Detection of Peanut Oil Adulteration Mixed with Rapeseed Oil Using Gas Chromatography and Gas Chromatography–Ion Mobility Spectrometry Article First Online: 10 July 2019 Abstract
In this study, the feasibility of gas chromatography (GC) and gas chromatography–ion mobility spectrometry (GC–IMS) systems for detecting peanut oil (PO) adulterated with rapeseed oil (RO) in different ratios was evaluated. In the GC analysis, the oils were categorized on the basis of fatty acid compositions. In the GC–IMS analysis, the oils were distinguished on the basis of volatile fractions. To demonstrate the high quality of the GC–IMS results, principal component analysis (PCA) and cluster analysis (CA) were conducted. The results showed that fatty acid profiles in PO exhibited higher amounts of palmitic acid (10.70 ± 0.18%), linoleic acid (32.87 ± 0.52%), and arachidic acid (2.30 ± 0.05%). RO had higher levels of linolenic acid (7.49 ± 0.36%) and erucic acid (8.02 ± 0.39%), which were not detected in PO. The linear regression analysis showed that the change in C18:2, C18:3, C20:1, and C22:1 content was highly correlated with the adulteration proportion of RO. However, only significant differences were visible in C18:3 and C20:1 when the adulteration proportion was a minimum of 5%. Satisfactory results of adulteration determination were obtained using the GC–IMS combined with the PCA and CA. Each oil type had unique characteristic compounds, and signals of some volatile compounds changed with the increase in the adulteration proportion especially at run times ranging from 100 to 300 s. For example, the intensity of peak signals of 89–92 increased with the addition of RO while peak intensity of 104 to 107 weakened. These individual signals revealed the volatile compounds responsible for the differences between PO and RO and could help to screen PO adulterated with RO. The established PCA scatter plots and CA could correctly differentiate authentic PO from adulterated samples with at least 1% of RO. Consequently, the GC–IMS shows higher efficiency and feasibility compared with the GC and may serve as a basis for the detection of adulteration of various substances.
Keywords Peanut oil Rapeseed oil Adulteration GC GC–IMS PCA CA Notes Compliance with Ethical Standards Conflict of Interest
Lili Tian declares no conflict of interest. Yuanyuan Zeng declares no conflict of interest. Xiuqian Zheng declares no conflict of interest. Yahuang Chiu declares no conflict of interest. Tristan Liu declares no conflict of interest.
This article does not contain any studies with animals or human participants performed by any of the authors.
Informed consent was obtained from all individual participants included in the study.
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Agiomyrgianaki A, Petrakis PV, Dais P (2010) Detection of refined olive oil adulteration with refined hazelnut oil by employing NMR spectroscopy and multivariate statistical analysis. Talanta 80:2165–2171.
https://doi.org/10.1016/j.talanta.2009.11.024 CrossRef Google Scholar
Anderson SL, Rovnyak D, Strein TG (2017) Identification of Edible Oils by Principal Component Analysis of H NMR Spectra. Journal of Chemical Education 94(9):1377–1382
CrossRef Google Scholar
Aparicio R, Aparicio-Ruíz R (2000) Authentication of vegetable oils by chromatographic techniques. J Chromatogr A
https://doi.org/10.1016/S0021-9673(00)00355-1 CrossRef Google Scholar
Apetrei IM, Apetrei C (2014) Detection of virgin olive oil adulteration using a voltammetric e-tongue. Comput Electron Agric 108:148–154.
https://doi.org/10.1016/j.compag.2014.08.002 CrossRef Google Scholar
Brendler C, Riebe D, Zenichowski K, Beitz T, Löhmannsröben HG (2014) Laser-based ion mobility spectrometer for the direct analysis of aromatic compounds in liquids. Int J Ion Mobil Spectrom 17:105–115.
https://doi.org/10.1007/s12127-014-0158-4 CrossRef Google Scholar
Brodnjak-Voncˇina D, Kodba ZC, Novicˇ M (2005) Multivariate data analysis in classification of vegetable oils characterized by the content of fatty acids. Chemom Intell Lab Syst 75:31–43.
https://doi.org/10.1016/j.chemolab.2004.04.011 CrossRef Google Scholar
Brown DF, Cater CM, Mattil KF, Darroch JG (1975) Effect of variety, growing location and their interaction on the fatty acid composition of peanuts. J Food Sci 40:1055–1060.
https://doi.org/10.1111/j.1365-2621.1975.tb02266.x CrossRef Google Scholar
Bu D, Brown CW (2000) Self-modeling mixture analysis by interactive principal component analysis. Appl Spectrosc 54:1214–1221.
