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Food Research International

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Relationships between composition, microstructure and cookingperformances of six potato varieties

Annalisa Romanoa,b,⁎, Vincenzo D'Ameliac, Veronica Galloa, Sara Palombaa, Domenico Carputoc,Paolo Masia,b

a Department of Agricultural Sciences, Division of Food Science and Technology, University of Naples Federico II, Via Università 100, 80055 Portici, Naples, Italyb Centre for Food Innovation and Development in the Food Industry, University of Naples Federico II, Via Università 100, 80055 Portici, Naples, Italyc Department of Agricultural Sciences, Division of Plant Genetics and Biotechnology, University of Naples Federico II, Via Università 100, 80055 Portici, Naples, Italy

A R T I C L E I N F O

Keywords:Solanum tuberosumStarchChemical propertiesThermal propertiesMechanical propertiesGenetic diversityMolecular markers

A B S T R A C T

Potatoes tubers are the raw materials of many processed food, such as cooked potatoes in hot water, bakedpotatoes and the most popular fried potatoes. The objective of this work was to study the impact of boiling,baking and frying on microstructure and properties of six potato varieties (Agata, Agria, Innovator, Lady Rosetta,Musica and Spunta) with different origin. Scanning Electron Microscopy revealed significant differences betweenvarieties and tuber microstructure changes following all cooking processes. Differential Scanning Calorimeteranalysis showed that the transition temperatures (ranging between 60 °C and 85 °C) and enthalpies of gelati-nization (2.1 J/g–3.9 J/g) of tubers were also variety dependent. In addition, the elasticity modulus of cookedsamples depended on process type and followed the order: baked potatoes > boiled > fried potatoes. In par-ticular, baked Lady Rosetta (224.3 kPa) showed the least decrease in rigidity between thermal processes. FriedAgria and Spunta, (56.3 and 61 kPa, respectively) had the smallest value of Young's modulus. Molecular markeranalyses provided a genetic fingerprinting of our varieties, allowing the identification of diagnostic markers.Innovator revealed an important genetic distance from the other varieties. Such distance corresponded to itsexclusive phenotypic traits, that are known to affect thermochemical properties. The information obtained inthis work may be useful to further study and associate genetic sequences with appreciable food technologicaltraits.

1. Introduction

Tubers of the cultivated potato (Solanum tuberosum) provide sig-nificant amounts of carbohydrates, potassium and ascorbic acid in thediet (Hale, Reddivari, Nzaramba, Bamberg, & Miller, 2008). Most ofcarbohydrate content is represented by starch (60–80% of dry matter),which is packaged in indigestible granules in parenchyma cellularcompartments (Singh, Kaur, Ezekiel, & Gurraya, 2005). Tubers areusually cooked before consumption; baking, boiling and frying re-present the most popular cooking methods (Romano et al., 2013; Tian,Chen, Ye, & Chen, 2016; Yang, Achaerandio, & Pujolà, 2016). Theyinvolve different types of heat transfer: pure convection from a liquidmedia such as oil (frying) or boiling water (boiling) and combined heattransmission by radiation from oven walls, (natural or forced) con-vection from the movement of hot moist air and conduction in baking.All heat treatments involve many physical, chemical and biochemicaltuber changes, depending on the temperature requirement, method of

application of heat and duration. As no single potato variety has beenshown to be appropriate for all cooking methods, screening of thevarieties is necessary for specific end use and for their ability to provideoptimum processing performance and product quality. The character-istics of cooked potatoes can be studied by microscopic observationsand textural measurements (Alcázar-Alay & Meireles, 2015). Starchgelatinization and cell wall separation are considered the two mainmodifications occurring during cooking treatment. The mechanism ofstarch gelatinisation depends on the amount of water available. Withina potato cell there are 3–4 g water per g starch (volume ratio water:starch+water= 0.8), which is enough to ensure that gelatinisationproceeds along the path characterized by a single endotherm peak(Biliaderis, Maurice, & Vose, 1986; Donovan, 1979). Gelatinisationtransitions starch from a semi-crystalline form (relatively indigestible)to an amorphous form that is easily digestible (Tester & Debon, 2000).Therefore, gelatinisation affects the rheological properties, makingstarch granules more accessible to enzymatic action. When starch

https://doi.org/10.1016/j.foodres.2018.07.033Received 27 March 2018; Received in revised form 29 June 2018; Accepted 26 July 2018

⁎ Corresponding author.E-mail address: annalisa.romano@unina.it (A. Romano).

Food Research International 114 (2018) 10–19

Available online 27 July 20180963-9969/ © 2018 Elsevier Ltd. All rights reserved.

