palm oil analysis in adulterated sesame oil using chromatography and ftir spectroscopy

Research Article

Palm oil analysis in adulterated sesame oil usingchromatography and FTIR spectroscopy

Abdul Rohman1,2 and Yaakob B. Che Man1

1 Halal Products Research Institute, Universiti Putra Malaysia, Serdang, Selangor, Malaysia2 Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Gadjah Mada University, Yogyakarta,

Indonesia

This study highlights the application of two analytical techniques, namely GC-FID and FTIR

spectroscopy, for analysis of refined-bleached-deodorized palm oil (RBD-PO) in adulterated sesame

oil (SeO). UsingGC-FID, the profiles of fatty acids were used for the evaluation of SeO adulteration. The

increased concentrations of palmitic and oleic acids together with the decreased levels of stearic, linoleic,

and linolenic acids with the increasing contents of RBD-PO in SeO can be used for monitoring the

presence of RBD-PO in SeO. Meanwhile, FTIR spectroscopy combined with multivariate calibration of

partial least square (PLS) has been successfully developed for the detection and quantification of RBD-

PO in SeO using the combined frequencies of 3040–2995, 1660–1654, and 1150–1050 cm�1. The

values of coefficient of determination (R2) for the relationship between actual versus FTIR-calculated

values of RBD-PO in SeO and root mean square error of calibration (RMSEC) obtained are 0.997 and

1.32% v/v, respectively. In addition, using three factors, the root mean square error of prediction

(RMSEP) value obtained using the developed PLS calibration model is relatively low, i.e., 1.83% v/v.

Practical Application: The adulteration practice is commonly encountered in fats and oils industry. It

involves the replacement of high value edible oils such as sesame oil with the lower ones like palm oil. Gas

chromatography and FTIR spectroscopy can be used as reliable and accurate analytical techniques for

detection and quantification of palm oil in sesame oil.

Keywords: Adulteration / FTIR spectroscopy / Gas chromatography / RBD-palm oil / Sesame oil

Received: June 1, 2010 / Revised: October 25, 2010 / Accepted: December 5, 2010

DOI: 10.1002/ejlt.201000369

1 Introduction

The authenticity of high value edible oil from some oil adul-

terants is of paramount importance due to the legal conform-

ity and religious aspect (especially halal and kosher) [1]. The

adulteration of high price oils with cheaper oils is motivated

by economic reasons in order to get the maximum profits.

Even though the adulteration action does not cause the health

problems, the primary consumer rights are violated by the

fraudulent practices [2].

Sesame oil (SeO) contains a large number of active com-

pounds having the beneficial health effects like antioxidant

and cardio-protective activities [3]. Besides, SeO has a pleas-

ant taste and specific odor. Compared with other types of

vegetable oils such as corn and palm oils, SeO is more

expensive by 5–10 times. Consequently, SeO may be adul-

terated with cheaper vegetable oils like soybean, corn, canola,

and palm oils [4, 5]. Therefore, the detection and quantifi-

cation of oil adulterants in SeO are highly demanded.

Several researchers have developed various methods to

detect the adulteration action resulting from the blending of

SeO with other vegetable oils. Such methods are GC for the

determination of fatty acid and carbon isotope ratio [4], HPLC

for analysis of triglycerides [6, 7], and electronic nose [5, 8].

*Additional corresponding author: A. Rohman

E-mail: [email protected]

Correspondence: Prof. Dr. Y. B. Che Man, Halal Products Research

Institute, Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor,

Malaysia

E-mail: [email protected]

Fax: þ03-89439745

Abbreviations: PLS, partial least square; RBD-PO, refined-bleached-

deodorized palm oil; RMSEC, root mean square error of calibration;

RMSEP, root mean square error of prediction; SeO, sesame oil; GC-FID,

gas chromatography-flame ionizationdetector;FTIR, Fourier transform infrared

522 Eur. J. Lipid Sci. Technol. 2011, 113, 522–527

� 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim www.ejlst.com

However, there is no report related to the use of FTIR spec-

troscopy in conjugationwithGC for analysis of palmoil in SeO.

