Assessing diversity of Maize (Zea mays L.) genotypes based on multivariate analysis of the quantitative traits

  • Sanjay Kumar Raut Agriculture and Forestry University, Rampur, Chitwan, Nepal
  • Surya Kanta Ghimire Agriculture and Forestry University, Rampur, Chitwan, Nepal
  • Chitra Bahadur Kunwar National Maize Research Program, Nepal Agriculture Research Council, Rampur, Chitwan, Nepal
  • Raju Kharel Agriculture and Forestry University, Rampur, Chitwan, Nepal
  • Manoj Sapkota Institute of Agriculture and Animal Science, Tribhuvan University, Rampur, Chitwan, Nepal
  • Shreena Pradhan Agriculture and Forestry University, Rampur, Chitwan, Nepal
Keywords: Cluster analysis, maize, multivariate analysis, PCA

Abstract

Fourteen genotypes along with one standard check of maize were evaluated in Randomized Complete Block Design with three replications. Observations were taken for days to 50% germination, 50% tasselling, silking, tasselling silking interval, plant height, ear height, number of tassel branches, tassel length, leaves below cob, leaves above cob, ear length, ear girth with kernels, number of rows per ear, number of grains per row, thousand kernel weight and grain yield. Principal component analysis and cluster analysis were done on the observed data. Four principal components governing 83.3% of the variance and four distinct clusters having five, two, four and three genotypes in the respective clusters were identified. The genotypes of second cluster, COMPOZ-NIPB and SO3TEY/LN, represented the genotypes showing highest number of tassel branch, ear diameter, ear length, leaf below ear, leaf above ear, grain rows per ear, grains per row, thousand kernel weight and grain yield.The selection of genotypes from the second cluster, characterised by high value of traits like grain row per column, number of grains per row, thousand kernel weight and grain yield, could lead to a fruitful selection of better performing genotypes for future breeding activities and can be selected as promising parents for hybridization.

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Published
2017-02-28
How to Cite
Raut, S., Ghimire, S., Kunwar, C., Kharel, R., Sapkota, M., & Pradhan, S. (2017). Assessing diversity of Maize (Zea mays L.) genotypes based on multivariate analysis of the quantitative traits. International Journal of Experimental Research and Review, 9, 63-69. Retrieved from https://qtanalytics.in/journals/index.php/IJERR/article/view/1304
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Articles