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J Mass Spectrom

Title:		Geographical discrimination of Chinese winter wheat using volatile compound analysis by HS-SPME/GC-MS coupled with multivariate statistical analysis
Author(s):		Wadood SA; Boli G; Xiaowen Z; Raza A; Yimin W;
Address:		"Institute of Food Science and Technology, Key Laboratory of Agro-Products Processing, CAAS, Ministry of Agriculture and Rural, Beijing, China. Beijing Advanced Innovation Center for Food Nutrition and Human Health, Laboratory of Molecular Sensory Science, Beijing Technology and Business University, Beijing, China"
Journal Title:		J Mass Spectrom
Year:		2020
Volume:		20191216
Issue:		1
Page Number:		e4453 -
DOI:		10.1002/jms.4453
ISSN/ISBN:		1096-9888 (Electronic) 1076-5174 (Linking)
Abstract:		"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 10 different wheat cultivars among three regions were examined by headspace solid phase microextraction 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 analysis of variance showed a significant influence of regions, wheat genotypes, and their interaction on the volatile composition of wheat. Principal component analysis 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"
Keywords:		China Discriminant Analysis Gas Chromatography-Mass Spectrometry/*methods Geography Multivariate Analysis Principal Component Analysis/methods Solid Phase Microextraction/*methods Triticum/*chemistry Volatile Organic Compounds/*analysis Hs-spme/gc-ms cult;
Notes:		"MedlineWadood, Syed Abdul Boli, Guo Xiaowen, Zhang Raza, Ali Yimin, Wei eng Chinese Academy of Agricultural Sciences (CAAS)/ Chinese Agricultural Research System/ 31371774/National Natural Science Foundation of China/ England 2019/10/28 J Mass Spectrom. 2020 Jan; 55(1):e4453. doi: 10.1002/jms.4453. Epub 2019 Dec 16"