发酵是工夫红茶加工的关键工序,对红茶品质形成起着极其重要的作用。本文提出一种基于嗅觉可视化技术的工夫红茶发酵程度判定方法。基于硅胶薄层层析板与16种卟啉衍生物设计构建了嗅觉可视化传感器及气体检测系统,用于工夫红茶发酵过程中挥发性气体数据采集。采用Fisher判别分析与BP-AdaBoost算法建立工夫红茶发酵程度判别模型。分析表明,Fisher判别函数可以实现不同发酵程度红茶100%分类,交叉验证分组正确率达90.74%;BP-AdaBoost算法建立判别模型,训练集相关系数（Rc）和预测集相关系数（Rp）分别为0.9578和0.9132;嗅觉可视化技术可以实现工夫红茶发酵程度判定,为工夫红茶发酵过程实时监控提供了理论依据。
Abstract
As the crucial procedure for production of black tea, fermentation plays an important role in quality control of black tea. This paper proposed a colorimetric sensor array-based artificial olfaction system to monitor black tea fermentation. Herein, a colorimetric sensor array by printing 16 chemical dyes including porphyrins/metalloporphyrins on a Silica gel thin-layer chromatography plate was utilized to detect volatile gases during black tea fermentation. Discrimination model was established by fisher discriminatory analysis and adaptive boosting algorithm based on BP-ANN (BP-Adaboost). Results showed that the discrimination rate and discrimination rate of cross-validation reached 100% and 90.74% respectively. BP-Adaboost model showed that the correlation coefficient of calibration set (Rc) and prediction set (Rp) were 0.9578 and 0.9132 respectively. This work demonstrates that it is feasible to distinguish the degree of black tea fermentation using a colorimetric sensor array-based artificial olfaction system.
关键词
BP-AdaBoost算法 /
Fisher判别 /
发酵程度 /
红茶
Key words
black tea /
BP-Adaboost algorithm /
fermentation degree /
Fisher discriminatory analysis
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参考文献
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基金
浙江省自然科学基金（LY16C160002）、浙江省重点研发计划（2015C02001）、国家星火计划（2015GA700006）
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