https://doi.org/10.1366/0003702001950797 CrossRef Google Scholar
Cazaussus A, Pes R, Sellier N, Tabet JC (1988) GC-MS and GC-MS-MS analysis of a complex essential oil. Chromatographia 25:865–869.
https://doi.org/10.1007/BF02311419 CrossRef Google Scholar
Chalchat JC, Özcan MM (2008) Comparative essential oil composition of flowers, leaves and stems of basil (Ocimum basilicum, L.) used as herb. Food Chem 110:501–503.
https://doi.org/10.1016/j.foodchem.2008.02.018 CrossRef Google Scholar
Clatworthy J, Buick D, Hankins M, Weinman J, Horne R (2005) The use and reporting of cluster analysis in health psychology: a review. Br J Health Psychol 10:329–358.
https://doi.org/10.1348/135910705X25697 CrossRef Google Scholar
CriadoGarcía L, Garridodelgado R, Arce L, López F, Peón R, Valcárcel M (2015) Simultaneous determination of benzene and phenol in heat transfer fluid by head-space gas chromatography hyphenated with ion mobility spectrometry. Talanta 144:944–952.
https://doi.org/10.1016/j.talanta.2015.07.053 CrossRef Google Scholar
Cui Y, Hao P, Liu B, Meng X (2017) Effect of traditional Chinese cooking methods on fatty acid profiles of vegetable oils. Food Chem 233:77–84.
https://doi.org/10.1016/j.foodchem.2017.04.084 CrossRef Google Scholar
Cunha SC, Oliveira MBPP (2006) Discrimination of vegetable oils by triacylglycerols evaluation of profile using HPLC/ELSD. Food Chem
https://doi.org/10.1016/j.foodchem.2005.03.029 CrossRef Google Scholar
Dilts D, Khamalah J, Plotkin A (1995) Using cluster analysis for medical resource decision making. Med Decis Mak 15:333–346.
https://doi.org/10.1177/0272989X9501500404 CrossRef Google Scholar
Dong XY, Zhong J, Wei F, Lv X, Wu L, Lei Y, Liao BS, Quek SY, Chen H (2015) Triacylglycerol composition profiling and comparison of high-oleic and normal peanut oils. J Am Oil Chem Soc 92:233–242.
https://doi.org/10.1007/s11746-014-2580-5 CrossRef Google Scholar
Eisen MB, Spellman PT, Brown PO, Botstein D (1998) Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 95:14863–14868.
https://doi.org/10.2307/48859 CrossRef Google Scholar
Etchegoin PG, Meyer M, Blackie E, Le Ru EC (2007) Statistics of single-molecule surface enhanced Raman scattering signals: fluctuation analysis with multiple analyte technique. Anal. Chem.79:8411–8415.
Ewing RG, Atkinson DA, Eiceman GA, Ewing GJ (2001) A critical review of ion mobility spectrometry for the detection of explosives and explosive related compounds. Talanta 54:515–529.
https://doi.org/10.1016/S0039-9140(00)00565-8 CrossRef Google Scholar
Fang G, Goh JY, Tay M, Lau HF, Li SF (2013) Characterization of oils and fats by 1 h NMR and GC/MS fingerprinting: classification, prediction and detection of adulteration. Food Chem 138:1461–1469.
https://doi.org/10.1016/j.foodchem.2012.09.136 CrossRef Google Scholar
Gallegos J, Garrido-Delgado R, Arce L, Medina LM (2015) Volatile metabolites of goat cheeses determined by ion mobility spectrometry potential applications in quality control. Food Anal Methods 8:1–11.
https://doi.org/10.1007/s12161-014-0050-1 CrossRef Google Scholar
Grégrová A, Čížková H, Mazáč J, & Voldřich M (2012) Authenticity assessment of spirit vinegar (part ii): analysis of samples from distribution chain. Kvasny Prumysl 58:350–354.
