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Hindawi Publishing CorporationJournal of SpectroscopyVolume 2013 Article ID 138728 5 pageshttpdxdoiorg1011552013138728

Research ArticleApplication of Fourier Transform Infrared Spectroscopy for theOxidation and Peroxide Value Evaluation in Virgin Walnut Oil

Pengjuan Liang1 Chaoyin Chen1 Shenglan Zhao2 Feng Ge1 Diqiu Liu1 Binqiu Liu1

Qimeng Fan2 Benyong Han1 and Xianfeng Xiong1

1 Faculty of Life Science and Technology Kunming University of Science and Technology Kunming 650500 China2 Faculty of Chinese Traditional Medicine Yunnan University of Chinese Traditional Medicine Kunming 650500 China

Correspondence should be addressed to Chaoyin Chen chaoyinchen163com and Shenglan Zhao zhaoshenglan163com

Received 11 May 2013 Revised 27 August 2013 Accepted 9 September 2013

Academic Editor Christoph Krafft

Copyright copy 2013 Pengjuan Liang et alThis is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

Recent developments in Fourier transform infrared spectroscopy-partial least squares (FTIR-PLSs) extend the application of thisstrategy to the field of the edible oils and fats research In this work FT-IR spectroscopy was used as an effective analytical toolto determine the peroxide value of virgin walnut oil (VWO) samples undergone during heating The spectra were recorded froma film of pure oil between two disks of KBr for each sample at frequency regions of 4000ndash650 cmminus1 Changes in the values of thefrequency of most of the bands of the spectra were observed and used to build the calibration model PLS model correlates theactual and FT-IR estimated value of peroxide value with a correlation coefficient of 099 and the root mean square error of thecalibration (RMSEC) value is 04838 The methodology has potential as a fast and accurate way for the quantification of peroxidevalue of the edible oils

1 Introduction

Theproduction of walnut constitutes a significant proportionof the income of farmers in many countries In the recentyears the peroxide value of virgin walnut oil (VWO) hasreceived great attention because of its sensory qualities andbiological activities Epidemiological studies show that VWOnot only reduces serum cholesterol but also has nutritionalcranial nerve cells which can adjust plant nerve functionOther experts discover that walnut oil does not only act asan officinal but also can be used as the ldquoold man and theinfant nutrition oilrdquo as well as aerial work and flight personnelseniorrsquos health care oil [1]

In this way VWO production is a promising factor to theviability of ecological economy Nevertheless VWO can be atarget of adulteration with cheaper oils or even metamorphicoils because of its higher prices in the global market Theadulteration comprises a great hazard not only for the eco-nomic development and prosperity of those communities butalso for the health and safety of VWO consumers Thereforethe development of rapid and accurate analytical techniques

capable of detecting the quality of VWO is currently highlydemanded

In fact the quality of oils depends on its chemical com-position that changes qualitatively and quantitatively oneof the most important indicators of performance and shelf-life is the oxidative stability of oils that is their resistanceto the oxidation process Previous study showed that theunsaturated fatty acid content of oils is higher that is theunsaturated level is higher and the oxidation is easier [2]Because of the unsaturated fatty acid in VWO is 90 andthere is about 474 of linolic acid and 158 of linolenic acid[3] VWO is easier to be oxidized

Generally the sample of oil is oxidized when subjectedto air or oxygen flow heating exposure to light catalysersand so forth Although the mechanism of the oil degradationprocess was influenced by the oxidative conditions it hasnormally been established as being a free radical mechanismyielding hydroperoxides also called primary oxidation prod-ucts [4] Because hydroperoxides are the primary productsformed as autoxidation commences and serve as precur-sors to the subsequent formation of secondary oxidation

2 Journal of Spectroscopy

products aldehydes ketones lactones alcohols acids andso forth they are expressed as peroxide value (PV) in thefoodsafety [5] The methods to quantify PV which is usedto determine the degree of the oxidation process are mostlyrelated to the measurement of the concentration of primaryor secondary oxidation products or both or to the amountof oxygen consumed during the process Among those PVwhich measures hydroperoxide concentration is one of themost popular [4]

