Abstract
Potato late blight (PLB) caused by Phytophthora infestans (Mont.) de Bary, is an important and serious threat to successful potato production in the world. It spreads through seed and soil residual material. In Pakistan, PLB disease may cause complete crop failure under severe epidemic conditions. Due to lack of resistance in indigenous potato germplasm, disease is managed through fungicides by the growers of Pakistan. Nonetheless, excessive use of fungicides cause resistance in the pathogen and create fatalistic effect on the environment. Disease predictive model under such situation may be effective tool to predict early onset of disease which is helpful to reduce number of sprays. The data of five susceptible to highly susceptible varieties sown for consecutively ten years were collected from Plant Pathology Section, Ayub Agricultural Research Institute (AARI), Faisalabad. A disease predictive model was developed based on ten years data of PLB severity and epidemiological variables using stepwise regression analysis. The model was validated by regression model based on two years data. The results revealed that the ten years model explained 74%, while two years model explained 80% disease variability. In accordance of variety wise models, SH-5 and Diamont models explained up to 91% and 89% disease variability, respectively during two year. The predictive model was used for the management of PLB disease and only three sprays were applied. Applied sprays reduced the PLB disease severity on all the five varieties (N-22, FD48-4, FD69-1, FSD White and Cardinal) up to 2.46, 6.50, 2.50, 8.46 and 1.67%, respectively. All the treatments significantly reduced the disease severity whereas Phenylamide and Propineb were the most effective as compared to the control. Prediction of disease model would be helpful to apply two or three sprays of fungicides (Phenylamide and Propineb) to control late blight of potato successfully. (C) 2016 Friends Science Publishers