Authors: Kalpana Singh; Manish Kumar; Shekhar Verma
Addresses: Department of Applied Science, CC2 building, IIIT, Jhalwa, Allahabad 211012, India ' Department of Information Technology, CC2 building, IIIT, Jhalwa, Allahabad 211012, India ' Department of Information Technology, CC2 building, IIIT, Jhalwa, Allahabad 211012, India
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.
Keywords: associated traits; association mining; classification rule mining; quantitative traits; yield components.
International Journal of Bioinformatics Research and Applications, 2017 Vol.13 No.3, pp.279 - 291
Received: 07 Jun 2016
Accepted: 28 Jan 2017
Published online: 08 Aug 2017 *