Grove WM (1985) The classification of psychopathology: Neo-Kraepelinian and quantitative approaches. Am J Psychiatry 142(6):771–a-772.
https://doi.org/10.1176/ajp.142.6.771-a CrossRef Google Scholar
Gurbanov R, Bilgin M, Severcan F (2016) Restoring effect of selenium on the molecular content, structure and fluidity of diabetic rat kidney brush border cell membrane. Biochim Biophys Acta 1858:845–854.
https://doi.org/10.1016/j.bbamem.2016.02.001 CrossRef Google Scholar
Hilali M, Charrouf Z, Soulhi AEA, Hachimi L, Guillaume D (2007) Detection of argan oil adulteration using quantitative campesterol GC-analysis. J Am Oil Chem Soc 84:761–764.
https://doi.org/10.1007/s11746-007-1084-y CrossRef Google Scholar
Imai C, Watanabe H, Haga N, Ii T (1974) Detection of adulteration of cottonseed oil by gas chromatography. J Am Oil Chem Soc 51:326–330.
https://doi.org/10.1007/BF02633007 CrossRef Google Scholar
Ivanova-Petropulos V, Mitrev S, Stafilov T, Markova N, Leitner E, Lankmayr E, Siegmund B (2015) Characterisation of traditional Macedonian edible oils by their fatty acid composition and their volatile compounds. Food Res Int 77:506–514.
https://doi.org/10.1016/j.foodres.2015.08.014 CrossRef Google Scholar
Jafari M, Kadivar M, Keramat J (2009) Detection of adulteration in Iranian olive oils using instrumental (GC, NMR, DSC) methods. J Am Oil Chem Soc 86:103–110.
https://doi.org/10.1007/s11746-008-1333-8 CrossRef Google Scholar
Johnstone IM, Lu AY (2009) On consistency and sparsity for principal components analysis in high dimensions. J Am Stat Assoc 104:682–693.
https://doi.org/10.1198/jasa.2009.0121 CrossRef Google Scholar
Jung HY, Kwak HS, Kim MJ, Kim Y, Kim KO, Kim SS (2017) Comparison of a descriptive analysis and instrumental measurements (electronic nose and electronic tongue) for the sensory profiling of Korean fermented soybean paste (doenjang). J Sens Stud
https://doi.org/10.1111/joss.12282 CrossRef Google Scholar
Knorr FJ, Futrell JH (1979) Separation of mass spectra of mixtures by factor analysis. Anal Chem
https://doi.org/10.1366/0003702001950797 CrossRef Google Scholar
Krisilova E, Levina A, Makarenko V (2014) Determination of the volatile compounds of vegetable oils using an ion-mobility spectrometer. J Anal Chem 69:371–376.
https://doi.org/10.1134/S1061934814020075 CrossRef Google Scholar
Lermagarcía MJ, Ramisramos G, Herreromartínez JM, Simóalfonso EF (2010) Authentication of extra virgin olive oils by Fourier-transform infrared spectroscopy. Food Chem 118:78–83.
https://doi.org/10.1016/j.foodchem.2009.04.092 CrossRef Google Scholar
Liang F, Kerpen K, Kuklya A, Telgheder U (2012) Fingerprint identification of volatile organic compounds in gasoline contaminated groundwater using gas chromatography differential ion mobility spectrometry. Int J Ion Mobil Spectrom 15:169–177.
https://doi.org/10.1007/s12127-012-0101-5 CrossRef Google Scholar
Mao H, Zeng A, Zhou Y, Fang H (2016) Application of chemical analysis technology in the analysis of edible oil adulteration. Modern Food 10:75–79
McLachlan GJ (1992) Cluster analysis and related techniques in medical research. Stat Methods Med Res 1:27–48.
https://doi.org/10.1177/096228029200100103 CrossRef Google Scholar
Miladinovic DL, Ilic BS, Matejic JS, Randjelovic VN, Nikolic DM, Mihajilovkrstev TM et al (2014) Chemical composition of the essential oil of
. Chem Nat Compd 50:1–2.
https://doi.org/10.1007/s10600-014-1120-8 CrossRef Google Scholar
Nieuwoudt HH, Prior BA, Pretorius IS, Manley M, Bauer FF (2004) Principal component analysis applied to Fourier transform infrared spectroscopy for the design of calibration sets for glycerol prediction models in wine and for the detection and classification of outlier samples. J Agric Food Chem 52:3726–3735.
https://doi.org/10.1021/jf035431q CrossRef Google Scholar
Park YW, Chang PS, Lee JH (2010) Application of triacylglycerol and fatty acid analyses to discriminate blended sesame oil with soybean oil. Food Chem
https://doi.org/10.1016/j.foodchem.2010.04.049 CrossRef Google Scholar
Rocío G-D, Lourdes A, Miguel V (2012) Multi-capillary column-ion mobility spectrometry: a potential screening system to differentiate virgin olive oils. Anal Bioanal Chem 402:489–498.
