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Classification of Maojian Teas from Different Geographical Origins by Micellar Electrokinetic Chromatography and Pattern Recognition Techniques

机译:通过胶束电动色谱法和图案识别技术从不同地理起源的毛泽东分类分类

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A micellar electrokinetic chromatography (MEKC) method was applied for the identification of geographical origins of Chinese green teas. Under the optimized conditions, chromatographic profiling of collected Maojian tea samples was obtained. Based on MEKC-UV profiling, twenty-four tea samples were successfully differentiated according to the relative peak areas of selected peaks in the chromatograms. Tea samples from Hubei and Henan provinces were classified correctly by hierarchical cluster analysis model (HCA) and principal component analysis (PCA). The application of linear discriminant analysis (LDA) gave correct assignation percentages of 100% for the training set and the prediction set. The overall results demonstrated that MEKC with pattern recognition could be successfully applied to discriminate Maojian teas according to their geographical origins.
机译:胶束电动色谱(MEKC)方法用于鉴定中国绿色茶的地理起源。在优化的条件下,获得了收集的毛剑茶样品的色谱分析。基于MEKC-UV谱分析,根据色谱图中所选峰的相对峰面积成功地分化了二十四个茶样品。通过分层集群分析模型(HCA)和主成分分析(PCA)正确地分类湖北和河南省省份的茶样品。线性判别分析(LDA)的应用使训练集的正确分配百分比为100%和预测集。总体结果表明,MEKC具有模式识别的MEKC可成功应用以根据其地理起源来鉴别毛泽东茶。

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