The multi-elemental isotope ratios analysis of oranges by ICP-MS and their geographic origin identification
Main Article Content
Keywords
inductively coupled plasma mass spectrometry, chemometrics, geographic origin, orange
Abstract
Inductively coupled plasma mass spectrometry was utilised to analyse the isotope ratios of 67 orange samples from different regions in China. To achieve geographic origin identification of the oranges, principal component analysis linear discriminant analysis (LDA) and partial least squares regression (PLSR) have been used. Twelve isotope ratios were considered as the significant variables by PLSR. A percentage of original classification was 97.0%, and the cross-validated rate of classification was 92.5% by the approach of LDA combine with PLSR. The results indicated that chemometrics techniques, combined with isotope ratios, were effective for the classification of oranges with geographical features. This study provided a theoretical reference for the discrimination and classification of oranges in China. It could be used as a theoretical reference for oranges discrimination worldwide.
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Zain, S.M., Behkami, S., Bakirdere, S. and Koki, I.B., 2016. Milk authentication and discrimination via metal content clustering – a case of comparing milk from Malaysia and selected countries of the world. Food Control 66: 306-314.
Zhao, H.Y., Guo, B.L., Wei, Y.M. and Zhang, B., 2012. Effects of wheat origin, genotype, and their interaction on multielement fingerprints for geographical traceability. Journal of Agricultural and Food Chemistry 60: 10957-10962.
Barbosa, R.M., Batista, B.L., Varrique, R.M., Coelho, V.A., Campiglia, A.D. and Barbosa, F., 2014. The use of advanced chemometric techniques and trace element levels for controlling the authenticity of organic coffee. Food Research International 61: 246-251.
Ben Mansour, A., Gargouri. B., Melliou. E., Magiatis, P. and Bouaziz, M., 2016. Oil quality parameters and quantitative measurement of major secoiridoid derivatives in Neb Jmel olive oil from various Tunisian origins using qNMR. Journal of the Science of Food and Agriculture 96: 4432-4439.
Burns, D.T., Tweed, L. and Walker, M.J., 2017. Ground roast coffee: review of analytical strategies to estimate geographic origin, species authenticity and adulteration by dilution. Food Analytical Methods 10: 2302-2310.
Chung, I.M., Kim, J.K., Prabakaran, M., Yang, J.H. and Kim, S.H., 2016. Authenticity of rice (Oryza sativa L.) geographical origin based on analysis of C, N, O and S stable isotope ratios: a preliminary case report in Korea, China and Philippine. Journal of the Science of Food and Agriculture 96: 2433-2439.
Cossignani, L., Blasi, F., Simonetti, M.S. and Montesano, D., 2018. Fatty acids and phytosterols to discriminate geographic origin of lycium barbarum berry. Food Analytical Methods 11: 1180-1188.
Gamboa-Becerra, R., Montero-Vargas, J.M., Martinez-Jarquin, S., Galvez-Ponce, E., Moreno-Pedraza, A. and Winkler, R., 2017. Rapid classification of coffee products by data mining models from direct electrospray and plasma-based mass spectrometry analyses. Food Analytical Methods 10: 1359-1368.
Geana, E.I., Sandru, C., Stanciu, V. and Ionete, R.E., 2017. Elemental profile and Sr-87/Sr-86 isotope ratio as fingerprints for geographical traceability of wines: an approach on Romanian Wines. Food Analytical Methods 10: 63-73.
Geana, I., Iordache, A., Ionete, R., Marinescu, A., Ranca, A. and Culea, M., 2013. Geographical origin identification of Romanian wines by ICP-MS elemental analysis. Food Chemistry 138: 1125-1134.
Giannetti, V., Mariani, M.B., Mannino, P. and Marini, F., 2017. Volatile fraction analysis by HS-SPME/GC-MS and chemometric modeling for traceability of apples cultivated in the Northeast Italy. Food Control 78: 215-221.
Guo, X., Huang, F., Zhang, H., Zhang, C.J., Hu, H.H. and Chen, W.B., 2016. Classification of traditional Chinese pork bacon based on physicochemical properties and chemometric techniques. Meat Science 117: 182-186.
