Abstract
Wheat crop is attacked by number of diseases some of which cause yield losses and deteriorates quality. Rust pathogens are most important pathogens of wheat which can cause considerable economic losses if uncontrolled. Stripe rust, caused by Puccinia striiformis f. sp. tritici, is an important wheat disease common in wheat growing areas experiencing cold and humid weather conditions during the crop season. Different meteorological parameters influence occurrence and development of stripe rust in northern India including Punjab. Based on investigations on relationship of stripe rust with weather parameters, weather based prediction model for stripe rust was developed using disease severity and weather data (2007-08 to 2018-19) recorded at Ludhiana. The data of 2009-10 and 2019-20 was used for validation of model. Regression model based on maximum and minimum temperature, morning relative humidity and sunshine hours gave good results. Validation of model indicated that relationship between observed values of disease and predicted values was very close.
Highlights
Wheat is an important source of food to majority of population of many developing countries
Stripe rust severity data was recorded at weekly interval and percentage weekly disease severity and terminal disease severity was calculated
Correlation coefficients were calculated between monthly stripe rust disease severity index and different
Summary
Wheat is an important source of food to majority of population of many developing countries. Six categories of the scale were determined on the basis of the per cent area of the leaf covered by infection as follows: meteorological parameters like temperature, relative humidity, sunshine hours and rainfall for pooled data to develop weather based epidemic window. Combinations of disease severity with different meteorological parameters were developed and best regression model with significant R2 and adjusted R2 value was selected.
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