Novel approach of validation of online interactive weather information-based disease risk assessment in grapes in India

Abstract

Grapevine (Vitis vinifera) is a globally important horticultural crop cultivated all over the world for its myriad uses. It is subjected to the infection of several diseases which attack susceptible grapevine varieties and cause severe loss in yield as well as to the economy. Application of fungicides is the major weapon against plant diseases, however, continuous application of fungicides leads to environmental pollution, emergence of fungicide resistance and pesticide residue in grapes. A weather-based disease forecasting model would enable the growers to take decisions at the right time for fungicide spray which will help in better disease management with reduced fungicide use. A reasonable level of prediction of downy mildew was obtained by using the disease forecasting model of MatWin II and IMETOS automatic weather data recorded. A multi-location trial was initiated to validate the prediction system to check the prediction of downy and powdery mildew and total reduction in the number of fungicide sprays for three consecutive years. Sprays were suggested when risk of disease was indicated by the model. Total five major parameters were observed i.e., terminal PDI of powdery and downy mildew, reduction in the number of sprays, yield and number of pesticide detection in both the plots. Results showed the significant reduction in terminal PDI of downy and powdery mildew along with increased yield and reduction in number of sprays and pesticide detections.