中文摘要：

应用近红外光谱技术,以偏最小二乘算法,计算预测了37种生药药材甲醇提取物的抗氧化活性。以交叉验证相关系数（R2）,交叉验证误差均方根（RMSECV）为指标,考察、比较了光谱预处理方法对模型效果的影响,以预测误差均方根（RMSEP）和相对分析误差（RPD）考核了样本的预测效果,采用1,1-二苯基-2-苦肼基（DPPH）法进行了验证。研究表明,采用一阶导数＋矢量归一化预处理法和筛选的近红外波段建模,预测性能最优,校正模型的R2为0.896 0,RMSECV为4.35%;预测样本的RMSEP为3.62%,RPD为2.38。近红外光谱分析技术便捷快速,可信度较高,可以用于生药抗氧化性质的整体评价。

英文摘要：

A prediction model was built to estimate the antioxidant property of methanol extracts of 38 crude drugs using Near Infrared Spectroscopy（NIS）with partial least squares（PLS）regression method.In order to enhance the chemical information and reduce data systemic noise,the effect of spectral pretreatment methods on the model were compared according to the correlation coefficients of cross validation（R2）and the root mean square errors of cross validation（RMSECV）.Prediction effects of the samples were investigated with the root mean square errors of prediction（RMSEP）,and the residual predictive deviation（RPD）.The DPPH method was employed for verification.The present results showed that the calibration model was developed by first derivative＋vector normalization with the selected spectral region,R2,RMSECV,RMSEP,and RPD were 0.896 0,4.35%,3.62%,and 2.38,respectively.The NIS model established in the present study was relatively stable,accurate and reliable for overall evaluation of antioxidant activity of crude drugs.However,it was necessary to improve the precision and the robustness of the model for practice.