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Effects of Waterlogging and Shading at Jointing and Grain-Filling Stages on Yield Components of Winter Wheat Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Commentary on Application of Data Mining in Fruit Quality Evaluation

Authors : Jinjian Hou, Dong Wang, Wenshen Jia, Ligang Pan

Published in: Computer and Computing Technologies in Agriculture IX

Publisher: Springer International Publishing

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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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Metadata
Title
Commentary on Application of Data Mining in Fruit Quality Evaluation
Authors
Jinjian Hou
Dong Wang
Wenshen Jia
Ligang Pan
Copyright Year
2016
Book
Computer and Computing Technologies in Agriculture IX

Print ISBN: 978-3-319-48353-5

Electronic ISBN: 978-3-319-48354-2

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-48354-2_51

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