In the past years the traditional method of establishingthe PV of edible oils is titration and the method has beenstandardized by ISO (39601977) or GBT 5538-1955 ISO(39602001) or GBT 5538-2005 The determination processof titration is susceptible to a variety of external factorsand the measured value has poor reproducibility and lowsensitivity only can be applied to the large concentration ofhydroperoxide determination

The recent developments in FT-IR spectroscopy instru-mentation and the application of this technique expand infood research facilitating particularly the studies on edibleoils and fats FT-IR methods have demonstrated themselvesto be rapid and nondestructive analytical tools with mini-mum sample preparation necessary Due to the fact that theintensities of the bands in the spectrum are proportional toconcentration (ie Beerrsquos law is obeyed) and coupled withthe chemometric techniques FT-IR spectroscopy becomes anexcellent tool for quantitative analysis Several applicationshave been performed using this analytical approach togetherwith chemometric methods to detect walnut oil adulteration[6] evaluate olive oil freshness [7] monitor fatty acid com-position of virgin olive oil [8] and assess oil oxidation [9ndash11]

Although a lot of work has already been published onthe determination of PV by FTIR spectroscopy differentarticles have different analysis methods A primary FTIRspectroscopic method for the determination of PV in edibleoils based on the stoichiometric reaction of triphenylphos-phine (TPP) with the hydroperoxides present in edible oils toproduce triphenylphosphine oxide (TPPO) accurate quan-titation of the TPPO by the measurement of the absorptionband at 542 cmminus1 provides a simple means of determiningPV [5 12] In an other study the authors analyzed PV of oilby near-infrared spectroscopy and established three modelsincluding PLS-regression multiple linear regression (MLR)and principal component regression (PCR) Comparativeanalysis indicated that the most reliable model was selectedamong the established models in predicting peroxide valueof soybean oil [13] In this study MIR spectroscopy (4000ndash650 cmminus1) applied to VWO sample gives information onthe molecular bonds and therefore on the functional groupsof molecule Furthermore samples can be directly detectedwithout additional processing Compared with other articlesthe method in this study is more convenient

In this paper FT-IR spectroscopy is used for the oxidationand PV evaluation of virgin walnut oil The oxidation exper-iments were carried out in all cases by heating the samplesin a convection oven at 70∘C at different time the PV ofeach sample were determined by chemical and FT-IR spec-troscopy method PLS model correlates the actual and FT-IRestimated values of PV with a coefficient of determination

(R2) of 09918 This approach could represent a faster andmore accurate recognition tool for the determination walnutoil peroxide value since it is characterized by the simplicity ofsample preparation

2 Materials and Methods

21 Sample Oxidation Virgin walnut oil (VWO) was pur-chased from the local market The samples were placed in aconvection oven in uncovered polystyrene Petri dishes andheated at 70∘C for 1 2 3 4 5 6 8 and 10 d respectively

22 Chemical Method PV determination was performedaccording to the method proposed by ISO (39602001) orGBT 5538-2005 200ndash300 g of VWO sample was placed iniodine flask and dissolved in a blended solution of 50mLisooctane-glacial acetic acid (2 3 vv) A saturated solutionof KI (05mL) was added The mixture was shaken by handfor 05min and kept in the dark for another 3min After theaddition of 30mL distilled water the mixture was titratedagainst sodium thiosulphate (001M) until the yellow colouralmost disappeared Then about 05mL of starch indicator(005) solution was added Titration was sustained until theblue colour just disappeared A blank was also determinedunder similar conditions PV (meqkg) was calculated asfollows

PV (meqkg) = 119862 times (119881 minus 1198810

) times1000

119898 (1)

whereC is the sodium thiosulphate concentration (M)V andV0

represent the volumes of sodium thiosulphate exhaustedby the samples and the blank respectively (mL) andm is themass of VWO (g)

