基于近红外光谱的黄山毛峰茶鲜叶品质分析及等级快速评价

Study on quality analysis and class rapid evaluation of tea leaf materials based on near infrared technology

为科学分析茶鲜叶品质,快速直观评价鲜叶等级,采用偏最小二乘(PLS)法建立茶鲜叶中含水率、全氮量和粗纤维含量的近红外定量模型,通过分析近红外光谱-鲜叶内含成分-鲜叶等级间相关性,得到鲜叶等级近红外预测模型。结果表明,茶鲜叶中含水率、全氮量、粗纤维预测模型相关系数(RP)分别为0.9109,0.8989,0.8895,预测均方根误差(RMSEP)为0.361,0.103,0.195,鲜叶等级NIR模型的判别率为93.10%,模型有较高的预测性能。在此基础上自主研发的SNIR-2101茶叶品质分析仪适用性良好,这为茶鲜叶品质分析和等级快速评价提供新思路。

Three quantitative analysis models for fresh tea leaves,including moisture,total nitrogen and crude fiber,were built by applying near infrared spectroscopy combined with partial squares（NIR-PLS）,in order to analyze the quality of the fresh tea leaves,class correlation model based on three main contents by BP-ANN were built. Results showed that both the calibration samples and the prediction samples of models had acquired a high fitting degree,the value of RPwere 0.9109,0.8989,0.8895,RMSEP were 0.361,0.103,0.195.Based on the high correlation between near-infrared spectroscopy,fresh tea leaves component and class,class model were built by NIR-PLS,the discrimination ratio were 93.10%,the model had high prediction precision.This provided a new way of thinking for quality analysis and class rapid evaluation of tea leaf materials.