The method proposed by the authors was abbreviated as GCtimesFI MS to emphasize the similarity with comprehensive two-dimensional gas chromatography (GCtimesGC) However GCtimesGC would appear to be a more powerful method for the identification of FAMEs as a result of the formation of highly organized chemical-class patterns (5)

Isotope discrimination during plant biosynthesis can be exploited to evaluate geographic origin and adulteration of natural plant-derived foods For such aims isotope ratio mass spectrometry (IRMS) combined with gas chromatography is a useful analytical tool (6) IRMS enables the measurement of deviations of isotope abundance ratios from an agreed standard by only a few parts per thousand for C as well as for other atoms such as H n O and S A requirement for IRMS analysis is that each element must be converted into a gas before entrance to the ion source In particular the determination of the 13C12C ratio is now rather established and is obtained by converting the C atoms of a specific analyte into CO2 and then by comparing the C isotope ratio of that constituent to that of a known standard A dimensionless quantity (δ) is used to express the isotope ratio value of a specific solute in relation to the standard and is expressed in (7)

Schipilliti et al used solid-phase microextraction (SPME) to extract volatiles from the headspace of (organic) strawberries (as well as from other fruits such as pineapple and peach) (8) The extracted compounds were then subjected to GC analysis on an apolar 30 m times 025 mm times 025 microm capillary IRMS analysis was carried out for twelve characteristic strawberry aroma constituents and an authenticity range was constructed (Figure 3) Moreover SPME-GC-IRMS applications were carried out on non-organic strawberries and on strawberry-flavoured foods (yogurt sweets and ice lollies) As can be seen from the graph presented in Figure 3 the 13C12C δ values for non-organic strawberries were within the authenticity range while the δ values relative to the other food commodities indicated that ldquorealrdquo strawberry extracts had not been employed for flavouring

In general GC-IRMS is a very useful technique for unveiling adulterations in food analysis However it should be added that the series of connections from the GC column outlet (for example the

combustion chamber) to the ion source can cause substantial band broadening and ultimately resolution losses Consequently whenever the complexity of a food sample exceeds a certain level the use of a heart-cutting multidimensional GCndashIRMS system is advisable

One way to circumvent the insufficient resolutionselectivity observed in one-dimensional GC is to analyse the same sample on two columns with a different selectivity Such an approach was

Figure 3 Organic strawberry 13C12C δ authenticity range along with δ values derived for commercial strawberries and strawberry-flavoured foods For compound identification see (8) Adapted and reprinted from Journal of Chromatography A 1218(42) 7481ndash7486 (2011) L Schipilliti P Dugo

I Bonaccorsi and L Mondello Headspace-solid-phase microextraction coupled to Gas Chromatography-combustion-

isotope ratio Mass Spectrometer and to Enantioselective Gas Chromatography for Strawberry-flavoured food quality

control Copyright 2011 with permission from Elsevier

-14

-19

δ13C

-24

-29

-341 2 3 4 5 6 7 8

compounds

9 10

Min organicstrawberryMax organicstrawberryyogurt 1

yogurt 2

lolly ice

candles

commstrawberry

11 12

6

exploited by Sasamoto et al to analyse selected pesticides in a brewed green tea (9) The authors achieved a rapid twin-column GCndashMS experiment using dual low thermal mass (LTM) modules mounted on a gas chromatograph equipped with a quadrupole MS and a pulsed flame photometric detector (PFPd) The two columns used were of equivalent dimensions (10 m times 018 mm times 018 microm) with a different stationary phase (5 phenyl and 50 phenyl) and were attached to a single injector The column outlets were connected to the detectors via a cross union Independent applications were performed using differential temperature programmes Such an approach is rather interesting because two TIC traces relative to two different capillaries can be stored as a single GCndashMS chromatogram Figure 4 illustrates the TIC trace relative to a mixture of 82 standard pesticides separated on each column Expansions derived from extracted-ion chromatograms [Figure 4(c) and 4(d)] highlight a series of co-elutions and ultimately the insufficient overall GC resolving power

Comprehensive Two-Dimensional GC-Based ProcessesIf a multidimensional GC (MdGC) instrument is used in food analysis then ideally totally-isolated compounds should be delivered to the mass spectrometer Although such a positive outcome is not always the case it is also true that in most MdGCndashMS applications an EI unit-mass resolution MS system [either single quadrupole or low-resolution (LR) ToF] is generally used The reason for such a choice is obvious being related to the high-resolution and selective nature of the GC step hence

decreasing the need for a powerful MS process (for example HR ToF MS or MSndashMS)

An MdGC set-up usually consists of two columns connected in series and characterized by a differing selectivity (for example apolar-polar polar-chiral etc) MdGC methods are classified into two large groups namely heart-cutting and comprehensive Approaches belonging to the former class are characterized by the transfer of a limited number of chromatography bands from the first to the second column In comprehensive two-dimensional GC the entire initial sample is analysed in both dimensions GCtimesGC experiments are normally performed using a conventional primary and a short secondary micro-bore column (1ndash2 m) the latter receives first-dimension cuts in a continuous and sequential manner

The GCtimesGC transfer device defined as modulator (usually cryogenic) enables the rapid accumulation and re-injection of chromatography bands from the first to the second column Second-dimension separations are very fast normally completed within 5ndash8 s The time between sequential second-dimension injections is defined as ldquomodulation periodrdquo and is equal to the analysis time on the secondary capillary Each second-dimension analysis is characterized by solutes with the same first-dimension elution time (expressed in min) and different second-dimension retention times [expressed in seconds (s)] If a 2000 s GCtimesGC application with a 5-s modulation period is considered then 400 5-s second-dimension traces stacked side-by-side will form a (monodimensional) comprehensive 2d GC chromatogram (only one detector is used) dedicated

Figure 4 (a) Full-scan GCndashMS chromatogram (c d) expansions derived from extracted-ion GCndashMS chromatograms and (b) a GC-PFPD chromatogram For compound identification see (9) Adapted and reprinted from Talanta 72(5) 1637ndash1643 (2007) K Sasamoto NOchial and H Kanda Dual low

thermal mass gas chromatographyndashmass spectrometry for fast dual-column separation of pesticides in complex sample

Copyright 2007 with permission from Elsevier

DB-5

8

8

10

12

14

16

4

2

1

2

3

4

5

0

0300 500 700 900 1100 1300 1500 1700

6

6

4

2

0

8

6

4

2

0

25 25

2626

(c)

(a)

(b)

(d)

2727

28

Retention time (min)

Retention time (min)

Retention time (min)

28 28

2831

3133 33

32

32

522 1310 1314 1318 1322 1326526 530 534 538

Inte

nsit

y x

104 a

u

Inte

nsit

y x

105 a

u

Inte

nsit

y x

108 a

u

Inte

nsit

y x

104 a

u

DB-17

Fast GC Columns to Analyze FAMEs

SPOnSOREd

Thermo Scientific FAST GC ColumnsReduce Analysis Times

Rob Bunn Thermo Fisher Scientific Runcorn Cheshire UK

Thermo Scientific FAST GC columns will save you timeand money by utilizing state-of-the-art technologyavailable in modern GCrsquos

Why Use FAST GC Columns

The major advantage of FAST GC columns is their abilityto deliver equivalent resolution compared with conventionallength and diameter columns in shorter analysis timesOften run times can be reduced by 50 using these columnsThese columns are not ideally suited for use with quadrupoleand ion trap mass spectrometers The peak width withthese columns can be as fast as half a second These fastpeaks place a heavier demand on the system as fastsampling rates are required

This new range of columns is especially suited tomodern gas chromatographs which have high pressure (upto 100 psi) electronic pressure control and detectors withfast sampling rates Detectors such as the FID ECD andEPD all have fast sampling rates and can handle the verynarrow peaks that FAST GC columns provide Additionallythe very latest GCrsquos can handle very fast oven temperatureprogram rates and programmed pressure profiles whichare advantageous for these columns

What Liner Should I Use with FAST GC Columns

For FAST GC column applications a liner with a smallerinternal diameter and a small volume is suitable Mostconventional liners have an internal diameter of about 4or 5 mm But with FAST GC columns it is recommendedto use a liner of approximately 2 mm ID In narrow borecapillary chromatography the band broadening that occurswithin the column is minimal But the low carrier gasflow rates associated with the technique can exaggeratethe band broadening that occurs in the injection port Insome cases the sample band in the liner could expandfaster than it is drawn into the column causing incompletesample transfer in splitless and band broadening in splitinjections For this reason it is very important to use inletliners with small internal diameters to increase the velocityof the carrier gas through the liner This results in muchhigher sensitivity and allows you to take full advantage ofthe higher efficiency associated with FAST GC columns

Applications for FAST GC Columns

FAST GC columns are especially suited for screeningapplications For example screening of water and soilsamples for environmental pollutants or drug screening inhuman and animal samples This application note presentsa number of examples demonstrating applications ofThermo Scientific FAST GC capillary columns Analysistimes with FAST GC columns can be reduced even furtherwith temperature programs higher than 30 degCminConditions used in these applications are also attainablewith most GCs PAH analysis is one of the most routinemethods used in environmental laboratories throughoutthe world

Key Words

bull TRACE GCColumns

bull FAST GC

bull HigherThroughput

bull Reduced Run Times

bull Screening

White PaperDSGSCFASTGC0509

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article2fast_gc_columnspdf

4

dimensions Furthermore MS databases are normally constructed using qMS spectra and thus peak assignment through database matching is quite reliable To reach sufficient degrees of sensitivity extracted-ion chromatograms must be used or even better (in sensitivity terms) the SIM mode It is clear that in the latter case full-scan spectral information is lost A disadvantage of qMS instrumentation can be mass spectral skewing an effect which can be observed particularly in fast GCndashMS analysis Skewing is related to the change of analyte concentration in the ion source during a scan causing the generation of inconsistent spectral profiles across a peak

during the experiment performed by Scandinaro et al the authors subjected 200 essential oils to fast GC-qMS analysis After a single spectrum was derived from each chromatogram by averaging the spectra relative to all peaks in the chromatogram (apart from the solvent) and was added to the database In principle each spectrum attained can be considered in the same manner as a direct MS injection The EI-MS FampF database was found to be an effective tool to give a reliable name to an unknown essential oil After the GCndashMS chromatogram can be used for compound-to-compound identification

Mass spectrometric systems can be considered in their own right as a second separative dimension However such an analytical characteristic is often masked when using the most common ionization mode namely EI In fact when using such an ionization procedure a great number of fragments are generated in the ion source for each compound thus creating complex spectral profiles On the other hand if a soft ionization method is used [for example chemical ionization (CI) field ionization (FI) or photoionization (PI)] generating a low degree of fragmentation then the separation potential of the mass analyser is exalted

Hejazi et al analysed fatty acid methyl ester (FAME) mixtures by using a highly polar cyanopropyl 60 m times 025 mm times 025 microm column with the latter entering the ion source of an HR-ToF MS instrument (4) Instead of using EI the authors applied FI a soft ionization method with very little or no fragmentation (the TIC is essentially a molecular-ion chromatogram) In the first dimension FAMEs were separated on the basis of increasing polarity while in the second MS dimension separation was dominated by molecular weight

The GC-FI ToF MS data was represented on a 2d plane with mz values located along an x-axis and elution times along a y-axis The GC elution times were manipulated so that the saturated FAMEs were shifted onto a horizontal line relative retention times with respect to the saturated FAME line were then derived for the other FAMEs The 2d plane derived

from the analysis of fish oil is illustrated in Figure 2 As can be seen analyte distribution is highly organized FAMEs with the same C number are located in specific zones while the same can be affirmed for analytes with the same number of double bonds A great amount of information was

20

α io

n 2

08

α io

n 2

36

α io

n 1

50

α io

n 1

08

CO

1Mo

CO

1Mo

Elut

ion

tim

e re

lati

ve t

o sa

tura

ted

FAM

Es

16

12

108

80

Relative elution time ofunbranched saturated FAMEs

Branched saturated FAMEs

120

150 200 250Molecular mz

300 350

OH

Anti-oxidant

140 150 160

161162

163

164

170

241

215

171

180

181

182

183

184

200

201

202

203

204

205

220

221

225

226

208150 236 108 208150 236mz mz

8

4

Figure 2 Bidimensional GC-FI ToF MS data derived from an analysis on fish oil Fragmentation under EI conditions for two positional isomers (C183) is shown on the left-hand side Adapted and reprinted from Analytical Chemistry 81(4)1450ndash1458 (2009) L Hejazi D Ebrahimi

M Guilhaus and DB Hibbert Determination of the Composition of Fatty Acid Mixtures using GCtimesFI-MS A

Comprehensive Two-Dimensional Separation Approach Copyright 2009 with permission from American Chemical

Society

5

obtained through the GC-FI ToF MS experiment (exact masses + 2d plane locations) however the GC-FI ToF MS data was not sufficient to distinguish positional isomers (that is C183ω3 and C183ω6) The method proposed by the authors was abbreviated as GCtimesFI MS to emphasize the similarity with comprehensive two-dimensional gas chromatography (GCtimesGC) However GCtimesGC would appear to be a more powerful method for the identification of FAMEs as a result of the formation of highly organized chemical-class patterns (5)

Isotope discrimination during plant biosynthesis can be exploited to evaluate geographic origin and adulteration of natural plant-derived foods For such aims isotope ratio mass spectrometry (IRMS) combined with gas chromatography is a useful analytical tool (6) IRMS enables the measurement of deviations of isotope abundance ratios from an agreed standard by only a few parts per thousand for C as well as for other atoms such as H n O and S A requirement for IRMS analysis is that each element must be converted into a gas before entrance to the ion source In particular the determination of the 13C12C ratio is now rather established and is obtained by converting the C atoms of a specific analyte into CO2 and then by comparing the C isotope ratio of that constituent to that of a known standard A dimensionless quantity (δ) is used to express the isotope ratio value of a specific solute in relation to the standard and is expressed in (7)

Schipilliti et al used solid-phase microextraction (SPME) to extract volatiles from the headspace of (organic) strawberries (as well as from other fruits such as pineapple and peach) (8) The extracted compounds were then subjected to GC analysis on an apolar 30 m times 025 mm times 025 microm capillary IRMS analysis was carried out for twelve characteristic strawberry aroma constituents and an authenticity range was constructed (Figure 3) Moreover SPME-GC-IRMS applications were carried out on non-organic strawberries and on strawberry-flavoured foods (yogurt sweets and ice lollies) As can be seen from the graph presented in Figure 3 the 13C12C δ values for non-organic strawberries were within the authenticity range while the δ values relative to the other food commodities indicated that ldquorealrdquo strawberry extracts had not been employed for flavouring

In general GC-IRMS is a very useful technique for unveiling adulterations in food analysis However it should be added that the series of connections from the GC column outlet (for example the

combustion chamber) to the ion source can cause substantial band broadening and ultimately resolution losses Consequently whenever the complexity of a food sample exceeds a certain level the use of a heart-cutting multidimensional GCndashIRMS system is advisable

One way to circumvent the insufficient resolutionselectivity observed in one-dimensional GC is to analyse the same sample on two columns with a different selectivity Such an approach was

Figure 3 Organic strawberry 13C12C δ authenticity range along with δ values derived for commercial strawberries and strawberry-flavoured foods For compound identification see (8) Adapted and reprinted from Journal of Chromatography A 1218(42) 7481ndash7486 (2011) L Schipilliti P Dugo

I Bonaccorsi and L Mondello Headspace-solid-phase microextraction coupled to Gas Chromatography-combustion-

isotope ratio Mass Spectrometer and to Enantioselective Gas Chromatography for Strawberry-flavoured food quality

control Copyright 2011 with permission from Elsevier

-14

-19

δ13C

-24

-29

-341 2 3 4 5 6 7 8

compounds

9 10

Min organicstrawberryMax organicstrawberryyogurt 1

yogurt 2

lolly ice

candles

commstrawberry

11 12

6

exploited by Sasamoto et al to analyse selected pesticides in a brewed green tea (9) The authors achieved a rapid twin-column GCndashMS experiment using dual low thermal mass (LTM) modules mounted on a gas chromatograph equipped with a quadrupole MS and a pulsed flame photometric detector (PFPd) The two columns used were of equivalent dimensions (10 m times 018 mm times 018 microm) with a different stationary phase (5 phenyl and 50 phenyl) and were attached to a single injector The column outlets were connected to the detectors via a cross union Independent applications were performed using differential temperature programmes Such an approach is rather interesting because two TIC traces relative to two different capillaries can be stored as a single GCndashMS chromatogram Figure 4 illustrates the TIC trace relative to a mixture of 82 standard pesticides separated on each column Expansions derived from extracted-ion chromatograms [Figure 4(c) and 4(d)] highlight a series of co-elutions and ultimately the insufficient overall GC resolving power

Comprehensive Two-Dimensional GC-Based ProcessesIf a multidimensional GC (MdGC) instrument is used in food analysis then ideally totally-isolated compounds should be delivered to the mass spectrometer Although such a positive outcome is not always the case it is also true that in most MdGCndashMS applications an EI unit-mass resolution MS system [either single quadrupole or low-resolution (LR) ToF] is generally used The reason for such a choice is obvious being related to the high-resolution and selective nature of the GC step hence

decreasing the need for a powerful MS process (for example HR ToF MS or MSndashMS)

An MdGC set-up usually consists of two columns connected in series and characterized by a differing selectivity (for example apolar-polar polar-chiral etc) MdGC methods are classified into two large groups namely heart-cutting and comprehensive Approaches belonging to the former class are characterized by the transfer of a limited number of chromatography bands from the first to the second column In comprehensive two-dimensional GC the entire initial sample is analysed in both dimensions GCtimesGC experiments are normally performed using a conventional primary and a short secondary micro-bore column (1ndash2 m) the latter receives first-dimension cuts in a continuous and sequential manner

The GCtimesGC transfer device defined as modulator (usually cryogenic) enables the rapid accumulation and re-injection of chromatography bands from the first to the second column Second-dimension separations are very fast normally completed within 5ndash8 s The time between sequential second-dimension injections is defined as ldquomodulation periodrdquo and is equal to the analysis time on the secondary capillary Each second-dimension analysis is characterized by solutes with the same first-dimension elution time (expressed in min) and different second-dimension retention times [expressed in seconds (s)] If a 2000 s GCtimesGC application with a 5-s modulation period is considered then 400 5-s second-dimension traces stacked side-by-side will form a (monodimensional) comprehensive 2d GC chromatogram (only one detector is used) dedicated

Figure 4 (a) Full-scan GCndashMS chromatogram (c d) expansions derived from extracted-ion GCndashMS chromatograms and (b) a GC-PFPD chromatogram For compound identification see (9) Adapted and reprinted from Talanta 72(5) 1637ndash1643 (2007) K Sasamoto NOchial and H Kanda Dual low

thermal mass gas chromatographyndashmass spectrometry for fast dual-column separation of pesticides in complex sample

Copyright 2007 with permission from Elsevier

DB-5

8

8

10

12

14

16

4

2

1

2

3

4

5

0

0300 500 700 900 1100 1300 1500 1700

6

6

4

2

0

8

6

4

2

0

25 25

2626

(c)

(a)

(b)

(d)

2727

28

Retention time (min)

Retention time (min)

Retention time (min)

28 28

2831

3133 33

32

32

522 1310 1314 1318 1322 1326526 530 534 538

Inte

nsit

y x

104 a

u

Inte

nsit

y x

105 a

u

Inte

nsit

y x

108 a

u

Inte

nsit

y x

104 a

u

DB-17

Fast GC Columns to Analyze FAMEs

SPOnSOREd

Thermo Scientific FAST GC ColumnsReduce Analysis Times

Rob Bunn Thermo Fisher Scientific Runcorn Cheshire UK

Thermo Scientific FAST GC columns will save you timeand money by utilizing state-of-the-art technologyavailable in modern GCrsquos

Why Use FAST GC Columns

The major advantage of FAST GC columns is their abilityto deliver equivalent resolution compared with conventionallength and diameter columns in shorter analysis timesOften run times can be reduced by 50 using these columnsThese columns are not ideally suited for use with quadrupoleand ion trap mass spectrometers The peak width withthese columns can be as fast as half a second These fastpeaks place a heavier demand on the system as fastsampling rates are required

This new range of columns is especially suited tomodern gas chromatographs which have high pressure (upto 100 psi) electronic pressure control and detectors withfast sampling rates Detectors such as the FID ECD andEPD all have fast sampling rates and can handle the verynarrow peaks that FAST GC columns provide Additionallythe very latest GCrsquos can handle very fast oven temperatureprogram rates and programmed pressure profiles whichare advantageous for these columns

What Liner Should I Use with FAST GC Columns

For FAST GC column applications a liner with a smallerinternal diameter and a small volume is suitable Mostconventional liners have an internal diameter of about 4or 5 mm But with FAST GC columns it is recommendedto use a liner of approximately 2 mm ID In narrow borecapillary chromatography the band broadening that occurswithin the column is minimal But the low carrier gasflow rates associated with the technique can exaggeratethe band broadening that occurs in the injection port Insome cases the sample band in the liner could expandfaster than it is drawn into the column causing incompletesample transfer in splitless and band broadening in splitinjections For this reason it is very important to use inletliners with small internal diameters to increase the velocityof the carrier gas through the liner This results in muchhigher sensitivity and allows you to take full advantage ofthe higher efficiency associated with FAST GC columns

Applications for FAST GC Columns

FAST GC columns are especially suited for screeningapplications For example screening of water and soilsamples for environmental pollutants or drug screening inhuman and animal samples This application note presentsa number of examples demonstrating applications ofThermo Scientific FAST GC capillary columns Analysistimes with FAST GC columns can be reduced even furtherwith temperature programs higher than 30 degCminConditions used in these applications are also attainablewith most GCs PAH analysis is one of the most routinemethods used in environmental laboratories throughoutthe world

Key Words

bull TRACE GCColumns

bull FAST GC

bull HigherThroughput

bull Reduced Run Times

bull Screening

White PaperDSGSCFASTGC0509

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article2fast_gc_columnspdf

5

obtained through the GC-FI ToF MS experiment (exact masses + 2d plane locations) however the GC-FI ToF MS data was not sufficient to distinguish positional isomers (that is C183ω3 and C183ω6) The method proposed by the authors was abbreviated as GCtimesFI MS to emphasize the similarity with comprehensive two-dimensional gas chromatography (GCtimesGC) However GCtimesGC would appear to be a more powerful method for the identification of FAMEs as a result of the formation of highly organized chemical-class patterns (5)

Isotope discrimination during plant biosynthesis can be exploited to evaluate geographic origin and adulteration of natural plant-derived foods For such aims isotope ratio mass spectrometry (IRMS) combined with gas chromatography is a useful analytical tool (6) IRMS enables the measurement of deviations of isotope abundance ratios from an agreed standard by only a few parts per thousand for C as well as for other atoms such as H n O and S A requirement for IRMS analysis is that each element must be converted into a gas before entrance to the ion source In particular the determination of the 13C12C ratio is now rather established and is obtained by converting the C atoms of a specific analyte into CO2 and then by comparing the C isotope ratio of that constituent to that of a known standard A dimensionless quantity (δ) is used to express the isotope ratio value of a specific solute in relation to the standard and is expressed in (7)

Schipilliti et al used solid-phase microextraction (SPME) to extract volatiles from the headspace of (organic) strawberries (as well as from other fruits such as pineapple and peach) (8) The extracted compounds were then subjected to GC analysis on an apolar 30 m times 025 mm times 025 microm capillary IRMS analysis was carried out for twelve characteristic strawberry aroma constituents and an authenticity range was constructed (Figure 3) Moreover SPME-GC-IRMS applications were carried out on non-organic strawberries and on strawberry-flavoured foods (yogurt sweets and ice lollies) As can be seen from the graph presented in Figure 3 the 13C12C δ values for non-organic strawberries were within the authenticity range while the δ values relative to the other food commodities indicated that ldquorealrdquo strawberry extracts had not been employed for flavouring

In general GC-IRMS is a very useful technique for unveiling adulterations in food analysis However it should be added that the series of connections from the GC column outlet (for example the

combustion chamber) to the ion source can cause substantial band broadening and ultimately resolution losses Consequently whenever the complexity of a food sample exceeds a certain level the use of a heart-cutting multidimensional GCndashIRMS system is advisable

