College of Chemical Engineering, Sichuan University of Science & Engineering, Zigong, 643000, China.
Luzhou Laojiao Group Co. Ltd, Luzhou, 646000, China.
J Food Sci. 2021 May;86(5):1861-1877. doi: 10.1111/1750-3841.15692. Epub 2021 Apr 6.
In order to differentiate and characterize Chinese Luzhou-flavor liquor according to geographical origins, the volatile flavor compounds were analyzed for forty commercial Luzhou-flavor liquor samples from Sichuan, Jiangsu, and Hubei provinces. A total of 113 volatile flavor compounds were quantified; among them, 29 flavor compounds were quantified according to the internal standard method. The differences in flavor composition among different brands of Luzhou-flavor liquor were compared. A data matrix of 64 (flavor components) × 40 (samples) was studied and interpreted using chemometric analysis. The research object could be naturally clustered according to geographical origin (brand) based on the hierarchical cluster analysis (HCA), principal component analysis (PCA) and multivariate analysis of variance (MANOVA) methods. A 100% of predication ability was obtained by the application of K-nearest neighbor model (KNN) for study sample classification. The results demonstrate that the abundance of volatile flavor components in liquors combined with appropriate multivariate statistical methods could be used for the division and traceability of liquors from different geographic origins. PRACTICAL APPLICATION: This study can provide the basis for the identification of liquor authenticity and the traceability of liquor.
为了根据地理起源对中国浓香型白酒进行区分和特征描述，对来自四川、江苏和湖北的 40 个商业浓香型白酒样品中的挥发性风味化合物进行了分析。共定量了 113 种挥发性风味化合物；其中，29 种风味化合物采用内标法进行定量。比较了不同品牌浓香型白酒的风味组成差异。使用化学计量学分析对 64（风味成分）×40（样品）的数据矩阵进行了研究和解释。基于层次聚类分析（HCA）、主成分分析（PCA）和多元方差分析（MANOVA）方法，研究对象可根据地理起源（品牌）自然聚类。应用 K-最近邻模型（KNN）对研究样本进行分类，可获得 100%的预测能力。结果表明，可利用酒中挥发性风味成分的丰度结合适当的多元统计方法，对来自不同地理起源的酒进行划分和溯源。实际应用：本研究可为鉴别酒的真伪和追溯酒的来源提供依据。
