Field evaluation of a predictive model to control anthracnose disease of mango in the Philippines.
Estrada A. B., Jeffries P., Dodd J. C.
Author Affiliation: Research School of Biosciences, University of Kent, Canterbury, Kent, CT2 6NJ, UK.
Plant Pathology 45 : 294-301
Abstract : Infection estimates determined by a predictive model were used to time fungicide sprays to control anthracnose disease (Glomerella cingulata) of mango in the Philippines. For an amount of disease on fruits after harvest which was acceptable to growers, this approach resulted in the application of 5 fewer sprays compared with a standard spray programme used by the growers in a field trial conducted in 1991-92. The model predicted only 2 high anthracnose-risk periods (>40% of conidia forming appressoria) throughout the duration of the growing period. Rainfall intensity and its time of occurrence during fruit development was found to greatly influence the amount of anthracnose and stem-end rot disease on fruits after harvest. Three relatively strong precipitations (>20 mm) within a month before harvest resulted in relatively high anthracnose infection of fruits after harvest. At a second field trial, rainfall periods during fruit development did not exceed 4 mm and resulted in virtually disease-free fruits after harvest, including those not treated with fungicide. Again the use of the predictive model resulted in the elimination of 5 fungicide treatments compared with the standard programme. It is concluded that the amount of rainfall and the time of its occurrence should be considered when planning a disease management scheme for the control of anthracnose on mango fruit.