José Eduardo B. A. Monteiro,
Paulo C. Sentelhas,
Mark L. Gleason,
Paul D. Esker, and
Ederaldo J. Chiavegato
First and second authors: Agrometeorology Group, Department of Exact Sciences, ESALQ, University of São Paulo, P.O. Box 9, 13418-900 Piracicaba, SP, Brazil; third author: Department of Plant Pathology, Iowa State University, Ames 50011; fourth author: Department of Plant Pathology, University of Wisconsin, Madison 53706; and fifth author: Department of Plant Production, ESALQ, University of São Paulo.
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Accepted for publication 27 November 2008.
Colletotrichum gossypii var. cephalosporioides, the fungus that causes ramulosis disease of cotton, is widespread in Brazil and can cause severe yield loss. Because weather conditions greatly affect disease development, the objective of this work was to develop weather-based models to assess disease favorability. Latent period, incidence, and severity of ramulosis symptoms were evaluated in controlled environment experiments using factorial combinations of temperature (15, 20, 25, 30, and 35°C) and leaf wetness duration (0, 4, 8, 16, 32, and 64 h after inoculation). Severity was modeled as an exponential function of leaf wetness duration and temperature. At the optimum temperature of disease development, 27°C, average latent period was 10 days. Maximum ramulosis severity occurred from 20 to 30°C, with sharp decreases at lower and higher temperatures. Ramulosis severity increased as wetness periods were increased from 4 to 32 h. In field experiments at Piracicaba, São Paulo State, Brazil, cotton plots were inoculated (105 conidia ml--1) and ramulosis severity was evaluated weekly. The model obtained from the controlled environment study was used to generate a disease favorability index for comparison with disease progress rate in the field. Hourly measurements of solar radiation, temperature, relative humidity, leaf wetness duration, rainfall, and wind speed were also evaluated as possible explanatory variables. Both the disease favorability model and a model based on rainfall explained ramulosis growth rate well, with R2 of 0.89 and 0.91, respectively. They are proposed as models of ramulosis development rate on cotton in Brazil, and weather--disease relationships revealed by this work can form the basis of a warning system for ramulosis development.
Additional keywords:disease forecasting system, Gossypium hirsutum, witches'-broom.
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