T

granules swell and their components are in solution, grains expandrapidly (Hoseney, Zeleznak, & Yost, 1986), driven by the gain in en-tropy, and form a weak gel plus some dissolved amylose (Jarvis,Mackenzie, & Duncan, 1992). The different gelatinization degree anddestruction of the native microstructure occurring with differentcooking methods influence the glycemic index of processed potatoes,with boiled samples having higher glycemic index than fried or bakedones (Tahvonen, Hietanen, Sihvonen, & Salminen, 2006). The maindifference in the glycemic response is due to the rate of starch digestionof starchy foods in the small intestine. The rate at which starch is di-gested depends on a number of factors such as the molecular structureof starch (Leeman, Barstrom, & Bjorck, 2005), the size of granules(Noda et al., 2004), the metabolic processes occurring during storage aswell as cooking methods (Lu et al., 2011). Since end products and heattreatments may be very different, the raw material for each processshould preferably possess specific characteristics to maintain thequality of processed potato products. As an example, the texture ofpotato crisps is dependent mainly on the starch content of the rawpotato tubers. Starch content is significantly affected by the genotype,the environment and their interaction (Bach, Yada, Bizimungu, Fang, &Sullivan, 2013). It is reported that several alleles at multiple genetic locicontribute to starch content, making its genetic control rather complex(Chen, Salamini, & Gebhardt, 2001; Werij, Furrer, van Eck, Visser, &Bachem, 2012). The quality of crisps and tuber fiber content are alsodetermined by the nonstarch polysaccharides of the cell wall. Potatoeswith closely packed small and irregular parenchymatous cells havebeen observed to be relatively hard and cohesive. In contrast, potatoeswith large, loosely packed cells are generally less hard. It should bepointed out that the cell wall characteristics of cooked potato also playan important role in the release of glucose during starch digestion inour body (Singh, Kaur, & Singh, 2013).

As a follow up to a former study about tuber starch characteristics of21 potato varieties (Romano et al., 2018), the objective of this work wasto study the impact of traditional cooking processes on microstructureand cooking performances of six well known potato varieties with dif-ferent origin according to a multidisciplinary approach. These varietiesrepresent a diverse range of commercial materials commonly used aseither fresh or processed potatoes. Knowledge of their properties is animportant target to address the use of specific varieties and also has thepotential to optimize processing performances. In addition, it may helpthe choice of suitable parents in breeding programs aimed at devel-oping potato varieties with specific process attributes. To highlightdiagnostic DNA polymorphisms and to find possible relationships withthe diversity detected at phenotypic level, varieties used in this studywere also subjected to analysis with molecular markers.

2. Materials and methods

2.1. Materials

Six commercially available potato varieties were used. According totheir cooking type, Agata, Agria, Musica and Spunta are classified asfairly firm to firm varieties, whereas Innovator and Lady Rosetta aremealy to fairly firm varieties (www.europotato.org). Plants were grownin the field in Celano (central Italy) in the summer 2016 to collectleaves for DNA analysis and to produce tubers for determining char-acteristics and properties. Approximately 30 kg of each potato varietywere harvested when leaves started senescing, about 120 days afterplanting. Only medium-sized tubers (approximately 5 cm in diameter asmeasured perpendicular to the apical-stolon end axis, regardless oforientation) were collected. The selection of tubers with similar shapeand size is felt important because variations in the activity of enzymessuch as granule-bound starch synthase during growth may affect starchgranule morphology in potatoes (Fulton et al., 2002). Tubers werestored in the dark at 7 °C for a week before evaluating starch andmoisture content.

2.2. Sample preparation and cooking processes

Tubers were washed with tap water and the periderm was peeledimmediately before testing. Each tuber was cut into two equal halves.Cylindrical samples having diameters of 16mm and height of 20mmwere taken from each half (excluding the core region) using a boreroperating perpendicularly to the two cut planes. This procedure mini-mized the large textural differences occurring between the cortex andthe pith tissues (Anzaldùa-Morales, Bourne, & Shower, 1992). Sixsamples of each variety were prepared for each cooking treatment.Three cooking processes were considered: baking, boiling and frying.Cooking conditions were determined in a preliminary experiment foreach heat treatment to ensure similar tenderness after cooking (data notshown) as reported by Adília, Aliyu, Hungerford, and G. (2015). Theconditions used in each cooking treatment were:

Baking: the cylindrical specimens were baked in a hot-air oven(Mod. ALFA 41DA, Smeg, Italy) at 180 ± 5 °C for 15min.

Boiling: the cylindrical specimens cooked in boiling distilled water(100 °C) for 6min and relation potato/water (1:3). Distilled water wasused to avoid the pH effects on textural properties (softening) of boiledsamples (Reeve, 1977).

Frying: the cylindrical specimens were immersed in a deep fat fryer(mod 41014, Termozeta, China) at 185 ± 2 °C for 5min with sun-flower oil in oil ratio of 1:20 (w/v), which was deemed by Andrés,Arguelles, Castelló, and Heredia (2013) to be sufficient to avoid majorchanges occurring in terms of product-to-oil ratio, oil composition, andtemperature.

Each individual cooking experiment was conducted in triplicate.

2.3. Microstructure analysis

Scanning Electron Microscopy (SEM, LEO EVO 40, Zeiss, Germany)was used to examine the microstructure of the raw (fresh) and pro-cessed samples to determine the effects of baking, boiling and frying onthe structure of our varieties. Potato slices (thickness of 0.1mm) werecut from the raw and cooked cylindrical specimens (par. 2.2) and werelyophilized by a freeze dryer (mod. Alpha 1–2 LD plus, Christ,Germany), at −50 °C for 48 h. Samples were then dried at the criticalpoint and coated with gold particles in an automated critical point drier(model SCD 050, Leica, Vienna). Microstructure of raw and cookedsamples was examined by SEM with a 20 kV acceleration voltage and a×1000 magnification. Particle size and shape of raw starch granuleswere studied using a method based on image analysis protocol of SEMmicrographs as already reported (Romano et al., 2018). Three micro-graphs were selected randomly from the total of 6 micrographs col-lected per variety. Micrographs were processed by Image Pro Plus 6.1for Windows® (Media Cybernetics Inc.). Computed parameters includedthe following:

• starch granule diameter (μm).

