Journal of Pure and Applied MicrobiologyVol. 8 No. 6

Correlation and Regression Analysis for Assessing Wheat Yellow Rust Severity using Relevant Weather Data in Jammu Subtropics of India

Rayees A. Ahanger1*, Vishal Gupta1, Hilal A. Bhat2, Nisar A. Dar1 and V.K. Razdan1

1Sher-e-Kashmir, University of Agricultural Sciences and Technology-Jammu, Chatha - 180 009, India. 2Sher-e-Kashmir, University of Agricultural Sciences and Technology, Srinagar, Shalimar - 190 025, India.

Received on 16 August 2014 and accepted on 25 October 2014



Various meteorological variables were used to assess their effect on yellow rust severity of wheat varieties Agra local and PBW-343 at research station, SKUAST-J, Chatha. Disease severity was recorded in the plots following modified Cobb?s scale at different dates. The disease severity data was correlated with various meteorological variables viz., Tmax (maximum temperature), Tmin (minimum temperature), Tave (average temperature), RHmax(maximum relative humidity), RHmin (minimum relative humidity), RHave (average relative humidity) and Rainfall. There was significantly positive correlation between disease severity and minimum, maximum and average temperature, whereas, minimum, maximum and average relative humidity showed negative though significant correlation. The rainfall of 20.7 mm, Tave 14.6oC and RHave of 85.5% were found conducive for disease development. The regression model depicted that the weather parameters taken under study contributed more than 80.2 and 81.1 per cent in the development of yellow rust in Agra local and PBW-343, respectively.

Keywords : Yellow rust, Puccinia striiformis, Weather, Correlation, Regression, Infection rate.