Previous View
APSnet Home
Phytopathology Home


Ecology and Epidemiology

A Computer Simulation Model for Cercospora Leaf Spot of Peanut. G. R. Knudsen, Research associate, Southern Region, ARS, USDA, Oxford Tobacco Research Laboratory, Oxford, NC 27565, and North Carolina State University, Raleigh, 27695-7616, Present address: Department of Plant, Soil, and Entomological Sciences, University of Idaho, Moscow 83843; H. W. Spurr, Jr.(2), and C. S. Johnson(3). (2)Research plant pathologist, ARS, USDA, and Professor, North Carolina State University; (3)Assistant professor, Virginia Polytechnic Institute and State University, Blackstone 23824. Phytopathology 77:1118-1121. Accepted for publication 23 December 1986. This article is in the public domain and not copyrightable. It may be freely reprinted with customary crediting of the source. The American Phytopathological Society, 1987. DOI: 10.1094/Phyto-77-1118.

A computer simulation model was developed to predict disease progression of Cercospora leaf spot of peanut (causal agents: Cercospora arachidicola and Cercosporidium personatum). The model was derived in part from an advisory system used for fungicide scheduling in North Carolina and Virginia. Basic infection rate was modeled as a function of hours of relative humidity > 95%, minimum temperature during the period of high humidity, amount of infectious tissue, and proportion of uninfected tissue remaining. Latent and infectious periods were treated as distributed delay processes, and host plant growth (increase in leaflet number) was described as a logistic process. The model was validated using independent weather and disease severity data from field trials with peanut cultivar Florigiant, in which C. arachidicola was the predominant pathogen. Simulated disease progress curves and periods of rapid disease increase were similar to those observed in field trials. The model effectively ranked four epidemics in terms of end-of-season disease severity and area under the disease progress curve.

Additional keywords: disease forecast, early leaf spot, late leaf spot.