• starch granule surface area (μm2).

• starch granule roundness. This measurement calculates the circu-larity of an object:

=

PπAF

roundness4

i

i

2

where AFi is the area of the ith starch granule and Pi is the measuredperimeter of the ith starch granule. A perfect circle has a shape factor of1 and a line has a shape factor approaching to zero.

Starch granule area distribution analysis was also performed bycounting the percentages of granules falling into three predefined areaclasses: small (< 350 μm2), medium (350–1250 μm2) and large(> 1250 μm2).

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2.4. Tuber properties

2.4.1. Dry matter, moisture content and total starch contentThe dry matter and the moisture content of samples were de-

termined by the AACC method (AACC number 44-15.02, 1999). Two-3 g of sample were dried for 24 h at 105 °C. Samples were removed fromthe oven and immediately placed in a desiccator prior to weighing aftercooling and within 30min. The dried samples weight was subtracted tothe respective initial weight. The results were calculated both as per-centage of water per sample weight (%) and the percentage on the drymatter content (%). Average values of three dry matter measurementswere calculated for each raw sample. Three moisture content de-terminations were performed for each cooking treatment. Total starch(TS) of raw tubers was determined using an enzymatic assay kit (TotalStarch Assay Kit, Megazyme International Ireland) by AACC method(number 76-13.01, 2014). All these results were expressed as percen-tage weight / weight on dry basis. Average values of three measure-ments were calculated for each variety.

2.4.2. Thermal analysisThermal behaviour of the samples were determined using a

Differential Scanning Calorimeter (DSC Q200, TA Instruments, Milan,Italy) as reported by Romano et al. (2018). Raw samples (15–25mg)were scanned from 20 to 100 °C at a rate of 10 °C/min in a sealedaluminum pan using an empty pan as the reference. The enthalpytransition (ΔH), onset temperature (T0), peak temperature (Tp) and endtemperature (Te) of endotherms were measured. Average values ofthree measurements were calculated for each sample.

2.4.3. Mechanical analysisThe evolution of the elastic modulus during cooking of the samples

was measured with a dynamometer operating in compression mode.Raw and cooked samples were submitted to a compression test bymeans of an Instron Universal Testing Machine (Instron Ltd., mod.4467, High Wycombe, GB), equipped with a 1 kN load cell. Cylindricalsamples (diameter 16mm, height 20mm) were placed between parallelplates and deformed to 80% their initial height, at a crosshead speed of10mm/min. Original data were converted into stress vs. Henky's de-formation, and the modulus of elasticity (Young's modulus) was cal-culated from the initial linear region of the curve. Tests were performedby using five samples of each variety for each cooking process. Datareported are the mean of ten values.

2.5. Microsatellite (SSR) analysis

DNA extraction was carried out using the Qiagen Plant DNeasy Kitaccording to the manufacturer's instructions (Qiagen, Valencia, CA,USA). Analyses were performed with 22 nuclear microsatellite (SSR)primer pairs chosen from already used in Romano et al., 2018. All SSRswere recommended by CIP (www.cipotato.org), based on quality cri-teria, genome coverage, and locus-specific information content. PCRreactions were performed in a 20 μL volume containing 1 reactionbuffer with 1.6mM MgCl2, 0.2 mM of each dNTP, 30 pM FAM labelledforward SSR primer, 30 pM reverse SSR primer, 1 unit of goTaq poly-merase (Promega, Madison, WI, USA) and 30 ng of genomic DNA.Amplification consisted of 5 cycles at 94 °C for 45 s, Ta C+5 for 60 s,72 °C for 30 s; 30 cycles at 94 °C for 45 s, Ta C for 60 s, 72 °C for 30 swith the annealing temperature reduced by 1 °C per cycle (touchdownPCR), then one elongation cycle at 72 °C for 20min. Amplificationproducts were checked and quantified on 2% agarose/TAE gel using 1Kb plus ladder (Life Technologies, Carlsbad, CA, USA) and displayed atthe transilluminator. PCR products were separated on an ABI PRISM®

3130 DNA Analyzer system (Applied Biosystems, Foster City, USA). Sizecalibration was performed with the molecular weight ladder GeneScan®500 ROXTM Size Standard. SSR alleles were detected and scored by theGeneScan® Analysis software (Applied Biosystems, Foster City, USA) as

present (1) or absent (0).