23 FT-IR Spectra Acquisition FT-IR spectra of sampleswere obtained using Shimadzu IRPrestige-21 equipped withDLATGS as detector and potassium bromide (KBr) as beamsplitter and controlled with the IRsolution software A smallquantity (sim20120583L) of the sample was deposited with the useof a Pasteur pipette between two well-polished KBr diskscreating a thin film in IR region of 4000ndash650 cmminus1 byaccumulating 40 scans with the resolution of 4 cmminus1 Thesespectra were subtracted from reference spectrum of airacquired by collecting a spectrum from the cleaned KBr disksblank before the measurement of each oil sample replicationAt the end of every scan the surface of KBr disk was cleanedwith hexane twice dried with special soft tissue then cleanedwith acetone and finally dried with soft tissue following thecollection of each spectrum The samples of spectra werecollected in triplicate and displayed as the average spectra

24 Chemometric The chemometric analyses were per-formed using the software SIMCA-P Quantification of thePV of VWO was carried out using partial least square (PLS)[14 15] PLS algorithm is an effective chemometric tool Ittakes the advantages of multiple linear regression (MLR)and principal component regression (PCR) it has strongpredictive ability relatively simplemodel and so forth which

Journal of Spectroscopy 3

Table 1 The peroxide value (PV) of each sample used in bothcalibration and validation

Samples Peroxide value (meqkg)Calibration Validation

1 41432 423562 90373 1847583 108598 2852174 152708 3613135 175795 4661116 293056 5737787 295217 661588 339717 7501649 432461 81402910 472113 98029911 5813512 62326413 65218414 77229415 80089116 94389717 98329918 120144

makes Fourier transform infrared (FT-IR) spectroscopymorepowerful and useful [16 17] For quantitative analysis 18samples were selected for calibration and 10 samples forvalidation The PV of each sample used in both calibrationand validation is presented in Table 1 Each sample wassubjected to FT-IR analysis

3 Results and Discussion

31 FT-IR Spectrum of VWO As a descriptive example avirgin walnut oil FT-IR spectrum is presented from 4000 to650 cmminus1 in Figure 1 The assignment of functional groupsresponsible for IR absorption peak is as follows 3009 (CndashH stretching vibration of the cis-double bond) 2947ndash2954(symmetric stretching vibration shoulder of CH

3

) 2926 and2854 (symmetric and asymmetric stretching vibration ofCH2

resp) 1745 (C=O stretching vibrations) 1465 and 1458(bending vibrations of the CH

2

and CH3

) 1398 (bending inplane vibrations of CH cis-olefinic groups) 1377 (bendingvibrations of CH

2

groups) 1238 1163 1120 and 1099 (CndashOstretching vibration) [18ndash23]

32 Evaluation of Oxidation Figure 2 shows the infraredspectra of the walnut oil sample under the oxidative con-ditions of heating at 0 6 8 and 10 days respectively Theinfrared spectra of the samples are similar in their originalstate however there are some differences which are relatedto the width and intensity of some bands as well as thepresence or absence of others [24 25] The frequency of thecis-double bond stretching vibration band near 3009 cmminus1remains almost unaltered or suffers a very slow shiftingtoward smaller wavelength values The band at 2926 cmminus1

increases its absorbance and width The band at 2854 cmminus1and the shoulder at 2949 cmminus1 increase their intensity dueto surrounding chemical changes as a consequence of theoxidation process There is another major absorbance near1746 cmminus1 and the change of this band can be associatedwith the appearance of saturated aldehyde functional groups[26 27] or other secondary oxidation products that cause anabsorbance at 1728 cmminus1 which overlaps with the stretchingvibration at 1746 cmminus1 of the ester carbonyl functional groupof the triglycerides A very weak band of the spectrum isnear 1399 cmminus1 which has been proved to be closely relatedto the proportion of the oleic acyl groups in the sample [24]and some authors have associated it with bending in planevibrations of CH cis-olefinic groups [28] The frequency ofthis band remains practically unchangedor increases slightlyTwo other bands present in all samples of oil are near 1238and 1163 cmminus1 and have been proved to be related to theproportion in the sample of saturated acyl groups [24] Thefrequencies of both bands suffer similar changes duringthe oxidation process and increase their intensity althoughthe changes are sharper in the band near 1163 cmminus1 Thefrequency of band near 1099 cmminus1 does not generally sufferlarge variations except in oil samples rich in oleic acyl groupsAs the oxidation process advances the frequency of this banddiminishes and reaches a minimum value

