Studies of weather effect on frog-eye spot disease in Bidi tobacco using logistics regression

K R Joshi K R Joshi,Y M Rojasra Y M Rojasra,D J Parmar D J Parmar

doi:10.54386/jam.v20i2.524

Abstract

The frog-eye spot (FES) disease caused by Cercospor anicotianae Ell. and Eve. is a major problem in both nursery as well as in the main field of bidi tobacco growing environments. Eight years data (2008-2015) on occurrence of disease and weather parameters were used for logistics regression analysis. The results indicated that sunshine hours (BSS) and minimum temperature (Tmin) were positiveand highly significant, whereas maximum temperature (Tmax) and rainfall (R) were found negative and highly significant.Further results of odd ratio indicated that every increase in 1 unit in BSS and Tmin, the risk of FES increases 1.7 and 1.4 times, respectively, whereas increase in 1 unit in Tmax and rainfall, the risk of FES decreases at rate of 0.6 and 1.0 times, respectively.

Highlights

Humid and warm weather during August-September is highly congenial for development of the disease
Scale data on frog-eye spot (FES) converted into 0 and 1(FES_code) and weather parameters were subjected to Logistic regression analysis similar to regression technique with different in the nature of dependent variable.The dependent variable assumes exactly two distinct value (0 or 1) represent status of phenomenon like absent or present of disease
The results of logistic regression analysis indicated that weather parameters bright sunshine hours (BSS) and Tmin formed positive and highly significant, whereas Tmax and total rainfall (TOTR) were found negative and highly significant (Table 1)

Summary

Introduction

Humid and warm weather during August-September is highly congenial for development of the disease. Data on weather parameters such as bright sunshine hours (BSS), rainfall (R), rainy days (RD), Maximum and minimum temperature (Tmax, Tmin), relative humidity morning and evening (RH1, RH2), vapor pressure morning and evening (VP1, VP2) and total rainfall (TOTR)were obtained from Agro-meteorological observatory, AAU, Anand. Logistic equation was derived to identify indicator variables responsible for disease initiation.

Results

Conclusion