2.6. Statistical analysis

All experimental results are reported as means and standard de-viation of at least three independent experiments. Statistical analysiswas performed using SPSS version 19.0 (SPSS Inc., Chicago, IL, USA).Analysis of variance was conducted to evaluate the effect of variety onparameters during cooking processes. Significant differences betweenthe detected parameters were compared by means of Duncan's multiplecomparison test at the 95% confidence level (p≤ .05). In addition, aprincipal component analysis (PCA) was carried out to visualize pos-sible relationships within the data matrix. To decide the number ofprincipal components (PCs), the eigenvalues of the correlation matrix,indicating the percentage of variability explained by each component,were tabulated and a screen plot was constructed. Nearest neighboranalysis was used to find the spatial relationships among the multipleobjects by calculating their distances. A standardized n-space Euclidiandistance was calculated to measure the similarity and relation whichcan be computed. The K value was 3, based on the number of principalcomponents extracted. Using SSR data, a similarity matrix was calcu-lated using the Dice coefficient and scoring for presence or absence ofeach allele in all varieties. The dendrogram was built through theUPGMA (Unweighted Pair Group Method with Arithmetic Mean)method. Clusters robustness was tested by bootstrap resampling(n=1000) with the software package WINBOOT.

3. Results and discussion

3.1. Microstructural analyses of raw samples

Starch features are considered a major factor affecting the perfor-mance of processed potatoes and other potato starch based foods(Singh, Kaur, & McCarthy, 2009; Smith, 2001). Scanning Electron Mi-croscopy (SEM) image analysis of starch granule surfaces (Fig. 1 andTable 1) revealed the presence of evident oval and spherical granules inparenchyma cellular compartments, with heterogeneous diameters(ranging from 9 μm in Musica to 70 μm in Agata) (data not shown). Allgranules had smooth surfaces and filled the parenchyma cellular com-partments, confirming previous reports by Singh et al. (2005), Bordoloi,Kaur, and Singh (2012) and Romano et al. (2018). The mean diameterof starch granules ranged from 21 μm of Musica (a firm variety) to37 μm of Innovator (a mealy variety), while the mean area varied from554 μm2 of Spunta to 1566 μm2 of Innovator and discriminated vari-eties into three statistical groups (P < .05) (Table 1). The averagevalue of roundness (shape descriptor) discriminated varieties into twostatistical groups (Table 1). Mean roundness describes the maximumdeviation of starch granules from a true circle. The highest roundnesswas observed in mealy variety Innovator (1.103). Granule size dis-tribution is considered an additional characteristic that is important forthe nutritional and functional properties of starch and its use (Romanoet al., 2016; Tester, Qi, & Karkalas, 2006). Our varieties were mainlycharacterized by medium (350–1250 μm2) and large (> 1250 μm2)starch granules (Fig. 2). Only Spunta and Musica had a considerablepercentage of small (< 350 μm2) granules (20% and 15%, respec-tively), while Agata showed only medium and large granules (80% and20%, respectively). This correlated with the fact that Agata area aver-aged 930.2 μm2 (Table 2), with a minimum value of 383.5 μm2. Allsamples had a percentage of medium granules higher than 50%. Mealy-cooking varieties (i.e. Innovator and Lady Rosetta) had the highestpercentage (about 40%) of large (> 1250 μm2) granules. The observedlarge variation in granule morphology may be ascribed to the genotype,the biochemistry of the amyloplast and also to the physiology of theplant (Svegmark & Hermansson, 1993). The microstructural classifica-tion of starch tubers can provide useful information for the develop-ment of tailored foods. In fact, the potato contributes substantially to

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total starch intake and is a food that yields variable glycemic responses.The relationships between the microstructure of potato tubers and itsimpact on carbohydrate digestion rates and the glycemic index havebeen studied by various researchers through in vitro methods (Colussi

et al., 2017; Ek, Wang, Brand-Miller, & J., & Copeland, L., 2014). Therate of starch digestion of starchy foods depends on several factors suchas the microstructure and size of the starch granules (Leeman et al.,2005; Noda et al., 2004) and cooking methods (Lu et al., 2011). Ac-cording to our microstructural results, starch from large granule vari-eties (e.g. Innovator) is expected to be digested less rapidly.

3.2. Chemical and thermal characteristics of raw samples

Table 2 reports dry matter content and total starch of varietiesstudied here. Dry matter is empirically defined as the percentage of asample's mass which stays after water has been evaporated. It is anincredibly important parameter of potato quality, as it influences theeffects of cooking on sensory attributes such as texture (Taylor,McDougall, & Stewart, 2007). Generally, texture is an essential factor inthe consumers' perception of the quality of potatoes (Garcìa-Segovia,Andrés-Bello, & Martìnez-Monzo, 2008). Besides, it is important forresearchers to recommend growers to use specific and appropriate

Fig. 1. SEM images of potato varieties Agata, Agria, Innovator, Lady Rosetta, Musica and Spunta.

Table 1Diameter (μm), area (μm2) and roundness of starch granules of tubers of sixpotato varieties, expressed as means ± S.D.

Diameter (μm) Area (μm2) Roundness

Agata 32.20 ± 21.24a,b 930.16 ± 365.0a,b 1.068 ± 0.04a

Agria 25.19 ± 16.59a,b 696.91 ± 327.3a 1.070 ± 0.05a

Innovator 36.88 ± 22.97b 1565.83 ± 1425.7c 1.103 ± 0.05b

Lady Rosetta 34.24 ± 9.02b 1240.88 ± 640.7b,c 1.077 ± 0.05a,b

Musica 21.33 ± 7.59a 842.71 ± 491.9a 1.089 ± 0.05a,b

Spunta 30.83 ± 13.15a,b 553.66 ± 265.5a 1.086 ± 0.03a,b

Means with a column with different letters are significantly different (Duncan'stest p≤ .05).

