Rice (Oryza Sativa L.) is one of the most important food crops in the world. Path coefficient analysis has been widely used in crop breeding to determine the nature of relationships between the grain yield (GY) and its contributing components. A field experiment was conducted in 2009 at Rice Research Station in Tonekabon, north of Iran. This experiment was arranged in a randomized complete block design with four replications. Seven rice cultivars and three lines were transplanted at its own optimum density. Sequential path analysis showed fertile tiller number m-2 (FT), filled grain number panicle-1 (FG) and thousand grain weight (THGW) as the first-order variables accounted for 73% of GY. The results indicated rice total dry matter at heading stage (RtdmHD) and rice tiller number at heading stage (RtillerHD) as predictor variables for FT as dependent variable. Three characters contain FG, panicle length (PL) and rice leaf area index (LAI) at heading stage (RlaiHD) explained 61% of the total variations of THGW. This procedure did not detect any predictor variable in the model for FG as response variable. The predictor variables were ordered in the first- and second-order paths for grain yield as response variable. The results indicated that grain yield depended mostly on FT, FG, THGW, RtdmHD, RtillerHD and PL and these traits can be good selection criteria for improving grain yield in rice.
Key words: Rice (Oryza sativa L.), path coefficient, phenotypic correlation, yield components.
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