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Classification of the Quality of Agarwood Oils from Malaysia using Z-Score Technique

Nurlaila Ismail, Mohd Hezri Fazalul Rahiman, Mohd Nasir Taib

Faculty of Electrical Engineering UiTM Shah Alam, Selangor, Malaysia [email protected], [email protected],

[email protected], [email protected]

Nor Azah Mohd Ali, Mailina Jamil Forest Research Institute Malaysia

52109, Selangor, Malaysia [email protected]

Saiful Nizam Tajuddin Faculty of Industry, Science and Technology,

University Malaysia Pahang, Malaysia [email protected]

Abstract—This paper presents classification of the quality of agarwood oils from Malaysia using Z-score technique. Six agarwood oil samples named as MU, MUS, MN, MNS, R5 and HD are analyzed by GC-MS to examine their chemical profiles. The extraction showed that at least forty three volatile compounds are found. The Z-score technique is proposed to identify the significant chemical compounds of the agarwood oils. It is found that six chemical compounds are recognized. They are β-agarofuran, α-agarofuran, 10-epi-�-eudesmol, α-eudesmol, dihydrocollumellarin and �-eudesmol. These volatile compounds have different abundances pattern responsible to the different qualities of agarwood oil such as high and low. The Z-score applied in this study give a promising result in discriminating agarwood oil to high and low quality. It is important and useful in solving the grading agarwood oil system which is currently done manually.

Keywords-chemical compounds, agarwood oil, Z-score, high and low qualities.

I. INTRODUCTION In recent years, there has been a dramatic increase in

agarwood oil usage in Malaysia whereby the extraction has become popular and widely applied [1-3]. It is shown by the increasing number of agarwood plantation in this country and the market demand of its oil from all over the world [2, 3]. Agarwood oil is concentrated volatile aromatic compounds produced by agarwood plant, extracted from the stem. Many researchers have highlighted that agarwood oil is produced as incense, perfumery and for traditional medicines [4-7].

The agarwood oil is traded worldwide and getting high market demand especially from United Arab Emirates, Saudi Arabia, China and Japan. The agarwood oils are traded differently depending on its grade. The demand of agarwood oil is high in the Middle East, where the oil symbolizes the society ranking, wealthiness and hospitality. The agarwood oil (especially black colour) is an important ingredient in the perfumery industry and it is be used to generate aroma in wedding ceremonies or banquets [3].

Many researchers had studied the differences of chemical composition in agarwood oil [6-16]. Most of them agreed that sesquiterpenes components and its chromone derivative were the major compounds in agarwood oil [6-8, 12, 14-16]. It was determinant to the high and low quality of agarwood oil [8, 16]. Different species of the sourcing plants is one of

the reasons that determine high and low quality of agarwood oil [16].

The implementation of data transformation is really important in several analysis such as neural networks, nearest neighbors and clustering classifiers. In neural network application, the learning phase in backpropagation algorithm are speed up by implementing data transformation [17]. There are many ways used by researchers for data transformation i.e. data mining such as min-max normalization, Z-score normalization and decimal scaling normalization [17, 18]. These methods are useful in improving the efficiency and accuracy of the mining algorithm [17]. The normalized data is scaled to a specified range such as 0,0 to 1.0 [17].

The min-max normalization uses the minimum and the maximum values in order to change the original data to it necessary normalized value. The Z-score as one of data transformation utilizes the mean and standard deviation of individual parameters.

The Z-score is a technique ‘to compare an individual to the normative database and standard deviations’ [19]. The first concept of this technique is introduced by Matousek and Petersen by computing means and standard deviations in a year age groups [20]. The Z-score is preferred to classify/ cluster the data, to standardize the information and to categorize the data into specific group [21, 22]. Not limited to that, zscore as one of the scaling methods was used to index the Intelligent Quotient (IQ) level into several groups using correlation between IQ scores and Electroencephalogram (EEG) power spectrum density (PSD) [23]. Z-score was found useful for relevance score in metasearch study [24].

Application of z-score in pattern recognition showed good performance in multimodal biometric systems recognition [24]. It is found that the technique has advantages such as sensitive to the data outliers, robust and efficient for the normalization procedure [24]. A research showed that Z-score is capable in modelling and successful in predicting the financial distress of companies in year 2000 [25]. The developed model is robust and sufficient to accommodate to the large firms [25].

In this study, the chemical compounds of selected agarwood oil from Malaysia are analysed by GC-MS technique. The Z-score is proposed to identify the significant

2013 IEEE 3rd International Conference on System Engineering and Technology, 19 - 20 Aug. 2013, Shah Alam, Malaysia

978-1-4799-1030-4/13/$31.00 ©2013 IEEE 78

chemical compounds of the agarwood oils. Then, the result is followed by the abundances pattern of the significant compounds for the all samples in classifying them to the high and low quality. The findings are shown and discussed before the conclusion is made.

II. METHODOLOGY

A. Data preparation Six samples of agarwood oils from Malaysia coded as

MU, MUS, MN, MNS, R5 and HD are collected at Forest Research Institute Malaysia (FRIM), Kepong, Selangor. The agarwood oils are extracted by GC-MS for their chemical compounds analysis. The standard operation procedure (SOP) for the GC-MS extraction is performed as recommended by NorAzah et. al. [12]. The chemical compounds are identified by matching them to the mass spectral library (HPCH2205.L; Wiley7Nist05a.L; NIST05a.L) and their compositions are presented in terms of abundances (%).