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varieties. Indeed, only the canning industry requires potato with a lowdry matter content, while for the production of industrial products (e.g.French fries and crisps), varieties with low dry matter content are notsuitable (Kabira & Berga, 2003). Usually, fresh potatoes contain about18–25% of dry matter. The dry matter content (DM) of our varietiesranged from 15% of Musica (a firm variety) to 24% of mealy varietiesInnovator and Lady Rosetta (Table 2). Total starch content (TS) sig-nificantly (P < .05) varied from 9% in Spunta and Musica to 13–15%in Innovator and Lady Rosetta (Table 2). This variability further out-lines that for these two traits genotypic differences exist (Bach et al.,2013; Jansen, Flamme, Schüler, & Vandrey, 2001). Interestingly, In-novator also showed the highest value of TS and DM when compared toa different subset of varieties and in two different environments (Chunget al., 2014). Our DM and TS results fit well with results of diameter andarea of visible starch granules (Table 1), in agreement with findings byKarlsson and Eliasson (2003).

When tubers are cooked, most of the starch becomes digestible dueto gelatinization. Starch gelatinization is an endothermic process thatcorresponds to the loss of crystalline order within the starch granulesunder particular heat and moisture conditions (Biliaderis et al., 1986).Romano et al. (2016) reported that there is a specific temperature in-terval for gelatinization corresponding to each starch species. Starchgelatinization is crucial for the digestibility, the palatability and thetextural changes of the raw starch matrix during cooking (Kim,Wiesenborn, & Grant, 1997; Yang et al., 2016). To study starch gela-tinization in potatoes, thermal analysis methods as differential scanningcalorimetry (DSC) could be used (Romano, Di Luccia, Romano,Sarghini, & Masi, 2015). A single endothermic transition, corresponding

mainly to the gelatinization transition of the starch, was observed in theDSC profiles of all tested samples (Supplemental Fig. 1). The thermalparameters (gelatinization peak temperatures, T0, Tp, Te and transitionenthalpies, ΔH) of our samples are reported in Table 2. The thermaltransition temperatures showed these ranges: T0 from 60 °C of In-novator to 62 °C of Agata and Agria; Tp from 71 °C (Spunta and LadyRosetta) to 73 °C (Agria) and Te from 81 °C (Spunta) to 85 °C (Agria).The ΔH values significantly discriminated potato varieties into threestatistical groups (P < .05). The highest gelatinization enthalpiesnormalized to TS were observed in mealy varieties Lady Rosetta andInnovator (2.1–2.2 J/g). The degree of gelatinization is directly mea-sured from the gelatinization enthalpy (Kaur & Singh, 2005). It refers tothe energy required to disrupt the native structure of the starch granuleand to determine its digestibility. However, the total amount of starch isthe principal factor affected by gelatinization (Troncoso, Zúñiga,Ramírez, Parada, & Germain, 2009). Therefore, high ΔH values of tu-bers suggests that the starch granules that melt during gelatinizationare resistant and strongly associated with their native structure, inagreement with granule size results (Fig. 1 and Table 1) and TS values(Table 2). Similarly, the low value of transition temperatures and thelowest ΔH of Spunta may be attributed to the reduced thermal granulestability of this variety characterized by a low TS content (Table 2) andsmaller granules (Fig. 1).

3.3. Effects of cooking processes on microstructural changes

To study effects of cooking processes at microstructural level, SEManalyses were performed on all samples. All cooking processes sig-nificantly changed the interior microstructure of tubers. Fig. 3 showsthe representative SEM images of three potato varieties, Agata, Musicaand Lady Rosetta, after cooking treatments: baking (Fig. 3a), boiling(Fig. 3b) and frying (Fig. 3c). As shown, most of the separated cells andsmall clusters tended to remain slightly angular after cooking, with thepolyhedral shapes distinctive of the raw microstructures. After baking(Fig. 3a), the potato parenchyma of all samples showed separatedswollen cells and breakage of cell wall (pectin). In mealy variety LadyRosetta, with the highest DM and TS (Table 1), swelling and cell walldistension were more evident than in Agata and Musica (Fig. 3a). Ourresults confirmed that cell sloughing mainly occurs in potatoes withhigh DM. In boiled samples (Fig. 3b), large differences were detectedamong varieties. The swelled starch granules of Agata diffused throughthe cell wall, that lost the original polyhedral shapes characteristic; bycontrast, in Lady Rosetta the area of the wall became enlarged due toswelling of the gelatinized starch and cell wall distension. In Musica,with a low DM and TS (Table 1), starch granules were completely ge-latinized. This produced a sponge-like structure (Fig. 3b), with the ty-pical cell wall distension and the middle lamella disruption as result ofincreased turgor pressure. Following boiling, gelatinised starch hasbeen reported to produce a sponge-like structure also in studies byMcComber, Horner, Chamberlin, and Cox (1994), Valetudie, Gallant,Bouchet, Colonna, and Champ (1999) and Sjoo, Eliasson, and Autio(2009). In fried potatoes, the external structure of the potato tissue is

0

10

20

30

40

50

60

70

80

90

100

Agata Agria Innovator LadyRosetta

Musica Spunta

)%(

ycneuqerF

>1250µm2

350-1250µm2

<350 µm2

Fig. 2. Particle size distribution (%) of starch granules of potato varieties Agata,Agria, Innovator, Lady Rosetta, Musica and Spunta.

