Recognition of Apple Freshness Based on Fisher Discriminant Analysis

Taking the top five apples sold on Taobao (Tianshui Huaniu, Aksu Tangxin, Luochuan Red Fuji, Cream Fuji and Huang Marshal) as the test objects, store at 20 ℃ and 55% relative humidity, on the 0th, 5th, 10th, 15th, 20th and 25th days of the storage period to determine its water content, hardness, color difference, soluble solid content (SSC) and titratable acid, and the sensory evaluation, cluster analysis and Fisher discrimination were carried out for five kinds of apples. Result showed that, the freshness of apples was divided into fresh, sub-fresh, acceptable and spoiled by sensory evaluation and cluster analysis. Two discriminant functions of apples during storage were obtained by Fisher discriminant analysis. The total coefficient of variation of function 1 was 93.90% (P=0.000), the overall coefficient of variation of function 2 was 6.10% (P=0.003), and both functions had discriminant significance (P<0.05). The samples were divided into test set and training set, the recognition rate of training set was 96.25%, and the recognition rate of test set was 92.5%. The results showed that the Fisher discriminant analysis model established with the physical and chemical indicators selected in this paper as the discriminant factors could effectively identify the freshness of apples.