FTIR spectroscopy has been widely used in food research

and has become a powerful analytical tool in the study of

edible fats and oils, especially for qualitative identification of

specific components in food [9]. FTIR combined with che-

mometrics is also a promising analytical technique for the

determination of components because the peak absorbances

of FTIR spectra are directly proportional to its concentration

according to the Beer’s law [10]. We have developed FTIR

spectroscopy combined with multivariate calibration and

discriminant analysis for the authentication of high edible

oils, namely cod liver oil [11], virgin coconut oil [12], and

extra virgin olive oil [13]. Meanwhile, GC was shown to be

useful technique for monitoring the changes of fatty acid

profiles in the adulterated oils [14]. The objective of this

study was to analyze the adulteration of SeO with refined-

bleached-deodorized palm oil (RBD-PO) using two analyti-

cal methods (GC and FTIR spectroscopy).

2 Materials and methods

2.1 Materials

Sesame oil (SeO) and RBD-PO were bought from the local

market in Serdang, Selangor, Malaysia. The oil samples were

packaged in polyethylene terephthalate (PET) bottles and the

dates of manufacturing were unidentified. Before being used

for analysis, all samples were stored in the dark and no any

treatments were subjected to them in order to keep their

compositions. Standards of fatty acid methyl ester

(FAME) were obtained from Sigma Chemicals (St. Louis,

MO, USA). All solvents used were of analytical grade.

2.2 The preparation of oil mixtures for GC analysis

SeO was blended with RBD-PO in the range of 5–60%RBD-

PO in SeO, namely 5, 10, 15, 20, 30, 40, 50, and 60% RBD-

PO in SeO v/v. These mixtures were kept in controlled RT

(208C) before and during authentication studies.

2.3 Determination of fatty acid compositions

The fatty acid composition of the authentic and mixtures of

RBD-PO and SeO was determined using GC-FID according

to Nor Hayati et al. [15]. In centrifuge tube, 100 mg oils was

accurately weighted in analytical balance (sensitivity of

0.1 mg) and added with 1.2 mLhexane and 0.25 mL sodium

methoxide 2 M in anhydrous methanol. The mixture was

vigorously mixed using a vortex at 2200 rpm for 60 s. In

order to separate sodium glycerolate, the mixture was sub-

sequently added with 0.5 mL saturated sodium chloride and

mixed using a vortex for 15 s. After that, 1 mL of the clear

supernatant was injected into an RTX capillary column

(0.25 mm internal diameter, 30 m length, and 0.2 mm film

thickness; Restex Corp., Bellefonte, PA, USA) and analyzed

using a gas chromatograph (Shimadzu GC-2010, Shimadzu

Corp., Tokyo, Japan), equipped with FID. The oven

temperature was programmed as follows: the initial tempera-

ture was 1008C (hold for 1 min), then ramped into 1808C(88C/min), increased from 180 to 2408C (108C/min), and

finally hold at 2408C for 5 min. The temperatures of detector

and injector were maintained at 2408C during the analysis.

The flow rate of carrier gas (helium) was 6.8 mL/min. The

FAME standards were used to identify the retention time of

samples. Quantification of fatty acid (percentage of fatty

acids) was calculated based on its peak area using internal

normalization technique.

Percentage ð%Þ fatty acid x

¼ Peak area of fatty acid x

Total peak area of all fatty acids� 100

2.4 Analysis using FTIR spectroscopy

RBD-PO in SeO was analyzed with the aid of multivariate

calibration of partial least square (PLS). In order to make

PLS calibration model, a-27 dataset of RBD-PO in SeO was

blended in the concentration range of 0–75% v/v. For pre-

diction, 20 independent samples were prepared. All oil

samples are scanned using FTIR spectrometer using the

conditions, as follows:

These spectra were subtracted against reference spectra

(air spectrum), acquired by collecting a spectrum from the

cleaned blank crystal before the measurement of each sample

replication. The sample spectra were done in triplicate and

displayed as the average spectra. At the end of every scan, the

surface of HATR crystal was cleaned with hexane twice and

dried with soft tissue, cleaned with acetone, and finally dried

with soft tissue following collection of each spectrum. The

spectral regions where the variations between RBD-PO and

SeO were observed were chosen for making PLS model. PLS

model correlates between FTIR absorbances of adulterant

(RBD-PO) with its percentage in SeO. The performance of

PLS calibration model was evaluated by computing the

FTIR spectrometer A Nicolet 6700 (Thermo Nicolet Corp.,

Madison, WI)

Detector Deuterated triglycine sulfate (DTGS)

Beam splitter KBr/Germanium

Software the OMNIC (Version 7.0 Thermo Nicolet)

Sampling technique Horizontal attenuated total reflectance

(HATR) using Smart ARK accessory

Scanning 32 scan

Resolution 4 cm�1

Measured regions 4000–650 cm�1

Temperature Controlled ambient temperature (208C)

Eur. J. Lipid Sci. Technol. 2011, 113, 522–527 Authentication of high value edible oils 523


coefficient of determination (R2) for the correlation between

actual and FTIR-calculated values of RBD-PO in SeO and

root mean square error of calibration (RMSEC). The PLS

calibrationmodel was further used to predict the independent

samples and the values of R2 and root mean square error of

prediction (RMSEP) were used as validity criteria for the

prediction power [16].