Table 2Dry Matter (DM), Total Starch (TS), onset (T0), peak (Tp), end (Te) transition temperatures and transition enthalpies (ΔH) of potato varieties, expressed asmeans ± S.D.

Variety DM (%) TS (%) T0 (°C) Tp (°C) Te (°C) ΔH⁎ (J/g)

Agata 17.9 ± 0.13b 10.80 ± 0.10b 62.2 ± 0.59b 72.7 ± 0.30b,c 84.5 ± 0.36b,c 1.3 ± 0.09b

Agria 18.6 ± 0.42b 10.23 ± 0.68b 62.2 ± 0.71b 73.3 ± 0.42c 85.2 ± 0.53c 1.3 ± 0.06b

Innovator 23.9 ± 0.71d 13.20 ± 0.43c 60.1 ± 0.64a 71.8 ± 0.04a,b 84.5 ± 0.43b,c 2.1 ± 0.18c

Lady Rosetta 24.4 ± 1.30d 15.24 ± 0.04d 60.5 ± 1.90a,b 71.1 ± 0.99a 83.5 ± 0.75b 2.2 ± 0.50c

Musica 15.3 ± 0.14a 9.52 ± 0.13a 61.6 ± 0.64a,b 72.0 ± 0.56a,b 83.7 ± 1.31b,c 1.3 ± 0.12b

Spunta 20.3 ± 0.79c 9.22 ± 0.01a 61.0 ± 0.24a,b 71.0 ± 0.58a 81.0 ± 0.92a 1.0 ± 0.09a,b

(a–c) Different subscripts letters within a column indicate significant differences (p < .05) between varieties.⁎ Normalized to TS.

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exposed to hot oil (temperature about 180 °C). This process causes crustformation (not explored in this study), softening of the middle lamellabetween cells, starch gelatinization and dehydration (Rahimi, Adewale,Ngadi, Agyare, & Koehler, 2017). As shown in Fig. 3c, a sponge-likestructure was evident in all samples. Since SEM observations were fo-cused on the interior pulp and our potatoes had a relatively high TS(Table 2), the major influence on microstructure of examined varietiesshould be due to gelatinization of starch during heating. This appears tobe more emphasized but analogous to the osmotic dehydration of themiddle lamella and the cell wall of baked potatoes (Fig. 3a). In fact, theruptured structure of fried potatoes can be a result of osmotic dehy-dration which disrupts the middle lamella and dissolves the cell wall(pectin) (Oladejo et al., 2017; Prinzivalli, Brambilla, Maffi, Lo Scalzo, &

Torreggiani, 2006). With respect to microstructural dimensions, starchgranules expanded due to water absorption and starch gelatinizationwith a consequent cell wall distension and middle lamella disruption.This is due to the different granule architecture (crystalline to amor-phous ratio) and the different characteristics of starch that can varygreatly among potato varieties and cooking processes.

3.4. Effects of cooking processes on moisture content and textural changes

Structural changes that potatoes undergo on cooking provide a widevariety of textural qualities. In products with relatively high starchcontent, such as potatoes, the major influence on texture could be re-lated to the gelatinization of starch during heating (Jarvis & Duncan,

Fig. 3. Representative SEM images of potato varieties Agata, Musica and Lady Rosetta (100 μm length scale bar) after: a) baking; b) boiling; c) frying.

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1992; Kim et al., 1997). In turn, the removal of moisture during thermalprocessing of potato products has evident effects on the physical attri-butes, which can be measured by textural properties of the material(Troncoso et al., 2009). To better understand the structural changesoccurring during the different processes, moisture content and texturalproperties of our potatoes were analyzed. Raw tuber moisture contentranged from 76% in Musica and Innovator to 85% in Lady Rosetta(Table 3). Following boiling, an increase of moisture content occurred.

Compared to raw potatoes, the highest increase was observed in firmvarieties Agata and Spunta, the lowest in mealy variety Lady Rosetta.By contrast, after baking and frying, moisture content decreased. Infact, these processes are very complex unit operations leading to nu-merous changes, such as transition and evaporation of water. Theamount of moisture evaporation was more evident after baking, whenthe highest decrease in moisture content with respect to raw potatoeswas observed in Lady Rosetta (from 84.7% to 67.8%). After frying, thehighest decrease in moisture content was found in Agria (from 81.4% to73.2%).

