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Research Article Open access CC BY 4.0

Assessment of Genetic Variability and Character Association of Myanmar Local Rice (Oryza sativa L.) Germplasm

Nyo Mar Htwe, Su Latt Phyu, Chan Nyein Thu

Journal of Experimental Agriculture International · pp. 1–10 · Published 7 Sep 2019

10.9734/jeai/2019/v40i330369

Abstract

Forty-two Myanmar local rice genotypes were evaluated to estimate the magnitude of genetic variability and relationship of some agronomic traits. Randomized Complete Block (RCB) design with three replications was used to design this experiment at the Department of Plant Breeding, Physiology and Ecology, Yezin Agricultural University in Myanmar, 2017 (dry season). STAR (Statistical Tool for Agricultural Research, version 2.0.1) statistical software for analysis of variance and genetic parameter, and SPAR 2 software for path analysis were used to obtain the optimal result in the collected data: plant height, effective tillers hill-1, panicle/straw weight ratio, panicle length, filled grain percent, spikelet panicle-1, 1000 grain weight, harvest index, yield plant-1. Genotypes showed highly significant difference for all the traits studied, meaning that the genotypes constitute a pool of germplasm with adequate genetic variability. Genetic variance was higher than environmental variance and heritability were above 80 % in all characters, which ensures the predominance of the genetic components among genotypes. The slight difference between genotypic coefficient variation (GCV) and phenotypic coefficient of variation (PCV) in all characters indicated there is enough genetic variability for the traits to be facilitated selection. High heritability with high genetic advance for spikelet panicle-1 and filled grain percent, their strong and positive correlation and the positive direct effect on yield plant-1 indicated that these are important indicator characters and their manipulation through selection. These characters can be utilized as selection criteria for further breeding programs related to high yielding rice varieties.

Correlation genetic advance heritability path analysis variability.

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