Jandric, Z., Frew, R.D., Fernandez-Cedi, L.N. and Cannavan, A., 2017. An investigative study on discrimination of honey of various floral and geographical origins using UPLC-QToF MS and multivariate data analysis. Food Control 72: 189-197.
Kruzlicova, D., Fiket, Z. and Kniewald, G., 2013. Classification of Croatian wine varieties using multivariate analysis of data obtained by high resolution ICP-MS analysis. Food Research International 54: 621-626.
Li, J.J., Fu, B.B., Huo, D.Q., Hou, C.J., Yang, M., Shen, C.H., Luo, H.B. and Yang, P., 2017. Discrimination of Chinese teas according to major amino acid composition by a colorimetric IDA sensor. Sensors and Actuators B: Chemical 240: 770-778.
Luykx, D. and Van Ruth, S.M., 2008. An overview of analytical methods for determining the geographical origin of food products. Food Chemistry 107: 897-911.
Mandrile, L., Zeppa, G., Giovannozzi, A.M. and Rossi, A.M., 2016. Controlling protected designation of origin of wine by Raman spectroscopy. Food Chemistry 211: 260-267.
Manton, W.I., 2010. Determination of the provenance of cocoa by soil protolith ages and assessment of anthropogenic lead contamination by Pb/Nd and lead isotope ratios. Journal of Agricultural and Food Chemistry 58: 713-721.
Martin, A.E., Watling, R.J. and Lee, G.S., 2012. The multi-element determination and regional discrimination of Australian wines. Food Chemistry 133: 1081-1089.
Oliveira, L.F., Braga, S., Augusto, F., Hashimoto, J.C., Efraim, P. and Poppi, R.J., 2016. Differentiation of cocoa nibs from distinct origins using comprehensive two-dimensional gas chromatography and multivariate analysis. Food Research International 90: 133-138.
Selih, V.S., Sala, M. and Drgan, V., 2014. Multi-element analysis of wines by ICP-MS and ICP-OES and their classification according to geographical origin in Slovenia. Food Chemistry 153: 414-423.
Song, B.Y., Ryu, J.S., Shin, H.S. and Lee, K.S., 2014. Determination of the source of bioavailable Sr using Sr-87/Sr-86 tracers: a case study of hot pepper and rice. Journal of Agricultural and Food Chemistry 62: 9232-9238.
Song, S.Q., Zhang, X.M., Hayat, K., Huang, M.G., Liu, P., Karangwa, E., Gu, F.L., Jia, C.S., Xia, S.Q., Xiao, Z.B. and Niu, Y.W., 2010. Contribution of beef base to aroma characteristics of beeflike process flavour assessed by descriptive sensory analysis and gas chromatography olfactometry and partial least squares regression. Journal of Chromatography A 1217: 7788-7799.
Sun, H.W., Xia, L.Y., Liang, S.Z. and Shen, S.G., 2014. The correlation of inorganic anion contents in rice and its soils based on four geographical origin. Food Analytical Methods 7: 1791-1797.
Vetrova, O.V., Kalashnikova, D.A., Melkov, V.N. and Simonova, G.V., 2017. Detection of honey adulterations with sugar syrups by stable isotope mass spectrometry. Journal of Analytical Chemistry 72: 756-760.
Yang, R., 2011. The economic value evaluation of geographical indication products. Chinese Agricultural Science Bulletin 27: 432-435.
Zain, S.M., Behkami, S., Bakirdere, S. and Koki, I.B., 2016. Milk authentication and discrimination via metal content clustering – a case of comparing milk from Malaysia and selected countries of the world. Food Control 66: 306-314.
Zhao, H.Y., Guo, B.L., Wei, Y.M. and Zhang, B., 2012. Effects of wheat origin, genotype, and their interaction on multielement fingerprints for geographical traceability. Journal of Agricultural and Food Chemistry 60: 10957-10962.
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Dec 10, 2018
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