33 Calibration Model The calibration model of PV wascarried out by using PLS algorithm The PV of each sampleused in calibration is presented in Table 1 The spectralregions used for PLS calibration models are 3009 2989 29492926 2881 2854 2744 1790 1746 1710 1487 1465 1462 14581408 1398 1392 1377 1311 1238 1217 1163 1126 1120 1110 and1099 1041 cmminus1 (Figure 1) The selection of these frequencyregions was based on the optimisation processes in whichthey offered the highest values of R2 and the lowest values oferror either in calibration or in prediction models Althoughspecific band directly related to PV was at approximately3500 cmminus1 samples with 4ndash90 PV at this band were veryweak and it was very difficult to differentiate from noise Sothe band of 3500 cmminus1 was totally removed

Figure 3 shows the PLS calibration model which corre-lates the actual and estimated PV of VWO obtained from FT-IR spectra at the specified regions The relationship betweenthe actual and the observed value of PV showed a goodcorrelation with coefficient of determination (R2) valuesbeing 09918The evaluation of the error in calibrationmodelwas obtained by calculating the root mean square error ofcalibration (RMSEC) [29] RMSEC value is 04838 thereforethe high value of R2 and low value of RMSEC indicate thesuccess of calibration model

34 Validation Model In order to estimate the predictionability of the developed model PLS calibration model wasused to predict the values of PV of 10 VWO samples asvalidation data sets (Table 1) Figure 3 shows the PLS valida-tion model which correlates the actual and estimated PV ofVWO obtained from FT-IR spectra at the specified regions


Table 2 PLS performance for analysis of calibration and validation model

Model Principal components 1198772 Std dev RMSEC (meqkg) RMSEP (meqkg)Calibration 10 09918 0236 04838Validation 10 09903 0257 03545

2926

2949

3009

2881

2989

2744

2854

1746

1790 17101487

1462

1458

1398

13921408

13111110

1041

10991120

1163

1238

11261377

1465

1217

4000 3800 3600 3400 3200 2800 2600 2400 2200 2000 1900 1800 1700 1600 1500 1400 1300 1200 1100 1000 900 800 700

1 cm

225

2

175

15

125

1

075

05

025

Abs

3000

Figure 1 IR spectra of virgin walnut oil (VWO) sample before oxidation

DCBA

Abs

3525

3375

3225

3075

2925

2775

2625

2475

2325

2175

2025

1950

1875

1800

1725

1650

1500

1425

1350

1275

1200

1125

1050

1575

Figure 2 FTIR spectra of the virgin walnut oil (VWO) sample after 0 6 8 and 10 days respectively under oxidative condition at region of4000ndash1030 cmminus1 (A) 0 day (B) 6 days (C) 8 days (D) 10 days

120

100

80

60

40

20

00 10 20 30 40 50 60 70 80 90 100 110 120

FTIR PLS (meqkg)

Chem

ical

met

hod

(meq

kg)

y =R2 = 099031005lowastx + 0162

Figure 3 Iodometric and estimated values of peroxide value (PV)for calibration and validation sets (998771 calibration set ◼ validationset)

as well as calibration model The values of R2 and RMSEP[29] are 09903 and 03545 respectively Based on this resultit can be stated that PLS appears to have a reasonable abilityto estimate the PV of VWO samples Table 2 compiled PLS

performance in terms of R2 standard deviation (Std dev)RMSEC RMSEP and the number of principal componentsfor quantification of the PV of VWO

4 Conclusions

From the results here obtained it can be concluded that FT-IR spectroscopy is an adequate technique for detecting thechanges produced in virgin walnut oil sample during anoxidation process The changes observed in the frequencyvalues of most of the bands of the spectra throughout theoxidation experiment provide accurate information about thedifferent stages of the process and for this reason FTIR-PLScould be useful to evaluate the oxidative state of VWO andto determine the PV one of the most important indicators ofperformance and shelf-life in a simple accurate and fast way

Acknowledgments

The authors gratefully acknowledge the financial sup-port of State Science and Technology Support Program


