Assessment of Variability and Genetic Diversity Study in an Advanced Segregating Population in Rice with Blast Resistance Genes Introgression

Blast disease caused by a pathogenic fungus, Magnaphorthe oryzae, is the most destructive disease and has resulted in more than 50% of crop losses worldwide, including in Malaysia. The present study was conducted to investigate genetic variability among 36 advanced lines of MR264 × PS2 rice with bla...

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Bibliographic Details
Published in:Journal of Experimental Biology and Agricultural Sciences
Main Author: Hasan N.; Rafii M.Y.; Harun A.R.; Ali N.S.; Mazlan N.; Abdullah S.
Format: Article
Language:English
Published: Editorial board of Journal of Experimental Biology and Agricultural Sciences 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129976988&doi=10.18006%2f2022.10%282%29.306.317&partnerID=40&md5=35b65843d4f9c37c4f996bda225fde95
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Summary:Blast disease caused by a pathogenic fungus, Magnaphorthe oryzae, is the most destructive disease and has resulted in more than 50% of crop losses worldwide, including in Malaysia. The present study was conducted to investigate genetic variability among 36 advanced lines of MR264 × PS2 rice with blast resistance genes introduced at the Faculty of Applied Sciences, Universiti Teknologi MARA, Malaysia. Traits such as days of maturity, plant height, grain width, and seed setting rate exhibited negative skewness in this study, indicating a doubling of gene effects. Seed setting rate and 1000 grain weight showed positive kurtosis, indicating gene interactions. The phenotypic coefficient of variation (PCV) was slightly higher than the genotypic coefficient of variation (GCV) for all traits, indicating that environmental influences affect the expression of these traits. High heritability associated with high genetic advance as a percentage of the mean was observed for filled grains per panicle. In addition, the second-highest value for high heritability and the high genetic advance was observed for the number of tillers. Cluster and principal component analysis revealed that 36 advanced lines were grouped into four clusters based on ten agromorphological traits. Clusters A and C had higher mean values for most of the traits studied than clusters B and D. Desirable recombinants for higher yields with a broad genetic base can be generated by using cross lines from different clusters. @ Production and Hosting by Horizon Publisher India [HPI]. All rights reserved.
ISSN:23208694
DOI:10.18006/2022.10(2).306.317