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Simulation of Potato Late Blight in the Andes. II: Validation of the LATEBLIGHT Model

First author: Department of Plant Pathology, 213 Bradfield Hall, Cornell University, Ithaca, NY 14853; second, third, and fourth authors: International Potato Center (CIP), P.O. Box 1558, Lima 12, Peru; fifth author: Department of Plant Pathology, ARO, The Volcani Center, Bet Dagan 50250, Israel; and sixth author: Department of Plant Pathology, 334 Plant Sciences Building, Cornell University, Ithaca, NY 14853

LATEBLIGHT, a mathematical model that simulates the effect of weather, host growth and resistance, and fungicide use on asexual development and growth of Phytophthora infestans on potato foliage, was validated for the Andes of Peru. Validation was needed due to recent modifications made to the model, and because the model had not been formally tested outside of New York State. Prior to validation, procedures to estimate the starting time of the epidemic, the amount of initial inoculum, and leaf wetness duration were developed. Observed data for validation were from field trials with three potato cultivars in the Peruvian locations of Comas and Huancayo in the department of Junín, and Oxapampa in the department of Pasco in 1999 and 2000 for a total of 12 epidemics. These data had not been used previously for estimating model parameters. Observed and simulated epidemics were compared graphically using disease progress curves and numerically using the area under the disease progress curve in a confidence interval test, an equivalence test, and an envelope of acceptance test. The level of agreement between observed and simulated epidemics was high, and the model was found to be valid according to subjective and objective performance criteria. The approach of measuring fitness components of potato cultivars infected with isolates of a certain clonal lineage of P. infestans under controlled conditions and then using the experimental results as parameters of LATEBLIGHT proved to be effective. Fungicide treatments were not considered in this study.

Additional keywords: data validation , operational validation , tropical highlands .