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Efficacy and Economics of Fungicides and their Application Schedule for Early Blight (Alternaria solani) Management and Yield of Tomato at South Tigray, Ethiopia

Mehari Desta and Mohammed Yesuf

Early blight, caused by Alternaria solani, is the most pressing problem of tomato Production and productivity in Tigray region. However, only limited attempts have been made to tackle this problem in the study area. Therefore, this study was conducted to (1) investigate the efficacy and spray frequencies of fungicides (2) determine yield loss incurred due to early blight and (3) assess cost benefit of the fungicides. Three fungicides (ridomil gold, Agrolaxyl and Mancozeb) each with three spray frequencies (every 7, 14 and 21 days) were evaluated using moderately susceptible variety, Melkashola in a Randomized Complete Block Design (RCBD) with three replications. Significant differences were observed among the treatments in-terms of disease incidence (DI), disease severity (DS), and AUDPC and disease progress rate (DPR) and; yield and yield components. Mancozeb among the fungicides and weekly spray among the spray frequencies were found the most effective in controlling the disease and improving the yield of tomato. Application of Mancozeb every week minimizes the disease by (47.75%) and consequently improves the yield by (112.48%). Weekly application of Mancozeb was found the most effective in controlling the disease with minimum values of DS (10.45%), AUDPC (266.0%-days), and DPR (0.09) and; higher marketable yield of (355.68 q/ha) and most economical with maximum marginal rate of return (MRR) (2,671.3%). Bi-weekly spray of Mancozeb also gave next higher MRR (1,724.3%). Maximum yield loss (52.94%) as compared to the most protected plot was incurred on untreated plots. Therefore, from the findings it can be conclude that application of mancozeb at weekly interval can be considered as the best management strategy to reduce disease epidemics and improve tomato yield.

Isenção de responsabilidade: Este resumo foi traduzido usando ferramentas de inteligência artificial e ainda não foi revisado ou verificado