基于近红外光谱法的大佛龙井茶品质评价研究

为探索科学、客观的茶叶品质评价方法，以大佛龙井茶为分析对象，采用近红外光谱偏最小二乘法(NIRS-PLS)，分别建立了干茶色泽、汤色、香气、滋味、叶底单因子得分及五因子总分、六因子总分共7个定量分析模型。结果表明，在主成分因子数不大于10的情况下，各模型校正相关系数R_c为90.48%～98.43%，校正均方根误差RMSEC为1.14～2.09，预测相关系数R_p为90.00%～96.65%，预测均方根误差RMSEP为1.52～2.84，7个模型校正集和预测集均获得较高的拟合度;其中五因子总分模型预测性能最好(R_p为96.65%、RMSEP为1.52)，同时，总分模型精度均高于单因子模型。研究结果表明应用近红外光谱法进行大佛龙井茶的品质评价是可行的。

Study on Quality Evaluation of Dafo Longjing Tea Based on Near Infrared Spectroscopy

Seven quantitative analysis models for Dafo Longjing tea, including tea color, liquor color, aroma, taste, infused leaf, total points of five factors and total points of six factors, were built by applying near infrared spectroscopy combined with partial least squares (NIRS-PLS), in order to find a objective and scientific method for tea quality evaluation. Results showed that both the calibration samples and the prediction samples of the seven models had acquired a high fitting degree when the number of principal components was below 10, and the value of R_c, RMSEC, R_p and RMSEP were between 90.48%～98.43%, 1.14%～2.09%, 90.00%～96.65%, and 1.52%～2.84%, respectively. Among them, the total points of five factors model had the best prediction performance, and the value of R_p and RMSEP was 96.65% and 1.52%, respectively. Moreover, it was also found that the prediction precision of total points models were higher than that of single factor ones. It seems that the quality evaluation of Dafo Longjing tea could be realized by using NIRS-PLS to some extent.