Volume 11, Issue 30 (9-2019)
J Crop Breed 2019, 11(30): 178-187 |
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Nabipour A, Norouzi M. (2019). Genetic Diversity of Agronomic Traits in Advanced Breeding Lines of Rice (Oryza Sativa). J Crop Breed. 11(30), 178-187. doi:10.29252/jcb.11.30.178
URL: http://jcb.sanru.ac.ir/article-1-817-en.html
URL: http://jcb.sanru.ac.ir/article-1-817-en.html
1- Rice Research Institute of Iran, Mazandaran Branch, Agriculture Research, Education and Extension Organization, Amil, Iran
2- Agricultural research, education and extension organization
2- Agricultural research, education and extension organization
Abstract: (3020 Views)
Successful reorganization of rice genetic structure to improve grain yield needs extensive information on the traits that influence yield, either directly or indirectly, and the amount of their genetic diversity. In order to assess the genetic diversity of some agronomic traits among the promising lines of rice and their relation to yield, twenty lines along with a superior local check (Fajr) were evaluated under randomized complete blocks with 3 replications at Rice Research Station, Amol, in 2011. Studied traits included number of tillers, panicle length, paddy and grain length, paddy and grain width, plant height, grain shape, number of grains, percentage of filled and empty seeds, thousand grain weight and grain and paddy yield. The results of analysis of variance revealed highly significant differences among the genotypes for all the traits except for grain width. Comparison of means suggested that the lines NA5, NA17, NA9 had higher yields than the other lines. NA5 was also superior in terms of seed weight and grain length. Grain yield had significant correlation with grain length, 1000-grain weight and plant height; however the strongest correlation with yield was related to 1000-grain weight. Based on stepwise regression, plant height and grain weight were entered into path analysis, where grain weight had higher direct and indirect effects than plant height. Therefore, grain weight would be an appropriate criterion for selecting high-yielding genotypes. Cluster analysis using WARD method grouped the lines into 4 clusters.
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