3 Statistical analysis

Fatty acid profiles were subjected to one-way ANOVA and

followed with Duncan multiple comparison using SPSS ver-

sion 17.0 software (SPSS Inc.,Chicago, USA). The signifi-

cance value (p) less than 0.05 was statistically different.

Multivariate calibration was performed using the software

TQ AnalystTM version 6 (Thermo electron Corporation,

Madison, WI, USA) included in FTIR spectrometer.

4 Results and discussion

4.1 Analysis of RBD-PO in SeO using gaschromatography

Determination of fatty acid profiles seems to be very useful

technique for controlling the authenticity of high value veg-

etable oils like SeO [14]. In order to ensure that the used SeO

and RBD-PO have not been already mixed yet with other fats

and oils, their fatty acid compositions were used as purity

criteria. Table 1 showed that the fatty acid profiles of SeO and

RBD-PO were in agreement with those compiled in Codex

Alimentarius ranges [17]. The main fatty acids in RBD-PO

are palmitic (C16:0) and oleic (C18:1); meanwhile, oleic and

linoleic (C18:2) acids are major fatty acids composed SeO, as

shown in Table 1. This difference can be used to analyze SeO

adulterated with RBD-PO.

RBD-PO was added to SeO up to final concentrations of

5, 10, 15, 20, 30, 40, 50, and 60% v/v and its fatty acid

composition in these mixtures is shown in Table 2. The

concentrations of palmitic and oleic acids increased linearly

with the increasing amount of RBD-PO with R2 of 0.973 and

0.952, respectively. Meanwhile, the levels of stearic (C18:0),

linoleic, and linolenic (C18:3) were decreased with R2 of

0.981, 0.966, and 0.931, respectively, with the increasing

contents of RBD-PO (Fig. 1). Using GC-FID, it is possible

to detect the presence of RBD-PO in SeO as low as 1% v/v.

Some much cheaper vegetable oils than SeO such as corn,

soybean, and sunflower oils have the similar content of oleic

and linoleic acids; therefore, the presence of these oils makes

difficulty in SeO authentication. Therefore, the additional

method offering good analytical specificity is needed in order

to analyze the adulteration of SeO with RBD-PO.

4.2 Quantification of RBD-PO in SeO using FTIRspectroscopy

FTIR spectroscopy is a ‘‘fingerprint’’ technique; therefore,

this technique is potential tool to be used in the authentica-

tion studies. Figure 2 represents FTIR spectra of authentic

sesame and RBD-palm oils at mid IR regions of 4000–

650 cm�1. Each peak corresponds to functional groups

responsible for IR absorption; meanwhile the intensities of

each peak were correlated with the concentration of func-

tional groups present in analytes (RBD-PO). FTIR spec-

troscopy can be considered as one of the ‘‘fingerprint

analytical techniques’’ due to its capability to differentiate

FTIR spectra among edible fats and oils. Taking the differ-

ence of FTIR spectra in Fig. 2, it can be deduced that RBD-

PO can be differentiated from SeO at peaks in frequency

regions of 3007 (attributed from the stretching vibration of cis

vinilyc), 2852 (stretching vibration of CH2), 1654 (cisC––C),

as well as at 1117 and 1098 cm�1 which are corresponding to

C–O vibration [18]. The peak intensities in these regions are

different. For this reason, these frequencies were used for

quantification of RBD-PO in SeO.

The quantitative analysis of RBD-PO as adulterant in

SeO was carried out using multivariate calibration of PLS

Table 1. The fatty acid compositions of sesame oil and RBD-palm oil.

