Extraction of associated quantitative traits by association mining

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.