(2011BAD46B00) and Yunnan Science and Technology Pro-gram (2011AB006)

References

[1] S L Zhao C Y Chen and F Ge ldquoProgressive study on func-tions and componentsrdquo Journal of Yunnan University of Tradi-tional Chinese Medicine vol 33 pp 71ndash74 2010

[2] S G LiW T Xue andH Zhang ldquoResearch progress in analysismethods of peroxide value in edible oilsrdquo Cereals and Oils vol7 pp 35ndash38 2007

[3] B Y Wan H Z Dong and H Li ldquoResearch on the propertiesand nutrition of walnut oilrdquo China Western Cereals and OilsTechnology vol 26 pp 18ndash19 2001

[4] N Vlachos Y Skopelitis M Psaroudaki V Konstantinidou AChatzilazarou and E Tegou ldquoApplications of Fouriertransform-infrared spectroscopy to edible oilsrdquo AnalyticaChimica Acta vol 573-574 pp 459ndash465 2006

[5] K Ma F R van de Voort J Sedman and A A Ismail ldquoStoi-chiometric determination of hydroperoxides in fats and oilsby fourier transform infrared spectroscopyrdquo Journal of theAmerican Oil Chemistsrsquo Society vol 74 no 8 pp 897ndash906 1997

[6] P J Liang HWang C Y Chen et al ldquoThe use of Fourier trans-form infrared (FT-IR) spectroscopy for quantification of adul-teration in virgin walnut oilrdquo Journal of Spectroscopy vol 2013Article ID 305604 6 pages 2013

[7] N Sinelli M S Cosio C Gigliotti and E Casiraghi ldquoPrelimi-nary study on application of mid infrared spectroscopy for theevaluation of the virgin olive oil lsquofreshnessrsquordquo Analytica ChimicaActa vol 598 no 1 pp 128ndash134 2007

[8] R M Maggio T S Kaufman M D Carlo et al ldquoMonitoring offatty acid composition in virgin olive oil by Fourier transformedinfrared spectroscopy coupled with partial least squaresrdquo FoodChemistry vol 114 no 4 pp 1549ndash1554 2009

[9] M D Guillen and N Cabo ldquoFourier transform infrared spec-tra data versus peroxide and anisidine values to determineoxidative stability of edible oilsrdquo Food Chemistry vol 77 no 4pp 503ndash510 2002

[10] A Bendini L Cerretani F Di Virgilio P Belloni M Bonoli-Carbognin and G Lercker ldquoPreliminary evaluation of theapplication of the ftir spectroscopy to control the geographicorigin and quality of virgin olive oilsrdquo Journal of Food Qualityvol 30 no 4 pp 424ndash437 2007

[11] B Muik B Lendl A Molina-Diaz M Valcarcel and MJ Ayora-Canada ldquoTwo-dimensional correlation spectroscopyandmultivariate curve resolution for the study of lipid oxidationin edible oils monitored by FTIR and FT-Raman spectroscopyrdquoAnalytica Chimica Acta vol 593 no 1 pp 54ndash67 2007

[12] X Z Yu S K Du Z X Li and J Y Zhang ldquoStudy on detec-tion of peroxide value in edible oils using FTIR spectralreconstitution techniquerdquo Journal of Chinese Institute of FoodScience and Technology vol 11 pp 169ndash175 2011

[13] L Q Wang L Y Zhang and X C Zhu ldquoNear-infrared spec-troscopic analysis of peroxide value of soybean oilrdquo FoodScience vol 31 pp 205ndash207 2010

[14] HMartens and T NaesMultivariate Calibration JohnWiley ampSons Chichester UK 1989

[15] E VThomas ldquoA primer on multivariate calibrationrdquo AnalyticalChemistry vol 66 no 15 pp 795ndash804 1994

[16] E Y Zhu and P Y Yang Chemometrics and Its ApplicationScience Press Beijing China 2003

[17] L Zhang L M Zhang Y Li B P Liu X F Wang and J DWang ldquoApplication and improvement of partial-least-squaresin Fourier transform infrared spectroscopyrdquo Spectroscopy andSpectral Analysis vol 25 no 10 pp 1610ndash1613 2005

