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Geographical discrimination of Chinese winter wheat using volatile compounds analysis by HS-SPME/GC-MS coupled with multivariate statistical analysis.

This study aimed to develop a potential analytical method to discriminate the Chinese winter wheat according to geographical origin and cultivars. A total of 90 wheat samples of ten different wheat cultivars among three regions were examined by headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS). The peak areas of 32 main volatile compounds were selected and subjected to statistical analysis which revealed significant differences among different regions and cultivars. Multivariate ANOVA showed a significant influence of regions, wheat genotypes, and their interaction on the volatile composition of wheat. Principal component analysis (PCA) of the aromatic profile showed better visualization for wheat geographical origins. Finally, a classification model based on the linear discriminant analysis was successfully constructed for the discrimination of regions and cultivars with the correct classification percentages of 90 and 100%, respectively.