Fatty acida) RBD-palm oil Sesame oil Standard Codex Alimentarius [17]

Palm oil Sesame oil

C14:0 0.97 � 0.01 0.02 � 0.00 0.5–2.0 nd–0.1

C16:0 37.42 � 0.06 10.00 � 0.07 39.3–47.5 7.9–12

C16:1 0.19 � 0.00 0.14 � 0.00 nd–0.6 0.1–0.12

C18:0 4.79 � 0.24 7.27 � 1.09 3.5–6.0 4.8–6.1

C18:1 43.37 � 0.02 33.69 � 0.12 36.0–44.0 35.9–42.3

C18:2 11.75 � 0.04 46.95 � 0.16 9.0–12.0 41.5–47.9

C20:0 0.22 � 0.00 0.36 � 0.00 nd–1.0 0.3–0.6

C18:3 0.37 � 0.02 0.64 � 0.01 nd–0.5 0.3–0.4

C20:1 0.15 � 0.01 0.15 � 0.00 nd–0.4 0.1–0.5

C22:0 0.05 � 0.01 0.14 � 0.01 nd–0.2 nd–0.4

a) Each value in the table represents the means of triplicate analysis; SD is given after �.

524 A. Rohman and Y. B. Che Man Eur. J. Lipid Sci. Technol. 2011, 113, 522–527


algorithm. The adulterant of RBD-POwas separated into the

calibration and the prediction sets. The division into both sets

was done in order to obtain the similar mean values and SD

so that both sets spanned the full range of the studied RBD-

PO and SeO [19]. In the PLS model, evaluation of the

method linearity was performed in order to show the pro-

portional relationship between responses (absorbances) ver-

sus analyte concentrations of RBD-PO.

Using the optimization process, the combined frequency

regions of 3040–2995, 1660–1654, and 1150–1050 cm�1

were selected for quantification of RBD-PO in SeO due to

its ability to offer the highest values of R2 and the lowest

values of RMSEC. Figure 3 reveals the scatter plot for the

relationship between actual (x-axis) and FTIR-calculated

values (y-axis) of RBD-PO in PLS calibration model at

the optimized frequency regions with R2 and RMSEC values

of 0.997 and 1.32% v/v, respectively. The equation model

used for such relationship is: y ¼ 0.994x þ 0.123.

One of the main problems in PLS algorithm is over-

fitting, meaning that PLS model produces good model in

the calibration dataset, but the model will not perform well in

prediction/validation datasets using the similar samples. In

order to evaluate the over-fitting, a procedure of cross vali-

dation using leave-one-out technique was used [20]. In this

technique, one of the calibration samples is taken out from

the PLS calibration model and the residual samples are used

to build the PLSmodel. Subsequently, the removed sample is

calculated using the new PLS regression. This manner was

recurred, leaving each sample out in turn. The difference

between actual and calculated values of RBD-PO is com-

puted [20]. The number of factors used to build PLS model

was based on the minimum predicted residual error of sum of

squares (PRESS) values obtained. Three (3) factors were

enough to be used in PLS calibration model. The root mean

square error of cross validation (RMSECV) obtained during

the cross validation is 1.84. The performance of PLS cali-

Table 2. Fatty acid composition of sesame oil adulterated with RBD-palm oil.

FAa) Ratio (RBD-PO:SeO)

(0%:100%) (5%:95%) (10%:90%) (15%:85%) (20%:80%) (30%:70%) (40%:60%) (50%:50%) (60%:40%) (100%:0%)

C14:0 0.02 � 0.00a 0.12 � 0.01b 0.17 � 0.01bc 0.20 � 0.02cd 0.22 � 0.05cd 0.23 � 0.01d 0.43 � 0.01e 0.45 � 0.02e 0.56 � 0.06f 0.97 � 0.01g

C16:0 10.00 � 0.07a 12.48 � 0.12b 13.94 � 0.24c 14.83 � 0.50cd 15.51 � 0.47de 16.29 � 0.29e 21.55 � 0.73f 22.12 � 0.58f 23.38 � 1.08g 37.42 � 0.06h

C16:1 0.14 � 0.00a 0.14 � 0.00a 0.15 � 0.00ab 0.15 � 0.00ab 0.15 � 0.00ab 0.15 � 0.00ab 0.16 � 0.00bc 0.16 � 0.00bc 0.17 � 0.01c 0.19 � 0.00d

C18:0 7.27 � 1.09a 6.92 � 0.19ca 6.75 � 0.35ca 6.63 � 0.51ca 6.36 � 0.30bca 6.41 � 0.22bca 6.14 � 0.53bc 5.91 � 0.55bc 5.43 � 0.08ab 4.79 � 0.24a

C18:1 33.69 � 0.12a 35.45 � 0.50bc 35.58 � 0.74ab 36.34 � 0.73bc 35.76 � 0.15bc 36.45 � 0.76bc 36.75 � 0.49c 38.85 � 0.18d 39.17 � 0.28d 43.37 � 0.02e

