S.V. Nalawade, R.L. Bhilare, S.K. Ghodake, K.D. Bhoite and D.S. Thorvae
Abstract
The intensity of brown rust disease (Puccinia melanocephala) on sugarcane variety C oC 671 was recorded at D Block, Central Sugarcane Research Station Padegaon, Dist. Satara in Maharashtra for consecutive eight years. Based on the data on different weather parameters and the intensity of common rust on sugarcane, following multiple linear regression equation was developed for effective prediction of the occurrence and intensity of common rust on sugarcane. PDI (%) = -162.67 + 0.109 x Tmax â 0.068 x Tmin + 1.776 x RH-I â 0.088 x RH-II â 0.035 x RF [Where, PDI=Percent disease index, Tmax = Maximum temperature (oC), Tmin = Minimum temperature (oC), RH-I = Morning relative humidity (%), RH-II = Afternoon relative humidity (%) and RF = Rainfall (mm)]. The studies revealed that the maximum temperature of 28.3 to 31.7 oC, minimum temperature of 11.2 to 23.0 oC, morning relative humidity of 95 to 98 % and afternoon relative humidity of 52 to 87 % coupled with intermittent rainfall contributed significantly for the disease incidence and its further build-up. The data were subjected to step down regression analysis by eliminating the non-significantly related factors for predicting common rust on sugarcane using linear model. By employing this equation, the incidence of common rust on sugarcane could be predicted with an accuracy of 78.4 %. The actual observed (2014-15) and predicted values of PDI of common rust on sugarcane were compared. The standard residuals of PDI of common rust of sugarcane lied between -2.12 to +2.03 indicating high degree of accuracy of the model in predicting PDI of common rust of sugarcane. The linear regression equation developed was also validated with the disease data of the year 2015-16. The observed and predicted values of PDI of common rust of sugarcane were compared with Chi-square test for goodness of fit. The ï£2 Cal was less than ï£2 Tab for linear model indicating the best fitness of the equation. The standard residuals of PDI of common rust of sugarcane lied between -1.84 to +1.97 indicating high degree of accuracy of the model. Forecasting the incidence and spread of common rust of sugarcane helps in dopting effective fungicidal spray schedule. Hence, this model can be utilized in Agro-Advisories for predicting the occurrence of the common rust disease of sugarcane.