对应分析用于中国茶叶化学数据的综合分析

Correspondence Factor and Correspondence Cluster Analysis as Applied to Studies on the Quality of Chinese Tea

本文试图将对应因子分析(CFA)与对应聚类分析(CCA)应用于中国茶叶样品化学分析数据的直接处理,以深入研究茶叶品质与化学组成、样品来源及其它特性的相互关系。结果表明,本文方法不仅与主成分分析相当,且可获得样品与变量之间的综合化学信息,是有发展前途的化学计量学方法。

The advantages of correspondence factor analysis (CFA) were briefly discussed as a multivariate statistical technique and a valuable tool for continuous chemical data exploration.A new method,correspondence cluster analysis (CCA),was suggested.Both of them were used to interpret the chemical analysis data of various tea samples in order to study the correlation among the quality of tea samples and their chemical composition, origin and various characteristic parameters.The results show that CFA and CCA are two useful and important chemometries techniques which can be applied to real-valued con- tinuous chemical data.