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अमूर्त

Screening of Bread Wheat Genotypes for Slow Rusting Resistance to Yellow Rust (Puccinia striiformis f.sp. tritici) and Association among Parameters in Southeastern Ethiopia

Tilahun Bayisa, Habtamu Terefe, Tesfaye Letta

Rapid evolution and spread of new virulent races of yellow rust results in frequent failure of new varieties released in Ethiopia. Thus, it is inevitable to identify durable sources of resistance for wheat rusts. The study was conducted to identify slow rusting resistance to yellow rust among thirty bread wheat genotypes and to understand the association of slow rusting characters with grain yield at Sinana and Agarfa, Southeastern Ethiopia, during 2017 cropping season. The experiment was laid out in alpha lattice design with three replications. Susceptible varieties PBW 343, Morocco and Digalu were planted around experimental blocks to enhance natural infection. Disease parameters including Coefficient of Infection (CI), Final Rust Severity (FRS), Area Under Diseases Progress Curve (AUDPC) and infection rate (r-value) were used to identify slow rusting resistance. Analysis of variance revealed highly significant (P<0.01) difference among genotypes for all disease parameters at both locations. Genotype × environment interaction also showed significant differences for disease parameters. Based on CI, FRS and AUDPC values, bread wheat genotypes ETBW 8064, ETBW 8451, Kingbird, ETBW 8342, ETBW 8065, ETBW 8348, ETBW 8206, ETBW 8292, ETBW 8359 and ETBW 8290 grouped under high slow rusting resistance; genotypes ETBW 8163, ETBW 8070 and Pavov-76 grouped as susceptible at both locations. Genotypic and phenotypic correlation indicated CI, FRS and rvalue had negative and highly significant association with grain yield. Studied genotypes had wide variability for yellow rust regarding from complete resistance to susceptible. Therefore, best genotypes with durable slow rusting resistance can be used to transfer resistance genes to high yielding cultivars in wheat improvement programs.

अस्वीकृति: इस सारांश का अनुवाद कृत्रिम बुद्धिमत्ता उपकरणों का उपयोग करके किया गया है और इसे अभी तक समीक्षा या सत्यापित नहीं किया गया है।