Title: | Fingerprinting of Volatile Organic Compounds for the Geographical Discrimination of Rice Samples from Northeast China |
Author(s): | Asimi S; Ren X; Zhang M; Li S; Guan L; Wang Z; Liang S; Wang Z; |
Address: | "Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology and Business University, Beijing 100048, China. Beijing Engineering and Technology Research Center of Food Additives, Beijing Technology and Business University, 11 Fucheng Road, Beijing 100048, China" |
ISSN/ISBN: | 2304-8158 (Print) 2304-8158 (Electronic) 2304-8158 (Linking) |
Abstract: | "Rice's geographic origin and variety play a vital role in commercial rice trade and consumption. However, a method for rapidly discriminating the geographical origins of rice from a different region is still lacking. Therefore, the current study developed a volatile organic compound (VOC) based geographical discrimination method using headspace gas chromatography-mass spectrometry (HS-GC-MS) to discriminate rice samples from Heilongjiang, Jilin, and Liaoning provinces. The rice VOCs in Heilongjiang, Liaoning, and Jilin were analyzed by agglomerative hierarchical clustering (AHC), principal component analysis (PCA), and partial least squares discriminant analysis (PLS-DA). The results show that the optimum parameters for headspace solid phase microextraction (HS-SPME) involved the extraction of 3.0 g of rice at 80 degrees C within 40 min. A total of 35 VOCs were identified from 30 rice varieties from Northeast China. The PLS-DA model exhibited good discrimination (R(2) = 0.992, Q(2) = 0.983, and Accuracy = 1.0) for rice samples from Heilongjiang, Liaoning, and Jilin. Moreover, K-nearest neighbors showed good specificity (100%) and accuracy (100%) in identifying the origin of samples. In conclusion, the present study established VOC fingerprinting as a highly efficient approach to identifying rice's geographical origin. Our findings highlight the ability to discriminate rice from Heilongjiang, Liaoning, and Jilin provinces rapidly" |
Keywords: | Hs-gc-ms authenticity geographical origin partial least squares discriminant analysis (PLS-DA) rice volatile organic compound; |
Notes: | "PubMed-not-MEDLINEAsimi, Sailimuhan Ren, Xin Zhang, Min Li, Sixuan Guan, Lina Wang, Zhenhua Liang, Shan Wang, Ziyuan eng KM202010011006/General S& T project of Beijing Municipal Commission of Education/ 32101876/National Science Foundation of China/ Switzerland 2022/06/25 Foods. 2022 Jun 9; 11(12):1695. doi: 10.3390/foods11121695" |