C18:2 46.95 � 0.16g 43.10 � 0.68f 41.94 � 0.36ef 40.47 � 0.70de 39.92 � 1.55d 39.04 � 0.52d 32.61 � 0.31c 31.47 � 0.80c 24.89 � 0.14b 11.75 � 0.04a

C20:0 0.36 � 0.00f 0.34 � 0.01e 0.34 � 0.00e 0.33 � 0.01de 0.33 � 0.01de 0.32 � 0.01cd 0.30 � 0.00bc 0.29 � 0.01b 0.23 � 0.01a 0.22 � 0.00a

C18:3 0.64 � 0.01f 0.63 � 0.02ef 0.60 � 0.00de 0.60 � 0.00de 0.59 � 0.02d 0.59 � 0.02d 0.53 � 0.02c 0.53 � 0.01c 0.42 � 0.01b 0.37 � 0.02a

C20:1 0.15 � 0.00a 0.15 � 0.00a 0.15 � 0.00a 0.15 � 0.00a 0.15 � 0.00a 0.15 � 0.00a 0.15 � 0.00a 0.15 � 0.00a 0.15 � 0.00a 0.15 � 0.01a

C22:0 0.14 � 0.01b 0.13 � 0.01b 0.13 � 0.01b 0.13 � 0.00b 0.13 � 0.01b 0.07 � 0.00a 0.07 � 0.00a 0.06 � 0.00a 0.06 � 0.00a 0.05 � 0.01a

a) Each value in the table represents the means of triplicate analysis; SD is given after �. Means within each row with different letters are

significantly different at p < 0.05.

FA, fatty acid.

Figure 1. The composition changes of main fatty acids in SeO adulterated with different levels of RBD-PO.



bration model was used to predict the data set of samples

containing of RBD-PO with concentration ranges of 0.0–

65.0% v/v in SeO. The R2 for the linear regression between

actual value (x-axis) and FTIR-predicted value (y-axis) is

0.996 (Fig. 4), with RMSEP value of 1.83% v/v, using the

equationmodel of y ¼ 0.983x þ 0.515. These results exhibi-

ted the capability of FTIR spectroscopy in conjunction with

multivariate calibration of PLS to quantify the presence of

RBD-PO in SeO. With FTIR spectroscopy, the limit of

detection obtained, as expressed as yb þ 3Sb (yb is intercept

of PLS calibrationmodel expressing the blank signal and Sb is

SD of intercept), for analysis of RBD-PO in SeO is 1.86% v/v.

5 Conclusions

It can be concluded that the presence of RBD-PO as adul-

terant in SeO can bemonitored using the changes of fatty acid

profiles (palmitic, stearic, oleic, linoleic, and linolenic acids)

as determined using GC-FID. In addition, FTIR spec-

troscopy has emerged as promising technique for detection

Figure 2. FTIR spectra of sesame oil and RBD-palm oil at mid infrared region (4000–650 cmS1).

Figure 3. The scatter plot for the relationship between actual ver-

sus FTIR predicted values of RBD-PO in PLS calibration model.

Figure 4. The relationship between actual versus FTIR predicted

values of RBD-PO in the prediction model of independent

samples.

526 A. Rohman and Y. B. Che Man Eur. J. Lipid Sci. Technol. 2011, 113, 522–527


and quantification of RBD-PO in SeO at the combined

frequency regions of 3040–2995, 1660–1654, and 1150–

1050 cm�1 with acceptable R2, RMSEC, and RMSEP

values.

The Authors thank to Ministry of science, technology, and

innovations (MOSTI), Malaysia for the funding supports during

this research. Abdul Rohman acknowledges to The Directorate of

Higher Education, Ministry of National Education, Republic of

Indonesia for its financial support during his Ph.D program in

Halal Products Research Institute, UPM, Malaysia.

The authors have declared no conflict of interest.

References

[1] Kamm, W., Dionisi, F., Hischenhuber, C., Engel, K. H.,Authenticity assessment of fats and oils. Food Rev. Int. 2001,17, 249–290.

[2] Ulberth, F., Buchgraber, M., Authenticity of fats and oils.Eur. J. Lipid Sci. Technol. 2000, 102, 687–694.

[3] Dachtler, M., Frans, H. M., Stijn, F. V., Beindorff, C. M.,Fritsche, J., On-line LC-NMR-MS characterization of ses-ame oil extracts and assessment of their antioxidant activity.Eur. J. Lipid Sci. Technol. 2003, 105, 488–496.