B. The Z-score technique The objective of the Z-score technique in this study is to

identify the significant chemical compounds of agarwood oils based on GC-MS data. The calculation of Z-score is done automatically via Matlab software version R2010a by applying the formulae given by Eqn. (1) [24]

(1)

where is an individual value, is mean of population

and is standard deviation of population.

III. RESULT AND DISCUSSION Table 1 tabulates the compositions of chemical

compounds of the selected agarwood oils from Malaysia. There are at least forty three compounds are extracted by GC-MS. These compounds show that the agarwood oil is a complex mixture of sesquiterpenes and its chromone derivatives. From the result it can seen that two chemical compounds exist in all samples. They are α-muurolene and �-eudesmol. The abundances of α-muurolene are 2.80%, 2.85%, 1.75%, 2.14%, 0.25% and 0.11% in MU, MUS, MN, MNS, R5 and HD, respectively. Meanwhile the abundances of �-eudesmol are 13.80%, 8.87%, 8.03%, 12.36%, 3.24% and 1.45% in MU, MUS, MN, MNS, R5 and HD, respectively. Between both compounds, �-eudesmol has the highest abundances with the value of 13.80%.

TABLE I. VOLATILE COMPOUNDS COMPOSITION (%) OF THE AGARWOOD OILS

Fig. 1 shows the abundances patterns for the chemical

compounds of the selected agarwood oils from Malaysia. By quick inspection, it is observed that there are five high peaks of abundances which belong to compound no. 16 i.e. �-cadinene, compound no. 20 i.e. selina-3, 7(11)-diene, compound no. 29 i.e. �-eudesmol, compound no. 36 i.e. α-eudesmol and compound no. 40 i.e. 14-hydroxy- α-muurolene. Among these peaks, α-eudesmol has the highest abundances with 18.57% in MNS oil and α-guaiene shows the lowest abundances in MUS oil with the value of 0.17%. The 0.00% of abundances indicates that the chemical compound is not detected in the agarwood oil.


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Fig. 1The chemical compounds and its abundances pattern of the selected

agarwood oils from Malaysia

Table II depicts the significant volatile compounds as

identified by Z-score technique in the agarwood oils. It is found that six significant compounds are recognized. They are β-agarofuran, α-agarofuran, 10-epi-�-eudesmol, α-eudesmol, dihydrocollumellarin and �-eudesmol. β-agarofuran and α-agarofuran are not detected in MU, MUS

and MN. β-agarofuran is found in MNS and HD oils with the abundances of 2.21% and 0.43% while α-agarofuran exists in MNS, R5 and HD with the percentages of 1.42%, 0.25% and 0.64%, respectively. 10-epi-�-eudesmol is identified in all agarwood oils except not in R5 oil. α-eudesmol has the abundances of 15.02%, 13.44% and 18.57% in MUS, MN and MNS, respectively. The chemical compound i.e. dihydrocollumellarin is detected in MU, MUS, MN and MNS with the abundances value of 4.52%, 3.47%, 5.41% and 4.16%, accordingly. Among these compounds, �-eudesmol does appear in all samples. The abundances for this compounds is 13.80%, 8.87%, 8.03%, 12.36%, 3.24% and 1.45% in MU, MUS, MN, MNS, R5 and HD, respectively. This finding is supported by the graphical observation in the abundances pattern in Fig. 1, where �-eudesmol is noted to have the highest abundances. This compound also is similar to the major/common compound exists in all samples as mentioned in Table I.

TABLE II. THE SIGNIFICANT VOLATILE COMPOUNDS AS IDENTIFIED BY Z-SCORE

Fig. 2 presents the abundances pattern of six significant volatile compounds as identified by Z-score. Graphically, two patterns of abundances are shown. The first pattern gives consistent type for three samples of agarwood oils such as MUS, MN and MNS. The second pattern other abundances pattern for MU, R5 and HD agarwood oils. It is observed that compound no. 4 i.e. α-eudesmol responsible to discriminate all samples to two groups. The first group has abundances value for α-eudesmol and the second one have none abundances or in other word, this compound does not exist i.e. in MU, R5 and HD. Based on review in literature domain, the agarwood oil with high abundances in their chemical compound is class as high quality agarwood oil [26]. Due to this, MUS, MN and MNS are categorized as high quality and MU, R5 and HD oils as low quality. Therefore, the finding from this study revealed that MUS, MN and MNS samples are belong to the high quality agarwood oil and MU oil is low quality of agarwood oil. The finding from this study shows that there is various kinds of the sourcing agarwood oils and become as one of the reasons that discriminate them to high and low quality [16].


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Fig. 2 The abundances pattern of the six significant chemical compounds identified by Z-score

IV. CONCLUSION This paper presents the application of Z-score in

identifying the significant chemical compounds of agarwood oils from Malaysia, then classifies them to two qualities of oils such as high and low. The significant chemical compounds recognized are β-agarofuran, α-agarofuran, 10-epi-�-eudesmol, α-eudesmol, dihydrocollumellarin and �-eudesmol. Their abundances pattern is beneficial for future analysis of agarwood oil grading system such as ANN and k-NN. Not limited to that, it also provide solution to the manual grading agarwood oil system with its advantages such as easy, simple, robust and automatic.

ACKNOWLEDGEMENT The data used in this study is collected at Forest Research

Institute Malaysia (FRIM). The authors would like thank all staff involved and Advanced Signal Processing (ASP) Research Group members, Faculty of Electrical Engineering, UiTM Shah Alam and excellent fund from UiTM coded 600-RMI/DANA/ 5/3/RIF 614/2012 awarded to Mohd Nasir Taib

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