Abstract

Yield and yield components are the most important quantitative traits, which are correlated with each other and with other morphological and physiological quantitative traits. These correlated quantitative traits are important to develop high-yielding varieties of various crops to combat the needs of increasing population. In this regard, this paper work utilised data mining approaches such as classification rule, association rule and frequent pattern mining to extract patterns/rules from quantitative trait locus database to find yield components and associated quantitative traits of 10 economically important crops. This study provides a simple, fast and exhaustive approach for finding yield components and associated quantitative traits, in comparison to traditional approaches.

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