Geographical specificity of fatty acid and multi-element fingerprints of soybean in northern China

Main Article Content

Cui Dong Sheng
Jia Hong Yu
Lai Han Qing
Wang Zhao Hui
Mao Xue Fei


soya bean, fingerprint characteristics, cluster heat map, geographical origin


Soybean is an important food crop in China. Recently, crops cultivated in specific geographical locations have started attracting high prices. Therefore, developing a technique to identify the geographical origin of a crop is crucial to prevent fraud. In this work, we measured the contents of five fatty acids and 17 elements in soybean samples produced in Heilongjiang, the Inner Mongolia Autonomous Region, Jilin and Liaoning using gas chromatography and inductively coupled plasma mass spectrometry. Correlation analysis, principal component analysis and cluster analysis were used to identify the relationship between the metabolic fingerprint and the geographical location. Our results showed a significant correlation between the contents of fatty acids and geographical origin. Principal component analysis provided a preliminary classification of all variables. Hierarchical clustering, based on heat maps, showed that all samples could be classified based on their geographical origins. The model established by partial least squares discriminant analysis showed 89.9% predictive ability, further proving that the 14 classification indexes, comprising fatty acids and elements, could be used as molecular fingerprints to identify and distinguish soybean samples from four different production areas. Besides, pairs of soybean sample fingerprints from the four provinces were compared, and the differences in fatty acid and element contents between the provinces were explained based on the climatic environment and soil distribution. In conclusion, our method of classifying and confirming soybean production areas through fatty acid and multi-element fingerprints can potentially be used for identifying soybean of similar origins.

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Alessandro, Z., Dora, M., Sonia, S., Antonia, Z. and Gian, L.M., 2018. Botanical traceability of unifloral honeys by chemometrics based on head-space gas chromatography. European Food Research and Technology 244: 2149–2157. 10.1007/s00217-018-3123-3

Aung, M.M. and Chang, Y.S., 2014. Traceability in a food supply chain: safety and quality perspectives. Food Control 39: 172–184. 10.1016/j.foodcont.2013.11.007

Cao, Y.Q., Xie, F.T., Dong, L.J., Wang, Y.Z., Song, S.H. and Wang, W.B., 2015. Research progress of oleic acid content in soybean seeds. Soybean Science 34: 329–334.

Chen, Y.H., Zhang, D.J., Zhang, G.F., Wang, Y. and Wang, C.Y., 2016. Construction of DNA fingerprint of the Japonica rice in Jiansanjiang area of Heilongjiang Province. Cereal & Feed Industry 07: 16–19.

Chung, I.-M., Kim, J.-K., Lee, J.-K. and Kim, S.-H., 2015. Discrimination of geographical origin of rice (Oryza sativa L.) by multielement analysis using inductively coupled plasma atomic emission spectroscopy and multivariate analysis. Journal of Cereal Science 65: 252–259. 10.1016/j.jcs.2015.08.001

Coelho, I., Matos, A.S., Teixeira, R., Nascimento, A., Bordado, J., Donard, O. and Castanheira, I., 2018. Combining multielement analysis and chemometrics to trace the geographical origin of Rocha Pear. Journal of Food Composition and Analysis 77: 1–8. 10.1016/j.jfca.2018.12.005

Cui, Y.J., Shi, Y.M., Liu, G.D. and Yang, X., 2008. Element content characteristics of black soil in Southern Songnen plain of Heilongjiang Province. Geoscience 22: 929–933.

Dai, Y.X., Liang, Y.T., Zhang, Y.H. and Zhang, J.H., 2014. Pollution status of lead and cadmium in some farmland soils in Chifeng city. Journal of Diseases Monitor & Control 8: 391–392.

Dornbos, D.L. and Mullen, R.E., 1992. Soybean seed protein and oil contents and fatty acid composition adjustments by drought and temperature. Journal of the American Oil Chemists Society 69: 228–231. 10.1007/BF02635891

Gonzálvez, A., Armenta, S. and Guardia, M.D.L., 2011. Geographical traceability of “Arròs de Valencia” rice grain based on mineral element composition. Food Chemistry 126: 1254–1260. 10.1016/j.foodchem.2010.11.032

Gu, Y.R., Zhang, T. and Bai, H.Y., 1995. Attribute classification of soil environmental background values in inner mongolia. Inner Mongolia Environmental Protection 01: 6–9.

Hao, M., Dai, X.D., Jiang, B. and Jin, L.M., 2016. Measurement of fatty acid in three kinds of tea by GC-MS. Tianjin Agricultural Sciences 22: 15–17.

Jiang, Z.Q., 2018. Research progress on traceability of grain origin produced by mineral element fingerprint analysis technology. Farm Products Processing 05: 70–71.

Jin, X.X., Pan, L.G. and Li, A., 2018. Progress in application of stable isotope technology in agricultural product safety. Vegetables 09: 29–34.

Li, L.Q., Wu, Z.Y., Zhang, Q. and Li, Y., 2014. State of the art review of the impact of climatic change on bioavailability of mineral elements in crops. Acta Ecologica Sinica 34: 1053–1060. 10.5846/stxb201305141057

Liao, J.F., 2004. Effect of soil environment on trace elements in crops. In: The 6th National Symposium on Research and Progress of Trace Elements in chinese chemical society, Fujian, China, p. Chinese Chemical Cociety 2004–12:3.