https://doi.org/10.1007/s00216-011-5328-1 CrossRef Google Scholar
Rodríguez-Maecker R, Vyhmeister E, Meisen S, Martinez AR, Kuklya A, Telgheder U (2017) Identification of terpenes and essential oils by means of static headspace gas chromatography-ion mobility spectrometry. Anal Bioanal Chem 409:1–9.
https://doi.org/10.1007/s00216-017-0613-2 CrossRef Google Scholar
Sathe SK, Seeram NP, Kshirsagar HH, Heber D, Lapsley KA (2008) Fatty acid composition of California grown almonds. J Food Sci 73(8):C607–C614.
https://doi.org/10.1111/j.1750-3841.2008.00936.x CrossRef Google Scholar
Sharma A, Khare SK, Gupta MN (2002) Enzyme-assisted aqueous extraction of peanut oil. J Am Oil Chem Soc 79:215–218.
https://doi.org/10.1007/s11746-002-0463-0 CrossRef Google Scholar
Tan J, Li R, Jiang ZT, Shi M, Xiao YQ, Jia B, Lu TX, Wang H (2018) Detection of extra virgin olive oil adulteration with edible oils using front-face fluorescence and visible spectroscopies. J Am Oil Chem Soc 95:535–546.
https://doi.org/10.1002/aocs.12071 CrossRef Google Scholar
Tsimidou M, Macrae R (1987) Authentication of virgin olive oils using principal component analysis of triglyceride and fatty acid profiles: part 2—detection of adulteration with other vegetable oils. Food Chem 25:251–258.
https://doi.org/10.1016/0308-8146(87)90011-2 CrossRef Google Scholar
Vandeginste BG, Derks W, Kateman G (1985) Multicomponent self-modelling curve resolution in high-performance liquid chromatography by iterative target transformation analysis. Anal Chim Acta 173:253–264.
https://doi.org/10.1016/S0003-2670(00)84962-4 CrossRef Google Scholar
Weir MR, Maibach EW, Bakris GL, Black HR, Chawla P, Messerli FH, Neutel JM, Weber MA (2000) Implications of a healthy lifestyle and medication analysis for improving hypertension control. Arch Intern Med 160:481–490.
https://doi.org/10.1001/archinte.160.4.481 CrossRef Google Scholar
Wu Z, Li H, Tu D (2015) Application of Fourier transform infrared (FT-IR) spectroscopy combined with chemometrics for analysis of rapeseed oil adulterated with refining and purificating waste cooking oil. Food Anal Methods 8:2581–2587.
https://doi.org/10.1007/s12161-015-0149-z CrossRef Google Scholar
Xie J, Li XU, Zhang QH, Hong-Yun WU (2013a) Headspace solid phase microextraction of volatile flavor components from rapeseed oil. Food Sci 34:281–285.
https://doi.org/10.7506/spkx1002-6630-201312058 Google Scholar
Xie J, Liu T, Yu Y, Song G, Hu Y (2013b) Rapid detection and quantification by GC–MS of camellia seed oil adulterated with soybean oil. J Am Oil Chem Soc 90:641–646.
https://doi.org/10.1007/s11746-013-2209-0 CrossRef Google Scholar
Yan XL (2011) A qualitative & quantitative study of distinguishing adulteration in camellia oil by gas chromatography. Food Engineering 137:63–71
Yang F, Xue CY (2013) Research advancement of nutritional characteristics and functions of common edible oils. Food & Nutrition in China 19:63–66
Yang Y, Ferro MD, Cavaco I, Liang Y (2013) Detection and identification of extra virgin olive oil adulteration by GC-MS combined with chemometrics. J Agric Food Chem 61:3693–3702.
https://doi.org/10.1021/jf4000538 CrossRef Google Scholar
Zhang L, Shuai Q, Li P, Zhang Q, Ma F, Zhang W, Ding X (2016) Ion mobility spectrometry fingerprints: a rapid detection technology for adulteration of sesame oil. Food Chem 192:60–66.
https://doi.org/10.1016/j.foodchem.2015.06.096 CrossRef Google Scholar
Zhu W, Wang X, Chen L (2017) Rapid detection of peanut oil adulteration using low-field nuclear magnetic resonance and chemometrics. Food Chem 216:268–274.
https://doi.org/10.1016/j.foodchem.2016.08.051 CrossRef Google Scholar
Zou MQ, Zhang XF, Qi XH, Ma HL, Dong Y, Liu CW, Guo X, Wang H (2009) Rapid authentication of olive oil adulteration by Raman spectrometry. J Agric Food Chem 57:6001–6006.
https://doi.org/10.1021/jf900217s CrossRef Google Scholar Copyright information
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