Comparison of different parameters for evaluation of partial resis- tance to rice blast disease

Abstract

Aim: To evaluate and identify the most suitable parameter for easy and quick recognisation of rice genotypes possessing partial resistance to rice blast disease. Experimental Design: The tested varieties were grown in one meter long single-row plots surrounded by the blast susceptible spreader rows of Karuna, with a spacing of 10 x 5 cm in a Uniform Blast Nursery pattern. The experiment was conducted in a randomized complete block design with three replications. Place and Duration of Study: The experiments were conducted at the Central Rice Research Institute farm, Cuttack, continuously for nine seasons from 1998 to 2001. Methodology: The disease severity was recorded at every alternate day intervals from disease initiation till end of epidemic. The disease scores were subjected to estimation of 12 parameters for evaluation of resistance. The data on 12 parameters for 42 rice genotypes tested across nine seasons were subjected to principal component analysis, in order to classify and ordinate the response of the genotypes and determine the relative importance of parameters. Results: The cluster analysis classified the 42 genotypes into 4 groups of A&B as susceptible and C&D as partial resistant (PR) clusters, during each season of study. The PR genotype groups were characterized by lower estimates of Final disease severity(FDS), Mean disease severity(MDS), Area under disease progress curve(AUDPC), Relative AUDPC(RAUDPC), logistic infection rate(r), Gompertz infection rate(k), genotype score on first(PC-1) and second(PC-2) principal components, logit line intercept(logit-a), Gompit line intercept(gompit-a), and higher estimates of days to reach 50% severity in logistic model(T50r ) and Gompertz model(T50k).Ordination of genotypes onto the PC-1 & PC-2 planes recognized 19 genotypes in group C and 12 genotypes in group D as PR, while rest of the 11 genotypes in cluster-A & B were susceptible. The relative importance of the parameters analyzed by factor analysis revealed that FDS, MDS, AUDPC, RAUDPC, r, k and PC-1 were the top ranking parameters with highly significant correlation among them. Conclusion: One can choose any of the above seven top ranking parameters for easy identification of PR genotypes, depending upon the available resources for computation. Among the 42 rice genotypes, 12 in cluster-D and 19 in cluster-C were identified as possessing partial resistance. The technique of principal component analysis, the ordination and positioning of genotypes on the ordination figure emerged as a valuable tool in identification of rice genotypes possessing PR to blast disease.