Liu, L., 2014. Nutritional components of soybean and its comprehensive utilization prospect. Journal of Inner Mongolia University for Nationalities (Natural Science Edition) 29: 175–178.

Ma, Y.Y., Guo, B.L., Wei, Y.M. and Zhao, H.Y., 2014. Research progress on traceability technology of origin of plant-derived food. Food Science 35: 246–250.

Mehari, B., Redi-Abshiro, M., Chandravanshi, B.S., Combrinck, S., McCrindle, R. and Atlabachew, M., 2019. GC-MS profiling of fatty acids in green coffee (Coffea arabica L.) beans and chemometric modeling for tracing geographical origins from Ethiopia. Journal of the Science of Food and Agriculture 99: 3811–3823. 10.1002/jsfa.9603

Michael, P.-R., Gaiad, J.E., Hidalgo, M.J., Avanza, M.V. and Pellerano, R.G., 2019. Classification of cowpea beans using multielemental fingerprinting combined with supervised learning. Food Control 95: 232–241. 10.1016/j.foodcont.2018.08.001

Pérez-Castaño, E., Medina-Rodríguez, S. and Bagur-González, M., 2019. Discrimination and classification of extra virgin olive oil using a chemometric approach based on TMS-4,4’-desmetylsterols GC(FID) fingerprints of edible vegetable oils. Food Chemistry 274: 518–525. 10.1016/j.foodchem.2018.08.128

Sun, X.Q., Mao, Z.X., Fu, H., Huang, D.J. and Li, Q., 2014. Fatty acid characteristics of forage and its influence factors. Pratacultural Science 31: 1774–1780.

Tian, X.J., Long, M., Wang, J., Ma, Z.R., Wei, Z.B., Chen, S.E., Gao, D.D. and Ding, B., 2018. Tracing the origin of wolfberry fruit based on odor information of electronic nose and multivariate statistical analysis. Acta Agriculturae Zhejiangensis 30: 1604–1611.

Wang, F., Zhao, H., Yu, C., Tang, J., Wu, W. and Yang, Q., 2020. Determination of the geographical origin of maize (Zea mays L.) using mineral element fingerprints. Journal of the Science of Food and Agriculture 100: 1294–1300. 10.1002/jsfa.10144

Wang, L.Y., 2012. Analysis of soil pollution in Tieling City. Journal of Environmental Management College of China 22: 60–63.

Wang, Z.H., Zheng, H., Zhao, Q. and Zhang, D.L., 2019. Canonical correspondence analysis on the distribution environment and mineral elements of Liuhe River Rice. Food Science 40: 318–324.

Wu, Y.Y., 1986. Background value of soil environment in Shenyang City. Environmental Protection Science 04: 24–28.

Xiao, R., Ma, Y., Zhang, D. and Qian, L., 2018. Discrimination of conventional and organic rice using untargeted LC-MS-based metabolomics. Journal of Cereal Science 82: 73–81. 10.1016/j.jcs.2018.05.012

Yun, W.L., Hou, Q. and Li, Y.W., 2013. Spatial distribution of soil hydrological characteristics in inner mongolia. Journal of Arid Land Resources and Environment 27: 193–197.

Zhang, J., Yang, R., Chen, R., Li, Y.C., Peng, Y. and Wen, X., 2019a. Geographical origin discrimination of pepper (Capsicum annuum L.) based on multi-elemental concentrations combined with chemometrics. Food Science and Biotechnology 28: 1627–1635. 10.1007/s10068-019-00619-3

Zhang, X., Han, D., Chen, X., Zhao, X., Cheng, J. and Liu, Y., 2019b. Combined use of fatty acid profile and fatty acid δC fingerprinting for origin traceability of scallops (Patinopecten yessoensis, Chlamys farreri, and Argopecten irradians). Food Chemistry 298: 124966. 10.1016/j.foodchem.2019.124966

Zhang, X., Liu, Y., Li, Y. and Zhao, X., 2017. Identification of the geographical origins of sea cucumber ( Apostichopus japonicus ) in northern China by using stable isotope ratios and fatty acid profiles. Food Chemistry 218: 269–276. 10.1016/j.foodchem.2016.08.083

Zhang, Y., Wang, D. and Li, X., 2018. Research progress on origin tracing of agricultural products based on near infrared spectroscopy. Journal of Food Safety & Quality 9: 6161–6166.

Zhao, Y., Si, W., Tian, G.Q. and He, X.R., 2018. Monitoring report on soybean production and market dynamics (August 2018). Soybean Science & Technology 04: 12–21.

Zhao, Y., Zhao, C., Li, Y., Chang, Y., Zhang, J., Zeng, Z., Lu, X. and Xu, G., 2014. Study of metabolite differences of flue-cured tobacco from different regions using a pseudotargeted gas chromatography with mass spectrometry selected-ion monitoring method. Journal of Separation Science 37: 2177–2184. 10.1002/jssc.201400097