One way to circumvent the insufficient resolutionselectivity observed in one-dimensional GC is to analyse the same sample on two columns with a different selectivity Such an approach was

Figure 3 Organic strawberry 13C12C δ authenticity range along with δ values derived for commercial strawberries and strawberry-flavoured foods For compound identification see (8) Adapted and reprinted from Journal of Chromatography A 1218(42) 7481ndash7486 (2011) L Schipilliti P Dugo

I Bonaccorsi and L Mondello Headspace-solid-phase microextraction coupled to Gas Chromatography-combustion-

isotope ratio Mass Spectrometer and to Enantioselective Gas Chromatography for Strawberry-flavoured food quality

control Copyright 2011 with permission from Elsevier

-14

-19

δ13C

-24

-29

-341 2 3 4 5 6 7 8

compounds

9 10

Min organicstrawberryMax organicstrawberryyogurt 1

yogurt 2

lolly ice

candles

commstrawberry

11 12

6

exploited by Sasamoto et al to analyse selected pesticides in a brewed green tea (9) The authors achieved a rapid twin-column GCndashMS experiment using dual low thermal mass (LTM) modules mounted on a gas chromatograph equipped with a quadrupole MS and a pulsed flame photometric detector (PFPd) The two columns used were of equivalent dimensions (10 m times 018 mm times 018 microm) with a different stationary phase (5 phenyl and 50 phenyl) and were attached to a single injector The column outlets were connected to the detectors via a cross union Independent applications were performed using differential temperature programmes Such an approach is rather interesting because two TIC traces relative to two different capillaries can be stored as a single GCndashMS chromatogram Figure 4 illustrates the TIC trace relative to a mixture of 82 standard pesticides separated on each column Expansions derived from extracted-ion chromatograms [Figure 4(c) and 4(d)] highlight a series of co-elutions and ultimately the insufficient overall GC resolving power

Comprehensive Two-Dimensional GC-Based ProcessesIf a multidimensional GC (MdGC) instrument is used in food analysis then ideally totally-isolated compounds should be delivered to the mass spectrometer Although such a positive outcome is not always the case it is also true that in most MdGCndashMS applications an EI unit-mass resolution MS system [either single quadrupole or low-resolution (LR) ToF] is generally used The reason for such a choice is obvious being related to the high-resolution and selective nature of the GC step hence

decreasing the need for a powerful MS process (for example HR ToF MS or MSndashMS)

An MdGC set-up usually consists of two columns connected in series and characterized by a differing selectivity (for example apolar-polar polar-chiral etc) MdGC methods are classified into two large groups namely heart-cutting and comprehensive Approaches belonging to the former class are characterized by the transfer of a limited number of chromatography bands from the first to the second column In comprehensive two-dimensional GC the entire initial sample is analysed in both dimensions GCtimesGC experiments are normally performed using a conventional primary and a short secondary micro-bore column (1ndash2 m) the latter receives first-dimension cuts in a continuous and sequential manner

The GCtimesGC transfer device defined as modulator (usually cryogenic) enables the rapid accumulation and re-injection of chromatography bands from the first to the second column Second-dimension separations are very fast normally completed within 5ndash8 s The time between sequential second-dimension injections is defined as ldquomodulation periodrdquo and is equal to the analysis time on the secondary capillary Each second-dimension analysis is characterized by solutes with the same first-dimension elution time (expressed in min) and different second-dimension retention times [expressed in seconds (s)] If a 2000 s GCtimesGC application with a 5-s modulation period is considered then 400 5-s second-dimension traces stacked side-by-side will form a (monodimensional) comprehensive 2d GC chromatogram (only one detector is used) dedicated

Figure 4 (a) Full-scan GCndashMS chromatogram (c d) expansions derived from extracted-ion GCndashMS chromatograms and (b) a GC-PFPD chromatogram For compound identification see (9) Adapted and reprinted from Talanta 72(5) 1637ndash1643 (2007) K Sasamoto NOchial and H Kanda Dual low

thermal mass gas chromatographyndashmass spectrometry for fast dual-column separation of pesticides in complex sample

Copyright 2007 with permission from Elsevier

DB-5

8

8

10

12

14

16

4

2

1

2

3

4

5

0

0300 500 700 900 1100 1300 1500 1700

6

6

4

2

0

8

6

4

2

0

25 25

2626

(c)

(a)

(b)

(d)

2727

28

Retention time (min)

Retention time (min)

Retention time (min)

28 28

2831

3133 33

32

32

522 1310 1314 1318 1322 1326526 530 534 538

Inte

nsit

y x

104 a

u

Inte

nsit

y x

105 a

u

Inte

nsit

y x

108 a

u

Inte

nsit

y x

104 a

u

DB-17

Fast GC Columns to Analyze FAMEs

SPOnSOREd

Thermo Scientific FAST GC ColumnsReduce Analysis Times

Rob Bunn Thermo Fisher Scientific Runcorn Cheshire UK

Thermo Scientific FAST GC columns will save you timeand money by utilizing state-of-the-art technologyavailable in modern GCrsquos

Why Use FAST GC Columns

The major advantage of FAST GC columns is their abilityto deliver equivalent resolution compared with conventionallength and diameter columns in shorter analysis timesOften run times can be reduced by 50 using these columnsThese columns are not ideally suited for use with quadrupoleand ion trap mass spectrometers The peak width withthese columns can be as fast as half a second These fastpeaks place a heavier demand on the system as fastsampling rates are required

This new range of columns is especially suited tomodern gas chromatographs which have high pressure (upto 100 psi) electronic pressure control and detectors withfast sampling rates Detectors such as the FID ECD andEPD all have fast sampling rates and can handle the verynarrow peaks that FAST GC columns provide Additionallythe very latest GCrsquos can handle very fast oven temperatureprogram rates and programmed pressure profiles whichare advantageous for these columns

What Liner Should I Use with FAST GC Columns

For FAST GC column applications a liner with a smallerinternal diameter and a small volume is suitable Mostconventional liners have an internal diameter of about 4or 5 mm But with FAST GC columns it is recommendedto use a liner of approximately 2 mm ID In narrow borecapillary chromatography the band broadening that occurswithin the column is minimal But the low carrier gasflow rates associated with the technique can exaggeratethe band broadening that occurs in the injection port Insome cases the sample band in the liner could expandfaster than it is drawn into the column causing incompletesample transfer in splitless and band broadening in splitinjections For this reason it is very important to use inletliners with small internal diameters to increase the velocityof the carrier gas through the liner This results in muchhigher sensitivity and allows you to take full advantage ofthe higher efficiency associated with FAST GC columns

Applications for FAST GC Columns

FAST GC columns are especially suited for screeningapplications For example screening of water and soilsamples for environmental pollutants or drug screening inhuman and animal samples This application note presentsa number of examples demonstrating applications ofThermo Scientific FAST GC capillary columns Analysistimes with FAST GC columns can be reduced even furtherwith temperature programs higher than 30 degCminConditions used in these applications are also attainablewith most GCs PAH analysis is one of the most routinemethods used in environmental laboratories throughoutthe world

Key Words

bull TRACE GCColumns

bull FAST GC

bull HigherThroughput

bull Reduced Run Times

bull Screening

White PaperDSGSCFASTGC0509

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article2fast_gc_columnspdf

6

exploited by Sasamoto et al to analyse selected pesticides in a brewed green tea (9) The authors achieved a rapid twin-column GCndashMS experiment using dual low thermal mass (LTM) modules mounted on a gas chromatograph equipped with a quadrupole MS and a pulsed flame photometric detector (PFPd) The two columns used were of equivalent dimensions (10 m times 018 mm times 018 microm) with a different stationary phase (5 phenyl and 50 phenyl) and were attached to a single injector The column outlets were connected to the detectors via a cross union Independent applications were performed using differential temperature programmes Such an approach is rather interesting because two TIC traces relative to two different capillaries can be stored as a single GCndashMS chromatogram Figure 4 illustrates the TIC trace relative to a mixture of 82 standard pesticides separated on each column Expansions derived from extracted-ion chromatograms [Figure 4(c) and 4(d)] highlight a series of co-elutions and ultimately the insufficient overall GC resolving power

Comprehensive Two-Dimensional GC-Based ProcessesIf a multidimensional GC (MdGC) instrument is used in food analysis then ideally totally-isolated compounds should be delivered to the mass spectrometer Although such a positive outcome is not always the case it is also true that in most MdGCndashMS applications an EI unit-mass resolution MS system [either single quadrupole or low-resolution (LR) ToF] is generally used The reason for such a choice is obvious being related to the high-resolution and selective nature of the GC step hence

decreasing the need for a powerful MS process (for example HR ToF MS or MSndashMS)

An MdGC set-up usually consists of two columns connected in series and characterized by a differing selectivity (for example apolar-polar polar-chiral etc) MdGC methods are classified into two large groups namely heart-cutting and comprehensive Approaches belonging to the former class are characterized by the transfer of a limited number of chromatography bands from the first to the second column In comprehensive two-dimensional GC the entire initial sample is analysed in both dimensions GCtimesGC experiments are normally performed using a conventional primary and a short secondary micro-bore column (1ndash2 m) the latter receives first-dimension cuts in a continuous and sequential manner

The GCtimesGC transfer device defined as modulator (usually cryogenic) enables the rapid accumulation and re-injection of chromatography bands from the first to the second column Second-dimension separations are very fast normally completed within 5ndash8 s The time between sequential second-dimension injections is defined as ldquomodulation periodrdquo and is equal to the analysis time on the secondary capillary Each second-dimension analysis is characterized by solutes with the same first-dimension elution time (expressed in min) and different second-dimension retention times [expressed in seconds (s)] If a 2000 s GCtimesGC application with a 5-s modulation period is considered then 400 5-s second-dimension traces stacked side-by-side will form a (monodimensional) comprehensive 2d GC chromatogram (only one detector is used) dedicated

Figure 4 (a) Full-scan GCndashMS chromatogram (c d) expansions derived from extracted-ion GCndashMS chromatograms and (b) a GC-PFPD chromatogram For compound identification see (9) Adapted and reprinted from Talanta 72(5) 1637ndash1643 (2007) K Sasamoto NOchial and H Kanda Dual low

thermal mass gas chromatographyndashmass spectrometry for fast dual-column separation of pesticides in complex sample

Copyright 2007 with permission from Elsevier

DB-5

8

8

10

12

14

16

4

2

1

2

3

4

5

0

0300 500 700 900 1100 1300 1500 1700

6

6

4

2

0

8

6

4

2

0

25 25

2626

(c)

(a)

(b)

(d)

2727

28

Retention time (min)

Retention time (min)

Retention time (min)

28 28

2831

3133 33

32

32

522 1310 1314 1318 1322 1326526 530 534 538

Inte

nsit

y x

104 a

u

Inte

nsit

y x

105 a

u

Inte

nsit

y x

108 a

u

Inte

nsit

y x

104 a

u

DB-17

Fast GC Columns to Analyze FAMEs

SPOnSOREd

Thermo Scientific FAST GC ColumnsReduce Analysis Times

Rob Bunn Thermo Fisher Scientific Runcorn Cheshire UK

Thermo Scientific FAST GC columns will save you timeand money by utilizing state-of-the-art technologyavailable in modern GCrsquos

Why Use FAST GC Columns

The major advantage of FAST GC columns is their abilityto deliver equivalent resolution compared with conventionallength and diameter columns in shorter analysis timesOften run times can be reduced by 50 using these columnsThese columns are not ideally suited for use with quadrupoleand ion trap mass spectrometers The peak width withthese columns can be as fast as half a second These fastpeaks place a heavier demand on the system as fastsampling rates are required

This new range of columns is especially suited tomodern gas chromatographs which have high pressure (upto 100 psi) electronic pressure control and detectors withfast sampling rates Detectors such as the FID ECD andEPD all have fast sampling rates and can handle the verynarrow peaks that FAST GC columns provide Additionallythe very latest GCrsquos can handle very fast oven temperatureprogram rates and programmed pressure profiles whichare advantageous for these columns

What Liner Should I Use with FAST GC Columns

For FAST GC column applications a liner with a smallerinternal diameter and a small volume is suitable Mostconventional liners have an internal diameter of about 4or 5 mm But with FAST GC columns it is recommendedto use a liner of approximately 2 mm ID In narrow borecapillary chromatography the band broadening that occurswithin the column is minimal But the low carrier gasflow rates associated with the technique can exaggeratethe band broadening that occurs in the injection port Insome cases the sample band in the liner could expandfaster than it is drawn into the column causing incompletesample transfer in splitless and band broadening in splitinjections For this reason it is very important to use inletliners with small internal diameters to increase the velocityof the carrier gas through the liner This results in muchhigher sensitivity and allows you to take full advantage ofthe higher efficiency associated with FAST GC columns

Applications for FAST GC Columns

FAST GC columns are especially suited for screeningapplications For example screening of water and soilsamples for environmental pollutants or drug screening inhuman and animal samples This application note presentsa number of examples demonstrating applications ofThermo Scientific FAST GC capillary columns Analysistimes with FAST GC columns can be reduced even furtherwith temperature programs higher than 30 degCminConditions used in these applications are also attainablewith most GCs PAH analysis is one of the most routinemethods used in environmental laboratories throughoutthe world

Key Words

bull TRACE GCColumns

bull FAST GC

bull HigherThroughput

bull Reduced Run Times

bull Screening

White PaperDSGSCFASTGC0509

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article2fast_gc_columnspdf

7

software is necessary to generate a bidimensional GC space each high-speed chromatogram is positioned at 90deg to an x-axis while the compounds separated in the second dimension are aligned along a y-axis and are characterized by an oval shape With regards to quantification issues it is necessary to sum the peak areas relative to the same compound in each high-speed second-dimension trace again by using dedicated software For more details on GCtimesGC the reader is directed to the literature (10)

A common characteristic of all GCtimesGC separations is that very narrow GC peaks (200ndash500 msec) are generated For this reason high-speed (up to 500 Hz) LR ToF MS systems have dominated the GCtimesGC market over the past decade The reason for such a supremacy is mainly related to quantification at least

8ndash10 data pointspeak are necessary for correct peak reconstruction

Silva et al reported an SPME-GCtimesGC-LR ToF MS investigation on the headspace of marine salt (11) The ToF mass spectrometer was operated at a 100 Hz spectral acquisition frequency using a 41ndash415 mz mass range Prior to entrance in the ion source the analytes were separated on an apolar-polar column combination The GCtimesGC-LR ToF MS instrument was equipped with dedicated software for instrumental control and data processing Automated data processing was used to tentatively identify peaks with a signal-to-noise threshold gt

100 The SPMEndashGCtimesGCndashLR ToF MS result for the most complex (101 identified compounds) salt sample is shown in Figure 5 As can be observed the bidimensional chromatogram is characterized both by unsuspected complexity and by the formation of chemical-class patterns The investigation of Silva et al highlighted a series of positive features of GCtimesGC namely increased separation power enhanced sensitivity (due to cryogenic modulation) and the generation of structured chromatograms

Recently Purcaro et al evaluated the performance of a novel rapid-scanning (scan speed 20000 amus) qMS system in the GCtimesGC analysis of pesticides contained in water (12) The analytes were extracted by using direct solid-phase microextraction and then separated on a ldquo5 diphenylrdquo 30 m times 025 mm times 025 microm primary column (SLB-5ms) and on a medium-polarity ionic liquid 1 m times 010 mm times 008 microm secondary one (SLB-IL59) The MS system was operated using a wide 50ndash450 mz mass range (which is necessary for heavier weight components) and a 33 Hz spectral production rate a frequency which was found sufficient for reliable quantification The authors reported that the time required to achieve a scan was 195 msec accompanied by an interscan delay of less than 11 msec Heptachlor namely the fastest peak generated (base width of circa 300 msec) was reconstructed with

ten data points Spectra derived at different peak points showed good spectral consistency Under a more common GC mass range (50ndash340 mz) the qMS system has been capable of producing 50 spectras (13)

Figure 5 SPME-GCtimesGC-LR ToF MS chromatogram relative to the headspace of marine salt with indication of the chemical-class patterns For compound identification see (11) Adapted and reprinted from Journal of Chromatography A 1217(34) 5511ndash5521 (2010) I Silva SM Rocha

M A Colmbra and PJ Marriot Headspace Solid-phase Microextraction with Comprehensive Two-dimensional Gas

Chromatography Time-of-flight Mass Spectrometry for the Determination of Volatile Compounds from Marine Salt

Copyright 2010 with permission from Elsevier

Lactones

127

96

102 119

109

142155

107105

73

78

58

133

26

194

C9

300

01

23

4

800 13001st Dimension retention time(s)

2nd

Dim

ensi

on

ret

enti

on

tim

e(s)

1800

C10 C11C12 C13 C14 C15 C16 C17 C18 C19 C20

TerpenoidsAliphatic AlcoholsAliphatic Aldehydes

Aliphatic Hydrocarbons

8

ConclusionsA brief overview of some of the current possibilities in the field of gas chromatographyndashmass spectrometry analysis of foods has been discussed The number of instrumental options is high and the present contribution can only in part direct the food analyst to the most appropriate choice on the basis of the initial analytical objective

In the case of target analysis then a single GC column combined with an appropriate MS approach (MSndashMS SIM EIC deconvolution methods etc) can do the job fine If the entire chemical profile of a low-to-medium complexity food sample needs to be unravelled then straightforward GC with unit-mass resolution MS is a still a good choice In the case of a highly complex sample then the need for a powerful GC step is in many cases required Obviously a method such as GCtimesGC is suitable for the analyses of unknowns as well as for target analysis

Francesco Cacciola 12 Paola Donato 31 Marco Beccaria 1Paola Dugo 13 and Luigi Mondello 13

1 Dipartimento Farmaco chimico Universitagrave degli Studi di Messina Messina Italy2 Chromaleont srl A spin-off of the University of Messina co Dipartimento Farmaco-chimico Universitagrave degli Studi di Messina Messina Italy

3 Centro Integrato di Ricerca (CIR) Universitagrave Campus Bio-Medico Roma Italy

How to Cite this Article

PQ Tranchida P Dugo and L Mondello ldquoAdvances in GC-MS for Food Analysisrdquo LCGC Europe 25(s5) ldquoAdvances in Food Analysisrdquo supplement 25ndash30 (2012)

References(1) T Cajka J Hajslova O Lacina K Mastovska and SJ Lehotay J Chromatogr A 1186(1ndash2) 281ndash294 (2008)(2) U Koesukwiwat SJ Lehotay and N Leepipatpiboon J Chromatogr A 1218(39) 7039ndash7050 (2010)(3) M Scandinaro PQ Tranchida R Costa P Dugo G Dugo and L Mondello LCbullGC Europe 23(9) 456ndash464 (2010)(4) L Hejazi D Ebrahimi M Guilhaus and DB Hibbert Anal Chem 81(4) 1450ndash1458 (2009)(5) PQ Tranchida R Costa P Donato D Sciarrone C Ragonese P Dugo G Dugo and L Mondello J Sep Sci 31(19)

3347ndash3351 (2008)(6) A Mosandl in RG Berger (Ed) Flavours and Fragrances ndash Chemistry Bioprocessing and Sustainability Springer p

379 (2007)(7) JT Brenna TN Corso HJ Tobias and RJ Caimi Mass Spectrom Rev 16(5) 227ndash258 (1997)(8) L Schipilliti P Dugo I Bonaccorsi and L Mondello J Chromatogr A 1218(42) 7481ndash7486 (2011)(9) K Sasamoto N Ochiai and H Kanda Talanta 72(5) 1637ndash1643 (2007)(10) M Adahchour J Beens and UA Th Brinkman J Chromatogr A 1186(1ndash2) 67ndash108 (2008)(11) I Silva SM Rocha MA Coimbra and PJ Marriott J Chromatogr A 1217(34) 5511ndash5521 (2010)(12) G Purcaro PQ Tranchida L Conte A Obiedzińska P Dugo G Dugo and L Mondello J Sep Sci 34(18) 2411ndash2417 (2011)(13) G Purcaro PQ Tranchida C Ragonese L Conte P Dugo G Dugo and L Mondello Anal Chem 82(20)

8583ndash8590 (2010)

Interview with author Luigi Mondello

InTERVIEW

8

ConclusionsA brief overview of some of the current possibilities in the field of gas chromatographyndashmass spectrometry analysis of foods has been discussed The number of instrumental options is high and the present contribution can only in part direct the food analyst to the most appropriate choice on the basis of the initial analytical objective

In the case of target analysis then a single GC column combined with an appropriate MS approach (MSndashMS SIM EIC deconvolution methods etc) can do the job fine If the entire chemical profile of a low-to-medium complexity food sample needs to be unravelled then straightforward GC with unit-mass resolution MS is a still a good choice In the case of a highly complex sample then the need for a powerful GC step is in many cases required Obviously a method such as GCtimesGC is suitable for the analyses of unknowns as well as for target analysis

Francesco Cacciola 12 Paola Donato 31 Marco Beccaria 1Paola Dugo 13 and Luigi Mondello 13

1 Dipartimento Farmaco chimico Universitagrave degli Studi di Messina Messina Italy2 Chromaleont srl A spin-off of the University of Messina co Dipartimento Farmaco-chimico Universitagrave degli Studi di Messina Messina Italy

3 Centro Integrato di Ricerca (CIR) Universitagrave Campus Bio-Medico Roma Italy

How to Cite this Article

PQ Tranchida P Dugo and L Mondello ldquoAdvances in GC-MS for Food Analysisrdquo LCGC Europe 25(s5) ldquoAdvances in Food Analysisrdquo supplement 25ndash30 (2012)

References(1) T Cajka J Hajslova O Lacina K Mastovska and SJ Lehotay J Chromatogr A 1186(1ndash2) 281ndash294 (2008)(2) U Koesukwiwat SJ Lehotay and N Leepipatpiboon J Chromatogr A 1218(39) 7039ndash7050 (2010)(3) M Scandinaro PQ Tranchida R Costa P Dugo G Dugo and L Mondello LCbullGC Europe 23(9) 456ndash464 (2010)(4) L Hejazi D Ebrahimi M Guilhaus and DB Hibbert Anal Chem 81(4) 1450ndash1458 (2009)(5) PQ Tranchida R Costa P Donato D Sciarrone C Ragonese P Dugo G Dugo and L Mondello J Sep Sci 31(19)

3347ndash3351 (2008)(6) A Mosandl in RG Berger (Ed) Flavours and Fragrances ndash Chemistry Bioprocessing and Sustainability Springer p

379 (2007)(7) JT Brenna TN Corso HJ Tobias and RJ Caimi Mass Spectrom Rev 16(5) 227ndash258 (1997)(8) L Schipilliti P Dugo I Bonaccorsi and L Mondello J Chromatogr A 1218(42) 7481ndash7486 (2011)(9) K Sasamoto N Ochiai and H Kanda Talanta 72(5) 1637ndash1643 (2007)(10) M Adahchour J Beens and UA Th Brinkman J Chromatogr A 1186(1ndash2) 67ndash108 (2008)(11) I Silva SM Rocha MA Coimbra and PJ Marriott J Chromatogr A 1217(34) 5511ndash5521 (2010)(12) G Purcaro PQ Tranchida L Conte A Obiedzińska P Dugo G Dugo and L Mondello J Sep Sci 34(18) 2411ndash2417 (2011)(13) G Purcaro PQ Tranchida C Ragonese L Conte P Dugo G Dugo and L Mondello Anal Chem 82(20)

8583ndash8590 (2010)

Interview with author Luigi Mondello

InTERVIEW

1

Determination of Phenylurea Herbicidesin Tap Water and Soft Drink Samplesby HPLCndashUV and Solid-Phase Extraction

By Manpreet Kaur Ashok Kumar Malik and Baldev Singh

HP

LC

Phenylurea herbicides are used widely in a broad range of herbicide formulations as well as for nonagricultural use consequently their residues frequently are detected as major water contaminants in areas where these are used extensively (1) Diuron

and linuron are substituted urea compounds that are soluble in water and can migrate in soil and enter the food chain (2) These herbicides are of significant toxicological risk to humans and wildlife Diuron which is used in cotton growing areas and with fruit crops is rated as the third most hazardous pesticide for groundwater resources These herbicides also are applied on railway tracks to maintain quality and provide a safer working environment (3) but this may lead to groundwater contamination as their leaching potential is significant Phenylureas enter the environment through pathways such as spray drift runoff from treated fields and leaching into groundwater Most of the excess material penetrates into the soil where it is subjected to the action of microorganisms (4) and degradation as studied by Canonica and colleagues (5) Phenylureas are unstable photochemically as discussed by Khodja and colleagues (6) but these can persist in water

