GENETIC DIVERGENCE FOR YIELD AND ITS COMPONENTS IN MYANMAR LOCAL RICE (ORYZA SATIVA L.) GERMPLASM.
Journal Title: International Journal of Advanced Research (IJAR) - Year 2019, Vol 7, Issue 7
Abstract
The experiment was conducted at the Department of Plant Breeding, Physiology and Ecology field, Yezin Agricultural University in Myanmar, 2017 (dry season) to determine the genetic diversity among forty-two local rice genotypes by using cluster and principle components analysis. The field was laid out in a randomized complete block design with three replications. Genotypes showed highly significant difference for all the traits studied, which suggests that the genotypes constitute a pool of germplasm with adequate genetic variability. Five major groups were observed among 42 local rice genotypes based on multivariate analysis. The genotypes within the Cluster V has highest mean value for yield plant-1, spikelet panicle-1, filled grain percent, harvest index, panicle/straw weight ratio, panicle weight, effective tiller-1, and lowest value of straw weight. Therefore, these genotypes should be selected for potential genotypes used in future breeding programs. The maximum inter cluster distances were observed between cluster II and V followed by cluster I and II. Therefore, crosses involving between cluster V and cluster II might exhibit high heterosis for yield and crosses between cluster I and II might exhibit higher heterosis for earliness and dwarf stature. The first three principal components explained 81.627% of the total variations, thus suggesting that traits such as yield per plant, harvest index, panicle/straw weight ratio, panicle weight, filled grain percent, effective tillers hill-1 and spikelet panicle-1 were the principal discriminatory characteristics. Therefore, the high level of genetic variation and the traits contributing for the variation was identified. Hence these genotypes can be utilized for trait improvement in breeding programs for the traits contributing for major variation.
Authors and Affiliations
Nyo Mar Htwe, Chan Nyein Thu.
Keywords
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- EP ID EP616037
- DOI 10.21474/IJAR01/9347
- Views 50
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