NEW APPROACH OF DISCRIMINATION OF VARIETIES OF JUICY PEACH BY NEAR INFRARED SPECTRA BASED ON PCA AND MDA MODEL
基于主成分和多类判别分析的可见-红外光谱水蜜桃品种鉴别新方法

A new method for discrimination of varieties of juicy peach by means of visible-near infrared spectroscopy(NIRS) was developed.First,the spectral curves of three varieties juicy peaches were measured by spectrometer;the pretreated spectra data of juicy peach were analyzed through principal component analysis(PCA).Then the diagnostic information from PCA was used as inputs of multiple discriminant analysis(MDA) for pattern recognition.The 2-dimontional plot was drawn with first and second principal components,which indicated that it was a good clustering analysis for classification varieties of juicy peach.The result of the analysis suggested that the reliabilities of first 8 principal components were more than 94.38%.60 samples from three varieties selected randomly.Then they were used to build discriminating model.15 unknown samples were validated by this model.The recognition rate is 100%.This model is reliable and practicable.So this study can offer a new approach to the fast discrimination of varieties of juicy peach.