[18] N B Colthup L H Daly and S E Wiberly Introduction toInfrared and Raman Spectroscopy Accademic Press New YorkNY USA 3rd edition 1990

[19] M K Ahmed J K Daun and R Przybylski ldquoFT-IR basedmethodology for quantitation of total tocopherols tocotrienolsand plastochromanol-8 in vegetable oilsrdquo Journal of FoodComposition and Analysis vol 18 no 5 pp 359ndash364 2005

[20] H Yang J Irudayaraj and M M Paradkar ldquoDiscriminantanalysis of edible oils and fats by FTIR FT-NIR and FT-Ramanspectroscopyrdquo Food Chemistry vol 93 no 1 pp 25ndash32 2005

[21] M D Guillen N Cabo and J Agric ldquoMethods for monitoringcomposition and flavor quality of cheese using a rapid spectro-scopic methodrdquo Food Chemistry vol 46 no 5 pp 1788ndash17931998

[22] J Coates and R A Meyers Encyclopaedia of Analytical Chem-istry John Wiley amp Sons Chichester UK 2000

[23] J Workman Handbook of Organic Compounds AcademicPress London UK 2001

[24] M D Guillen and N Cabo ldquoCharacterization of edible oils andlard by fourier transform infrared spectroscopy Relationshipsbetween composition and frequency of concrete bands inthe fingerprint regionrdquo Journal of the American Oil ChemistsrsquoSociety vol 74 no 10 pp 1281ndash1286 1997

[25] M D Guillen and N Cabo ldquoRelationships between the compo-sition of edible oils and lard and the ratio of the absorbance ofspecific bands of their fourier transform infrared spectra Roleof some bands of the fingerprint regionrdquo Journal of Agriculturaland Food Chemistry vol 46 no 5 pp 1788ndash1793 1998

[26] E N Frankel Lipid Oxidation Oily Press 1980[27] R J Hamilton ldquoThe chemistry of rancidity in foodsrdquo in Ran-

cidity in Foods J C Allen and R J Hamilton Eds ElsevierApplied Science Publishers London UK 1989

[28] D B Dahlberg S M Lee S J Wenger and J A Vargo ldquoClas-sification of vegetable oils by FT-IRrdquo Applied Spectroscopy vol51 no 8 pp 1118ndash1124 1997

[29] M M Paradkar and J Irudayaraj ldquoA rapid FTIR spectroscopicmethod for estimation of caffeine in soft drinks and totalmethylxanthines in tea and coffeerdquo Journal of Food Science vol67 no 7 pp 2507ndash2511 2002

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Advances in

Physical Chemistry

Hindawi Publishing Corporationhttpwwwhindawicom

Analytical Methods in Chemistry

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Volume 2014

Bioinorganic Chemistry and ApplicationsHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

SpectroscopyInternational Journal of


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Medicinal ChemistryInternational Journal of


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Applied ChemistryJournal of



Theoretical ChemistryJournal of


Journal of

Spectroscopy

Analytical ChemistryInternational Journal of


Journal of


Quantum Chemistry


Organic Chemistry International

ElectrochemistryInternational Journal of



CatalystsJournal of


products aldehydes ketones lactones alcohols acids andso forth they are expressed as peroxide value (PV) in thefoodsafety [5] The methods to quantify PV which is usedto determine the degree of the oxidation process are mostlyrelated to the measurement of the concentration of primaryor secondary oxidation products or both or to the amountof oxygen consumed during the process Among those PVwhich measures hydroperoxide concentration is one of themost popular [4]

In the past years the traditional method of establishingthe PV of edible oils is titration and the method has beenstandardized by ISO (39601977) or GBT 5538-1955 ISO(39602001) or GBT 5538-2005 The determination processof titration is susceptible to a variety of external factorsand the measured value has poor reproducibility and lowsensitivity only can be applied to the large concentration ofhydroperoxide determination

