关键词: 苹果分类, 近红外光谱, 线性判别分析, 二次判别分析, 模糊非相关判别转换, Foley-Sammon判别分析

Abstract: Classification of apples 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 are 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 Uncorrelated Discriminant Transformation（FUDT） and Foley-Sammon discriminant analysis. K-nearest neighbor is used to finish the classification. The classification results show that FUDT can extract the discriminant information of NIR spectra more effectively, and achieves the highest classification accuracy.

Key words: classification of apples, near infrared spectroscopy, Linear Discriminant Analysis（LDA）, Quadratic Discriminant Analysis（QDA）, Fuzzy Uncorrelated Discriminant Transformation（FUDT）, Foley-Sammon discriminant analysis