Leng Hong-Qiong, Guo Ya-Dong, Liu Wei, Zhang Tao, Deng Liang, Shen Zhi-Qiang
School of Pharmaceutical Science & Yunnan Key Laboratory of Pharmacology for Natural Products, Kunming Medical University, Kunming 650500, China.
Guang Pu Xue Yu Guang Pu Fen Xi. 2013 Jul;33(7):1801-4.
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.
本研究的目的是探讨采用傅里叶变换近红外（FT-NIR）光谱法预测烟草中绿原酸、芦丁、东莨菪素和总多酚的可行性。采用偏最小二乘法（PLS）回归方法、二阶导数和诺里斯导数滤波器，在7500至4000 cm(-1)范围内对烟草中的绿原酸、芦丁、东莨菪素和总多酚进行近红外光谱预测。对于绿原酸、芦丁、东莨菪素和总多酚，测定系数分别为0.976 6、0.941 9、0.957 1和0.9——6 6。它们的SEP/SEC值<1.2，SD/SEP值>2。四个校正模型的交叉验证均方根误差（RMSECV）分别为1.938 9、1.046 2、0.047 9和2.745 2。将近红外光谱法与传统方法进行了比较。结果表明，在0.05的显著水平下，两种方法无显著差异。近红外光谱技术可准确分析烟草中的绿原酸、芦丁、东莨菪素和总多酚。 （注：原文中“0.9——6 6”可能有误，翻译时保留原样）