[4] Seo, H.-Y., Ha, J., Sin, D.-B., Shim, S.-L. et al., Detection ofcorn oil in adulterated sesame oil by chromatography andcarbon isotope analysis. J. Am. Oil Chem. Soc. 2010, 87, 621–626.

[5] Hai, Z., Wang, J., Electronic nose and data analysis fordetection of maize oil adulteration in sesame oil. Sens.Actuators, B 2006, 119, 449–455.

[6] Yamajaki, M., Nagao, A., Yamamoto, H., Estimation of themixing ratio of foreign oil in adulterated sesame oil II. Ricebran oil or rapeseed oil. J. Jpn. Oil Chem. Soc. 1993, 43, 10–17.

[7] Lee, D. S., Lee, E. S., Kim, H. J., Kim, S. O., Kim, K.,Reversed phase liquid chromatographic determination oftriacylglycerol composition in sesame oils and the chemo-metric detection of adulteration.Anal. Chim. Acta 2001, 429,321–330.

[8] Hai, Z., Wang, J., Detection of adulteration in camellia seedoil and sesame oil using an electronic nose. Eur. J. Lipid Sci.Technol. 2006, 108, 116–124.

[9] Che Man, Y. B., Syahariza, Z. A., Rohman, A., Chapter 1.Fourier transform infrared ( FTIR) spectroscopy:

development, techniques, and application in the analysesof fats and oils. in: Ress, O. J. (Ed.), Fourier TransformInfrared Spectroscopy, Nova Science Publishers, New York2010, pp. 1–36.

[10] Guillen, M. D., Cabo, N., Infrared spectroscopy in the studyof edible oils and fats. J. Sci. Food Agric. 1997, 75, 1–11.

[11] Rohman, A., Che Man, Y. B., Analysis of cod-liver oil adul-teration using Fourier transform infrared (FTIR) spec-troscopy. J. Am. Oil Chem. Soc. 2009, 86, 1149–1153.

[12] Rohman, A., Che Man, Y. B., Monitoring of virgin coconutoil (VCO) adulteration with palm oil using Fourier transforminfrared (FTIR) spectroscopy. J. Food Lipids 2009, 16, 618–628.

[13] Rohman, A., Che Man, Y. B., Fourier transform infrared(FTIR) spectroscopy for analysis of extra virgin olive oiladulterated with palm oil. Food Res. Int. 2010, 43, 886–892.

[14] Christopoulou, E., Lazaraki, M., Komaitis, M., Kaselimis,K., Effectivenes of determinations of fatty acids and trigly-cerides for the detection of adulteration of olive oils withvegetable oils. Food Chem. 2004, 84, 463–474.

[15] Nor hayati, I., Che Man, Y. B., Tan, C. P., Nor Aini, I.,Physicochemical characteristics of soybean oil, palm kernelolein, and their binary blends. Int. J. Food Sci. Technol. 2009,44, 152–161.

[16] Gallardo-Velazquez, T., Osorio-Revilla, G., Cardenas-Bailon, F., Beltran-Orozco, M. C., Determination of ternarysolutions concentration in liquid-liquid extraction by the useof attenuated total reflectance-Fourier transform infraredspectroscopy and multivariate data analysis. Can. J. Chem.Eng. 2008, 86, 77–83.

[17] Codex Alimentarius Commision, 2nd Edn., Revised. CodexStandard for Named vegetable Oils, CX-Stan 210-1999 2001.

[18] Pavia, D. L., Lampman, G. M., Kriz-jr, G. S., Introdoction toSpectroscopy: A Guide for Students of Organic Chemistry, 3thEdn., Thomson Learning Inc., London 2001.

[19] Pavia, D. L., Lampman, G. M., Kriz-jr, G. S., Introdoction toSpectroscopy: A Guide for Students of Organic Chemistry, 3thEdn., Thomson Learning Inc., London 2001.

[20] Wang, L., Lee, F. S. C., Wang, X., He, Y., Feasibility studyof quantifying and discriminating soybean oil adulteration incamellia oils by attenuated total reflectance MIR and fiberoptic diffuse reflectance NIR. Food Chem. 2006, 95, 529–536.

[21] Miller, J. N., Miller, J. C., Statistics and Chemometrics forAnalytical Chemistry, 5th Edn., Pearson EducationLimited, Edinburgh Gate Harlow, England 2005,pp. 213–239.



palm oil analysis in adulterated sesame oil using chromatography and ftir spectroscopy

Documents