基于遗传算法的安溪铁观音品质快速评价研究

为探究一种快速无损的安溪铁观音品质评价方法,利用遗传算法(GA)对茶样的近红外光谱特征波长进行筛选,结合偏最小二乘(PLS),建立全谱段的PLS定量模型与GA-PLS模型。结果表明,傅里叶变换近红外(FT-NIR)全谱段光谱在经过平滑+二阶导数+归一化处理后,PLS模型预测性能最高,建模结果为:校正集相关系数R_C=0.921,校正集均方根误差RMSEC=0.543,验证集相关系数R_P=0.913,验证集均方根误差RMSEP=0.665。选用近红外光谱6 670~4 000cm-1谱区,采用遗传算法进行特征波长筛选,参与建模数据点数从1 557缩减到408个。优选波段后,GA-PLS建模结果为:校正集相关系数R_C=0.959,校正集均方根误差RMSEC=0.413,验证集相关系数R_P=0.940,验证集均方根误差RMSEP=0.587。可见,GA-PLS模型的校正集和验证集的预测结果均优于全谱段PLS模型。结果说明,在传统的近红外光谱技术结合化学计量学方法的建模基础上,加入遗传算法进行波长筛选,能有效提高模型预测能力,实现方法学的创新研究,且GA-PLS品质评价模型具有较强的参考和推广价值,为提高我国茶叶品质的检测技术水平提供新的方法借鉴。

Rapid Quality Evaluation of Anxi Tieguanyin Tea Based on Genetic Algorithm

Anxi Tieguanyin tea was collected as the researc h materials in this study.In order to find a fast and non-destructive method f or rapid quality evaluation of Anxi Tieguanyin tea,the Genetic Algorithm (GA) w as applied to wavelength selection befoe it is combined with partial least squar es (PLS) to construct PLS and GA-PLS calibration model.The results showed that the PLS model displayed the highest prediction performance after the Fourier tr ansform near-infrared (FT-NIR) spectrum being processed by smoothing,the seco nd derivative and normalized methods.Statistic results with PLS:RC=0.921,RMSEC=0.543,RP=0.913,RMSEP=0.665.NIR spectra ranging from 6 670 to 4 000 cm-1 wer e selected,and 1 557 data volume for building calibration model were reduced to408 with Genetic algorithm.Statistic results with GA-PLS:RC=0.959,RM SEC=0.413,RP=0.940,RMSEP=0.587.It has shown that the prediction precision of calibration set and validation set of GA-PLS model is better than those of PLS model.According to the results,it can effectively improve the prediction a bility of the model when the Genetic Algorithm (GA) is applied to select the wav elengths in a traditional model which is based on the near infrared spectroscopy combined with partial least squares.It can also achieve the innovation of the methodology.Furthermore,the quality evaluation GA-PLS model provides strong reference and possesses promotional value.In addition,it provides valuable ref erence and new avenue for improving the standard of detection technology of tea quality in China.