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Abstrakt

Distribution and Physiological Races of Wheat Stem Rust (Puccinia graminis F. Sp tritici) in North and East Shoa Zones of Ethiopia

Kitessa Gutu*, Girma Adugna, Netsanet Bacha

Wheat (Triticum aestivumL.) is the most important staple crop in temperate zones and is in increasing demand in countries undergoing urbanization and industrialization. However, its production is affected by many biotic and abiotic factors. Among biotic production constraints; wheat stem rust ( Puccinia graminis f.sp tritici) is the most important one. This study was (i) to assess the importance of wheat stem rust in North and East Shoa zones of central Ethiopia and (ii) to identify physiological races. Purposive multistage sampling was used to select major wheat growing districts and farmers associations from each zone. Wheat stem rust race identification was carried out via inoculation of isolates on susceptible line (McNair); single pustule isolation; inoculation on standard differential sets and infection type evaluation of each line fourteen days after inoculation. One hundred fifty wheat fields (75 from each zone) were assessed. Wheat stem rust was observed in 71 (94.7%) and 52 (73.3%) of wheat fields in East and North Shoa zones, respectively. Disease incidence and severity were significantly different (p < 0.0001) between the two zones. Six physiological races of Puccinia graminis f.sp tritici (pgt) namely; TKTTF, TTTTF, TKKTF, TTKTT, TTKTF and TTTTT were identified. TKKTF was the dominant race which was detected from 40 (48.2%) samples followed by TKTTF (Digelu race) which was identified from 28 (33.7%) samples. But, TTTTT, TTKTT and TTTTF were less frequent races. They were identified from 1 (1.2%), 2 (2.4%) and 4 (4.8%) samples, respectively. The majority of resistance genes in differential host lines (80-100%) were defeated with the races. Resistance genes Sr24 and Sr31 were effective to majority of races identified. Hence, they can be used as source of resistance in breeding program.

Haftungsausschluss: Dieser Abstract wurde mit Hilfe von Künstlicher Intelligenz übersetzt und wurde noch nicht überprüft oder verifiziert.