FT-NIR光谱法测定烟草中绿原酸、芸香苷、莨菪亭及总多酚含量

研究应用傅里叶变换近红外光谱法快速测定烟草中绿原酸、芸香苷、莨菪亭及总多酚含量的可行性。使用偏最小二乘法(PLS)为建模方法, 选择7 500～4 000 cm-1谱段，采用二阶导数和Norris滤波法进行光谱预处理，建立了烟草中绿原酸、芸香苷、莨菪亭及总多酚的近红外预测模型。组分最佳PLS预测模型的相关系数r分别为0.976 6，0.941 9，0.957 1和0.966 6，SEP均小于1.2倍的SEC，验证集样本的标准偏差(SD)/SEP均大于2。交叉检验的均方差(RMSECV)分别为1.938 9，1.046 2，0.047 9和2.745 2。实验验证了模型偏差的显著性，将近红外光谱技术与常规标准检测方法相比较。结果表明:两种方法测得值在显著水平0.05时，不存在显著性差异，近红外光谱技术可以准确地定量分析烟草中绿原酸、芸香苷、莨菪亭及总多酚。

Determination of Chlorogenic Acid, Rutin, Scopoletin and Total Polyphenol in Tobacco by Fourier Transform Near Infrared Spectroscopy

The objective of the present study was to investigate the feasibility of predicting chlorogenic acid, rutin, scopoletin and total polyphenol in tobacco by Fourier transform near-infrared (FT-NIR) spectroscopy. The partial least squares(PLS) regression method, second derivative and Norris derivative filter were applied in the NIR spectroscopy prediction of chlorogenic acid, rutin, scopoletin and total polyphenol in the range of 7 500 to 4 000 cm-1. For chlorogenic acid, rutin, scopoletin and total polyphenol, the determination coefficients were 0.976 6, 0.941 9, 0.957 1 and 0.966 6, respectively. The SEP/SEC values for them were <1.2, and the SD/SEP values for them were >2. The root mean square error of cross validation (RMSECV) of the four calibration models were 1.938 9, 1.046 2, 0.047 9 and 2.745 2, respectively. NIR spectroscopy was compared with the conventional methods. The results show that the two methods showed no significant difference at the significant level of 0.05. NIR spectroscopy technology can accurately analyze chlorogenic acid, rutin, scopoletin and total polyphenol in tobacco.