DISCRIMINATION YEARS OF ROUGH RICE BY USING VISIBLE/NEAR INFRARED SPECTROSCOPY BASED ON INDEPENDENT COMPONENT ANALYSIS AND BP NEURAL NETWORK
基于独立组分分析和BP神经网络的可见/ 近红外光谱稻谷年份的鉴别

A new method for discrimination years of rough rice based on independent component analysis was developed by using visible/near infrared spectroscopy(Vis/NIRS).First,the Vis/NIR loading weight of rough rice with different years was got by using independent component analysis(ICA)and setting the wavelengths corresponding to the maximal correlation as the inputs of artificial neural network(ANN),then the discrimination model was build.120 samples(40 with each year)from three years were selected randomly as a calibration set;the left 60 samples(20 with each year)were as the prediction set.The discrimination rate of 100% was achieved.Synchronously,the sensitive wavelengths corresponding to the main components in rough rice were obtained with ICA.It indicates that the result for discrimination years of rough rice is very good based on ICA method,and it offers a new approach to the fast discrimination years of rough rice.