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Ecology and Epidemiology

Influence of Primary Weather Variables on Sorghum Leaf Blight Severity in Southern Africa. G. G. Hennessy, Agroclimatology consultant, Southern Africa Development Coordination Conference/International Crops Research Institute in the Semi-Arid Tropics Sorghum and Millet Improvement Program (SADCC/ICRISAT SMIP), P.O. Box 776, Bulawayo, Zimbabwe, Africa; W. A. J. de Milliano(2), and C. G. McLaren(3). (2)Principal cereals pathologist, Southern Africa Development Coordination Conference\International Crops Research Institute in the Semi-Arid Tropics Sorghum and Millet Improvement Program (SADCC/ICRISAT SMIP), P.O. Box 776, Bulawayo, Zimbabwe, Africa; (3)Chief biometrician, Department of Research and Specialist Services, P.O. Box 8108, Causeway, Zimbabwe, Africa. Phytopathology 80:943-945. Accepted for publication 7 May 1990. Copyright 1990 The American Phytopathological Society. DOI: 10.1094/Phyto-80-943.

A study was conducted on the effect of climatic factors (rainfall, minimum and maximum air temperature) on severity of leaf blight over several locations and years in southern Africa. The weather data used were from 2 wk before sowing to 3 wk after sowing. Temperature was the most important variable predicting disease severity after dough stage of the crop. High disease severities coincided with minimum temperatures between 14 and 16 C and mean temperatures of 20.8 to 22.2 C. Low severity at dough stage of the sorghum or absence of leaf blight was associated with minimum temperatures above 16 C from 2 wk before sowing to 3 wk after sowing. Discriminant analysis conducted using temperature from very early in the season correctly classified 88% of the cases into three disease severity categories; no, low, and medium-to-high disease. Therefore, primary weather variables, in particular air temperature, may be valuable predictors of disease severity early in the season. These results may be used to identify and map disease levels for large areas using past temperature data.

Additional keywords: disease prediction, Exserohilum turcicum, Sorghum bicolor.