The recent developments in FT-IR spectroscopy instru-mentation and the application of this technique expand infood research facilitating particularly the studies on edibleoils and fats FT-IR methods have demonstrated themselvesto be rapid and nondestructive analytical tools with mini-mum sample preparation necessary Due to the fact that theintensities of the bands in the spectrum are proportional toconcentration (ie Beerrsquos law is obeyed) and coupled withthe chemometric techniques FT-IR spectroscopy becomes anexcellent tool for quantitative analysis Several applicationshave been performed using this analytical approach togetherwith chemometric methods to detect walnut oil adulteration[6] evaluate olive oil freshness [7] monitor fatty acid com-position of virgin olive oil [8] and assess oil oxidation [9ndash11]

Although a lot of work has already been published onthe determination of PV by FTIR spectroscopy differentarticles have different analysis methods A primary FTIRspectroscopic method for the determination of PV in edibleoils based on the stoichiometric reaction of triphenylphos-phine (TPP) with the hydroperoxides present in edible oils toproduce triphenylphosphine oxide (TPPO) accurate quan-titation of the TPPO by the measurement of the absorptionband at 542 cmminus1 provides a simple means of determiningPV [5 12] In an other study the authors analyzed PV of oilby near-infrared spectroscopy and established three modelsincluding PLS-regression multiple linear regression (MLR)and principal component regression (PCR) Comparativeanalysis indicated that the most reliable model was selectedamong the established models in predicting peroxide valueof soybean oil [13] In this study MIR spectroscopy (4000ndash650 cmminus1) applied to VWO sample gives information onthe molecular bonds and therefore on the functional groupsof molecule Furthermore samples can be directly detectedwithout additional processing Compared with other articlesthe method in this study is more convenient

In this paper FT-IR spectroscopy is used for the oxidationand PV evaluation of virgin walnut oil The oxidation exper-iments were carried out in all cases by heating the samplesin a convection oven at 70∘C at different time the PV ofeach sample were determined by chemical and FT-IR spec-troscopy method PLS model correlates the actual and FT-IRestimated values of PV with a coefficient of determination

(R2) of 09918 This approach could represent a faster andmore accurate recognition tool for the determination walnutoil peroxide value since it is characterized by the simplicity ofsample preparation

2 Materials and Methods

21 Sample Oxidation Virgin walnut oil (VWO) was pur-chased from the local market The samples were placed in aconvection oven in uncovered polystyrene Petri dishes andheated at 70∘C for 1 2 3 4 5 6 8 and 10 d respectively

22 Chemical Method PV determination was performedaccording to the method proposed by ISO (39602001) orGBT 5538-2005 200ndash300 g of VWO sample was placed iniodine flask and dissolved in a blended solution of 50mLisooctane-glacial acetic acid (2 3 vv) A saturated solutionof KI (05mL) was added The mixture was shaken by handfor 05min and kept in the dark for another 3min After theaddition of 30mL distilled water the mixture was titratedagainst sodium thiosulphate (001M) until the yellow colouralmost disappeared Then about 05mL of starch indicator(005) solution was added Titration was sustained until theblue colour just disappeared A blank was also determinedunder similar conditions PV (meqkg) was calculated asfollows

PV (meqkg) = 119862 times (119881 minus 1198810

) times1000

119898 (1)

whereC is the sodium thiosulphate concentration (M)V andV0

represent the volumes of sodium thiosulphate exhaustedby the samples and the blank respectively (mL) andm is themass of VWO (g)

23 FT-IR Spectra Acquisition FT-IR spectra of sampleswere obtained using Shimadzu IRPrestige-21 equipped withDLATGS as detector and potassium bromide (KBr) as beamsplitter and controlled with the IRsolution software A smallquantity (sim20120583L) of the sample was deposited with the useof a Pasteur pipette between two well-polished KBr diskscreating a thin film in IR region of 4000ndash650 cmminus1 byaccumulating 40 scans with the resolution of 4 cmminus1 Thesespectra were subtracted from reference spectrum of airacquired by collecting a spectrum from the cleaned KBr disksblank before the measurement of each oil sample replicationAt the end of every scan the surface of KBr disk was cleanedwith hexane twice dried with special soft tissue then cleanedwith acetone and finally dried with soft tissue following thecollection of each spectrum The samples of spectra werecollected in triplicate and displayed as the average spectra

