Commentary on Application of Data Mining in Fruit Quality Evaluation - Archive ouverte HAL Access content directly
Conference Papers Year : 2016

Commentary on Application of Data Mining in Fruit Quality Evaluation

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Abstract

In order to provide reference for the fruit quality research and fruit selective breeding, in this paper, data mining methods of fruit quality in recent years, including fuzzy comprehensive evaluation method, analytic hierarchy process method, gray correlation degree analysis method and so on, which were compared for the characteristics of advantages and disadvantages. Furtherly, the main evaluation factors of the common fruits were summarized. Finally, the research on data mining methods of the fruit quality was summarized and prospected. This review indicated that data mining methods could evaluate multi-index of fruit quality comprehensively, which will provide reference for rapid detection of fruit quality and cultivation of the excellent species. Meanwhile, it will be a new direction in the field of fruit quality research by studying more main factors of fruit quality and simplifying the evaluation procedures in the near future.
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hal-01614200 , version 1 (10-10-2017)

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Attribution - CC BY 4.0

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Jinjian Hou, Dong Wang, Wenshen Jia, Ligang Pan. Commentary on Application of Data Mining in Fruit Quality Evaluation. 9th International Conference on Computer and Computing Technologies in Agriculture (CCTA), Sep 2015, Beijing, China. pp.505-513, ⟨10.1007/978-3-319-48354-2_51⟩. ⟨hal-01614200⟩
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