A simple and sensitive high performance liquid chromatography (HPLC)ndashUV method has been developed for the analysis of phenylurea herbicides namely monuron diuron linuron metazachlor and metoxuron that involves a preconcentration step using solid-phase extraction The mobile phase used was acetonitrilendashwater at a flow rate of 1 mLmin with direct UV absorbance detection at 210 nm Separation of analytes was studied on a C18 column The method was applied successfully to the analysis of the herbicides in three soft drink brands and tap water Good linearity and repeatability were observed for all the pesticides studied

2

for several days or weeks depending on the temperature and pH Cases of incidental pesticide pollution of water reservoirs (2ndash47ndash13) have become more numerous in recent years

Phenylurea residues can be found in water sources processed products and on the crops where these are applied In India most of the soft drink bottling plants use surface water from canals and rivers which have a high risk of pesticide contamination The water treatment measures used are insufficient for complete removal of these pesticide residues which have been found to be above permissible limits The evidence for the abovestated facts was provided in a 2003 Centre for Science and Environment (CSE New Delhi India) report that found several pesticide residues in many soft drink samples of leading international brands procured from all over India The CSE findings were affirmed further by a Joint Parliamentary Committee (JPC) created to verify the facts In 2006 CSE conducted another round of tests and found pesticides yet again in soft drink samples Keeping this in mind the present work has great importance as it involves the determination of phenyl urea herbicides in soft drink samples and tap water

Therefore it is imperative that sensitive selective and efficient methods for herbicide analysis be designed The common analytical methods used are high performance liquid chromatography (HPLC)ndashUV (2ndash47ndash9) solid-phase microextraction (SPME)ndashHPLC (10) diode array (11) immunosorbent trace enrichment and HPLC (1214) LCndashmass spectrometry (MS) (1516) gas chromatography (GC)ndashMS (13) capillary electrophoresis (1718 19) photochemically induced fluorescence (2021) and derivative spectrophotometry (22) A useful review is presented by Sherma (23) on the use of thin-layer chromatography (TLC) and its modified versions for the analysis of these herbicides Solid-phase extraction (SPE) of phenylurea herbicides has been reported in literature by several workers (24ndash29) The SPE of soft drinks has been reported extensively (30ndash36) As the use of polar and degradable pesticides becomes widespread it is urgent that more sensitive analytical methods be developed for their residual analysis in various matrices HPLC has several advantages over GC as it can be used for simultaneous analysis of thermally unstable nonvolatile polar and neutral species without a derivative step Because of the thermally unstable nature of phenylurea herbicides the direct application of GC to these compounds is not possible and derivatization prior to the detection is needed For this reason HPLC with UV absorption or fluorescence detection (7ndash10) is preferred over GC As a result HPLC is gaining popularity and preference as a pesticide analyzing technique

The present work describes a simple and sensitive HPLCndashUV method for the analysis of phenyl urea herbicides (namely monuron diuron linuron metazachlor and metoxuron) and it involves a single-step preconcentration by SPE

Phenolic Acids in Red Wine by SPE and HPLC

SPoNSorED

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article3herbicides_wineV3pdf

2

for several days or weeks depending on the temperature and pH Cases of incidental pesticide pollution of water reservoirs (2ndash47ndash13) have become more numerous in recent years

Phenylurea residues can be found in water sources processed products and on the crops where these are applied In India most of the soft drink bottling plants use surface water from canals and rivers which have a high risk of pesticide contamination The water treatment measures used are insufficient for complete removal of these pesticide residues which have been found to be above permissible limits The evidence for the abovestated facts was provided in a 2003 Centre for Science and Environment (CSE New Delhi India) report that found several pesticide residues in many soft drink samples of leading international brands procured from all over India The CSE findings were affirmed further by a Joint Parliamentary Committee (JPC) created to verify the facts In 2006 CSE conducted another round of tests and found pesticides yet again in soft drink samples Keeping this in mind the present work has great importance as it involves the determination of phenyl urea herbicides in soft drink samples and tap water

Therefore it is imperative that sensitive selective and efficient methods for herbicide analysis be designed The common analytical methods used are high performance liquid chromatography (HPLC)ndashUV (2ndash47ndash9) solid-phase microextraction (SPME)ndashHPLC (10) diode array (11) immunosorbent trace enrichment and HPLC (1214) LCndashmass spectrometry (MS) (1516) gas chromatography (GC)ndashMS (13) capillary electrophoresis (1718 19) photochemically induced fluorescence (2021) and derivative spectrophotometry (22) A useful review is presented by Sherma (23) on the use of thin-layer chromatography (TLC) and its modified versions for the analysis of these herbicides Solid-phase extraction (SPE) of phenylurea herbicides has been reported in literature by several workers (24ndash29) The SPE of soft drinks has been reported extensively (30ndash36) As the use of polar and degradable pesticides becomes widespread it is urgent that more sensitive analytical methods be developed for their residual analysis in various matrices HPLC has several advantages over GC as it can be used for simultaneous analysis of thermally unstable nonvolatile polar and neutral species without a derivative step Because of the thermally unstable nature of phenylurea herbicides the direct application of GC to these compounds is not possible and derivatization prior to the detection is needed For this reason HPLC with UV absorption or fluorescence detection (7ndash10) is preferred over GC As a result HPLC is gaining popularity and preference as a pesticide analyzing technique

The present work describes a simple and sensitive HPLCndashUV method for the analysis of phenyl urea herbicides (namely monuron diuron linuron metazachlor and metoxuron) and it involves a single-step preconcentration by SPE

Phenolic Acids in Red Wine by SPE and HPLC

SPoNSorED

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article3herbicides_wineV3pdf

3

Materials and MethodsThe HPLC system used included a P680 HPLC pump (Dionex Sunnyvale California) a 250 mm times 46 mm 5-microm Acclaim C18 rP analytical column (Dionex) and a UVD 170U detector operated at a wavelength of 210 nm coupled to a Chromeleon computer program for the acquisition of data (Dionex)

Monuron diuron linuron metoxuron and metazachlor (Figure 1) pesticide standards were obtained from riedel-de-Haen (Seelze Germany) HPLC-grade acetonitrile and methanol were obtained from JT Baker (Phillipsburg New Jersey) All the solvents were filtered through nylon 66 membrane filters (rankem New Delhi India) using a filtration assembly (Perfit India) and sonicated before use Triple-distilled water was used for all purposes

Standard PreparationStock solutions were prepared in a mixture of 5050 methanolndashwater All the solutions were stored under refrigeration below 4 degC

Sample PreparationThe SPE of the tap water and soft drink samples was performed using a Visiprep SPE vacuum manifold (Supelco Bellefonte Pennsylvania) and C18 cartridges from JT Baker The SPE cartridges were attached to the solvent-recovery assembly and connected to a vacuum pump The conditioning was done with 1 mL each of acetonitrile methanol and triple-distilled water

Soft drink samples The presence of phenylurea herbicides was studied in three different types of locally purchased soft drinks (Coke Mirinda and Limca) These were filtered with nylon 66 membrane filters and degassed by sonicating for 30 min The samples were spiked with the metoxuron monuron diuron metazachlor and linuron at a concentration of 5 ngmL A 20-mL volume of these samples was passed through the C18 SPE cartridges under vacuum and the analytes were eluted with 15 mL of

acetonitrile The eluants were further used for the HPLCndashUV analysis The sample blanks also were prepared similarly

Tap water sample The tap water sample was taken from the laboratory It was filtered and then degassed with an ultrasonic bath The sample was spiked with metoxuron monuron diuron metazachlor and linuron at a concentration of 5 ngmL each A 50-mL sample of the tap

DiuronLinuron

MetazachlorMonuron

Metoxuron

CH3

O

CH3 H

CN

CI

CIN CH3N

H

N

O

O

C

CI

CI

CH3

NNN

CI C

CH3

OCH2

CH2

H3C

CH3 N N

H

CI

O

C

CH3

CI

CH3O

CH3

CH3

NNH

O

C

Figure 1 Structures of phenylurea herbicides

4

water containing the mixture of herbicides was preconcentrated using C18 SPE cartridges A 15-mL volume of acetonitrile was used for the elution and the eluant was subjected to HPLCndashUV analysis The sample blanks were prepared by the same method

ProcedureAliquots of the mixture of five herbicides were taken having concentrations of 5ndash500 ppb These mixtures were analyzed at an optimum wavelength of 210 nm The mobile phase is an important factor in HPLC analysis as it interacts with solute species of the sample Hence the composition of the mobile phase was selected carefully as 6040 acetonitrilendashwater and the flow rate was set at 1 mLmin All measurements were taken at ambient temperature The calibration curves for all five herbicides were prepared and the curves were linear in the range studied

Results and DiscussionHPLCndashUV studies The separation of these herbicides was studied using direct injection of samples and parameters such as the effect of flow rate selection of suitable wavelength and composition of mobile phase were optimized The composition of the mobile phase was 6040 acetonitrilendashwater At higher flow rates than 10 mLmin the separations were not up to the baseline and with lower flow rates peak tailing was observed so the flow rate was optimized to 10 mLmin The wavelength for detection was selected from the UV absorption spectra of the five herbicides as 210 nm

Preparation of calibration curves The calibration curves were constructed for the detection of monuron linuron diuron metoxuron and metazachlor in the range of 5ndash500 ppb under the optimized conditions using the HPLC with UV detection The calibration curves were linear over this range Various characteristics of HPLCndashUV including regression equation working range and rSD are summarized in Table I The LoDs of the phenylurea herbicides were calculated using 33 times Sm (S = standard deviation m = slope of calibration curve) and they were found to be in the range 082ndash129 ngmL Characteristic chromatograms with HPLCndashUV detection at 210 nm are shown in Figures 2 and 3 for the separation of these herbicides

(a)

3

25

2

15

Abs

orba

nce

(mA

U)

Retention time (min)

1

05

0

3 5 7 9 11 13

(c)

(d)

(b)

Figure 3 HPLCndashUV chromatograms of (a) tap water (b) Coke (c) Limca and (d) Mirinda spiked with a mixture of phenylurea herbicides containing 5 ppb of each obtained after preconcentration by SPE

Ab

sorb

ance

(m

AU

)

Retention time (min)

1

08

06

04

02

0

-02-1 4

12 3

4 5

9 14

-04

Figure 2 HPLCndashUV chromatogram of mixture containing 5 ppb each of the phenylurea herbicides 1 = metoxuron 2 = monuron 3 = diuron 4 = metazachlor

5

Recoveries repeatability and LODs The method detection limits were calculated for these herbicides per the ICH Harmonized Tripartite Guidelines (wwwichorgLoBmediaMEDIA417pdf) The method LoQs can be calculated by using 10 times Sm The accuracy ( recovery) and precision (rSD) of the HPLCndashUV method were evaluated for each analyte by analyzing a standard of known concentration (5 ngmL) five times and quantifying it using the calibration curves Method optimization and validation parameters are presented in Tables I and II Good linearity and repeatability were observed for all the compounds studied (with correlation coefficient gt099) The method gives satisfactory results when used to quantify these herbicides in soft drink and tap water samples (Table II) with percentage recoveries ranging from 75 to 901

ApplicationsThe phenylurea herbicides were studied in various soft drink and tap water samples and no interfering peaks appeared at the retention times of these herbicides in the spiked samples The tap water Coke Mirinda and Limca (Figure 3) samples were spiked with metoxuron monuron diuron metazachlor and linuron at a concentration of 5 ngmL The analytical validation for the simultaneous quantification of metoxuron monuron diuron metazachlor and linuron has been performed with good recovery The recoveries obtained are very good in all cases Thus this method can be used to detect the presence of these harmful herbicides in the soft drink and water samples

Table II Analytical figures of merit obtained using various samples

Samples testedPhenylurea Herbicide

Metoxuron Monuron Diuron Metazachlor Linuron

Tap water

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 092 084 091 130 135

LOQ (ngmL) 276 252 273 390 405

Recovery (RSD) 806 (4) 842 (31) 901 (4) 871 (4) 763 (5)

Limca

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 095 089 099 139 141

LOQ (ngmL) 285 267 297 417 423

Recovery (RSD) 794 (4) 831 (4) 878 (42) 878 (45) 754 (51)

Coke

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 095 090 10 137 140

LOQ (ngmL) 285 270 30 411 420

Recovery (RSD) 775 (46) 802 (47) 886 (5) 853 (5) 773 (48)

Mirinda

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 096 089 099 137 142

LOQ (ngmL) 288 267 297 411 426

Recovery (RSD) 811 (34) 834 (32) 876 (4) 851 (43) 773 (53)

Samples spiked at 5 ngmL n = 5

Table I Analytical figures of merit obtained under optimum conditions

Characteristic Metoxuron Monuron Diuron Metazachlor Linuron

Regression equation 00016x + 00712 00014x + 00308 00035x + 0128 00017x + 0083 0002x + 01664

R2 0992 0994 0992 0992 0993

Retention time (min) 43 49 725 868 124

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD = 33 times Sm (ngmL) 092 082 093 128 129

LOQ = 10 times Sm (ngmL) 276 246 279 384 387

Recovery (RSD) 810 (24) 854 (3) 911 (3) 882 (32) 923 (5)

Amount of phenylurea herbicides taken 5 ngmL each (n = 5)

6

ConclusionsThe objective of the current study is to develop a simple isocratic reproducible specific and highly sensitive method for quantitative and qualitative determination of phenylurea herbicides In the present method the analysis time is 13 min (linuron tr 124 min) which is rapid in comparison to some of the other reported methods like Patsias and colleagues (37) (linuron tr 1888 min) Gerecke and colleagues (38) (linuron tr 1758 min) and Mughari and colleagues (39) (linuron tr 15 min) The proposed method can determine phenylurea herbicides at very low concentrations The present paper describes the application of HPLC to the separation and quantitative determination of five phenylurea herbicides and the feasibility of the method developed was tested by simultaneous determination of these herbicides in different brands of soft drinks and in tap water samples Good linearity and repeatability were observed for all the compounds studied (with correlation coefficient gt099) It is hoped that the results of the present study contribute to increased scientific knowledge in the field of pesticide residue analysis in various food and environmental samples

Manpreet Kaur Ashok Kumar Malik and Baldev Singh are with the Department of Chemistry Punjabi University Punjab India

How to Cite this ArticleM Kaur AK Malik and B Singh ldquoDetermination of Phenylurea Herbicides in Tap Water and Soft Drink Samples by HPLCndash

UV and Solid-Phase Extractionrdquo LCGC North America 29(4) 338ndash347 (2011)

References(1) SR Sorensen CN Albers and J Aamand Appl Environ Microbiol 74 2332ndash2340 (2008)(2) GMF Pinto and ICSF Jardim J Liq Chrom and Rel Technol 23 1353ndash1363 (2000) (3) H Cederlund E Boumlrjesson K Oumlnneby and J Stenstroumlm Soil Biology and Biochemistry 39 473ndash484 (2007)(4) E Van-der-Heeft E Dijkman RA Baumann and EA Hogendorn J Chromatogr A 879 39ndash50 (2000)(5) S Canonica and HU Laubscher Photochem Photobiol Sci 7 547ndash551 (2008)(6) AA Khodja B Laverdine C Richard and T Sehili Int J Photoenergy 4 147ndash151 (2002)(7) LE Sojo DS Gamble and DW Gutzman J Agric Food Chem 45 3634ndash3641 (1997)(8) J F Lawerence C Menard MC Hennion V Pichon F LeGoffic and N Durand J Chromatogr A 732 147ndash154 (1996)(9) Organonitrogen pesticides Method 5601 NIOSH manual of analytical methods 1ndash21 (1998) (10) H Berrada G Font and JC Molto JChromatogr A 1042 9ndash14 (2004) (11) R Jeannot H Sabik and E Genin J Chromatogr A 879 55ndash71 (2000)(12) S Herrera A Martin Esteban P Fernandez D Stevenson and C Camara Fresinius J Anal Chem 362 547ndash551 (1998)(13) Fast multi-residue pesticide analysis in soil and vegetable samples application note mass spectrometry wwwappliedbio-

systemscom

High-Pressure IC forBeverage Analysis webcast

SPoNSorED

7

(14) A Martin-Esteban P Fernandez D Stevenson and C Camara Analyst 122 1113ndash1117 (1997)(15) I Ferrer and D Barcelo Analusis Magazine 26 118ndash122 (1998)(16) T Yarita K Sugino T Ihara and A Nomura Analytical communications 35 91ndash92 (1998)(17) MS Barroso LN Konda and G Morovjan J High Resol Chromatogr 22 171ndash176 (1999)(18) S Batista E Silva S Galhardo P Viana and MJ Cerejeira Int J Env Anal Chem 82 601ndash609 (2002)(19) M Chicharro E Bermejo A Sanchez A Zapardiel A Fernandez-Gutierrez and D Arraez Anal Bioanal Chem 382

519ndash526 (2005)(20) A Bautista JJ Aaron MC Mahedero and A Munoz de La Pena Analusis 27 857ndash863 (1999)(21) MD Gil-Garciacutea M Martinez-Galera P Parrilla-Vaacutezquez AR Mughari and IM Ortiz-Rodriacuteguez Journal of Fluores-

cence 18 365ndash373 (2008)(22) I Baranowiska and C Pieszko Anal Letters 35 413ndash486 (2002)(23) J Sherma Acta Chromatographia 15 5ndash30 (2005)(24) MMC de la Pentildea and A Bautista-Saacutenchez Talanta 13 279ndash285 (2003)(25) I Ferrer V Pichon MC Hennion and D Barceloacute Journal of Chromatography A 1 91ndash98 (1997)(26) F Li D Martens and A Kettrup Se Pu 19 534ndash537 (2001)(27) T Cserhati E Forgaacutecs Z Deyl I Miksik and A Eckhardt Biomedical Chromatography 18 350ndash359 (2004)(28) MJI Mattina Journal of Chromatography A 549 237ndash245 (1991)(29) M Hamada and R Wintersteiger Journal of Planar Chromatography-Modern TLC 15 11ndash18 (2002)(30) JF Garciacutea-Reyes B Gilbert-Loacutepez and A Molina-Diacuteaz Anal Chem 30 8966ndash8974 (2002)(31) MA Mumin KF Akhter and MZ Abedin Malaysian Journal of Chemistry 8 45ndash51 (2008)(32) X L Cao J Corriveau and S Popovic J Agric Food Chem 57 1307ndash1311 (2009) (33) Z Pan L Wang W Mo C Wang W Hu and J Zhang Anal Chim Acta 545 218ndash223 (2005)(34) R Lucena S Cardenas M Gallego and M Valcarcel Anal Chim Acta 530 283ndash289 (2005)(35) E Papadopoulou-Mourkidou J Patsias E Papadakis and A Koukourikou Fresenius J Anal Chem 371 491ndash496

(2001)(36) N Yoshioka and K Ichihashi Talanta 74 1408ndash1413 (2008)(37) J Patsias and E Papadopoulou-Mourkidou JAOAC International 82 968ndash981 (1999)(38) A C Gerecke C Tixier T Bartels RP Schwarzenbach and SR Muumlller J chromatography A 930 9ndash19 (2001)(39) AR Mughari P Parrilla Vaacutezquez and M M Galera Anal Chimica Acta 593 157ndash163 (2007)

1

Data Handling amp Validation in Automated Detection of Food Toxicants

By Hans Mol Arjen Lommen Paul Zomer Henk van der Kamp Martijn van der Lee and Arjen Gerssen

Da

ta H

an

Dli

ng

During production processing storage and transport of food and feed a variety of potentially hazardous compounds may enter the food chain These include residues left after treatment of crops and animals with pesticides and veterinary drugs natural

toxins produced by fungi (mycotoxins) and plants environmental contaminants (persistent pollutants) and processing contaminants The potential presence of these compounds is an important issue in the field of food and feed safety Consequently extensive legislation has been established to protect consumers from unnecessary or excessive exposure to these substances Analytical chemists are facing a huge challenge when it comes to efficient verification of compliance of a wide variety of products with this legislation and preferably at the same time to provide occurrence data for lsquonewrsquo contaminants which are not yet regulated In short hundreds of different products need to be analysed for thousands of known contaminants and more

Within each class of contaminants the current lsquogold standardrsquo to deal with this challenge is the use of multi-analyte methods based on LC or GC with tandem MS detection Such methods typically cover tens to several hundreds of analytes and are well established in the field of pesticides1ndash3 with other fields following the same concept (eg mycotoxins45 and

Generic methods based on chromatography with full scan MS detection are maturing Progress has been made in the development of software for automated detection or identification of the analytes but this still is the bottleneck inhibiting implementation for routine analysis Validation of qualitative wide-scope screening is another hurdle to be taken before application An overview of current chromatography-based food toxicant screening is presented

Using Full Scan gCndashMS and lCndashMS

KEY POINTSFull scan acquisition is more straightforward than SIM and tandem MS and enables the detection of many more analytes without the need for knowing a priori

Although the time spent on sample preparation and set up of instrumental acquisition methods is declining the opposite is true for optimization of automated detection and finding the fit-for-purpose balance between false positives and false negatives

Systematic validation studies of fully automated chromatography-based screening methods are still lacking

The next challenge after developing generic screening methods is the development of generic software tools for data evaluation and data mining

2

veterinary drugs67) The instrumental methods involve targeted acquisition where detection of each compound is individually optimized during instrumental method development The methods are typically extensively validated with respect to quantitative performance and data handling usually involves a manual review of extracted ion chromatograms to verify peak assignment and integration

A logical next step is to combine multi-methods beyond their contaminant class The feasibility of this approach has recently been demonstrated8 by simultaneous determination of pesticides veterinary drugs mycotoxins and plant toxins in a variety of food and feed commodities Sample preparation for such integrated methods is very generic and straightforward (as simple as a single extractiondilution step) Because the anticipated number of analytes to be covered in this approach is beyond what can easily be accommodated by tandem MS full scan MS is the detection method of choice Here the measurement is non-targeted which makes the instrumental analysis much more straightforward (ie no application-specific instrument adjustments or optimization needed no acquisition-time windows) In principle the scope of the method is unlimited As long as analytes elute from the column and are ionized in the source they can be detected The moment of setting the scope of the method shifts from before to after the instrumental analysis

The conclusion from the trend described above is that both sample preparation and instrumental analysis are becoming more and more generic and to a certain extent independent of the analyte of current or future interest This also means that the main effort in terms of development optimization and validation is clearly moving from sample preparation and instrumental analysis towards data processing to ensure reliable detection of the compounds of interest

This paper will provide a brief overview of the full scan MS options currently available for chromatography-based wide-scope screening of food toxicants Aspects related to automated detection and identification will be discussed based on literature and experiences within the authorsrsquo laboratory with emphasis on data handling An in-house developed software package (MetAlign) which features instrument independent and uniform data preprocessing and automated identification will be presented

General Considerations on Automated DetectionIdentification After Full Scan MS MeasurementThe raw data files obtained after GC or LC with full scan MS detection are typically 20ndash500 Mb and contain information on retention time (1 or 2 dimensional) mz = 50ndash1000 (nominal or accurate mass) and abundance (from noise to saturation) Getting meaningful results out of this huge amount of

