Studies on ANN Models of Determination of Tea Polyphenol and Amylose in Tea by Near-Infrared Spectroscopy
LUO Yi-fan1, 2, GUO Zhen-fei3, ZHU Zhen-yu4, WANG Chuan-pi1, JIANG He-yuan1, HAN Bao-yu1*
1.Key Laboratory of Tea Chemical Engineering of Ministry of Agriculture, Hangzhou 310008, China 2.College of Chemistry and Environment, South China Normal University, Guangzhou 510631, China 3.College of Biotechnology, South China Agricultural University, Guangzhou 510624, China 4.Basic Medical College of Zhongshan University, Guangzhou 510089, China
Abstract：The objectives of the present paper were to build the models for the determination of tea polyphenol (TP) and tea amylose (TA) in tea by near-infrared spectroscopy (NIR).According to the range of 7 432.3-6 155.7 cm-1 and 5 484.6-4 192.5 cm-1 of NIR spectra, the models are built for determining the contents of TP and TA in tea with the input layer, hidden layer and node ((8，4，1) and (7，5，1) respectively) in network structure by the artificial neural network.The correlation coefficient (ｒ), the root mean square error of cross validation (RMSECV) and the root mean square error of prediction (RMSEP) were selected as the indexes for evaluating the performance of calibration models.The results show that ｒ, RMSECV and RSECV by the model samples for TP and TA are 0.984 7，0.460 and 0.123，and 0.947 0，0.136 and 0.224 respectively，and ｒ, RMSEP and RSEP by the prediction samples for TP and TA are 0.980 4，0.529 and 0.017, and 0.968 2，0.111 and 0.029 8 respectively.These indicated that the NIR-ANN models can be used to determine the contents of TP and TA in tea.
罗一帆1，2，郭振飞3，朱振宇4，王川丕1，江和源1，韩宝瑜1* . 近红外光谱测定茶叶中茶多酚和茶多糖的人工神经网络模型研究[J]. 光谱学与光谱分析, 2005, 25(08): 1230-1233.
LUO Yi-fan1, 2, GUO Zhen-fei3, ZHU Zhen-yu4, WANG Chuan-pi1, JIANG He-yuan1, HAN Bao-yu1* . Studies on ANN Models of Determination of Tea Polyphenol and Amylose in Tea by Near-Infrared Spectroscopy . SPECTROSCOPY AND SPECTRAL ANALYSIS, 2005, 25(08): 1230-1233.
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