Year 2016, Volume 62 Issue 4 (15.12.2016)

Year : 2016
Volume : 62
Issue : 4 (15.12.2016)
   
Authors : Soghra KIANI and Kayvan AGAHI
Title : CORRELATION AND PATH COEFFICIENT ANALYSIS OF MORPHOLOGICAL TRAITS AFFECTING GRAIN SHAPE IN RICE GENOTYPES (ORYZA SATIVA L.)
Abstract : This work was undertaken to look into the interrelationships among morphological traits and rice grain shape. For this purpose, a set of 25 rice genotypes was sown and subjected to a farm survey, based on the standard evaluation system for rice. Correlation coefficient analysis showed that the grain shape was positively correlated with grain length, panicle length, plant height and the number of tillers while, there were statistically significant and negative correlations between grain shape with maturity date, number of grains per panicle, grain breadth, 100-grain weight and flag leaf width. Sequential path analysis revealed that grain breadth, grain length and number of grains per panicle, as first-order variables, was responsible for about 98% of the variation in grain shape. Also, 100-grain weight, maturity date, number of tillers and flag leaf width were determined as second-order predictors. Amongst second-order predictors, 100-grain weight was a noteworthy trait regarding its high direct and indirect effects on grain breadth and grain length. Study of multicollinearity measures revealed that sequentializing of predictor variables reduced problems due to multicollinearity leading to a better understanding of the interrelationships among the various traits and their relative contribution. Also, the bootstrap analysis indicated that all direct effects were significant. The results suggested that grain breadth, grain length and number of grains per panicle, as first-order predictor variables had the highest direct effect on grain shape and could be used as a selection criterion to improve rice grain shape. Also, 100-grain weight, maturity date, number of tillers and flag leaf width, as second-order predictor variables affect the rice grain shape indirectly through their effects on first-order predictors. The authors recommend for the use of sequential equation modeling to conduct a proper sequential path analysis
For citation : Kiani S., Agahi K.(2016): Correlation and path coefficient analysis of morphological traits affecting grain shape in rice genotypes (Oryza Sativa l.) Agriculture and Forestry, 62 (4): 227-237. DOI: 10.17707/AgricultForest.62.4.24
Keywords : Conventional path analysis, sequential path analysis, stepwise multiple linear regression, structural equation modeling
   
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