3

information in an efficient manner is not a trivial task In principle two approaches can be pursued non-targeted and targeted data evaluation With non-targeted data analysis the raw data file is processed to obtain a list of all individual peaks present in the entire chromatographic run The number of peaks can be in the 10 000s which rules out a manual identification Without any a priori information one could restrict the evaluation to the major peaks but these are usually originating from non-toxic endogenous compounds rather than contaminants which are mostly present at low levels Another option is to filter out contaminants by comparing overall LCndashMS or GCndashMS profiles of samples with profiles obtained after analysis of the corresponding non-contaminated product For this extensive databases for the different food commodities would be required which still need to be generated Consequently a more feasible option for the time being is to perform a targeted data evaluation based on libraries containing information on the target compounds All individual peaks assigned after data (pre)processing can then be matched against the information in the library Alternatively the software could use the target library as a starting point and restrict the search to compound-specific retention time windows and ion traces from the raw data file Either way some sort of match between experimental data and library data is obtained Depending on the MS device used this match can be based on a combination of retention time(s) ions ratios mass spectra isotope patterns andor mass accuracy Criteria will have to be set for each of the match parameters in such a way that the number of so-called lsquofalse negativesrsquo and lsquofalse positivesrsquo are within acceptable limits False negatives are compounds known to be present in the sample but missed by the automated screening method false positives are compounds known to be absent but appearing on the list of (provisionally) detected compounds

GC-Full Scan MSVarious options for full scan MS detection are available for GC Single quadrupole and ion trap instruments have been commonly applied for food analysis since the 1990s especially for the determination of pesticide residues in vegetables and fruits Sensitivity limitations encountered in the past when using full scan acquisition have been overcome by large volume injection using PTV injectors9 and improvements in MS devices A big advantage of GCndashMS is that the MS spectra obtained after electron ionization are highly characteristic and to a large extent are instrument independent This means that spectra generated elsewhere can be used and that libraries can be purchased Despite the screening potential the instruments were and still are mainly used for quantitative analysis rather than for screening One reason for this is that the spectra of the analytes in the sample often contain interfering ions from other compounds which complicates automated matching against library spectra To a certain extent the quality of sample extraction can be improved by software alogorithms such as deconvolution that resolve spectra from overlapping peaks and background Deconvolution software tools are available both commercially and as free downloads (for example AMDIS from NIST10) A second reason for the limited

Screening and Quantitating Pesticides in Water with LC-MS

SPONSOrED

httplearnpharmasciencecomtablet-appsfood-issue1article4pesticidespdf

4

water containing the mixture of herbicides was preconcentrated using C18 SPE cartridges A 15-mL volume of acetonitrile was used for the elution and the eluant was subjected to HPLCndashUV analysis The sample blanks were prepared by the same method

ProcedureAliquots of the mixture of five herbicides were taken having concentrations of 5ndash500 ppb These mixtures were analyzed at an optimum wavelength of 210 nm The mobile phase is an important factor in HPLC analysis as it interacts with solute species of the sample Hence the composition of the mobile phase was selected carefully as 6040 acetonitrilendashwater and the flow rate was set at 1 mLmin All measurements were taken at ambient temperature The calibration curves for all five herbicides were prepared and the curves were linear in the range studied

Results and DiscussionHPLCndashUV studies The separation of these herbicides was studied using direct injection of samples and parameters such as the effect of flow rate selection of suitable wavelength and composition of mobile phase were optimized The composition of the mobile phase was 6040 acetonitrilendashwater At higher flow rates than 10 mLmin the separations were not up to the baseline and with lower flow rates peak tailing was observed so the flow rate was optimized to 10 mLmin The wavelength for detection was selected from the UV absorption spectra of the five herbicides as 210 nm

Preparation of calibration curves The calibration curves were constructed for the detection of monuron linuron diuron metoxuron and metazachlor in the range of 5ndash500 ppb under the optimized conditions using the HPLC with UV detection The calibration curves were linear over this range Various characteristics of HPLCndashUV including regression equation working range and rSD are summarized in Table I The LoDs of the phenylurea herbicides were calculated using 33 times Sm (S = standard deviation m = slope of calibration curve) and they were found to be in the range 082ndash129 ngmL Characteristic chromatograms with HPLCndashUV detection at 210 nm are shown in Figures 2 and 3 for the separation of these herbicides

(a)

3

25

2

15

Abs

orba

nce

(mA

U)

Retention time (min)

1

05

0

3 5 7 9 11 13

(c)

(d)

(b)

Figure 3 HPLCndashUV chromatograms of (a) tap water (b) Coke (c) Limca and (d) Mirinda spiked with a mixture of phenylurea herbicides containing 5 ppb of each obtained after preconcentration by SPE

Ab

sorb

ance

(m

AU

)

Retention time (min)

1

08

06

04

02

0

-02-1 4

12 3

4 5

9 14

-04

Figure 2 HPLCndashUV chromatogram of mixture containing 5 ppb each of the phenylurea herbicides 1 = metoxuron 2 = monuron 3 = diuron 4 = metazachlor

5

Recoveries repeatability and LODs The method detection limits were calculated for these herbicides per the ICH Harmonized Tripartite Guidelines (wwwichorgLoBmediaMEDIA417pdf) The method LoQs can be calculated by using 10 times Sm The accuracy ( recovery) and precision (rSD) of the HPLCndashUV method were evaluated for each analyte by analyzing a standard of known concentration (5 ngmL) five times and quantifying it using the calibration curves Method optimization and validation parameters are presented in Tables I and II Good linearity and repeatability were observed for all the compounds studied (with correlation coefficient gt099) The method gives satisfactory results when used to quantify these herbicides in soft drink and tap water samples (Table II) with percentage recoveries ranging from 75 to 901

ApplicationsThe phenylurea herbicides were studied in various soft drink and tap water samples and no interfering peaks appeared at the retention times of these herbicides in the spiked samples The tap water Coke Mirinda and Limca (Figure 3) samples were spiked with metoxuron monuron diuron metazachlor and linuron at a concentration of 5 ngmL The analytical validation for the simultaneous quantification of metoxuron monuron diuron metazachlor and linuron has been performed with good recovery The recoveries obtained are very good in all cases Thus this method can be used to detect the presence of these harmful herbicides in the soft drink and water samples

Table II Analytical figures of merit obtained using various samples

Samples testedPhenylurea Herbicide

Metoxuron Monuron Diuron Metazachlor Linuron

Tap water

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 092 084 091 130 135

LOQ (ngmL) 276 252 273 390 405

Recovery (RSD) 806 (4) 842 (31) 901 (4) 871 (4) 763 (5)

Limca

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 095 089 099 139 141

LOQ (ngmL) 285 267 297 417 423

Recovery (RSD) 794 (4) 831 (4) 878 (42) 878 (45) 754 (51)

Coke

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 095 090 10 137 140

LOQ (ngmL) 285 270 30 411 420

Recovery (RSD) 775 (46) 802 (47) 886 (5) 853 (5) 773 (48)

Mirinda

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 096 089 099 137 142

LOQ (ngmL) 288 267 297 411 426

Recovery (RSD) 811 (34) 834 (32) 876 (4) 851 (43) 773 (53)

Samples spiked at 5 ngmL n = 5

Table I Analytical figures of merit obtained under optimum conditions

Characteristic Metoxuron Monuron Diuron Metazachlor Linuron

Regression equation 00016x + 00712 00014x + 00308 00035x + 0128 00017x + 0083 0002x + 01664

R2 0992 0994 0992 0992 0993

Retention time (min) 43 49 725 868 124

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD = 33 times Sm (ngmL) 092 082 093 128 129

LOQ = 10 times Sm (ngmL) 276 246 279 384 387

Recovery (RSD) 810 (24) 854 (3) 911 (3) 882 (32) 923 (5)

Amount of phenylurea herbicides taken 5 ngmL each (n = 5)

6

ConclusionsThe objective of the current study is to develop a simple isocratic reproducible specific and highly sensitive method for quantitative and qualitative determination of phenylurea herbicides In the present method the analysis time is 13 min (linuron tr 124 min) which is rapid in comparison to some of the other reported methods like Patsias and colleagues (37) (linuron tr 1888 min) Gerecke and colleagues (38) (linuron tr 1758 min) and Mughari and colleagues (39) (linuron tr 15 min) The proposed method can determine phenylurea herbicides at very low concentrations The present paper describes the application of HPLC to the separation and quantitative determination of five phenylurea herbicides and the feasibility of the method developed was tested by simultaneous determination of these herbicides in different brands of soft drinks and in tap water samples Good linearity and repeatability were observed for all the compounds studied (with correlation coefficient gt099) It is hoped that the results of the present study contribute to increased scientific knowledge in the field of pesticide residue analysis in various food and environmental samples

Manpreet Kaur Ashok Kumar Malik and Baldev Singh are with the Department of Chemistry Punjabi University Punjab India

How to Cite this ArticleM Kaur AK Malik and B Singh ldquoDetermination of Phenylurea Herbicides in Tap Water and Soft Drink Samples by HPLCndash

UV and Solid-Phase Extractionrdquo LCGC North America 29(4) 338ndash347 (2011)

References(1) SR Sorensen CN Albers and J Aamand Appl Environ Microbiol 74 2332ndash2340 (2008)(2) GMF Pinto and ICSF Jardim J Liq Chrom and Rel Technol 23 1353ndash1363 (2000) (3) H Cederlund E Boumlrjesson K Oumlnneby and J Stenstroumlm Soil Biology and Biochemistry 39 473ndash484 (2007)(4) E Van-der-Heeft E Dijkman RA Baumann and EA Hogendorn J Chromatogr A 879 39ndash50 (2000)(5) S Canonica and HU Laubscher Photochem Photobiol Sci 7 547ndash551 (2008)(6) AA Khodja B Laverdine C Richard and T Sehili Int J Photoenergy 4 147ndash151 (2002)(7) LE Sojo DS Gamble and DW Gutzman J Agric Food Chem 45 3634ndash3641 (1997)(8) J F Lawerence C Menard MC Hennion V Pichon F LeGoffic and N Durand J Chromatogr A 732 147ndash154 (1996)(9) Organonitrogen pesticides Method 5601 NIOSH manual of analytical methods 1ndash21 (1998) (10) H Berrada G Font and JC Molto JChromatogr A 1042 9ndash14 (2004) (11) R Jeannot H Sabik and E Genin J Chromatogr A 879 55ndash71 (2000)(12) S Herrera A Martin Esteban P Fernandez D Stevenson and C Camara Fresinius J Anal Chem 362 547ndash551 (1998)(13) Fast multi-residue pesticide analysis in soil and vegetable samples application note mass spectrometry wwwappliedbio-

systemscom

High-Pressure IC forBeverage Analysis webcast

SPoNSorED

7

(14) A Martin-Esteban P Fernandez D Stevenson and C Camara Analyst 122 1113ndash1117 (1997)(15) I Ferrer and D Barcelo Analusis Magazine 26 118ndash122 (1998)(16) T Yarita K Sugino T Ihara and A Nomura Analytical communications 35 91ndash92 (1998)(17) MS Barroso LN Konda and G Morovjan J High Resol Chromatogr 22 171ndash176 (1999)(18) S Batista E Silva S Galhardo P Viana and MJ Cerejeira Int J Env Anal Chem 82 601ndash609 (2002)(19) M Chicharro E Bermejo A Sanchez A Zapardiel A Fernandez-Gutierrez and D Arraez Anal Bioanal Chem 382

519ndash526 (2005)(20) A Bautista JJ Aaron MC Mahedero and A Munoz de La Pena Analusis 27 857ndash863 (1999)(21) MD Gil-Garciacutea M Martinez-Galera P Parrilla-Vaacutezquez AR Mughari and IM Ortiz-Rodriacuteguez Journal of Fluores-

cence 18 365ndash373 (2008)(22) I Baranowiska and C Pieszko Anal Letters 35 413ndash486 (2002)(23) J Sherma Acta Chromatographia 15 5ndash30 (2005)(24) MMC de la Pentildea and A Bautista-Saacutenchez Talanta 13 279ndash285 (2003)(25) I Ferrer V Pichon MC Hennion and D Barceloacute Journal of Chromatography A 1 91ndash98 (1997)(26) F Li D Martens and A Kettrup Se Pu 19 534ndash537 (2001)(27) T Cserhati E Forgaacutecs Z Deyl I Miksik and A Eckhardt Biomedical Chromatography 18 350ndash359 (2004)(28) MJI Mattina Journal of Chromatography A 549 237ndash245 (1991)(29) M Hamada and R Wintersteiger Journal of Planar Chromatography-Modern TLC 15 11ndash18 (2002)(30) JF Garciacutea-Reyes B Gilbert-Loacutepez and A Molina-Diacuteaz Anal Chem 30 8966ndash8974 (2002)(31) MA Mumin KF Akhter and MZ Abedin Malaysian Journal of Chemistry 8 45ndash51 (2008)(32) X L Cao J Corriveau and S Popovic J Agric Food Chem 57 1307ndash1311 (2009) (33) Z Pan L Wang W Mo C Wang W Hu and J Zhang Anal Chim Acta 545 218ndash223 (2005)(34) R Lucena S Cardenas M Gallego and M Valcarcel Anal Chim Acta 530 283ndash289 (2005)(35) E Papadopoulou-Mourkidou J Patsias E Papadakis and A Koukourikou Fresenius J Anal Chem 371 491ndash496

(2001)(36) N Yoshioka and K Ichihashi Talanta 74 1408ndash1413 (2008)(37) J Patsias and E Papadopoulou-Mourkidou JAOAC International 82 968ndash981 (1999)(38) A C Gerecke C Tixier T Bartels RP Schwarzenbach and SR Muumlller J chromatography A 930 9ndash19 (2001)(39) AR Mughari P Parrilla Vaacutezquez and M M Galera Anal Chimica Acta 593 157ndash163 (2007)

1

Data Handling amp Validation in Automated Detection of Food Toxicants

By Hans Mol Arjen Lommen Paul Zomer Henk van der Kamp Martijn van der Lee and Arjen Gerssen

Da

ta H

an

Dli

ng

During production processing storage and transport of food and feed a variety of potentially hazardous compounds may enter the food chain These include residues left after treatment of crops and animals with pesticides and veterinary drugs natural

toxins produced by fungi (mycotoxins) and plants environmental contaminants (persistent pollutants) and processing contaminants The potential presence of these compounds is an important issue in the field of food and feed safety Consequently extensive legislation has been established to protect consumers from unnecessary or excessive exposure to these substances Analytical chemists are facing a huge challenge when it comes to efficient verification of compliance of a wide variety of products with this legislation and preferably at the same time to provide occurrence data for lsquonewrsquo contaminants which are not yet regulated In short hundreds of different products need to be analysed for thousands of known contaminants and more

Within each class of contaminants the current lsquogold standardrsquo to deal with this challenge is the use of multi-analyte methods based on LC or GC with tandem MS detection Such methods typically cover tens to several hundreds of analytes and are well established in the field of pesticides1ndash3 with other fields following the same concept (eg mycotoxins45 and

Generic methods based on chromatography with full scan MS detection are maturing Progress has been made in the development of software for automated detection or identification of the analytes but this still is the bottleneck inhibiting implementation for routine analysis Validation of qualitative wide-scope screening is another hurdle to be taken before application An overview of current chromatography-based food toxicant screening is presented

Using Full Scan gCndashMS and lCndashMS

KEY POINTSFull scan acquisition is more straightforward than SIM and tandem MS and enables the detection of many more analytes without the need for knowing a priori

Although the time spent on sample preparation and set up of instrumental acquisition methods is declining the opposite is true for optimization of automated detection and finding the fit-for-purpose balance between false positives and false negatives

Systematic validation studies of fully automated chromatography-based screening methods are still lacking

The next challenge after developing generic screening methods is the development of generic software tools for data evaluation and data mining

2

veterinary drugs67) The instrumental methods involve targeted acquisition where detection of each compound is individually optimized during instrumental method development The methods are typically extensively validated with respect to quantitative performance and data handling usually involves a manual review of extracted ion chromatograms to verify peak assignment and integration

A logical next step is to combine multi-methods beyond their contaminant class The feasibility of this approach has recently been demonstrated8 by simultaneous determination of pesticides veterinary drugs mycotoxins and plant toxins in a variety of food and feed commodities Sample preparation for such integrated methods is very generic and straightforward (as simple as a single extractiondilution step) Because the anticipated number of analytes to be covered in this approach is beyond what can easily be accommodated by tandem MS full scan MS is the detection method of choice Here the measurement is non-targeted which makes the instrumental analysis much more straightforward (ie no application-specific instrument adjustments or optimization needed no acquisition-time windows) In principle the scope of the method is unlimited As long as analytes elute from the column and are ionized in the source they can be detected The moment of setting the scope of the method shifts from before to after the instrumental analysis

The conclusion from the trend described above is that both sample preparation and instrumental analysis are becoming more and more generic and to a certain extent independent of the analyte of current or future interest This also means that the main effort in terms of development optimization and validation is clearly moving from sample preparation and instrumental analysis towards data processing to ensure reliable detection of the compounds of interest

This paper will provide a brief overview of the full scan MS options currently available for chromatography-based wide-scope screening of food toxicants Aspects related to automated detection and identification will be discussed based on literature and experiences within the authorsrsquo laboratory with emphasis on data handling An in-house developed software package (MetAlign) which features instrument independent and uniform data preprocessing and automated identification will be presented

General Considerations on Automated DetectionIdentification After Full Scan MS MeasurementThe raw data files obtained after GC or LC with full scan MS detection are typically 20ndash500 Mb and contain information on retention time (1 or 2 dimensional) mz = 50ndash1000 (nominal or accurate mass) and abundance (from noise to saturation) Getting meaningful results out of this huge amount of

3

information in an efficient manner is not a trivial task In principle two approaches can be pursued non-targeted and targeted data evaluation With non-targeted data analysis the raw data file is processed to obtain a list of all individual peaks present in the entire chromatographic run The number of peaks can be in the 10 000s which rules out a manual identification Without any a priori information one could restrict the evaluation to the major peaks but these are usually originating from non-toxic endogenous compounds rather than contaminants which are mostly present at low levels Another option is to filter out contaminants by comparing overall LCndashMS or GCndashMS profiles of samples with profiles obtained after analysis of the corresponding non-contaminated product For this extensive databases for the different food commodities would be required which still need to be generated Consequently a more feasible option for the time being is to perform a targeted data evaluation based on libraries containing information on the target compounds All individual peaks assigned after data (pre)processing can then be matched against the information in the library Alternatively the software could use the target library as a starting point and restrict the search to compound-specific retention time windows and ion traces from the raw data file Either way some sort of match between experimental data and library data is obtained Depending on the MS device used this match can be based on a combination of retention time(s) ions ratios mass spectra isotope patterns andor mass accuracy Criteria will have to be set for each of the match parameters in such a way that the number of so-called lsquofalse negativesrsquo and lsquofalse positivesrsquo are within acceptable limits False negatives are compounds known to be present in the sample but missed by the automated screening method false positives are compounds known to be absent but appearing on the list of (provisionally) detected compounds

GC-Full Scan MSVarious options for full scan MS detection are available for GC Single quadrupole and ion trap instruments have been commonly applied for food analysis since the 1990s especially for the determination of pesticide residues in vegetables and fruits Sensitivity limitations encountered in the past when using full scan acquisition have been overcome by large volume injection using PTV injectors9 and improvements in MS devices A big advantage of GCndashMS is that the MS spectra obtained after electron ionization are highly characteristic and to a large extent are instrument independent This means that spectra generated elsewhere can be used and that libraries can be purchased Despite the screening potential the instruments were and still are mainly used for quantitative analysis rather than for screening One reason for this is that the spectra of the analytes in the sample often contain interfering ions from other compounds which complicates automated matching against library spectra To a certain extent the quality of sample extraction can be improved by software alogorithms such as deconvolution that resolve spectra from overlapping peaks and background Deconvolution software tools are available both commercially and as free downloads (for example AMDIS from NIST10) A second reason for the limited

Screening and Quantitating Pesticides in Water with LC-MS

SPONSOrED

httplearnpharmasciencecomtablet-appsfood-issue1article4pesticidespdf

5

Recoveries repeatability and LODs The method detection limits were calculated for these herbicides per the ICH Harmonized Tripartite Guidelines (wwwichorgLoBmediaMEDIA417pdf) The method LoQs can be calculated by using 10 times Sm The accuracy ( recovery) and precision (rSD) of the HPLCndashUV method were evaluated for each analyte by analyzing a standard of known concentration (5 ngmL) five times and quantifying it using the calibration curves Method optimization and validation parameters are presented in Tables I and II Good linearity and repeatability were observed for all the compounds studied (with correlation coefficient gt099) The method gives satisfactory results when used to quantify these herbicides in soft drink and tap water samples (Table II) with percentage recoveries ranging from 75 to 901

ApplicationsThe phenylurea herbicides were studied in various soft drink and tap water samples and no interfering peaks appeared at the retention times of these herbicides in the spiked samples The tap water Coke Mirinda and Limca (Figure 3) samples were spiked with metoxuron monuron diuron metazachlor and linuron at a concentration of 5 ngmL The analytical validation for the simultaneous quantification of metoxuron monuron diuron metazachlor and linuron has been performed with good recovery The recoveries obtained are very good in all cases Thus this method can be used to detect the presence of these harmful herbicides in the soft drink and water samples

Table II Analytical figures of merit obtained using various samples

Samples testedPhenylurea Herbicide

Metoxuron Monuron Diuron Metazachlor Linuron

Tap water

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 092 084 091 130 135

LOQ (ngmL) 276 252 273 390 405

Recovery (RSD) 806 (4) 842 (31) 901 (4) 871 (4) 763 (5)

Limca

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 095 089 099 139 141

LOQ (ngmL) 285 267 297 417 423

Recovery (RSD) 794 (4) 831 (4) 878 (42) 878 (45) 754 (51)

Coke

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 095 090 10 137 140

LOQ (ngmL) 285 270 30 411 420

Recovery (RSD) 775 (46) 802 (47) 886 (5) 853 (5) 773 (48)

Mirinda

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD (ngmL) 096 089 099 137 142

LOQ (ngmL) 288 267 297 411 426

Recovery (RSD) 811 (34) 834 (32) 876 (4) 851 (43) 773 (53)

Samples spiked at 5 ngmL n = 5

Table I Analytical figures of merit obtained under optimum conditions

Characteristic Metoxuron Monuron Diuron Metazachlor Linuron

Regression equation 00016x + 00712 00014x + 00308 00035x + 0128 00017x + 0083 0002x + 01664

R2 0992 0994 0992 0992 0993

Retention time (min) 43 49 725 868 124

Linear range (ngmL) 5ndash500 5ndash500 5ndash500 5ndash500 5ndash500

LOD = 33 times Sm (ngmL) 092 082 093 128 129

LOQ = 10 times Sm (ngmL) 276 246 279 384 387

Recovery (RSD) 810 (24) 854 (3) 911 (3) 882 (32) 923 (5)

Amount of phenylurea herbicides taken 5 ngmL each (n = 5)

6

ConclusionsThe objective of the current study is to develop a simple isocratic reproducible specific and highly sensitive method for quantitative and qualitative determination of phenylurea herbicides In the present method the analysis time is 13 min (linuron tr 124 min) which is rapid in comparison to some of the other reported methods like Patsias and colleagues (37) (linuron tr 1888 min) Gerecke and colleagues (38) (linuron tr 1758 min) and Mughari and colleagues (39) (linuron tr 15 min) The proposed method can determine phenylurea herbicides at very low concentrations The present paper describes the application of HPLC to the separation and quantitative determination of five phenylurea herbicides and the feasibility of the method developed was tested by simultaneous determination of these herbicides in different brands of soft drinks and in tap water samples Good linearity and repeatability were observed for all the compounds studied (with correlation coefficient gt099) It is hoped that the results of the present study contribute to increased scientific knowledge in the field of pesticide residue analysis in various food and environmental samples

Manpreet Kaur Ashok Kumar Malik and Baldev Singh are with the Department of Chemistry Punjabi University Punjab India

How to Cite this ArticleM Kaur AK Malik and B Singh ldquoDetermination of Phenylurea Herbicides in Tap Water and Soft Drink Samples by HPLCndash

UV and Solid-Phase Extractionrdquo LCGC North America 29(4) 338ndash347 (2011)

