Classification of Apple Using near Infrared Spectroscopy Based on Fuzzy Discriminant Analysis

Abstract

Classification of apple is an important link in postharvest commercialization processing. To realize the non-destructive, rapid and effective discrimination of apple fruits, the near infrared reflectance spectra of four varieties of apples were collected using near infrared spectroscopy, reduced by principal component analysis (PCA) and used to extract the discriminant information by linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), fuzzy discriminant analysis (FDA) and Foley-Sammon discriminant analysis. Finally k-nearest neighbor finished the classification. The classification results showed that FDA could extract the discriminant information of NIR spectra more effectively, and achieved the highest classification accuracy.