Bayes逐步判别法在绿茶板栗香化学识别上的应用

由经验丰富的感官审评专家对各茶样进行感官审评,依据感官审评结果将茶样分为板栗香型、非板栗香型两大类;应用Bayes逐步筛选过程对具有板栗香茶样的共有成分先进行筛选,再以筛选出的香气成分为变量,建立判别方程。交叉验证和检验样本验证结果显示:用筛选出的顺-茉莉酮和香叶基丙酮建立的判别方程,在训练数据集判别和交叉验证中,判别正确率均达到94.44%;对8个检验样本都做出了正确的判断,正确率为100%,可认为,该判别方程有效,判别结果理想。此外,由顺-茉莉酮和香叶基丙酮的主成分图也可得出,筛选出的变量对板栗香与非板栗香具有很好的区分效果。

Application of Bayes Stepwise Discrimination Analysis on Chemical Recognition of Green Tea with Chestnut-like Aroma

The teas are classified into two categories—teas with chestnut-like aroma and other ones without chestnut-like aroma, according to the organoleptic evaluation results carried out by experienced experts. The screening process was conducted on the common components of teas with chestnut-like aroma along with the Bayes stepwise screening process, and set the aromatic components after screening as the variables. Then the discrimination equation was established. Results of cross-validation and validation of testing samples demonstrated that the correct rates of discrimination equation, established by cis-jasmone and geranylacetone, reached 94.44% in both discrimination analysis and cross-validation of training dataset, and the 8 testing samples are judged correctly, the correct rates of discrimination was 100%, Thus, it can be concluded that the discrimination equation worked effectively and the results was satisfactory. In addition, it can be seen that the chestnut-like aroma could be distinguished effectively by the selected variables in the principal components figure of cis-jasmone and geranylacetone.