Classification of Different Blueberry Cultivars by Analysis of Physical Factors, Chemical and Nutritional Ingredients, and Antioxidant Capacities
Blueberry fruits of different cultivars are featured with different quality indices. In this work, three types of quality factors, including 6 physical parameters, 12 chemical and nutritional components, and 3 antioxidant indices, were measured to compare and classify blueberry fruits from 12 differ...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Journal of Food Quality |
| Online Access: | http://dx.doi.org/10.1155/2020/9474158 |
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| author | Juan Song Qiong Shi Si-Min Yan Hai-Yan Fu Si-Zhan Wu Lu Xu |
| author_facet | Juan Song Qiong Shi Si-Min Yan Hai-Yan Fu Si-Zhan Wu Lu Xu |
| author_sort | Juan Song |
| collection | DOAJ |
| description | Blueberry fruits of different cultivars are featured with different quality indices. In this work, three types of quality factors, including 6 physical parameters, 12 chemical and nutritional components, and 3 antioxidant indices, were measured to compare and classify blueberry fruits from 12 different cultivars in China. Using the autoscaled data of quality factors, unsupervised principal component analysis was performed for exploratory analysis of intercultivar differences and the influences of quality factors. A supervised classification method, partial least squares discriminant analysis (PLSDA), was combined with the global particle swarm optimization algorithm (PSO) and two multiclass strategies, one-versus-rest (OVR) and one-versus-one (OVO), to select discriminative quality factors and develop classification models of the 12 cultivars. As a result, OVO-PLSDA with 8 quality factors could achieve the classification accuracy of 0.915. This study will provide new insights into the quality variations and key factors among different blueberry cultivars. |
| format | Article |
| id | doaj-art-fbb32b5f3b4a41899b49f7dc020ffed5 |
| institution | Kabale University |
| issn | 0146-9428 1745-4557 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Food Quality |
| spelling | doaj-art-fbb32b5f3b4a41899b49f7dc020ffed52025-02-03T01:04:22ZengWileyJournal of Food Quality0146-94281745-45572020-01-01202010.1155/2020/94741589474158Classification of Different Blueberry Cultivars by Analysis of Physical Factors, Chemical and Nutritional Ingredients, and Antioxidant CapacitiesJuan Song0Qiong Shi1Si-Min Yan2Hai-Yan Fu3Si-Zhan Wu4Lu Xu5College of Material and Chemical Engineering, Tongren University, Tongren 554300, Guizhou, ChinaThe Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, College of Pharmacy, South-Central University for Nationalities, Wuhan 430074, ChinaShanghai Institute of Quality Inspection and Technical Research, Shanghai 201114, ChinaThe Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, College of Pharmacy, South-Central University for Nationalities, Wuhan 430074, ChinaCollege of Material and Chemical Engineering, Tongren University, Tongren 554300, Guizhou, ChinaCollege of Material and Chemical Engineering, Tongren University, Tongren 554300, Guizhou, ChinaBlueberry fruits of different cultivars are featured with different quality indices. In this work, three types of quality factors, including 6 physical parameters, 12 chemical and nutritional components, and 3 antioxidant indices, were measured to compare and classify blueberry fruits from 12 different cultivars in China. Using the autoscaled data of quality factors, unsupervised principal component analysis was performed for exploratory analysis of intercultivar differences and the influences of quality factors. A supervised classification method, partial least squares discriminant analysis (PLSDA), was combined with the global particle swarm optimization algorithm (PSO) and two multiclass strategies, one-versus-rest (OVR) and one-versus-one (OVO), to select discriminative quality factors and develop classification models of the 12 cultivars. As a result, OVO-PLSDA with 8 quality factors could achieve the classification accuracy of 0.915. This study will provide new insights into the quality variations and key factors among different blueberry cultivars.http://dx.doi.org/10.1155/2020/9474158 |
| spellingShingle | Juan Song Qiong Shi Si-Min Yan Hai-Yan Fu Si-Zhan Wu Lu Xu Classification of Different Blueberry Cultivars by Analysis of Physical Factors, Chemical and Nutritional Ingredients, and Antioxidant Capacities Journal of Food Quality |
| title | Classification of Different Blueberry Cultivars by Analysis of Physical Factors, Chemical and Nutritional Ingredients, and Antioxidant Capacities |
| title_full | Classification of Different Blueberry Cultivars by Analysis of Physical Factors, Chemical and Nutritional Ingredients, and Antioxidant Capacities |
| title_fullStr | Classification of Different Blueberry Cultivars by Analysis of Physical Factors, Chemical and Nutritional Ingredients, and Antioxidant Capacities |
| title_full_unstemmed | Classification of Different Blueberry Cultivars by Analysis of Physical Factors, Chemical and Nutritional Ingredients, and Antioxidant Capacities |
| title_short | Classification of Different Blueberry Cultivars by Analysis of Physical Factors, Chemical and Nutritional Ingredients, and Antioxidant Capacities |
| title_sort | classification of different blueberry cultivars by analysis of physical factors chemical and nutritional ingredients and antioxidant capacities |
| url | http://dx.doi.org/10.1155/2020/9474158 |
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