References(1) SR Sorensen CN Albers and J Aamand Appl Environ Microbiol 74 2332ndash2340 (2008)(2) GMF Pinto and ICSF Jardim J Liq Chrom and Rel Technol 23 1353ndash1363 (2000) (3) H Cederlund E Boumlrjesson K Oumlnneby and J Stenstroumlm Soil Biology and Biochemistry 39 473ndash484 (2007)(4) E Van-der-Heeft E Dijkman RA Baumann and EA Hogendorn J Chromatogr A 879 39ndash50 (2000)(5) S Canonica and HU Laubscher Photochem Photobiol Sci 7 547ndash551 (2008)(6) AA Khodja B Laverdine C Richard and T Sehili Int J Photoenergy 4 147ndash151 (2002)(7) LE Sojo DS Gamble and DW Gutzman J Agric Food Chem 45 3634ndash3641 (1997)(8) J F Lawerence C Menard MC Hennion V Pichon F LeGoffic and N Durand J Chromatogr A 732 147ndash154 (1996)(9) Organonitrogen pesticides Method 5601 NIOSH manual of analytical methods 1ndash21 (1998) (10) H Berrada G Font and JC Molto JChromatogr A 1042 9ndash14 (2004) (11) R Jeannot H Sabik and E Genin J Chromatogr A 879 55ndash71 (2000)(12) S Herrera A Martin Esteban P Fernandez D Stevenson and C Camara Fresinius J Anal Chem 362 547ndash551 (1998)(13) Fast multi-residue pesticide analysis in soil and vegetable samples application note mass spectrometry wwwappliedbio-

systemscom

High-Pressure IC forBeverage Analysis webcast

SPoNSorED

7

(14) A Martin-Esteban P Fernandez D Stevenson and C Camara Analyst 122 1113ndash1117 (1997)(15) I Ferrer and D Barcelo Analusis Magazine 26 118ndash122 (1998)(16) T Yarita K Sugino T Ihara and A Nomura Analytical communications 35 91ndash92 (1998)(17) MS Barroso LN Konda and G Morovjan J High Resol Chromatogr 22 171ndash176 (1999)(18) S Batista E Silva S Galhardo P Viana and MJ Cerejeira Int J Env Anal Chem 82 601ndash609 (2002)(19) M Chicharro E Bermejo A Sanchez A Zapardiel A Fernandez-Gutierrez and D Arraez Anal Bioanal Chem 382

519ndash526 (2005)(20) A Bautista JJ Aaron MC Mahedero and A Munoz de La Pena Analusis 27 857ndash863 (1999)(21) MD Gil-Garciacutea M Martinez-Galera P Parrilla-Vaacutezquez AR Mughari and IM Ortiz-Rodriacuteguez Journal of Fluores-

cence 18 365ndash373 (2008)(22) I Baranowiska and C Pieszko Anal Letters 35 413ndash486 (2002)(23) J Sherma Acta Chromatographia 15 5ndash30 (2005)(24) MMC de la Pentildea and A Bautista-Saacutenchez Talanta 13 279ndash285 (2003)(25) I Ferrer V Pichon MC Hennion and D Barceloacute Journal of Chromatography A 1 91ndash98 (1997)(26) F Li D Martens and A Kettrup Se Pu 19 534ndash537 (2001)(27) T Cserhati E Forgaacutecs Z Deyl I Miksik and A Eckhardt Biomedical Chromatography 18 350ndash359 (2004)(28) MJI Mattina Journal of Chromatography A 549 237ndash245 (1991)(29) M Hamada and R Wintersteiger Journal of Planar Chromatography-Modern TLC 15 11ndash18 (2002)(30) JF Garciacutea-Reyes B Gilbert-Loacutepez and A Molina-Diacuteaz Anal Chem 30 8966ndash8974 (2002)(31) MA Mumin KF Akhter and MZ Abedin Malaysian Journal of Chemistry 8 45ndash51 (2008)(32) X L Cao J Corriveau and S Popovic J Agric Food Chem 57 1307ndash1311 (2009) (33) Z Pan L Wang W Mo C Wang W Hu and J Zhang Anal Chim Acta 545 218ndash223 (2005)(34) R Lucena S Cardenas M Gallego and M Valcarcel Anal Chim Acta 530 283ndash289 (2005)(35) E Papadopoulou-Mourkidou J Patsias E Papadakis and A Koukourikou Fresenius J Anal Chem 371 491ndash496

(2001)(36) N Yoshioka and K Ichihashi Talanta 74 1408ndash1413 (2008)(37) J Patsias and E Papadopoulou-Mourkidou JAOAC International 82 968ndash981 (1999)(38) A C Gerecke C Tixier T Bartels RP Schwarzenbach and SR Muumlller J chromatography A 930 9ndash19 (2001)(39) AR Mughari P Parrilla Vaacutezquez and M M Galera Anal Chimica Acta 593 157ndash163 (2007)

1

Data Handling amp Validation in Automated Detection of Food Toxicants

By Hans Mol Arjen Lommen Paul Zomer Henk van der Kamp Martijn van der Lee and Arjen Gerssen

Da

ta H

an

Dli

ng

During production processing storage and transport of food and feed a variety of potentially hazardous compounds may enter the food chain These include residues left after treatment of crops and animals with pesticides and veterinary drugs natural

toxins produced by fungi (mycotoxins) and plants environmental contaminants (persistent pollutants) and processing contaminants The potential presence of these compounds is an important issue in the field of food and feed safety Consequently extensive legislation has been established to protect consumers from unnecessary or excessive exposure to these substances Analytical chemists are facing a huge challenge when it comes to efficient verification of compliance of a wide variety of products with this legislation and preferably at the same time to provide occurrence data for lsquonewrsquo contaminants which are not yet regulated In short hundreds of different products need to be analysed for thousands of known contaminants and more

Within each class of contaminants the current lsquogold standardrsquo to deal with this challenge is the use of multi-analyte methods based on LC or GC with tandem MS detection Such methods typically cover tens to several hundreds of analytes and are well established in the field of pesticides1ndash3 with other fields following the same concept (eg mycotoxins45 and

Generic methods based on chromatography with full scan MS detection are maturing Progress has been made in the development of software for automated detection or identification of the analytes but this still is the bottleneck inhibiting implementation for routine analysis Validation of qualitative wide-scope screening is another hurdle to be taken before application An overview of current chromatography-based food toxicant screening is presented

Using Full Scan gCndashMS and lCndashMS

KEY POINTSFull scan acquisition is more straightforward than SIM and tandem MS and enables the detection of many more analytes without the need for knowing a priori

Although the time spent on sample preparation and set up of instrumental acquisition methods is declining the opposite is true for optimization of automated detection and finding the fit-for-purpose balance between false positives and false negatives

Systematic validation studies of fully automated chromatography-based screening methods are still lacking

The next challenge after developing generic screening methods is the development of generic software tools for data evaluation and data mining

2

veterinary drugs67) The instrumental methods involve targeted acquisition where detection of each compound is individually optimized during instrumental method development The methods are typically extensively validated with respect to quantitative performance and data handling usually involves a manual review of extracted ion chromatograms to verify peak assignment and integration

A logical next step is to combine multi-methods beyond their contaminant class The feasibility of this approach has recently been demonstrated8 by simultaneous determination of pesticides veterinary drugs mycotoxins and plant toxins in a variety of food and feed commodities Sample preparation for such integrated methods is very generic and straightforward (as simple as a single extractiondilution step) Because the anticipated number of analytes to be covered in this approach is beyond what can easily be accommodated by tandem MS full scan MS is the detection method of choice Here the measurement is non-targeted which makes the instrumental analysis much more straightforward (ie no application-specific instrument adjustments or optimization needed no acquisition-time windows) In principle the scope of the method is unlimited As long as analytes elute from the column and are ionized in the source they can be detected The moment of setting the scope of the method shifts from before to after the instrumental analysis

The conclusion from the trend described above is that both sample preparation and instrumental analysis are becoming more and more generic and to a certain extent independent of the analyte of current or future interest This also means that the main effort in terms of development optimization and validation is clearly moving from sample preparation and instrumental analysis towards data processing to ensure reliable detection of the compounds of interest

This paper will provide a brief overview of the full scan MS options currently available for chromatography-based wide-scope screening of food toxicants Aspects related to automated detection and identification will be discussed based on literature and experiences within the authorsrsquo laboratory with emphasis on data handling An in-house developed software package (MetAlign) which features instrument independent and uniform data preprocessing and automated identification will be presented

General Considerations on Automated DetectionIdentification After Full Scan MS MeasurementThe raw data files obtained after GC or LC with full scan MS detection are typically 20ndash500 Mb and contain information on retention time (1 or 2 dimensional) mz = 50ndash1000 (nominal or accurate mass) and abundance (from noise to saturation) Getting meaningful results out of this huge amount of

3

information in an efficient manner is not a trivial task In principle two approaches can be pursued non-targeted and targeted data evaluation With non-targeted data analysis the raw data file is processed to obtain a list of all individual peaks present in the entire chromatographic run The number of peaks can be in the 10 000s which rules out a manual identification Without any a priori information one could restrict the evaluation to the major peaks but these are usually originating from non-toxic endogenous compounds rather than contaminants which are mostly present at low levels Another option is to filter out contaminants by comparing overall LCndashMS or GCndashMS profiles of samples with profiles obtained after analysis of the corresponding non-contaminated product For this extensive databases for the different food commodities would be required which still need to be generated Consequently a more feasible option for the time being is to perform a targeted data evaluation based on libraries containing information on the target compounds All individual peaks assigned after data (pre)processing can then be matched against the information in the library Alternatively the software could use the target library as a starting point and restrict the search to compound-specific retention time windows and ion traces from the raw data file Either way some sort of match between experimental data and library data is obtained Depending on the MS device used this match can be based on a combination of retention time(s) ions ratios mass spectra isotope patterns andor mass accuracy Criteria will have to be set for each of the match parameters in such a way that the number of so-called lsquofalse negativesrsquo and lsquofalse positivesrsquo are within acceptable limits False negatives are compounds known to be present in the sample but missed by the automated screening method false positives are compounds known to be absent but appearing on the list of (provisionally) detected compounds

GC-Full Scan MSVarious options for full scan MS detection are available for GC Single quadrupole and ion trap instruments have been commonly applied for food analysis since the 1990s especially for the determination of pesticide residues in vegetables and fruits Sensitivity limitations encountered in the past when using full scan acquisition have been overcome by large volume injection using PTV injectors9 and improvements in MS devices A big advantage of GCndashMS is that the MS spectra obtained after electron ionization are highly characteristic and to a large extent are instrument independent This means that spectra generated elsewhere can be used and that libraries can be purchased Despite the screening potential the instruments were and still are mainly used for quantitative analysis rather than for screening One reason for this is that the spectra of the analytes in the sample often contain interfering ions from other compounds which complicates automated matching against library spectra To a certain extent the quality of sample extraction can be improved by software alogorithms such as deconvolution that resolve spectra from overlapping peaks and background Deconvolution software tools are available both commercially and as free downloads (for example AMDIS from NIST10) A second reason for the limited

Screening and Quantitating Pesticides in Water with LC-MS

SPONSOrED

httplearnpharmasciencecomtablet-appsfood-issue1article4pesticidespdf

6

ConclusionsThe objective of the current study is to develop a simple isocratic reproducible specific and highly sensitive method for quantitative and qualitative determination of phenylurea herbicides In the present method the analysis time is 13 min (linuron tr 124 min) which is rapid in comparison to some of the other reported methods like Patsias and colleagues (37) (linuron tr 1888 min) Gerecke and colleagues (38) (linuron tr 1758 min) and Mughari and colleagues (39) (linuron tr 15 min) The proposed method can determine phenylurea herbicides at very low concentrations The present paper describes the application of HPLC to the separation and quantitative determination of five phenylurea herbicides and the feasibility of the method developed was tested by simultaneous determination of these herbicides in different brands of soft drinks and in tap water samples Good linearity and repeatability were observed for all the compounds studied (with correlation coefficient gt099) It is hoped that the results of the present study contribute to increased scientific knowledge in the field of pesticide residue analysis in various food and environmental samples

Manpreet Kaur Ashok Kumar Malik and Baldev Singh are with the Department of Chemistry Punjabi University Punjab India

How to Cite this ArticleM Kaur AK Malik and B Singh ldquoDetermination of Phenylurea Herbicides in Tap Water and Soft Drink Samples by HPLCndash

UV and Solid-Phase Extractionrdquo LCGC North America 29(4) 338ndash347 (2011)

References(1) SR Sorensen CN Albers and J Aamand Appl Environ Microbiol 74 2332ndash2340 (2008)(2) GMF Pinto and ICSF Jardim J Liq Chrom and Rel Technol 23 1353ndash1363 (2000) (3) H Cederlund E Boumlrjesson K Oumlnneby and J Stenstroumlm Soil Biology and Biochemistry 39 473ndash484 (2007)(4) E Van-der-Heeft E Dijkman RA Baumann and EA Hogendorn J Chromatogr A 879 39ndash50 (2000)(5) S Canonica and HU Laubscher Photochem Photobiol Sci 7 547ndash551 (2008)(6) AA Khodja B Laverdine C Richard and T Sehili Int J Photoenergy 4 147ndash151 (2002)(7) LE Sojo DS Gamble and DW Gutzman J Agric Food Chem 45 3634ndash3641 (1997)(8) J F Lawerence C Menard MC Hennion V Pichon F LeGoffic and N Durand J Chromatogr A 732 147ndash154 (1996)(9) Organonitrogen pesticides Method 5601 NIOSH manual of analytical methods 1ndash21 (1998) (10) H Berrada G Font and JC Molto JChromatogr A 1042 9ndash14 (2004) (11) R Jeannot H Sabik and E Genin J Chromatogr A 879 55ndash71 (2000)(12) S Herrera A Martin Esteban P Fernandez D Stevenson and C Camara Fresinius J Anal Chem 362 547ndash551 (1998)(13) Fast multi-residue pesticide analysis in soil and vegetable samples application note mass spectrometry wwwappliedbio-

systemscom

High-Pressure IC forBeverage Analysis webcast

SPoNSorED

7

(14) A Martin-Esteban P Fernandez D Stevenson and C Camara Analyst 122 1113ndash1117 (1997)(15) I Ferrer and D Barcelo Analusis Magazine 26 118ndash122 (1998)(16) T Yarita K Sugino T Ihara and A Nomura Analytical communications 35 91ndash92 (1998)(17) MS Barroso LN Konda and G Morovjan J High Resol Chromatogr 22 171ndash176 (1999)(18) S Batista E Silva S Galhardo P Viana and MJ Cerejeira Int J Env Anal Chem 82 601ndash609 (2002)(19) M Chicharro E Bermejo A Sanchez A Zapardiel A Fernandez-Gutierrez and D Arraez Anal Bioanal Chem 382

519ndash526 (2005)(20) A Bautista JJ Aaron MC Mahedero and A Munoz de La Pena Analusis 27 857ndash863 (1999)(21) MD Gil-Garciacutea M Martinez-Galera P Parrilla-Vaacutezquez AR Mughari and IM Ortiz-Rodriacuteguez Journal of Fluores-

cence 18 365ndash373 (2008)(22) I Baranowiska and C Pieszko Anal Letters 35 413ndash486 (2002)(23) J Sherma Acta Chromatographia 15 5ndash30 (2005)(24) MMC de la Pentildea and A Bautista-Saacutenchez Talanta 13 279ndash285 (2003)(25) I Ferrer V Pichon MC Hennion and D Barceloacute Journal of Chromatography A 1 91ndash98 (1997)(26) F Li D Martens and A Kettrup Se Pu 19 534ndash537 (2001)(27) T Cserhati E Forgaacutecs Z Deyl I Miksik and A Eckhardt Biomedical Chromatography 18 350ndash359 (2004)(28) MJI Mattina Journal of Chromatography A 549 237ndash245 (1991)(29) M Hamada and R Wintersteiger Journal of Planar Chromatography-Modern TLC 15 11ndash18 (2002)(30) JF Garciacutea-Reyes B Gilbert-Loacutepez and A Molina-Diacuteaz Anal Chem 30 8966ndash8974 (2002)(31) MA Mumin KF Akhter and MZ Abedin Malaysian Journal of Chemistry 8 45ndash51 (2008)(32) X L Cao J Corriveau and S Popovic J Agric Food Chem 57 1307ndash1311 (2009) (33) Z Pan L Wang W Mo C Wang W Hu and J Zhang Anal Chim Acta 545 218ndash223 (2005)(34) R Lucena S Cardenas M Gallego and M Valcarcel Anal Chim Acta 530 283ndash289 (2005)(35) E Papadopoulou-Mourkidou J Patsias E Papadakis and A Koukourikou Fresenius J Anal Chem 371 491ndash496

(2001)(36) N Yoshioka and K Ichihashi Talanta 74 1408ndash1413 (2008)(37) J Patsias and E Papadopoulou-Mourkidou JAOAC International 82 968ndash981 (1999)(38) A C Gerecke C Tixier T Bartels RP Schwarzenbach and SR Muumlller J chromatography A 930 9ndash19 (2001)(39) AR Mughari P Parrilla Vaacutezquez and M M Galera Anal Chimica Acta 593 157ndash163 (2007)

1

Data Handling amp Validation in Automated Detection of Food Toxicants

By Hans Mol Arjen Lommen Paul Zomer Henk van der Kamp Martijn van der Lee and Arjen Gerssen

Da

ta H

an

Dli

ng

During production processing storage and transport of food and feed a variety of potentially hazardous compounds may enter the food chain These include residues left after treatment of crops and animals with pesticides and veterinary drugs natural

toxins produced by fungi (mycotoxins) and plants environmental contaminants (persistent pollutants) and processing contaminants The potential presence of these compounds is an important issue in the field of food and feed safety Consequently extensive legislation has been established to protect consumers from unnecessary or excessive exposure to these substances Analytical chemists are facing a huge challenge when it comes to efficient verification of compliance of a wide variety of products with this legislation and preferably at the same time to provide occurrence data for lsquonewrsquo contaminants which are not yet regulated In short hundreds of different products need to be analysed for thousands of known contaminants and more

Within each class of contaminants the current lsquogold standardrsquo to deal with this challenge is the use of multi-analyte methods based on LC or GC with tandem MS detection Such methods typically cover tens to several hundreds of analytes and are well established in the field of pesticides1ndash3 with other fields following the same concept (eg mycotoxins45 and

Generic methods based on chromatography with full scan MS detection are maturing Progress has been made in the development of software for automated detection or identification of the analytes but this still is the bottleneck inhibiting implementation for routine analysis Validation of qualitative wide-scope screening is another hurdle to be taken before application An overview of current chromatography-based food toxicant screening is presented

Using Full Scan gCndashMS and lCndashMS

KEY POINTSFull scan acquisition is more straightforward than SIM and tandem MS and enables the detection of many more analytes without the need for knowing a priori

Although the time spent on sample preparation and set up of instrumental acquisition methods is declining the opposite is true for optimization of automated detection and finding the fit-for-purpose balance between false positives and false negatives

Systematic validation studies of fully automated chromatography-based screening methods are still lacking

The next challenge after developing generic screening methods is the development of generic software tools for data evaluation and data mining

2

veterinary drugs67) The instrumental methods involve targeted acquisition where detection of each compound is individually optimized during instrumental method development The methods are typically extensively validated with respect to quantitative performance and data handling usually involves a manual review of extracted ion chromatograms to verify peak assignment and integration

A logical next step is to combine multi-methods beyond their contaminant class The feasibility of this approach has recently been demonstrated8 by simultaneous determination of pesticides veterinary drugs mycotoxins and plant toxins in a variety of food and feed commodities Sample preparation for such integrated methods is very generic and straightforward (as simple as a single extractiondilution step) Because the anticipated number of analytes to be covered in this approach is beyond what can easily be accommodated by tandem MS full scan MS is the detection method of choice Here the measurement is non-targeted which makes the instrumental analysis much more straightforward (ie no application-specific instrument adjustments or optimization needed no acquisition-time windows) In principle the scope of the method is unlimited As long as analytes elute from the column and are ionized in the source they can be detected The moment of setting the scope of the method shifts from before to after the instrumental analysis

The conclusion from the trend described above is that both sample preparation and instrumental analysis are becoming more and more generic and to a certain extent independent of the analyte of current or future interest This also means that the main effort in terms of development optimization and validation is clearly moving from sample preparation and instrumental analysis towards data processing to ensure reliable detection of the compounds of interest

This paper will provide a brief overview of the full scan MS options currently available for chromatography-based wide-scope screening of food toxicants Aspects related to automated detection and identification will be discussed based on literature and experiences within the authorsrsquo laboratory with emphasis on data handling An in-house developed software package (MetAlign) which features instrument independent and uniform data preprocessing and automated identification will be presented

General Considerations on Automated DetectionIdentification After Full Scan MS MeasurementThe raw data files obtained after GC or LC with full scan MS detection are typically 20ndash500 Mb and contain information on retention time (1 or 2 dimensional) mz = 50ndash1000 (nominal or accurate mass) and abundance (from noise to saturation) Getting meaningful results out of this huge amount of

3

information in an efficient manner is not a trivial task In principle two approaches can be pursued non-targeted and targeted data evaluation With non-targeted data analysis the raw data file is processed to obtain a list of all individual peaks present in the entire chromatographic run The number of peaks can be in the 10 000s which rules out a manual identification Without any a priori information one could restrict the evaluation to the major peaks but these are usually originating from non-toxic endogenous compounds rather than contaminants which are mostly present at low levels Another option is to filter out contaminants by comparing overall LCndashMS or GCndashMS profiles of samples with profiles obtained after analysis of the corresponding non-contaminated product For this extensive databases for the different food commodities would be required which still need to be generated Consequently a more feasible option for the time being is to perform a targeted data evaluation based on libraries containing information on the target compounds All individual peaks assigned after data (pre)processing can then be matched against the information in the library Alternatively the software could use the target library as a starting point and restrict the search to compound-specific retention time windows and ion traces from the raw data file Either way some sort of match between experimental data and library data is obtained Depending on the MS device used this match can be based on a combination of retention time(s) ions ratios mass spectra isotope patterns andor mass accuracy Criteria will have to be set for each of the match parameters in such a way that the number of so-called lsquofalse negativesrsquo and lsquofalse positivesrsquo are within acceptable limits False negatives are compounds known to be present in the sample but missed by the automated screening method false positives are compounds known to be absent but appearing on the list of (provisionally) detected compounds

GC-Full Scan MSVarious options for full scan MS detection are available for GC Single quadrupole and ion trap instruments have been commonly applied for food analysis since the 1990s especially for the determination of pesticide residues in vegetables and fruits Sensitivity limitations encountered in the past when using full scan acquisition have been overcome by large volume injection using PTV injectors9 and improvements in MS devices A big advantage of GCndashMS is that the MS spectra obtained after electron ionization are highly characteristic and to a large extent are instrument independent This means that spectra generated elsewhere can be used and that libraries can be purchased Despite the screening potential the instruments were and still are mainly used for quantitative analysis rather than for screening One reason for this is that the spectra of the analytes in the sample often contain interfering ions from other compounds which complicates automated matching against library spectra To a certain extent the quality of sample extraction can be improved by software alogorithms such as deconvolution that resolve spectra from overlapping peaks and background Deconvolution software tools are available both commercially and as free downloads (for example AMDIS from NIST10) A second reason for the limited

Screening and Quantitating Pesticides in Water with LC-MS

SPONSOrED

httplearnpharmasciencecomtablet-appsfood-issue1article4pesticidespdf

7

(14) A Martin-Esteban P Fernandez D Stevenson and C Camara Analyst 122 1113ndash1117 (1997)(15) I Ferrer and D Barcelo Analusis Magazine 26 118ndash122 (1998)(16) T Yarita K Sugino T Ihara and A Nomura Analytical communications 35 91ndash92 (1998)(17) MS Barroso LN Konda and G Morovjan J High Resol Chromatogr 22 171ndash176 (1999)(18) S Batista E Silva S Galhardo P Viana and MJ Cerejeira Int J Env Anal Chem 82 601ndash609 (2002)(19) M Chicharro E Bermejo A Sanchez A Zapardiel A Fernandez-Gutierrez and D Arraez Anal Bioanal Chem 382

