利用HS-SPME/GC-MS法对云南主产区生咖啡豆中挥发性成分萃取与分析研究

为探究云南主产区生咖啡豆中挥发性成分的含量及组成方式，明晰地区间存在差异的特征性标志化合物，为咖啡豆的产地追溯及风味品质提升提供理论支撑，以云南保山、德宏、临沧和普洱4 个地区的生咖啡豆为试材，采用顶空固相微萃取-气相色谱质谱联用法(HS-SPME/GC-MS)检测，结合主成分分析(PCA)和系统聚类分析(HCA)对不同地区样品进行分类。结果表明：从4 个地区的生咖啡豆中共鉴定出42 种挥发性物质，主要以酸类为主，相对含量占32.96%，其次为酮类、醇类、碳氢类、酯类及醛类等。对不同地区样品进行主成分分析，第一主成分主要反映吡嗪类、酸类、醛类和碳氢类的信息，第二主成分主要反映醇类和酚类的信息。对不同地区样品进行聚类分析，可各自聚为一类，与主成分分析结果一致。试验获得了与特定地区样品相关性较大的挥发性物质，为云南主产区咖啡豆的分类鉴别及产地追溯提供理论参考。

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

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.