本文采用化学指标、电子舌技术与主成分分析（PCA）对海南兴隆地区不同烘焙度咖啡豆的滋味特性进行研究。结果表明：随着烘焙度增加，总固形物、总可溶性固形物、有机酸含量及可滴定酸度先增加后减少，pH值先减少后增加，葫芦巴碱含量逐渐减少，咖啡因含量基本不变，导致不同烘焙度的咖啡豆具有不同的滋味特性。原始电子感官数据经归一化处理后，采用PCA对其进行解析，可将样品大致分为四类：第一类包括极浅度（JQ）；第二类包括浅度（Q）、浅中度（QZ）和中度（Z）；第三类包括中深度（ZS）和深度（S）；第四类包括极深度（JS）和法式重度（FZ）。电子舌技术能有效鉴别不同烘焙度咖啡，且各类样品对传感器响应强度差异明显，在PCA的二维投影图上可区分开，并与滋味特性化学指标具有相关性。

Chemical indices and electronic tongue combined with principal component analysis (PCA) were used in this study to analyze the taste characteristics of coffee beans from the Xinglong region of Hainan roasted to different degrees. The results indicated that with increasing roasting degree, the contents of total solids, total soluble solids, and organic acids, as well as titratable acidity first increased and then decreased, the pH value first decreased and then increased, the trigonelline content decreased gradually, and the caffeine content remained essentially unchanged, leading to differences in the taste characteristics of coffee beans with different roasting degrees. After the raw electronic sensory data were normalized, PCA was performed and the coffee samples could be divided into four categories. The first category included extremely light (JQ) samples, the second category included light (Q), light medium (QZ), and medium (Z) samples, the third category included medium dark (ZS) and dark (S) samples, and the fourth category included extremely dark (JS) and French roast (FZ) samples. Electronic tongue combined with PCA could differentiate the coffee samples with different roasting degrees effectively. Additionally, the response intensities of different coffee samples to the sensor were significantly different; all samples could be grouped in the PCA biplot and were clearly correlated with the chemical indices of taste characteristics.

国家自然科学基金项目（31501404）；海南省应用技术研发与示范推广专项（ZDXM2015052)