519ndash526 (2005)(20) A Bautista JJ Aaron MC Mahedero and A Munoz de La Pena Analusis 27 857ndash863 (1999)(21) MD Gil-Garciacutea M Martinez-Galera P Parrilla-Vaacutezquez AR Mughari and IM Ortiz-Rodriacuteguez Journal of Fluores-

cence 18 365ndash373 (2008)(22) I Baranowiska and C Pieszko Anal Letters 35 413ndash486 (2002)(23) J Sherma Acta Chromatographia 15 5ndash30 (2005)(24) MMC de la Pentildea and A Bautista-Saacutenchez Talanta 13 279ndash285 (2003)(25) I Ferrer V Pichon MC Hennion and D Barceloacute Journal of Chromatography A 1 91ndash98 (1997)(26) F Li D Martens and A Kettrup Se Pu 19 534ndash537 (2001)(27) T Cserhati E Forgaacutecs Z Deyl I Miksik and A Eckhardt Biomedical Chromatography 18 350ndash359 (2004)(28) MJI Mattina Journal of Chromatography A 549 237ndash245 (1991)(29) M Hamada and R Wintersteiger Journal of Planar Chromatography-Modern TLC 15 11ndash18 (2002)(30) JF Garciacutea-Reyes B Gilbert-Loacutepez and A Molina-Diacuteaz Anal Chem 30 8966ndash8974 (2002)(31) MA Mumin KF Akhter and MZ Abedin Malaysian Journal of Chemistry 8 45ndash51 (2008)(32) X L Cao J Corriveau and S Popovic J Agric Food Chem 57 1307ndash1311 (2009) (33) Z Pan L Wang W Mo C Wang W Hu and J Zhang Anal Chim Acta 545 218ndash223 (2005)(34) R Lucena S Cardenas M Gallego and M Valcarcel Anal Chim Acta 530 283ndash289 (2005)(35) E Papadopoulou-Mourkidou J Patsias E Papadakis and A Koukourikou Fresenius J Anal Chem 371 491ndash496

(2001)(36) N Yoshioka and K Ichihashi Talanta 74 1408ndash1413 (2008)(37) J Patsias and E Papadopoulou-Mourkidou JAOAC International 82 968ndash981 (1999)(38) A C Gerecke C Tixier T Bartels RP Schwarzenbach and SR Muumlller J chromatography A 930 9ndash19 (2001)(39) AR Mughari P Parrilla Vaacutezquez and M M Galera Anal Chimica Acta 593 157ndash163 (2007)

1

Data Handling amp Validation in Automated Detection of Food Toxicants

By Hans Mol Arjen Lommen Paul Zomer Henk van der Kamp Martijn van der Lee and Arjen Gerssen

Da

ta H

an

Dli

ng

During production processing storage and transport of food and feed a variety of potentially hazardous compounds may enter the food chain These include residues left after treatment of crops and animals with pesticides and veterinary drugs natural

toxins produced by fungi (mycotoxins) and plants environmental contaminants (persistent pollutants) and processing contaminants The potential presence of these compounds is an important issue in the field of food and feed safety Consequently extensive legislation has been established to protect consumers from unnecessary or excessive exposure to these substances Analytical chemists are facing a huge challenge when it comes to efficient verification of compliance of a wide variety of products with this legislation and preferably at the same time to provide occurrence data for lsquonewrsquo contaminants which are not yet regulated In short hundreds of different products need to be analysed for thousands of known contaminants and more

Within each class of contaminants the current lsquogold standardrsquo to deal with this challenge is the use of multi-analyte methods based on LC or GC with tandem MS detection Such methods typically cover tens to several hundreds of analytes and are well established in the field of pesticides1ndash3 with other fields following the same concept (eg mycotoxins45 and

Generic methods based on chromatography with full scan MS detection are maturing Progress has been made in the development of software for automated detection or identification of the analytes but this still is the bottleneck inhibiting implementation for routine analysis Validation of qualitative wide-scope screening is another hurdle to be taken before application An overview of current chromatography-based food toxicant screening is presented

Using Full Scan gCndashMS and lCndashMS

KEY POINTSFull scan acquisition is more straightforward than SIM and tandem MS and enables the detection of many more analytes without the need for knowing a priori

Although the time spent on sample preparation and set up of instrumental acquisition methods is declining the opposite is true for optimization of automated detection and finding the fit-for-purpose balance between false positives and false negatives

Systematic validation studies of fully automated chromatography-based screening methods are still lacking

The next challenge after developing generic screening methods is the development of generic software tools for data evaluation and data mining

2

veterinary drugs67) The instrumental methods involve targeted acquisition where detection of each compound is individually optimized during instrumental method development The methods are typically extensively validated with respect to quantitative performance and data handling usually involves a manual review of extracted ion chromatograms to verify peak assignment and integration

A logical next step is to combine multi-methods beyond their contaminant class The feasibility of this approach has recently been demonstrated8 by simultaneous determination of pesticides veterinary drugs mycotoxins and plant toxins in a variety of food and feed commodities Sample preparation for such integrated methods is very generic and straightforward (as simple as a single extractiondilution step) Because the anticipated number of analytes to be covered in this approach is beyond what can easily be accommodated by tandem MS full scan MS is the detection method of choice Here the measurement is non-targeted which makes the instrumental analysis much more straightforward (ie no application-specific instrument adjustments or optimization needed no acquisition-time windows) In principle the scope of the method is unlimited As long as analytes elute from the column and are ionized in the source they can be detected The moment of setting the scope of the method shifts from before to after the instrumental analysis

The conclusion from the trend described above is that both sample preparation and instrumental analysis are becoming more and more generic and to a certain extent independent of the analyte of current or future interest This also means that the main effort in terms of development optimization and validation is clearly moving from sample preparation and instrumental analysis towards data processing to ensure reliable detection of the compounds of interest

This paper will provide a brief overview of the full scan MS options currently available for chromatography-based wide-scope screening of food toxicants Aspects related to automated detection and identification will be discussed based on literature and experiences within the authorsrsquo laboratory with emphasis on data handling An in-house developed software package (MetAlign) which features instrument independent and uniform data preprocessing and automated identification will be presented

General Considerations on Automated DetectionIdentification After Full Scan MS MeasurementThe raw data files obtained after GC or LC with full scan MS detection are typically 20ndash500 Mb and contain information on retention time (1 or 2 dimensional) mz = 50ndash1000 (nominal or accurate mass) and abundance (from noise to saturation) Getting meaningful results out of this huge amount of

3

information in an efficient manner is not a trivial task In principle two approaches can be pursued non-targeted and targeted data evaluation With non-targeted data analysis the raw data file is processed to obtain a list of all individual peaks present in the entire chromatographic run The number of peaks can be in the 10 000s which rules out a manual identification Without any a priori information one could restrict the evaluation to the major peaks but these are usually originating from non-toxic endogenous compounds rather than contaminants which are mostly present at low levels Another option is to filter out contaminants by comparing overall LCndashMS or GCndashMS profiles of samples with profiles obtained after analysis of the corresponding non-contaminated product For this extensive databases for the different food commodities would be required which still need to be generated Consequently a more feasible option for the time being is to perform a targeted data evaluation based on libraries containing information on the target compounds All individual peaks assigned after data (pre)processing can then be matched against the information in the library Alternatively the software could use the target library as a starting point and restrict the search to compound-specific retention time windows and ion traces from the raw data file Either way some sort of match between experimental data and library data is obtained Depending on the MS device used this match can be based on a combination of retention time(s) ions ratios mass spectra isotope patterns andor mass accuracy Criteria will have to be set for each of the match parameters in such a way that the number of so-called lsquofalse negativesrsquo and lsquofalse positivesrsquo are within acceptable limits False negatives are compounds known to be present in the sample but missed by the automated screening method false positives are compounds known to be absent but appearing on the list of (provisionally) detected compounds

GC-Full Scan MSVarious options for full scan MS detection are available for GC Single quadrupole and ion trap instruments have been commonly applied for food analysis since the 1990s especially for the determination of pesticide residues in vegetables and fruits Sensitivity limitations encountered in the past when using full scan acquisition have been overcome by large volume injection using PTV injectors9 and improvements in MS devices A big advantage of GCndashMS is that the MS spectra obtained after electron ionization are highly characteristic and to a large extent are instrument independent This means that spectra generated elsewhere can be used and that libraries can be purchased Despite the screening potential the instruments were and still are mainly used for quantitative analysis rather than for screening One reason for this is that the spectra of the analytes in the sample often contain interfering ions from other compounds which complicates automated matching against library spectra To a certain extent the quality of sample extraction can be improved by software alogorithms such as deconvolution that resolve spectra from overlapping peaks and background Deconvolution software tools are available both commercially and as free downloads (for example AMDIS from NIST10) A second reason for the limited

Screening and Quantitating Pesticides in Water with LC-MS

SPONSOrED

httplearnpharmasciencecomtablet-appsfood-issue1article4pesticidespdf

1

Data Handling amp Validation in Automated Detection of Food Toxicants

By Hans Mol Arjen Lommen Paul Zomer Henk van der Kamp Martijn van der Lee and Arjen Gerssen

Da

ta H

an

Dli

ng

During production processing storage and transport of food and feed a variety of potentially hazardous compounds may enter the food chain These include residues left after treatment of crops and animals with pesticides and veterinary drugs natural

toxins produced by fungi (mycotoxins) and plants environmental contaminants (persistent pollutants) and processing contaminants The potential presence of these compounds is an important issue in the field of food and feed safety Consequently extensive legislation has been established to protect consumers from unnecessary or excessive exposure to these substances Analytical chemists are facing a huge challenge when it comes to efficient verification of compliance of a wide variety of products with this legislation and preferably at the same time to provide occurrence data for lsquonewrsquo contaminants which are not yet regulated In short hundreds of different products need to be analysed for thousands of known contaminants and more

Within each class of contaminants the current lsquogold standardrsquo to deal with this challenge is the use of multi-analyte methods based on LC or GC with tandem MS detection Such methods typically cover tens to several hundreds of analytes and are well established in the field of pesticides1ndash3 with other fields following the same concept (eg mycotoxins45 and

Generic methods based on chromatography with full scan MS detection are maturing Progress has been made in the development of software for automated detection or identification of the analytes but this still is the bottleneck inhibiting implementation for routine analysis Validation of qualitative wide-scope screening is another hurdle to be taken before application An overview of current chromatography-based food toxicant screening is presented

Using Full Scan gCndashMS and lCndashMS

KEY POINTSFull scan acquisition is more straightforward than SIM and tandem MS and enables the detection of many more analytes without the need for knowing a priori

Although the time spent on sample preparation and set up of instrumental acquisition methods is declining the opposite is true for optimization of automated detection and finding the fit-for-purpose balance between false positives and false negatives

Systematic validation studies of fully automated chromatography-based screening methods are still lacking

The next challenge after developing generic screening methods is the development of generic software tools for data evaluation and data mining

2

veterinary drugs67) The instrumental methods involve targeted acquisition where detection of each compound is individually optimized during instrumental method development The methods are typically extensively validated with respect to quantitative performance and data handling usually involves a manual review of extracted ion chromatograms to verify peak assignment and integration

A logical next step is to combine multi-methods beyond their contaminant class The feasibility of this approach has recently been demonstrated8 by simultaneous determination of pesticides veterinary drugs mycotoxins and plant toxins in a variety of food and feed commodities Sample preparation for such integrated methods is very generic and straightforward (as simple as a single extractiondilution step) Because the anticipated number of analytes to be covered in this approach is beyond what can easily be accommodated by tandem MS full scan MS is the detection method of choice Here the measurement is non-targeted which makes the instrumental analysis much more straightforward (ie no application-specific instrument adjustments or optimization needed no acquisition-time windows) In principle the scope of the method is unlimited As long as analytes elute from the column and are ionized in the source they can be detected The moment of setting the scope of the method shifts from before to after the instrumental analysis

The conclusion from the trend described above is that both sample preparation and instrumental analysis are becoming more and more generic and to a certain extent independent of the analyte of current or future interest This also means that the main effort in terms of development optimization and validation is clearly moving from sample preparation and instrumental analysis towards data processing to ensure reliable detection of the compounds of interest

This paper will provide a brief overview of the full scan MS options currently available for chromatography-based wide-scope screening of food toxicants Aspects related to automated detection and identification will be discussed based on literature and experiences within the authorsrsquo laboratory with emphasis on data handling An in-house developed software package (MetAlign) which features instrument independent and uniform data preprocessing and automated identification will be presented

General Considerations on Automated DetectionIdentification After Full Scan MS MeasurementThe raw data files obtained after GC or LC with full scan MS detection are typically 20ndash500 Mb and contain information on retention time (1 or 2 dimensional) mz = 50ndash1000 (nominal or accurate mass) and abundance (from noise to saturation) Getting meaningful results out of this huge amount of

3

information in an efficient manner is not a trivial task In principle two approaches can be pursued non-targeted and targeted data evaluation With non-targeted data analysis the raw data file is processed to obtain a list of all individual peaks present in the entire chromatographic run The number of peaks can be in the 10 000s which rules out a manual identification Without any a priori information one could restrict the evaluation to the major peaks but these are usually originating from non-toxic endogenous compounds rather than contaminants which are mostly present at low levels Another option is to filter out contaminants by comparing overall LCndashMS or GCndashMS profiles of samples with profiles obtained after analysis of the corresponding non-contaminated product For this extensive databases for the different food commodities would be required which still need to be generated Consequently a more feasible option for the time being is to perform a targeted data evaluation based on libraries containing information on the target compounds All individual peaks assigned after data (pre)processing can then be matched against the information in the library Alternatively the software could use the target library as a starting point and restrict the search to compound-specific retention time windows and ion traces from the raw data file Either way some sort of match between experimental data and library data is obtained Depending on the MS device used this match can be based on a combination of retention time(s) ions ratios mass spectra isotope patterns andor mass accuracy Criteria will have to be set for each of the match parameters in such a way that the number of so-called lsquofalse negativesrsquo and lsquofalse positivesrsquo are within acceptable limits False negatives are compounds known to be present in the sample but missed by the automated screening method false positives are compounds known to be absent but appearing on the list of (provisionally) detected compounds

GC-Full Scan MSVarious options for full scan MS detection are available for GC Single quadrupole and ion trap instruments have been commonly applied for food analysis since the 1990s especially for the determination of pesticide residues in vegetables and fruits Sensitivity limitations encountered in the past when using full scan acquisition have been overcome by large volume injection using PTV injectors9 and improvements in MS devices A big advantage of GCndashMS is that the MS spectra obtained after electron ionization are highly characteristic and to a large extent are instrument independent This means that spectra generated elsewhere can be used and that libraries can be purchased Despite the screening potential the instruments were and still are mainly used for quantitative analysis rather than for screening One reason for this is that the spectra of the analytes in the sample often contain interfering ions from other compounds which complicates automated matching against library spectra To a certain extent the quality of sample extraction can be improved by software alogorithms such as deconvolution that resolve spectra from overlapping peaks and background Deconvolution software tools are available both commercially and as free downloads (for example AMDIS from NIST10) A second reason for the limited

Screening and Quantitating Pesticides in Water with LC-MS

SPONSOrED

httplearnpharmasciencecomtablet-appsfood-issue1article4pesticidespdf

KEY POINTSFull scan acquisition is more straightforward than SIM and tandem MS and enables the detection of many more analytes without the need for knowing a priori

Although the time spent on sample preparation and set up of instrumental acquisition methods is declining the opposite is true for optimization of automated detection and finding the fit-for-purpose balance between false positives and false negatives

Systematic validation studies of fully automated chromatography-based screening methods are still lacking

The next challenge after developing generic screening methods is the development of generic software tools for data evaluation and data mining

2

veterinary drugs67) The instrumental methods involve targeted acquisition where detection of each compound is individually optimized during instrumental method development The methods are typically extensively validated with respect to quantitative performance and data handling usually involves a manual review of extracted ion chromatograms to verify peak assignment and integration

A logical next step is to combine multi-methods beyond their contaminant class The feasibility of this approach has recently been demonstrated8 by simultaneous determination of pesticides veterinary drugs mycotoxins and plant toxins in a variety of food and feed commodities Sample preparation for such integrated methods is very generic and straightforward (as simple as a single extractiondilution step) Because the anticipated number of analytes to be covered in this approach is beyond what can easily be accommodated by tandem MS full scan MS is the detection method of choice Here the measurement is non-targeted which makes the instrumental analysis much more straightforward (ie no application-specific instrument adjustments or optimization needed no acquisition-time windows) In principle the scope of the method is unlimited As long as analytes elute from the column and are ionized in the source they can be detected The moment of setting the scope of the method shifts from before to after the instrumental analysis

The conclusion from the trend described above is that both sample preparation and instrumental analysis are becoming more and more generic and to a certain extent independent of the analyte of current or future interest This also means that the main effort in terms of development optimization and validation is clearly moving from sample preparation and instrumental analysis towards data processing to ensure reliable detection of the compounds of interest

This paper will provide a brief overview of the full scan MS options currently available for chromatography-based wide-scope screening of food toxicants Aspects related to automated detection and identification will be discussed based on literature and experiences within the authorsrsquo laboratory with emphasis on data handling An in-house developed software package (MetAlign) which features instrument independent and uniform data preprocessing and automated identification will be presented

General Considerations on Automated DetectionIdentification After Full Scan MS MeasurementThe raw data files obtained after GC or LC with full scan MS detection are typically 20ndash500 Mb and contain information on retention time (1 or 2 dimensional) mz = 50ndash1000 (nominal or accurate mass) and abundance (from noise to saturation) Getting meaningful results out of this huge amount of

3

information in an efficient manner is not a trivial task In principle two approaches can be pursued non-targeted and targeted data evaluation With non-targeted data analysis the raw data file is processed to obtain a list of all individual peaks present in the entire chromatographic run The number of peaks can be in the 10 000s which rules out a manual identification Without any a priori information one could restrict the evaluation to the major peaks but these are usually originating from non-toxic endogenous compounds rather than contaminants which are mostly present at low levels Another option is to filter out contaminants by comparing overall LCndashMS or GCndashMS profiles of samples with profiles obtained after analysis of the corresponding non-contaminated product For this extensive databases for the different food commodities would be required which still need to be generated Consequently a more feasible option for the time being is to perform a targeted data evaluation based on libraries containing information on the target compounds All individual peaks assigned after data (pre)processing can then be matched against the information in the library Alternatively the software could use the target library as a starting point and restrict the search to compound-specific retention time windows and ion traces from the raw data file Either way some sort of match between experimental data and library data is obtained Depending on the MS device used this match can be based on a combination of retention time(s) ions ratios mass spectra isotope patterns andor mass accuracy Criteria will have to be set for each of the match parameters in such a way that the number of so-called lsquofalse negativesrsquo and lsquofalse positivesrsquo are within acceptable limits False negatives are compounds known to be present in the sample but missed by the automated screening method false positives are compounds known to be absent but appearing on the list of (provisionally) detected compounds

GC-Full Scan MSVarious options for full scan MS detection are available for GC Single quadrupole and ion trap instruments have been commonly applied for food analysis since the 1990s especially for the determination of pesticide residues in vegetables and fruits Sensitivity limitations encountered in the past when using full scan acquisition have been overcome by large volume injection using PTV injectors9 and improvements in MS devices A big advantage of GCndashMS is that the MS spectra obtained after electron ionization are highly characteristic and to a large extent are instrument independent This means that spectra generated elsewhere can be used and that libraries can be purchased Despite the screening potential the instruments were and still are mainly used for quantitative analysis rather than for screening One reason for this is that the spectra of the analytes in the sample often contain interfering ions from other compounds which complicates automated matching against library spectra To a certain extent the quality of sample extraction can be improved by software alogorithms such as deconvolution that resolve spectra from overlapping peaks and background Deconvolution software tools are available both commercially and as free downloads (for example AMDIS from NIST10) A second reason for the limited

Screening and Quantitating Pesticides in Water with LC-MS

SPONSOrED

httplearnpharmasciencecomtablet-appsfood-issue1article4pesticidespdf

3

information in an efficient manner is not a trivial task In principle two approaches can be pursued non-targeted and targeted data evaluation With non-targeted data analysis the raw data file is processed to obtain a list of all individual peaks present in the entire chromatographic run The number of peaks can be in the 10 000s which rules out a manual identification Without any a priori information one could restrict the evaluation to the major peaks but these are usually originating from non-toxic endogenous compounds rather than contaminants which are mostly present at low levels Another option is to filter out contaminants by comparing overall LCndashMS or GCndashMS profiles of samples with profiles obtained after analysis of the corresponding non-contaminated product For this extensive databases for the different food commodities would be required which still need to be generated Consequently a more feasible option for the time being is to perform a targeted data evaluation based on libraries containing information on the target compounds All individual peaks assigned after data (pre)processing can then be matched against the information in the library Alternatively the software could use the target library as a starting point and restrict the search to compound-specific retention time windows and ion traces from the raw data file Either way some sort of match between experimental data and library data is obtained Depending on the MS device used this match can be based on a combination of retention time(s) ions ratios mass spectra isotope patterns andor mass accuracy Criteria will have to be set for each of the match parameters in such a way that the number of so-called lsquofalse negativesrsquo and lsquofalse positivesrsquo are within acceptable limits False negatives are compounds known to be present in the sample but missed by the automated screening method false positives are compounds known to be absent but appearing on the list of (provisionally) detected compounds

GC-Full Scan MSVarious options for full scan MS detection are available for GC Single quadrupole and ion trap instruments have been commonly applied for food analysis since the 1990s especially for the determination of pesticide residues in vegetables and fruits Sensitivity limitations encountered in the past when using full scan acquisition have been overcome by large volume injection using PTV injectors9 and improvements in MS devices A big advantage of GCndashMS is that the MS spectra obtained after electron ionization are highly characteristic and to a large extent are instrument independent This means that spectra generated elsewhere can be used and that libraries can be purchased Despite the screening potential the instruments were and still are mainly used for quantitative analysis rather than for screening One reason for this is that the spectra of the analytes in the sample often contain interfering ions from other compounds which complicates automated matching against library spectra To a certain extent the quality of sample extraction can be improved by software alogorithms such as deconvolution that resolve spectra from overlapping peaks and background Deconvolution software tools are available both commercially and as free downloads (for example AMDIS from NIST10) A second reason for the limited

Screening and Quantitating Pesticides in Water with LC-MS

SPONSOrED

httplearnpharmasciencecomtablet-appsfood-issue1article4pesticidespdf

4

exploitation of the screening potential is the lack of dedicated sofware for automatic detection The standard sofware that comes with the GCndashMS instrument is usually able to perform searches of sample spectra against libraries but is often not really suited and not user-friendly with respect to automated identification and report generation in routine practice This has caused users to develop in-house solutions without1112 or with deconvolution1314 For the user deconvolution tools that are integrated into the instrumentrsquos data analysis software are most convenient Some instrument manufacturers offer this as default15 or as an optional package combined with dedicated libraries that not only include the mass spectra but also retention times for prescribed GC conditions16 For extracts of increasing complexity andor in case of lower analyte levels GC with full scan quadrupole or ion trap MS lacks selectivity even when applying preprocessing algorithms such as deconvolution Currently there are two options to improve selectivity in GC with full scan MS The first is the use of high resolutionaccurate mass MS detectors (GCndashhrTOF-MS) The higher selectivity arises from the ability to separate ions that have the same nominal mass but differ in their exact mass A main disadvantage is that to take full advantage of this exact mass library spectra are needed Because these are not (yet) available they would need to be generated by the user In addition the current mass resolving power (sim6000) and dynamic range are not adequate for all applications The second option to improve selectivity is through enhanced chromatographic resolution The current-state-of-the-art here is comprehensive GC (GCtimesGC) Compounds are typically first separated by volatility on a regular GC column and then by polarity on a second short narrow-bore column A visualization of the resulting separation is shown in Figure 1 For full scan MS detection a high scan speed is required (sim100ndash250 Hz) in order to have sufficient data points across the narrow (100 ms) chromatographic peaks TOF-MS detectors allowing scan speeds up to 500 Hz are available (nominal resolution only) Cleaner spectra are obtained in the first place due to the enhanced GC separation and also here data preprocessing for peak purification can be performed Given the comprehensiveness of this type of analysis its main application lies in profiling and classification of samples in various areas including metabolomics petrochemicals food and environmental17 but several applications for qualitative and quantitative determination of residues and contaminants have been reported18ndash20 Due to the complexity and the amount of data obtained after comprehensive GC analysis data handling is a major challenge Both proprietary software and in-house developed software tools for data handling have been described They have been excellently reviewed by Pierce et al21 At the moment no general lsquoready-to-usersquo solution is available for automated detection Consequently in our laboratory data handling after GCtimesGCndashTOF-MS analysis is performed using a combination of the instrument software for initial processing and deconvolution and an Excel macro for matching retention times data reduction and generation of a list of detected compounds Currently an in-house developed alternative for preprocessingresolving overlapping peaks called MetAlgin is being evaluated

