RULE BASED PREDICTION SYSTEM TO OPTIMIZE FUNGICIDE APPLICATIONS FOR CONTROL OF PODOSPHAERA APHANIS

Abstract

UK strawberry growers are under pressure from retailers to produce high quality fruit while reducing the amount of pesticides applied to control pathogens. Since strawberry growers started to use polythene tunnels to provide favorable conditions for strawberry production Podosphaera aphanis (strawberry powdery mildew) has become the major pathogen of UK strawberries. A rule based prediction system had been developed previously to identify when the P. aphanis inoculum present at a site poses the highest risk of developing into an epidemic. Sensitivity analysis was carried out on the parameters that describe the conditions within a tunnel to determine which of the parameters would have the smallest and greatest effects on the prediction of high risk days. The sensitivity analysis showed that the least sensitive parameters were maximum germination temperature, maximum growth temperature and leaf wetness. Changes in the growth temperature threshold had the greatest effect on the amount of predicted high risk days. The prediction system was tested in two commercial sites in the 2007 season where the growers managed half a field as they would have normally and the other half of the field had fungicides applied as predicted by the rule based system, for high risk days, for the development of P. aphanis. Results showed that the prediction system resulted in comparable control of P. aphanis on commercial sites with fewer fungicide applications.