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, col...

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Main Authors: Haijun SHEN, Tanglei ZHANG, Zhenxing XU, Ting YU, Zhongwen CAO
Format: Article
Language:zho
Published: The editorial department of Science and Technology of Food Industry 2023-02-01
Series:Shipin gongye ke-ji
Subjects:
Online Access:http://www.spgykj.com/cn/article/doi/10.13386/j.issn1002-0306.2022050023
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author Haijun SHEN
Tanglei ZHANG
Zhenxing XU
Ting YU
Zhongwen CAO
author_facet Haijun SHEN
Tanglei ZHANG
Zhenxing XU
Ting YU
Zhongwen CAO
author_sort Haijun SHEN
collection DOAJ
description 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.
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spelling doaj.art-d927b1ad1bec4f07841e8333af0ea2022023-02-08T08:00:16ZzhoThe editorial department of Science and Technology of Food IndustryShipin gongye ke-ji1002-03062023-02-0144436136810.13386/j.issn1002-0306.20220500232022050023-4Recognition of Apple Freshness Based on Fisher Discriminant AnalysisHaijun SHEN0Tanglei ZHANG1Zhenxing XU2Ting YU3Zhongwen CAO4Yangzhou Tourism and Business School, Jiangsu Union Technical Institute, Yangzhou 225001, ChinaSchool of Tourism and Cuisine, Yangzhou University, Yangzhou 225127, ChinaYangzhou Tourism and Business School, Jiangsu Union Technical Institute, Yangzhou 225001, ChinaYangzhou Tourism and Business School, Jiangsu Union Technical Institute, Yangzhou 225001, ChinaSchool of Tourism and Cuisine, Yangzhou University, Yangzhou 225127, ChinaTaking 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.http://www.spgykj.com/cn/article/doi/10.13386/j.issn1002-0306.2022050023fisher discriminant analysiscluster analysisapplefreshness
spellingShingle Haijun SHEN
Tanglei ZHANG
Zhenxing XU
Ting YU
Zhongwen CAO
Recognition of Apple Freshness Based on Fisher Discriminant Analysis
Shipin gongye ke-ji
fisher discriminant analysis
cluster analysis
apple
freshness
title Recognition of Apple Freshness Based on Fisher Discriminant Analysis
title_full Recognition of Apple Freshness Based on Fisher Discriminant Analysis
title_fullStr Recognition of Apple Freshness Based on Fisher Discriminant Analysis
title_full_unstemmed Recognition of Apple Freshness Based on Fisher Discriminant Analysis
title_short Recognition of Apple Freshness Based on Fisher Discriminant Analysis
title_sort recognition of apple freshness based on fisher discriminant analysis
topic fisher discriminant analysis
cluster analysis
apple
freshness
url http://www.spgykj.com/cn/article/doi/10.13386/j.issn1002-0306.2022050023
work_keys_str_mv AT haijunshen recognitionofapplefreshnessbasedonfisherdiscriminantanalysis
AT tangleizhang recognitionofapplefreshnessbasedonfisherdiscriminantanalysis
AT zhenxingxu recognitionofapplefreshnessbasedonfisherdiscriminantanalysis
AT tingyu recognitionofapplefreshnessbasedonfisherdiscriminantanalysis
AT zhongwencao recognitionofapplefreshnessbasedonfisherdiscriminantanalysis