Figure 1 Three-dimensional GCtimesGCndashTOFndashMS image obtained after a 10 microL injection of a standard solution containing gt200 pesticides (for more details see reference 19)

5

LC-Full Scan MSFor full scan measurement of low levels of toxicants in food and feed after LC separation high resolutionaccurate mass MS detectors are required During ionization little or no fragmentation occurs and compounds are detected through the accurate mass of their (de)protonated molecule or adduct TOF-MS has been used in most investigations Especially over the past few years resolution mass accuracy dynamic range scan speed and sensitivity have greatly improved In addition a single stage Orbitrap-MS has been introduced making a resolving power up to 100 000 an affordable option for food toxicant analysis

For selective and efficient automated detection a reliable high mass accuracy is essential The instrument specifications are typically within 5 ppm or even better However in practice this mass accuracy can only be achieved when co-eluting compounds with the same nominal mass can be mass spectrometrically resolved Consequently for real-life samples the resolving power of the MS is an important parameter as well This has been shown recently by Kellmann et al22 The resolving power required depends on the application that is on the complexity of the extract (sample complexity sample preparation) the analyte (sensitivity) and its concentration For generic extracts of honey a resolving power of 25 000 was sufficient for obtaining a mass accuracy of lt2 ppm for pesticides natural toxins and veterinary drugs down to the 001 mgkg level For a much more complex animal feed matrix 100 000 was needed The effect of resolving power on assigned mass accuracy is illustrated in Figure 2

Horse feed 25 ngg

0

10

20

30

40

50

60

70

80

90

100

10000 25000 50000 100000

Resolution

o

f 15

0 an

alyt

es

lt 2 ppm 2-5 ppm 5-10 ppm 10-25 ppm gt 25 ppmND

Figure 2 Effect of resolving power on mass assignment of residues and contaminants (0025 mgkg) in a complex compound feed matrix (for details see reference 22)

Retention Time Window

0

20

40

60

80

100

120

140

05 04 03 02 01 005

Rt Window (plusmn min) 1905 compounds Mass Accuracy plusmn 5 ppm

o

f Su

spec

t Hits

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Mass Accuracy

0

50

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200

25 10 5 25 1 05

Mass Accuracy (plusmn ppm) Rt plusmn 05 min 1905 compounds

o

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70

80

90

100

1905 1500 1200 900 600 300

of Compounds in Database Rt plusmn 05 min Mass Accuracy plusmn 5 ppm

o

f Su

spec

t Hits

Solvent Compound Feed

Figure 3(a) Effect of retention time tolerance on the number of provisionally detected compounds in non-contaminated samples (low response threshold) For sample preparation details see reference 8 for LC-MS analysis see reference 22

6

While the hardware to enable screening is becoming more and more fit-for-purpose development of software and databases for automated detection is still in full progress with major improvements being made in the past two years In its simplest form analytes can automatically be detected in the raw data through matching the accurate mass of peaks found against a list of target compounds with their exact mass and retention time However accurate mass and retention time alone are often not sufficiently unique for selective automatic identification Depending on the tolerances set for matching retention time and accurate mass the response threshold the complexity of the matrix and the number of compounds in the target database the number of potential detections triggering further confirmatory (data) analysis may be too high for screening purposes This is illustrated in Figure 3(a) and Figures 3(b) amp 3(c) To increase specificity isotope patterns can be used Like the exact mass they can be calculated and no prior experimental determination is required However for small molecules the isotope ions (except chlorine and bromine isotopes) have substantially lower abundance thereby increasing the limit of identification Another option to improve specificity in automated detection is through analyte fragments Such fragments can be induced during ionization (so-called in-source collision induced ionization IS-CID) or in a collision cell (eg a quadrupole of a QTOF) with the remark that no precursor ion selection is performed and fragmentation is done using fixed generic fragmentation conditions The formation of fragment ions to some extent but certainly their relative abundance depends on the instrument and conditions applied Therefore in contrast to GCndashMS spectral databases fragmentation patterns cannot easily be extrapolated and used in other laboratories and will need to be generated by the user (or vendor) for each instrument

Retention Time Window

0

20

40

60

80

100

120

140

05 04 03 02 01 005

Rt Window (plusmn min) 1905 compounds Mass Accuracy plusmn 5 ppm

o

f Su

spec

t Hits

Solvent Compound Feed

Mass Accuracy

0

50

100

150

200

25 10 5 25 1 05

Mass Accuracy (plusmn ppm) Rt plusmn 05 min 1905 compounds

o

f Su

spec

t Hits

Solvent Compound Feed

Compounds in Database

0

10

20

30

40

50

60

70

80

90

100

1905 1500 1200 900 600 300

of Compounds in Database Rt plusmn 05 min Mass Accuracy plusmn 5 ppm

o

f Su

spec

t Hits

Solvent Compound Feed

Figures 3(b) and 3(c) Effect of (b) mass accuracy tolerance and (c) number of entries on the number of provisionally detected compounds in non-contaminated samples (low response threshold) For sample preparation details see reference 8 for LC-MS analysis see reference 22

7

Toward Generic Data Processing and Data MiningWhile methods for generic extraction and subsequent full scan instrumental analysis are maturing universal approaches for data (pre)processing detection of toxicants and formats for archiving preprocessed result files hardly exist This means that the data files containing comprehensive information on a wide variety of food and feed samples and the (un)known toxicants they may contain can only be (further) explored by the laboratory that generated the data That laboratory might only be interested in pesticides (and just perform a targeted data analysis limited to that) while others might be interested in natural toxins in the same commodity Furthermore libraries used for automated detection may differ in scope which affects the output The issue as such is not unique for food toxicant analysis but unlike other areas such as metabolomics has hardly been addressed so far In our institute as a spin-off from development of data handling software for application in the field of metabolomics preprocessing tools are being applied and dedicated search tools have been developed for food toxicant screening The preprocessing tool called MetAlign is freely available and described in detail elsewhere23 One of the main features of MetAlign is that it can handle either direct or after automated conversion data from different vendors covering a broad range of GCndashMS and LCndashMS instruments both with nominal and accurate mass Data preprocessing involves baseline correction noise elimination and peak picking The software also deals with detector saturation and brand and instrument specific artifacts The output is a 50ndash500times reduced data file in a uniform format which can be exported to Excel or formats allowing visual review through proprietary instrument software already available in the laboratory (see Figure 4) Data alignment can be performed as well which can be of interest in searching for truly unknowns through comparison of profiles of the same products

The resulting files can be searched against target databases using dedicated modules for GCndashMS GCtimesGCndashMS (application to be published elsewhere) andLCndashMS Due to the strongly reduced size files can be easily stored and searching is fast A comparison of the automated detection performance after GCtimesGCndashTOF-MS between the instruments software and MetAlignGCGCMS_ search showed that in feed samples spiked with 106 analytes more compounds (32 vs 62 at the 00025 mgkg level) were found using the MetAlign software without increase in the number of false positives A generic approach for data preprocessing can facilitate data sharing and data mining thereby making much more efficient use of (existing) information available at different laboratories (Figure 5)

Figure 4 LCndashTOF-MS data file (a) before and (b) after preprocessing using MetAlign (see reference 23)

Figure 5 Data (pre)processing MetAlign as interface between instrument raw data and a uniform database for data mining23

8

Validation of Chromatography-Based (Qualitative) Screening MethodsOnce automated detection and reporting have been optimized the overall method (ie sample preparation + instrumental analysis + automated data processing and reporting) has to be validated before it can be applied in routine practice This essentially means that for a certain matrix (or group of matrices) at the anticipated reporting level the level of confidence of detection of the target analytes needs to be established False negatives need to be minimized for obvious reasons False positives are undesirable because they will trigger further manual data evaluation and confirmatory analyses which takes time and effort

Up to now only explorative evaluation of screening performance has been done using limited numbers of spiked samples or by comparison of the detection rate of the automated screening method with (earlier) results from established quantitative Lee et al tested automated identification using a test set of 106 pesticides and contaminants spiked to a complex compound feed sample at various levels using GCtimesGCndashTOF-MS19 Detection rates were clearly concentration dependent and varied from 100 to 73 to 17 for 010 001 and 0001 mgkg respectively Mezcua et al24 investigated the potential of LCndashTOF-MS based screening for pesticides in vegetables and fruits Automated detection was done using an in-house compiled database and instrument software Most pesticides found by the conventional LCndashMSndashMS method were also automatically found by the LCndashTOF-MS screening method

Very recently two groups did a more extensive verification of automated detection of pesticides using GCndashMS (single quadrupole) analysis combined with Agilentrsquos Deconvolution reporting Software tool Mezcua et al25 spiked 95 pesticides to eight vegetable and fruit samples at levels between 002 and 010 mgkg The evaluation of Norli et al26 involved a test set of 177 pesticides spiked in triplicate to 3 matrices at 002 and 01 mgkg The studies revealed that the detectability is as expected compound matrix and concentration dependent and that even in cases of repeated analysis of the same extract inconsistencies occurred with respect to automated detection In all studies mentioned the data generated were too limited to derive a confidence level for detectability of the target analytes in a certain matrix (group) On the other hand through analysis of real samples the studies did show that compared to the conventional methods more pesticides could be found in less time clearly demonstrating the potential of the approach This has been encouraging enough to apply the methods as an extension to the established quantitative multi-methods because any additional toxicant automatically found can be considered worthwhile

To summarize the above systematic validation studies of the qualitative screening methods are still lacking The limited availability of appropriate software andor target compound libraries up

Detection of Mycotoxins in Corn Meal with LC-MS-MS

SPONSOrED

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article4mycotoxinspdf

5

LC-Full Scan MSFor full scan measurement of low levels of toxicants in food and feed after LC separation high resolutionaccurate mass MS detectors are required During ionization little or no fragmentation occurs and compounds are detected through the accurate mass of their (de)protonated molecule or adduct TOF-MS has been used in most investigations Especially over the past few years resolution mass accuracy dynamic range scan speed and sensitivity have greatly improved In addition a single stage Orbitrap-MS has been introduced making a resolving power up to 100 000 an affordable option for food toxicant analysis

For selective and efficient automated detection a reliable high mass accuracy is essential The instrument specifications are typically within 5 ppm or even better However in practice this mass accuracy can only be achieved when co-eluting compounds with the same nominal mass can be mass spectrometrically resolved Consequently for real-life samples the resolving power of the MS is an important parameter as well This has been shown recently by Kellmann et al22 The resolving power required depends on the application that is on the complexity of the extract (sample complexity sample preparation) the analyte (sensitivity) and its concentration For generic extracts of honey a resolving power of 25 000 was sufficient for obtaining a mass accuracy of lt2 ppm for pesticides natural toxins and veterinary drugs down to the 001 mgkg level For a much more complex animal feed matrix 100 000 was needed The effect of resolving power on assigned mass accuracy is illustrated in Figure 2

Horse feed 25 ngg

0

10

20

30

40

50

60

70

80

90

100

10000 25000 50000 100000

Resolution

o

f 15

0 an

alyt

es

lt 2 ppm 2-5 ppm 5-10 ppm 10-25 ppm gt 25 ppmND

Figure 2 Effect of resolving power on mass assignment of residues and contaminants (0025 mgkg) in a complex compound feed matrix (for details see reference 22)

Retention Time Window

0

20

40

60

80

100

120

140

05 04 03 02 01 005

Rt Window (plusmn min) 1905 compounds Mass Accuracy plusmn 5 ppm

o

f Su

spec

t Hits

Solvent Compound Feed

Mass Accuracy

0

50

100

150

200

25 10 5 25 1 05

Mass Accuracy (plusmn ppm) Rt plusmn 05 min 1905 compounds

o

f Su

spec

t Hits

Solvent Compound Feed

Compounds in Database

0

10

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40

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70

80

90

100

1905 1500 1200 900 600 300

of Compounds in Database Rt plusmn 05 min Mass Accuracy plusmn 5 ppm

o

f Su

spec

t Hits

Solvent Compound Feed

Figure 3(a) Effect of retention time tolerance on the number of provisionally detected compounds in non-contaminated samples (low response threshold) For sample preparation details see reference 8 for LC-MS analysis see reference 22

6

While the hardware to enable screening is becoming more and more fit-for-purpose development of software and databases for automated detection is still in full progress with major improvements being made in the past two years In its simplest form analytes can automatically be detected in the raw data through matching the accurate mass of peaks found against a list of target compounds with their exact mass and retention time However accurate mass and retention time alone are often not sufficiently unique for selective automatic identification Depending on the tolerances set for matching retention time and accurate mass the response threshold the complexity of the matrix and the number of compounds in the target database the number of potential detections triggering further confirmatory (data) analysis may be too high for screening purposes This is illustrated in Figure 3(a) and Figures 3(b) amp 3(c) To increase specificity isotope patterns can be used Like the exact mass they can be calculated and no prior experimental determination is required However for small molecules the isotope ions (except chlorine and bromine isotopes) have substantially lower abundance thereby increasing the limit of identification Another option to improve specificity in automated detection is through analyte fragments Such fragments can be induced during ionization (so-called in-source collision induced ionization IS-CID) or in a collision cell (eg a quadrupole of a QTOF) with the remark that no precursor ion selection is performed and fragmentation is done using fixed generic fragmentation conditions The formation of fragment ions to some extent but certainly their relative abundance depends on the instrument and conditions applied Therefore in contrast to GCndashMS spectral databases fragmentation patterns cannot easily be extrapolated and used in other laboratories and will need to be generated by the user (or vendor) for each instrument

Retention Time Window

0

20

40

60

80

100

120

140

05 04 03 02 01 005

Rt Window (plusmn min) 1905 compounds Mass Accuracy plusmn 5 ppm

o

f Su

spec

t Hits

Solvent Compound Feed

Mass Accuracy

0

50

100

150

200

25 10 5 25 1 05

Mass Accuracy (plusmn ppm) Rt plusmn 05 min 1905 compounds

o

f Su

spec

t Hits

Solvent Compound Feed

Compounds in Database

0

10

20

30

40

50

60

70

80

90

100

1905 1500 1200 900 600 300

of Compounds in Database Rt plusmn 05 min Mass Accuracy plusmn 5 ppm

o

f Su

spec

t Hits

Solvent Compound Feed

Figures 3(b) and 3(c) Effect of (b) mass accuracy tolerance and (c) number of entries on the number of provisionally detected compounds in non-contaminated samples (low response threshold) For sample preparation details see reference 8 for LC-MS analysis see reference 22

7

Toward Generic Data Processing and Data MiningWhile methods for generic extraction and subsequent full scan instrumental analysis are maturing universal approaches for data (pre)processing detection of toxicants and formats for archiving preprocessed result files hardly exist This means that the data files containing comprehensive information on a wide variety of food and feed samples and the (un)known toxicants they may contain can only be (further) explored by the laboratory that generated the data That laboratory might only be interested in pesticides (and just perform a targeted data analysis limited to that) while others might be interested in natural toxins in the same commodity Furthermore libraries used for automated detection may differ in scope which affects the output The issue as such is not unique for food toxicant analysis but unlike other areas such as metabolomics has hardly been addressed so far In our institute as a spin-off from development of data handling software for application in the field of metabolomics preprocessing tools are being applied and dedicated search tools have been developed for food toxicant screening The preprocessing tool called MetAlign is freely available and described in detail elsewhere23 One of the main features of MetAlign is that it can handle either direct or after automated conversion data from different vendors covering a broad range of GCndashMS and LCndashMS instruments both with nominal and accurate mass Data preprocessing involves baseline correction noise elimination and peak picking The software also deals with detector saturation and brand and instrument specific artifacts The output is a 50ndash500times reduced data file in a uniform format which can be exported to Excel or formats allowing visual review through proprietary instrument software already available in the laboratory (see Figure 4) Data alignment can be performed as well which can be of interest in searching for truly unknowns through comparison of profiles of the same products

The resulting files can be searched against target databases using dedicated modules for GCndashMS GCtimesGCndashMS (application to be published elsewhere) andLCndashMS Due to the strongly reduced size files can be easily stored and searching is fast A comparison of the automated detection performance after GCtimesGCndashTOF-MS between the instruments software and MetAlignGCGCMS_ search showed that in feed samples spiked with 106 analytes more compounds (32 vs 62 at the 00025 mgkg level) were found using the MetAlign software without increase in the number of false positives A generic approach for data preprocessing can facilitate data sharing and data mining thereby making much more efficient use of (existing) information available at different laboratories (Figure 5)

Figure 4 LCndashTOF-MS data file (a) before and (b) after preprocessing using MetAlign (see reference 23)

Figure 5 Data (pre)processing MetAlign as interface between instrument raw data and a uniform database for data mining23

8

Validation of Chromatography-Based (Qualitative) Screening MethodsOnce automated detection and reporting have been optimized the overall method (ie sample preparation + instrumental analysis + automated data processing and reporting) has to be validated before it can be applied in routine practice This essentially means that for a certain matrix (or group of matrices) at the anticipated reporting level the level of confidence of detection of the target analytes needs to be established False negatives need to be minimized for obvious reasons False positives are undesirable because they will trigger further manual data evaluation and confirmatory analyses which takes time and effort

Up to now only explorative evaluation of screening performance has been done using limited numbers of spiked samples or by comparison of the detection rate of the automated screening method with (earlier) results from established quantitative Lee et al tested automated identification using a test set of 106 pesticides and contaminants spiked to a complex compound feed sample at various levels using GCtimesGCndashTOF-MS19 Detection rates were clearly concentration dependent and varied from 100 to 73 to 17 for 010 001 and 0001 mgkg respectively Mezcua et al24 investigated the potential of LCndashTOF-MS based screening for pesticides in vegetables and fruits Automated detection was done using an in-house compiled database and instrument software Most pesticides found by the conventional LCndashMSndashMS method were also automatically found by the LCndashTOF-MS screening method

Very recently two groups did a more extensive verification of automated detection of pesticides using GCndashMS (single quadrupole) analysis combined with Agilentrsquos Deconvolution reporting Software tool Mezcua et al25 spiked 95 pesticides to eight vegetable and fruit samples at levels between 002 and 010 mgkg The evaluation of Norli et al26 involved a test set of 177 pesticides spiked in triplicate to 3 matrices at 002 and 01 mgkg The studies revealed that the detectability is as expected compound matrix and concentration dependent and that even in cases of repeated analysis of the same extract inconsistencies occurred with respect to automated detection In all studies mentioned the data generated were too limited to derive a confidence level for detectability of the target analytes in a certain matrix (group) On the other hand through analysis of real samples the studies did show that compared to the conventional methods more pesticides could be found in less time clearly demonstrating the potential of the approach This has been encouraging enough to apply the methods as an extension to the established quantitative multi-methods because any additional toxicant automatically found can be considered worthwhile

To summarize the above systematic validation studies of the qualitative screening methods are still lacking The limited availability of appropriate software andor target compound libraries up

Detection of Mycotoxins in Corn Meal with LC-MS-MS

SPONSOrED

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article4mycotoxinspdf

6

While the hardware to enable screening is becoming more and more fit-for-purpose development of software and databases for automated detection is still in full progress with major improvements being made in the past two years In its simplest form analytes can automatically be detected in the raw data through matching the accurate mass of peaks found against a list of target compounds with their exact mass and retention time However accurate mass and retention time alone are often not sufficiently unique for selective automatic identification Depending on the tolerances set for matching retention time and accurate mass the response threshold the complexity of the matrix and the number of compounds in the target database the number of potential detections triggering further confirmatory (data) analysis may be too high for screening purposes This is illustrated in Figure 3(a) and Figures 3(b) amp 3(c) To increase specificity isotope patterns can be used Like the exact mass they can be calculated and no prior experimental determination is required However for small molecules the isotope ions (except chlorine and bromine isotopes) have substantially lower abundance thereby increasing the limit of identification Another option to improve specificity in automated detection is through analyte fragments Such fragments can be induced during ionization (so-called in-source collision induced ionization IS-CID) or in a collision cell (eg a quadrupole of a QTOF) with the remark that no precursor ion selection is performed and fragmentation is done using fixed generic fragmentation conditions The formation of fragment ions to some extent but certainly their relative abundance depends on the instrument and conditions applied Therefore in contrast to GCndashMS spectral databases fragmentation patterns cannot easily be extrapolated and used in other laboratories and will need to be generated by the user (or vendor) for each instrument

Retention Time Window

0

20

40

60

80

100

120

140

05 04 03 02 01 005

Rt Window (plusmn min) 1905 compounds Mass Accuracy plusmn 5 ppm

o

f Su

spec

t Hits

Solvent Compound Feed

Mass Accuracy

0

50

100

150

200

25 10 5 25 1 05

Mass Accuracy (plusmn ppm) Rt plusmn 05 min 1905 compounds

o

f Su

spec

t Hits

Solvent Compound Feed

Compounds in Database

0

10

20

30

40

50

60

70

80

90

100

1905 1500 1200 900 600 300

of Compounds in Database Rt plusmn 05 min Mass Accuracy plusmn 5 ppm

o

f Su

spec

t Hits

Solvent Compound Feed

Figures 3(b) and 3(c) Effect of (b) mass accuracy tolerance and (c) number of entries on the number of provisionally detected compounds in non-contaminated samples (low response threshold) For sample preparation details see reference 8 for LC-MS analysis see reference 22

7

Toward Generic Data Processing and Data MiningWhile methods for generic extraction and subsequent full scan instrumental analysis are maturing universal approaches for data (pre)processing detection of toxicants and formats for archiving preprocessed result files hardly exist This means that the data files containing comprehensive information on a wide variety of food and feed samples and the (un)known toxicants they may contain can only be (further) explored by the laboratory that generated the data That laboratory might only be interested in pesticides (and just perform a targeted data analysis limited to that) while others might be interested in natural toxins in the same commodity Furthermore libraries used for automated detection may differ in scope which affects the output The issue as such is not unique for food toxicant analysis but unlike other areas such as metabolomics has hardly been addressed so far In our institute as a spin-off from development of data handling software for application in the field of metabolomics preprocessing tools are being applied and dedicated search tools have been developed for food toxicant screening The preprocessing tool called MetAlign is freely available and described in detail elsewhere23 One of the main features of MetAlign is that it can handle either direct or after automated conversion data from different vendors covering a broad range of GCndashMS and LCndashMS instruments both with nominal and accurate mass Data preprocessing involves baseline correction noise elimination and peak picking The software also deals with detector saturation and brand and instrument specific artifacts The output is a 50ndash500times reduced data file in a uniform format which can be exported to Excel or formats allowing visual review through proprietary instrument software already available in the laboratory (see Figure 4) Data alignment can be performed as well which can be of interest in searching for truly unknowns through comparison of profiles of the same products

The resulting files can be searched against target databases using dedicated modules for GCndashMS GCtimesGCndashMS (application to be published elsewhere) andLCndashMS Due to the strongly reduced size files can be easily stored and searching is fast A comparison of the automated detection performance after GCtimesGCndashTOF-MS between the instruments software and MetAlignGCGCMS_ search showed that in feed samples spiked with 106 analytes more compounds (32 vs 62 at the 00025 mgkg level) were found using the MetAlign software without increase in the number of false positives A generic approach for data preprocessing can facilitate data sharing and data mining thereby making much more efficient use of (existing) information available at different laboratories (Figure 5)

Figure 4 LCndashTOF-MS data file (a) before and (b) after preprocessing using MetAlign (see reference 23)

Figure 5 Data (pre)processing MetAlign as interface between instrument raw data and a uniform database for data mining23

8

Validation of Chromatography-Based (Qualitative) Screening MethodsOnce automated detection and reporting have been optimized the overall method (ie sample preparation + instrumental analysis + automated data processing and reporting) has to be validated before it can be applied in routine practice This essentially means that for a certain matrix (or group of matrices) at the anticipated reporting level the level of confidence of detection of the target analytes needs to be established False negatives need to be minimized for obvious reasons False positives are undesirable because they will trigger further manual data evaluation and confirmatory analyses which takes time and effort

