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Extraction of associated quantitative traits by association mining

机译:通过关联挖掘提取相关的数量性状

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Most of the agronomically important traits are quantitative and found to be correlated to each other. These correlated quantitative traits are important to develop high yielding and resistant varieties of various economically important crops to combat the needs of increasing population. This paper work utilized data mining approach to extract patterns/rulesfrom quantitative trait locus database to find associated traits of 10 important crops. In comparison with traditional approaches, this study provides a simple and fast approach for finding associated quantitative traits.
机译:大多数农学上重要的性状是定量的,并发现彼此相关。这些相关的数量性状对于开发各种具有重要经济意义的农作物以应对不断增长的人口需求具有重要意义。本文利用数据挖掘方法从数量性状基因座数据库中提取模式/规则,以发现10种重要农作物的相关性状。与传统方法相比,本研究提供了一种简单快速的方法来查找相关的定量性状。

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