Welcome to Journal of Agriculture,

Journal of Agriculture ›› 2018, Vol. 8 ›› Issue (9): 71-79.doi: 10.11923/j.issn.2095-4050.cjas17090015

Previous Articles     Next Articles

Application of HS-SPME/GC-MS in Volatile Components Analysis of Green Coffee Beans from Major Production Areas in Yunnan Province

  

  • Received:2017-09-22 Revised:2017-11-02 Accepted:2017-12-25 Online:2018-09-19 Published:2018-09-19

Abstract: The paper aims to explore the volatile compounds and their relative contents of green coffee beans from major production areas in Yunnan Province, and find the characteristic chemical markers among different areas, as well as provide theoretical support for geographical origin traceability and flavor quality improvement of coffee beans. Green coffee beans from four geographical origins (Baoshan, Dehong, Lincang, and Pu’er) were used as experimental material in this study, the volatile compounds were determined by head-space solidphase microextraction coupled to gas chromatography-mass spectrometry (HS-SPME/GC-MS) and submitted to principal component analysis (PCA) and hierarchical cluster analysis (HCA) for multivariate statistical analysis. The results indicated that a total of 42 volatile components were identified in green coffee beans, the acids were the dominant volatile components and their relative contents accounted for 32.96%, followed by ketones, alcohols, hydrocarbons, esters, and aldehydes sequentially. PCA was applied to the data matrix (12 samples × 10 variables), the first principal component explained the information of pyrazines, acids, aldehydes, and hydrocarbon, and the second principal component accounted for the information of alcohols and phenols. HCA results demonstrated that these coffee samples could be clearly differentiated according to their geographical origins, which was in accordance with the results of PCA. This study obtained the volatile components correlated greatly with samples from specified areas, and could provide a theoretical basis for geographical origin identification and traceability of coffee beans from Yunnan Province.