Main Article Content
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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