The Young's modulus (elasticity modulus), which corresponded tothe initial linear region of the strain vs. Henky's deformation curve ofthe samples (Supplemental Fig. 2), was measured as a texture descriptor(Fig. 4). As expected, raw potatoes showed the highest rigidity, whilecooked samples showed reduced Young's modulus. The influence ofvarieties on Young's modulus could be partly explained by differencesin starch granule size or composition (moisture, DM and amylosecontent), as reported by Singh et al. (2005), who studied the cookingand textural characteristics of tubers from different potato cultivarsusing Instron universal testing machine. They found that potatoes tu-bers with lower amylose content, lightly packed cell arrangement andcomparatively larger cells showed lower hardness, cohesiveness andlonger cooking time. Our data also indicated that in general bakedpotatoes had the least decrease in rigidity and the lowest moisturecontent (Table 3), with Lady Rosetta showing the highest value ofYoung's modulus (224.3 kPa). By contrast, fried samples had thesmallest value, as evident in Agria and Spunta, (56.3 and 61 kPa, re-spectively). The main textural changes occurring during potato fryinginclude softening of the lamella between cells, starch gelatinization anddehydration (Bouchon & Aguilera, 2001). Our thermal (Table 2) andmicrostructural results (Fig. 3c) confirmed these events. Indeed, aruptured structure was evident for all fried potatoes. It is well knownthat the degree of cell rupturing and gelatinization influences the tex-ture or consistency of cooked potatoes and their products (Troncosoet al., 2009). Within each cooking process, the elasticity modulus wassignificantly different (p < .05) between varieties. Additionally, whenwe analyzed the effect of the cooking process via the variance of thestress at fracture, there were significant differences both between thedifferent treatments and varieties (p < .05), as shown in Table 3. Inconclusion, the changes in firmness were directly affected by the pro-cess of cooking and by the variety.

3.5. Principle component cluster analyses

Principle component analysis (PCA) was used to summarize therelationship between the properties of the potato cultivars that weretested before and after cooking with the different heat treatments. Inparticular, we analyzed the cumulative correlation of eight variables

Table 3Moisture content (%) and mechanical properties of raw, boiled, baked and fried potato varieties, expressed as means ± S.D.

Sample Parameter Variety

Agata Agria Innovator Lady Rosetta Musica Spunta

Moisture content (%)Raw 82,11c ± 0,13× 81,40c ± 0,42× 76,10c ± 0,71z 84,67c ± 0,83w 75,63b ± 1,30z 79,64c ± 0,79y

Boiled 88,60d ± 0,25w 84,90d ± 0,22× 81,14d ± 0,02y 85,37c ± 0,25× 79,41c ± 0,14z 85,86d ± 0,26×

Baked 68,73a ± 0,89y 70,47a ± 1,24× 66,62a ± 0,18z 67,79a ± 0,48z,y 68,83a ± 0,88y 69,3a ± 0,96y,x

Fried 74,55b ± 0,86w 73,25b ± 0,40× 71,00b ± 0,67y 75,19b ± 0,27w 68,82a ± 0,27z 76,64b ± 1,01v

Stress at fracture (kPa)Raw 1303.8d ± 101.2× 1233.0c ± 37.4× 1263.9c ± 47.2× 1194.8c ± 109.6× 984.7d ± 21.6y 772.3d ± 19.5z

Boiled 29.58a ± 1.0z 87.84b ± 5.1u 55.00a ± 0.4w 38.39a ± 2.2y 48.37a ± 4.8× 78.15b ± 0.3v

Baked 76.24c ± 2.4× 70.54a ± 1.4y 97.31b ± 3.3w 55.23b ± 2.9z 101.25c ± 1.9v 98.14c ± 1.4w,v

Fried 61.24b ± 2.4y 66.83a ± 1.2y 103.57b ± 0.8w 53.58b ± 1.1z 74.14b ± 8.2× 60.41a ± 1.5y

(a–d) For each parameter, different subscripts letters within a column indicate significant differences (p < .05) between processes.(z–u) Different superscripts letters within a row indicate significant differences (p < .05) between varieties.

Table 4Detected variety-specific alleles for the 22 SSR loci analyzed.

Varieties Locus (Alleles)

Agata STG10 (173); STI1 (200); STI30 (91).Agria STG10 (181); STM1053 (120); STM19 (211); STM5114 (286).Innovator STI14 (136, 145); STI3 (172); STM1053 (132); STM1104 (166);

STM19 (216); STM5114 (297); STM1064 (208).Lady Rosetta STG1 (145); STI33 (138); STM19 (182, 214); STM31 (175).Musica STI30 (86); STM1052 (89); STPoAc58(265).Spunta STG1(187); STI1 (207); STI12(191); STI33 (142); STI4 (110);

STM5127 (274).

1

10

100

1000

Lady Rosetta Innovator Agata Musica Spunta Agria

)aPk(suludo

ms'gnuoY

Variety

Raw Baking Boiling Frying

Fig. 4. The Young's modulus of raw, baking, boiling, frying of potato varietiesAgata, Agria, Innovator, Lady Rosetta, Musica and Spunta.

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related to the thermochemical properties (i.e. moisture content, To, Tp,Te and ΔΗ) and additional five related to the microstructural char-acteristic of starch and starch granule (i.e. starch granule roundness anddiameter; total starch content and dry matter) in order to identifyvectors yielding the greatest separation between samples. The resultsfrom the chosen vectors were then displayed in two dimensions (Fig. 5).The first two Principal Components (PC) accounted, respectively, for60.3% and 16.8% of the total variation in the dataset (Fig. 5). The sixvarieties were distributed in the all space defined by PCs, with In-novator and Lady Rosetta contributing more than the others in ac-counting for the variability of the two components (SupplementalFig. 3). This result is in accordance with the fact that these two varietiesbelong to a different cooking type group as compared to the others. Asuperimposition of score (Fig. 5) and loading plots (Fig. 5) was carriedout to distinguish those variables exerting the largest influence onsample distribution. Interestingly, all the parameters relative to starchgranules (diameter, area, roundness), along with DM and TS, exertedthe main influence on the separation of Innovator and Lady Rosettawith respect to the other varieties. We also used the K-nearest neighboranalysis (KNN) as a classification statistics to identify the best

discriminant variables. The result showed in Supplemental Fig. 4.confirmed that Innovator and Lady Rosetta were the most distantvarieties, especially for Total Starch (TS), Dry matter (DM) and onsetTemperature (T0).