Up to now only explorative evaluation of screening performance has been done using limited numbers of spiked samples or by comparison of the detection rate of the automated screening method with (earlier) results from established quantitative Lee et al tested automated identification using a test set of 106 pesticides and contaminants spiked to a complex compound feed sample at various levels using GCtimesGCndashTOF-MS19 Detection rates were clearly concentration dependent and varied from 100 to 73 to 17 for 010 001 and 0001 mgkg respectively Mezcua et al24 investigated the potential of LCndashTOF-MS based screening for pesticides in vegetables and fruits Automated detection was done using an in-house compiled database and instrument software Most pesticides found by the conventional LCndashMSndashMS method were also automatically found by the LCndashTOF-MS screening method

Very recently two groups did a more extensive verification of automated detection of pesticides using GCndashMS (single quadrupole) analysis combined with Agilentrsquos Deconvolution reporting Software tool Mezcua et al25 spiked 95 pesticides to eight vegetable and fruit samples at levels between 002 and 010 mgkg The evaluation of Norli et al26 involved a test set of 177 pesticides spiked in triplicate to 3 matrices at 002 and 01 mgkg The studies revealed that the detectability is as expected compound matrix and concentration dependent and that even in cases of repeated analysis of the same extract inconsistencies occurred with respect to automated detection In all studies mentioned the data generated were too limited to derive a confidence level for detectability of the target analytes in a certain matrix (group) On the other hand through analysis of real samples the studies did show that compared to the conventional methods more pesticides could be found in less time clearly demonstrating the potential of the approach This has been encouraging enough to apply the methods as an extension to the established quantitative multi-methods because any additional toxicant automatically found can be considered worthwhile

To summarize the above systematic validation studies of the qualitative screening methods are still lacking The limited availability of appropriate software andor target compound libraries up

Detection of Mycotoxins in Corn Meal with LC-MS-MS

SPONSOrED

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article4mycotoxinspdf

7

Toward Generic Data Processing and Data MiningWhile methods for generic extraction and subsequent full scan instrumental analysis are maturing universal approaches for data (pre)processing detection of toxicants and formats for archiving preprocessed result files hardly exist This means that the data files containing comprehensive information on a wide variety of food and feed samples and the (un)known toxicants they may contain can only be (further) explored by the laboratory that generated the data That laboratory might only be interested in pesticides (and just perform a targeted data analysis limited to that) while others might be interested in natural toxins in the same commodity Furthermore libraries used for automated detection may differ in scope which affects the output The issue as such is not unique for food toxicant analysis but unlike other areas such as metabolomics has hardly been addressed so far In our institute as a spin-off from development of data handling software for application in the field of metabolomics preprocessing tools are being applied and dedicated search tools have been developed for food toxicant screening The preprocessing tool called MetAlign is freely available and described in detail elsewhere23 One of the main features of MetAlign is that it can handle either direct or after automated conversion data from different vendors covering a broad range of GCndashMS and LCndashMS instruments both with nominal and accurate mass Data preprocessing involves baseline correction noise elimination and peak picking The software also deals with detector saturation and brand and instrument specific artifacts The output is a 50ndash500times reduced data file in a uniform format which can be exported to Excel or formats allowing visual review through proprietary instrument software already available in the laboratory (see Figure 4) Data alignment can be performed as well which can be of interest in searching for truly unknowns through comparison of profiles of the same products

The resulting files can be searched against target databases using dedicated modules for GCndashMS GCtimesGCndashMS (application to be published elsewhere) andLCndashMS Due to the strongly reduced size files can be easily stored and searching is fast A comparison of the automated detection performance after GCtimesGCndashTOF-MS between the instruments software and MetAlignGCGCMS_ search showed that in feed samples spiked with 106 analytes more compounds (32 vs 62 at the 00025 mgkg level) were found using the MetAlign software without increase in the number of false positives A generic approach for data preprocessing can facilitate data sharing and data mining thereby making much more efficient use of (existing) information available at different laboratories (Figure 5)

Figure 4 LCndashTOF-MS data file (a) before and (b) after preprocessing using MetAlign (see reference 23)

Figure 5 Data (pre)processing MetAlign as interface between instrument raw data and a uniform database for data mining23

8

Validation of Chromatography-Based (Qualitative) Screening MethodsOnce automated detection and reporting have been optimized the overall method (ie sample preparation + instrumental analysis + automated data processing and reporting) has to be validated before it can be applied in routine practice This essentially means that for a certain matrix (or group of matrices) at the anticipated reporting level the level of confidence of detection of the target analytes needs to be established False negatives need to be minimized for obvious reasons False positives are undesirable because they will trigger further manual data evaluation and confirmatory analyses which takes time and effort

Up to now only explorative evaluation of screening performance has been done using limited numbers of spiked samples or by comparison of the detection rate of the automated screening method with (earlier) results from established quantitative Lee et al tested automated identification using a test set of 106 pesticides and contaminants spiked to a complex compound feed sample at various levels using GCtimesGCndashTOF-MS19 Detection rates were clearly concentration dependent and varied from 100 to 73 to 17 for 010 001 and 0001 mgkg respectively Mezcua et al24 investigated the potential of LCndashTOF-MS based screening for pesticides in vegetables and fruits Automated detection was done using an in-house compiled database and instrument software Most pesticides found by the conventional LCndashMSndashMS method were also automatically found by the LCndashTOF-MS screening method

Very recently two groups did a more extensive verification of automated detection of pesticides using GCndashMS (single quadrupole) analysis combined with Agilentrsquos Deconvolution reporting Software tool Mezcua et al25 spiked 95 pesticides to eight vegetable and fruit samples at levels between 002 and 010 mgkg The evaluation of Norli et al26 involved a test set of 177 pesticides spiked in triplicate to 3 matrices at 002 and 01 mgkg The studies revealed that the detectability is as expected compound matrix and concentration dependent and that even in cases of repeated analysis of the same extract inconsistencies occurred with respect to automated detection In all studies mentioned the data generated were too limited to derive a confidence level for detectability of the target analytes in a certain matrix (group) On the other hand through analysis of real samples the studies did show that compared to the conventional methods more pesticides could be found in less time clearly demonstrating the potential of the approach This has been encouraging enough to apply the methods as an extension to the established quantitative multi-methods because any additional toxicant automatically found can be considered worthwhile

To summarize the above systematic validation studies of the qualitative screening methods are still lacking The limited availability of appropriate software andor target compound libraries up

Detection of Mycotoxins in Corn Meal with LC-MS-MS

SPONSOrED

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article4mycotoxinspdf

8

Validation of Chromatography-Based (Qualitative) Screening MethodsOnce automated detection and reporting have been optimized the overall method (ie sample preparation + instrumental analysis + automated data processing and reporting) has to be validated before it can be applied in routine practice This essentially means that for a certain matrix (or group of matrices) at the anticipated reporting level the level of confidence of detection of the target analytes needs to be established False negatives need to be minimized for obvious reasons False positives are undesirable because they will trigger further manual data evaluation and confirmatory analyses which takes time and effort

Up to now only explorative evaluation of screening performance has been done using limited numbers of spiked samples or by comparison of the detection rate of the automated screening method with (earlier) results from established quantitative Lee et al tested automated identification using a test set of 106 pesticides and contaminants spiked to a complex compound feed sample at various levels using GCtimesGCndashTOF-MS19 Detection rates were clearly concentration dependent and varied from 100 to 73 to 17 for 010 001 and 0001 mgkg respectively Mezcua et al24 investigated the potential of LCndashTOF-MS based screening for pesticides in vegetables and fruits Automated detection was done using an in-house compiled database and instrument software Most pesticides found by the conventional LCndashMSndashMS method were also automatically found by the LCndashTOF-MS screening method

Very recently two groups did a more extensive verification of automated detection of pesticides using GCndashMS (single quadrupole) analysis combined with Agilentrsquos Deconvolution reporting Software tool Mezcua et al25 spiked 95 pesticides to eight vegetable and fruit samples at levels between 002 and 010 mgkg The evaluation of Norli et al26 involved a test set of 177 pesticides spiked in triplicate to 3 matrices at 002 and 01 mgkg The studies revealed that the detectability is as expected compound matrix and concentration dependent and that even in cases of repeated analysis of the same extract inconsistencies occurred with respect to automated detection In all studies mentioned the data generated were too limited to derive a confidence level for detectability of the target analytes in a certain matrix (group) On the other hand through analysis of real samples the studies did show that compared to the conventional methods more pesticides could be found in less time clearly demonstrating the potential of the approach This has been encouraging enough to apply the methods as an extension to the established quantitative multi-methods because any additional toxicant automatically found can be considered worthwhile

To summarize the above systematic validation studies of the qualitative screening methods are still lacking The limited availability of appropriate software andor target compound libraries up

Detection of Mycotoxins in Corn Meal with LC-MS-MS

SPONSOrED

httpwwwlearnpharmasciencecomtablet-appsfood-issue1article4mycotoxinspdf

9

to now might be one reason for this Another reason might be that in contrast to quantitative methods validation procedures and criteria for qualitative chromatography-based methods were not very well addressed in guidance documents for residuescontaminant analysis For veterinary drugs EU directive 6572002 states that screening methods should be validated and that the lsquofalse compliant rate (false negatives) should be lt5 at the level of interestrsquo28 without providing much detail on how to establish this Fortunately beginning this year both the veterinary drug27 and the pesticide29 community in the EU came up with supplemental and updated guidance documents addressing this issue Essentially both documents prescribe that in an initial validation at least 20 samples spiked at the anticipated screening reporting level (lt MrL) need to be analysed and the target analyte(s) need to be detectable in at least 19 out of 20 samples (corresponding to the lt5 false negative rate) The initial validation needs to be continuously supplemented by analysis of spiked samples during routine analysis and periodical re-assessment of the data needs to be performed to demonstrate validity based on the extended data set

With the recent guidelines in mind a first retrospective evaluation of automatic detection of pesticides and contaminants in feed commodities after GCtimesGCndashTOF-MS analysis was done in the authorsrsquo laboratory The evaluation was based on spiked samples concurrently analysed with routine samples over a period of 9 months The results for 100 target compounds at the 005 mgkg level are summarized in Figure 6 It shows that at the software detection settings applied (which were not yet exhaustively optimized) gt90 of the target compounds are detected with a confidence level gt70 In a retrospective validation exercise for wheat the validation criterion was met for 70 of the analytes from the test set Across different feed commodities this percentage was substantially lower although it should be mentioned that this type of application is one of the most challenging in foodfeed toxicant analysis

ConclusionsChromatography combined with advanced full scan mass spectrometry is developing into a universal tool for screening (and quantitative determination) of a wide variety of food toxicants Time spent on sample preparation and the set-up of instrumental acquisition methods is declining The opposite is true for data processing optimization of software parameters for automated detection and finding the fit-for-purpose balance between false positives and false negatives but progress is being made The screening methods have already proven their added value In the foreseeable future such methods are likely to become more dominating thereby enabling more efficient and effective control of food safety and providing more comprehensive and more rapidly available data for risk assessment

Figure 6 Reliability of automated detection of residues and contaminants in feed commodities analysed with GCtimesGCndashTOF-MS Data processing and automatic detection ChromaToF 41 + Excel macro

10

Hans Mol is a senior scientist and heads the group of National Toxins and Pesticides at RIKILT He has over 15 yearrsquos experience in residue and contaminant analysis in the food chain using chromatography with a range of mass spectrometric techniques

Paul Zomer (BSc) is a research chemist in chromatography with various mass spectrometric detection techniques applied to pesticide residues and mycotoxins in feed and food matrices

Arjen Lommen is a senior scientist focusing on the development of data preprocessing and alignment software and adaption of this software for various applications ranging from metabolomics profiling to targeted screening Other areas of expertise include NMR

Henk van der Kamp (BSc) is a research chemist using gas chromatography mainly focusing on GCtimesGCndashTOF-MS analysis of food and feed with an emphasis on data evaluation and reporting

Martin van der Lee is a junior scientist with extensive experience in GCtimesGCndashTOF-MS analysis of pesticides and environmental contaminants His current work also focuses on elemental speciation analysis using chromatography with ICP-MS

Arjen Gerssen is finishing his PhD on the analysis of marine biotoxins As well as his continued involvement in this area his current research topics also include nano-LCndashMS and the development and the application of software tools for data evaluation in chromatographic screening methods and data mining

How to Cite this Article

H Mol A Lommen P Zomer H van der Kamp M van der Lee and A Gerssen ldquoData Handling and Validation in Auto-mated Detection of Food Toxicants Using Full Scan GCndashMS and LCndashMSrdquo LCGC Europe 23(4) 200ndash210 (2010)

References(1) HGJ Mol et al Anal Bioanal Chem 389 1715ndash1754 (2007)(2) P Payaacute et al Anal Bioanal Chem 389 1697ndash1714 (2007)(3) SJ Lehotay et al J AOAC Int 88(2) 595ndash614 (2005)(4) M Spanjer PM Rensen and JM Scholten Food Additives and Contaminants 25(4) 472ndash489 (2008)(5) V Vishwanath et al Anal Bioanal Chem 395 1355ndash1372 (2009)(6) S Bogialli and A Di Corcia Anal Bioanal Chem 395(4) 947ndash966 (2009)(7) G Stubbings and T Bigwood Anal Chim Acta 637(1ndash2) 68ndash78 (2009)(8) HGJ Mol et al Anal Chem 80 9450ndash9459 (2008)(9) E Hoh and K Mastovska J Chromatogr A 1186(1ndash2) 2ndash15 (2008)(10) National Institute of Standards and Technology Automated Mass Spectra l Deconvolution and

Identification System (AMDIS) httpchemdatanistgovmass-spcamdis(11) HJ Stan J Chromatogr A 892 347ndash377 (2000)

11

(12) K Kadokami et al J Chromatogr A 1089 219ndash226 (2005)(13) A Robbat J AOAC int 91 1467ndash1477 (2008)(14) W Zhang P Wu and C Li Rapid Commun Mass Spectrom 20 1563-1568 (2006)(15) S de Konig et al J Chromagr A 1008 247ndash252 (2003)(16) PL Wylie Screening for 926 pesticides and endocrine disruptors by GCMS with Deconvolution Reporting Software and a new

pesticide library Agilent Application note 5989-5076EN (2006)(17) HJ Cortes et al J Sep Sci 32(5ndash6) 883ndash904 (2009)(18) L Mondello et al Anal Bioanal Chem 389 1755ndash1763 (2007)(19) MK van der Lee et al J Chromatogr A 1186 325ndash339 (2008)(20) SH Patil et al J Chromatogr A 1217 2056ndash2064 (2009)(21) KM Pierce et al J Chromatogr A 1184 341ndash352 (2008)(22) M Kellmann et al J Am Soc Mass Spectrom 20(8) 1464ndash1476 (2009)(23) A Lommen Anal Chem 81(8) 3079ndash3086 (2009)(24) M Mezcua et al Anal Chem 81(3) 913ndash929 (2009)(25) M Mezcua et al J AOAC Int 92(6) 1790ndash1806 (2009)(26) HR Norli A Christiansen and B Hole J Chromatogr A 1217 2056ndash2064 (2010)(27) 2002657EC Official Journal of the European Communities L 2218-36 Commission decision of 12 August 2002 imple-

menting Council Directive 9623EC concerning the performance of analytical methods and the interpretation of results(28) Community Reference Laboratories Residues (CRLs) Guidelines for the validation of screening methods for residues of vet-

erinary medicines (initial validation and transfer) httpeceuropaeufoodfoodchemicalsafetyresiduesGuideline_Valida-tion_Screening_enpdf

(29) SANCO106842009 Method validation and quality control procedures for pesticides residues analysis in food and feed httpeceuropaeufoodplantprotectionresourcesqualcontrol_enpdf

R e s o u R c e s bull

Chromatography Applications Library

httpwwwthermoscientificcomapplicationslibrary

CHROMacademyrsquos Interactive HPLC Troubleshooter - Try it now at

httpwwwchromacademycomhplc_troubleshootingasp

CHROMacademyrsquos Interactive GC Troubleshooter

httpwwwchromacademycomgc_troubleshootingasp

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• cover
• TOC
• introduction
• article1
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• article3
• article4
• advertisement3

10

Hans Mol is a senior scientist and heads the group of National Toxins and Pesticides at RIKILT He has over 15 yearrsquos experience in residue and contaminant analysis in the food chain using chromatography with a range of mass spectrometric techniques

Paul Zomer (BSc) is a research chemist in chromatography with various mass spectrometric detection techniques applied to pesticide residues and mycotoxins in feed and food matrices

Arjen Lommen is a senior scientist focusing on the development of data preprocessing and alignment software and adaption of this software for various applications ranging from metabolomics profiling to targeted screening Other areas of expertise include NMR

Henk van der Kamp (BSc) is a research chemist using gas chromatography mainly focusing on GCtimesGCndashTOF-MS analysis of food and feed with an emphasis on data evaluation and reporting

Martin van der Lee is a junior scientist with extensive experience in GCtimesGCndashTOF-MS analysis of pesticides and environmental contaminants His current work also focuses on elemental speciation analysis using chromatography with ICP-MS

Arjen Gerssen is finishing his PhD on the analysis of marine biotoxins As well as his continued involvement in this area his current research topics also include nano-LCndashMS and the development and the application of software tools for data evaluation in chromatographic screening methods and data mining

How to Cite this Article

H Mol A Lommen P Zomer H van der Kamp M van der Lee and A Gerssen ldquoData Handling and Validation in Auto-mated Detection of Food Toxicants Using Full Scan GCndashMS and LCndashMSrdquo LCGC Europe 23(4) 200ndash210 (2010)

References(1) HGJ Mol et al Anal Bioanal Chem 389 1715ndash1754 (2007)(2) P Payaacute et al Anal Bioanal Chem 389 1697ndash1714 (2007)(3) SJ Lehotay et al J AOAC Int 88(2) 595ndash614 (2005)(4) M Spanjer PM Rensen and JM Scholten Food Additives and Contaminants 25(4) 472ndash489 (2008)(5) V Vishwanath et al Anal Bioanal Chem 395 1355ndash1372 (2009)(6) S Bogialli and A Di Corcia Anal Bioanal Chem 395(4) 947ndash966 (2009)(7) G Stubbings and T Bigwood Anal Chim Acta 637(1ndash2) 68ndash78 (2009)(8) HGJ Mol et al Anal Chem 80 9450ndash9459 (2008)(9) E Hoh and K Mastovska J Chromatogr A 1186(1ndash2) 2ndash15 (2008)(10) National Institute of Standards and Technology Automated Mass Spectra l Deconvolution and

Identification System (AMDIS) httpchemdatanistgovmass-spcamdis(11) HJ Stan J Chromatogr A 892 347ndash377 (2000)

11

(12) K Kadokami et al J Chromatogr A 1089 219ndash226 (2005)(13) A Robbat J AOAC int 91 1467ndash1477 (2008)(14) W Zhang P Wu and C Li Rapid Commun Mass Spectrom 20 1563-1568 (2006)(15) S de Konig et al J Chromagr A 1008 247ndash252 (2003)(16) PL Wylie Screening for 926 pesticides and endocrine disruptors by GCMS with Deconvolution Reporting Software and a new

pesticide library Agilent Application note 5989-5076EN (2006)(17) HJ Cortes et al J Sep Sci 32(5ndash6) 883ndash904 (2009)(18) L Mondello et al Anal Bioanal Chem 389 1755ndash1763 (2007)(19) MK van der Lee et al J Chromatogr A 1186 325ndash339 (2008)(20) SH Patil et al J Chromatogr A 1217 2056ndash2064 (2009)(21) KM Pierce et al J Chromatogr A 1184 341ndash352 (2008)(22) M Kellmann et al J Am Soc Mass Spectrom 20(8) 1464ndash1476 (2009)(23) A Lommen Anal Chem 81(8) 3079ndash3086 (2009)(24) M Mezcua et al Anal Chem 81(3) 913ndash929 (2009)(25) M Mezcua et al J AOAC Int 92(6) 1790ndash1806 (2009)(26) HR Norli A Christiansen and B Hole J Chromatogr A 1217 2056ndash2064 (2010)(27) 2002657EC Official Journal of the European Communities L 2218-36 Commission decision of 12 August 2002 imple-

menting Council Directive 9623EC concerning the performance of analytical methods and the interpretation of results(28) Community Reference Laboratories Residues (CRLs) Guidelines for the validation of screening methods for residues of vet-

erinary medicines (initial validation and transfer) httpeceuropaeufoodfoodchemicalsafetyresiduesGuideline_Valida-tion_Screening_enpdf

(29) SANCO106842009 Method validation and quality control procedures for pesticides residues analysis in food and feed httpeceuropaeufoodplantprotectionresourcesqualcontrol_enpdf

R e s o u R c e s bull

Chromatography Applications Library

httpwwwthermoscientificcomapplicationslibrary

CHROMacademyrsquos Interactive HPLC Troubleshooter - Try it now at

httpwwwchromacademycomhplc_troubleshootingasp

CHROMacademyrsquos Interactive GC Troubleshooter

httpwwwchromacademycomgc_troubleshootingasp

sponsoRed by

sponsoRed by

• cover
• TOC
• introduction
• article1
• advertisement1
• article2
• advertisement2
• article3
• article4
• advertisement3

11

(12) K Kadokami et al J Chromatogr A 1089 219ndash226 (2005)(13) A Robbat J AOAC int 91 1467ndash1477 (2008)(14) W Zhang P Wu and C Li Rapid Commun Mass Spectrom 20 1563-1568 (2006)(15) S de Konig et al J Chromagr A 1008 247ndash252 (2003)(16) PL Wylie Screening for 926 pesticides and endocrine disruptors by GCMS with Deconvolution Reporting Software and a new

pesticide library Agilent Application note 5989-5076EN (2006)(17) HJ Cortes et al J Sep Sci 32(5ndash6) 883ndash904 (2009)(18) L Mondello et al Anal Bioanal Chem 389 1755ndash1763 (2007)(19) MK van der Lee et al J Chromatogr A 1186 325ndash339 (2008)(20) SH Patil et al J Chromatogr A 1217 2056ndash2064 (2009)(21) KM Pierce et al J Chromatogr A 1184 341ndash352 (2008)(22) M Kellmann et al J Am Soc Mass Spectrom 20(8) 1464ndash1476 (2009)(23) A Lommen Anal Chem 81(8) 3079ndash3086 (2009)(24) M Mezcua et al Anal Chem 81(3) 913ndash929 (2009)(25) M Mezcua et al J AOAC Int 92(6) 1790ndash1806 (2009)(26) HR Norli A Christiansen and B Hole J Chromatogr A 1217 2056ndash2064 (2010)(27) 2002657EC Official Journal of the European Communities L 2218-36 Commission decision of 12 August 2002 imple-

menting Council Directive 9623EC concerning the performance of analytical methods and the interpretation of results(28) Community Reference Laboratories Residues (CRLs) Guidelines for the validation of screening methods for residues of vet-

erinary medicines (initial validation and transfer) httpeceuropaeufoodfoodchemicalsafetyresiduesGuideline_Valida-tion_Screening_enpdf

(29) SANCO106842009 Method validation and quality control procedures for pesticides residues analysis in food and feed httpeceuropaeufoodplantprotectionresourcesqualcontrol_enpdf

R e s o u R c e s bull

Chromatography Applications Library

httpwwwthermoscientificcomapplicationslibrary

CHROMacademyrsquos Interactive HPLC Troubleshooter - Try it now at

httpwwwchromacademycomhplc_troubleshootingasp

CHROMacademyrsquos Interactive GC Troubleshooter

httpwwwchromacademycomgc_troubleshootingasp

sponsoRed by

sponsoRed by

• cover
• TOC
• introduction
• article1
• advertisement1
• article2
• advertisement2
• article3
• article4
• advertisement3

R e s o u R c e s bull

Chromatography Applications Library

httpwwwthermoscientificcomapplicationslibrary

CHROMacademyrsquos Interactive HPLC Troubleshooter - Try it now at

httpwwwchromacademycomhplc_troubleshootingasp

CHROMacademyrsquos Interactive GC Troubleshooter

httpwwwchromacademycomgc_troubleshootingasp

sponsoRed by

sponsoRed by

• cover
• TOC
• introduction
• article1
• advertisement1
• article2
• advertisement2
• article3
• article4
• advertisement3