24 Chemometric The chemometric analyses were per-formed using the software SIMCA-P Quantification of thePV of VWO was carried out using partial least square (PLS)[14 15] PLS algorithm is an effective chemometric tool Ittakes the advantages of multiple linear regression (MLR)and principal component regression (PCR) it has strongpredictive ability relatively simplemodel and so forth which




1 41432 423562 90373 1847583 108598 2852174 152708 3613135 175795 4661116 293056 5737787 295217 661588 339717 7501649 432461 81402910 472113 98029911 5813512 62326413 65218414 77229415 80089116 94389717 98329918 120144




3



2

and CH3


2










2926

2949

3009

2881

2989

2744

2854

1746

1790 17101487

1462

1458

1398

13921408

13111110

1041

10991120

1163

1238

11261377

1465

1217

4000 3800 3600 3400 3200 2800 2600 2400 2200 2000 1900 1800 1700 1600 1500 1400 1300 1200 1100 1000 900 800 700

1 cm

225

2

175

15

125

1

075

05

025

Abs

3000


DCBA

Abs

3525

3375

3225

3075

2925

2775

2625

2475

2325

2175

2025

1950

1875

1800

1725

1650

1500

1425

1350

1275

1200

1125

1050

1575


120

100

80

60

40

20

00 10 20 30 40 50 60 70 80 90 100 110 120

FTIR PLS (meqkg)

Chem

ical

met

hod

(meq

kg)

y =R2 = 099031005lowastx + 0162




4 Conclusions


Acknowledgments




References







































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of




1 41432 423562 90373 1847583 108598 2852174 152708 3613135 175795 4661116 293056 5737787 295217 661588 339717 7501649 432461 81402910 472113 98029911 5813512 62326413 65218414 77229415 80089116 94389717 98329918 120144




3



2

and CH3


2










2926

2949

3009

2881

2989

2744

2854

1746

1790 17101487

1462

1458

1398

13921408

13111110

1041

10991120

1163

1238

11261377

1465

1217

4000 3800 3600 3400 3200 2800 2600 2400 2200 2000 1900 1800 1700 1600 1500 1400 1300 1200 1100 1000 900 800 700

1 cm

225

2

175

15

125

1

075

05

025

Abs

3000


DCBA

Abs

3525

3375

3225

3075

2925

2775

2625

2475

2325

2175

2025

1950

1875

1800

1725

1650

1500

1425

1350

1275

1200

1125

1050

1575


120

100

80

60

40

20

00 10 20 30 40 50 60 70 80 90 100 110 120

FTIR PLS (meqkg)

Chem

ical

met

hod

(meq

kg)

y =R2 = 099031005lowastx + 0162




4 Conclusions


Acknowledgments




References







































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of




2926

2949

3009

2881

2989

2744

2854

1746

1790 17101487

1462

1458

1398

13921408

13111110

1041

10991120

1163

1238

11261377

1465

1217

4000 3800 3600 3400 3200 2800 2600 2400 2200 2000 1900 1800 1700 1600 1500 1400 1300 1200 1100 1000 900 800 700

1 cm

225

2

175

15

125

1

075

05

025

Abs

3000


DCBA

Abs

3525

3375

3225

3075

2925

2775

2625

2475

2325

2175

2025

1950

1875

1800

1725

1650

1500

1425

1350

1275

1200

1125

1050

1575


120

100

80

60

40

20

00 10 20 30 40 50 60 70 80 90 100 110 120

FTIR PLS (meqkg)

Chem

ical

met

hod

(meq

kg)

y =R2 = 099031005lowastx + 0162




4 Conclusions


Acknowledgments




References







































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of



References







































Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of










Journal of

Chemistry


Advances in

Physical Chemistry



Journal of

Volume 2014














Journal of

Spectroscopy



Journal of


Quantum Chemistry






CatalystsJournal of

Documents

Research Article Application of Fourier Transform Infrared Spectroscopy …downloads.hindawi.com › journals › jspec › 2013 › 138728.pdf · 2019-07-31 · titation of the TPPO