3.6. Molecular marker analysis

To study whether all the phenotypic differences found here may beassociated to molecular variability, we analyzed the genetic diversity ofour varieties through molecular markers. A series of DNA markers as-sociated with increased or decreased total starch yield in potato havebeen identified previously by Schönhals et al. (2016). In our study, weevaluated the genetic diversity using 22 SSR markers. These markerswere previously proposed as reference for standardizing potato germ-plasm analyses across laboratories. Further, three of these SSRs arelocated in candidate genes for starch biosynthesis: STM1104 in granulebound starch synthase I (GBSSI, chromosome VIII), STM1052 in thetandem duplicated apoplastic invertase genes InvGE and InvGF (chro-mosome IX) and STM1106 in the apoplastic invertase gene InvCD141(chromosome X) (Milbourne et al., 1998; Schönhals et al., 2016). Intotal, 116 alleles were identified. On average, the number of alleles permarker was relatively high, varying from 2 (primer pairs STG25 andSTM5121) to 10 (primer pairs STM1053) (Supplemental Table 1). Thissuggests that the genetic base of the material studied here is ratherwide. Out of 22 loci, 18 were useful to identify variety-specific alleles(Table 4). These can be used as diagnostic markers for our varietieswith possible applications in breeding efforts and varietal authentica-tion (Govindaraj, Vetriventhan, & Srinivasan, 2015). The highestnumber of specific alleles (eight) was detected in Innovator (two atlocus STI14, and one at each of the STI3, STM1053, STM1104, STM19,STM5114 and STM1064). This variety also formed a unique and sepa-rated cluster in the SSR-derived UPGMA dendgrogram (Fig. 6). Theother varieties formed a bigger cluster in which two sub-clusters wereidentified, one composed by Spunta and Lady Rosetta and the other byAgata, Musica and Agria. No particular relation between SSR classifi-cation and the one drawn using the chemical – thermal characteristics(reported in the PCA diagram) was observed within this latter cluster.Probably SSR loci used, with the exception of STM1104, STM1052 andSTM1106, measured a different aspect of genetic diversity. Noteworthyis the genetic distance of Innovator compared to the other varieties ofthis work and those previously analyzed in Romano et al. (2018). In-novator genetic distance was in line with its high values of starchgranule roundness and diameter, TS and DM. Further, Innovator holds a

Fig. 5. Principal component analysis (PCA) on six potato varieties using 19variables. In the score and loading plots, samples and variables are plotted inthe space defined by the PCs, respectively.

Fig. 6. Tree diagram showing the genetic relationships among the potatovarieties used in this study. The genetic distance between varieties was esti-mated using DNA polymorphism from 22 SSR markers. The tree diagram wasconstructed through the UPGMA clustering method. The genetic distance on thex-axis is based on the Dice's coefficient.

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specific allele (166 bp) at STM1104 locus. This locus has been identifiedas diagnostic for starch content in potato. Indeed, STM1104 is part ofthe GBSSI encoding locus that controls starch biosynthesis and com-position in potato (Muth et al., 2008; Schönhals et al., 2016). Thepresence in Innovator of a high number of specific alleles distributed onsix loci may be the base for future studies aimed at developing diag-nostic molecular makers associated also to starch granule structure.This is an interesting trait for food technological processes and tubernutritional value. In this regard, we will focus on the association ofalleles at ST1104 locus with starch granule morphology.

4. Conclusions

The effects of cooking processes on the microstructure and proper-ties of potato varieties were investigated. We believe that four mainpoints emerged from this study. First, although starch characteristicsvaried from variety to variety, all raw samples had a percentage ofmedium granules higher than 50%. Mealy-cooking varieties, Innovatorand Lady Rosetta, had the highest percentage (about 40%) of large(> 1250 μm2) granules. Second, the chemical and thermal tuberproperties varied considerably with the variety. Tubers showed a singleendothermic transition corresponding mainly to the gelatinizationtransition of the starch, with thermal parameters significantly different,indicating that they may be suitable for diverse food applications.Third, the changes in firmness were directly affected by the process ofcooking and the variety. The elastic modulus (Young's modulus) fol-lowed the order: raw > baking > boiling > frying. In particular, thehighest Young's modulus was recorded for Lady Rosetta. Fourth, thegenetic fingerprinting through SSR markers provided a set of allelesable to discriminate our varieties and located in candidate genes forstarch biosynthesis.

All together, these results may help to better address the commercialuse of specific varieties and to optimize processing performances. Theymay also help in the choice of suitable parents in breeding programsaimed at developing potato varieties belonging to specific cooking ca-tegories.

Supplementary data to this article can be found online at https://doi.org/10.1016/j.foodres.2018.07.033.

Conflict of interest

The authors have declared no conflict of interest.

Acknowledgments

Thanks to F. Carucci for molecular analysis, R. Garramone and G.Coppola for technical help. This work was supported by the Ministry ofUniversity and Research (GenHORT Project: PON02_00395_3215002).

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