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Legume Research
Year : 2024, Volume : 47, Issue : 1
First page : ( 99) Last page : ( 105)
Print ISSN : 0250-5371. Online ISSN : 0976-0571.
Article DOI : 10.18805/LR-4492

A Logistic Regression Model for Predicting Sclerotinia Stem Rot in Egyptian Clover (Trifolium alexandrinum L.)

Bhardwaj N.R.1,*, Atri A.2, Rani U.2, Roy A.K.1

1ICAR-Indian Grassland and Fodder Research Institute, Jhansi-284 003, Uttar Pradesh, India

2Punjab Agricultural University, Ludhiana-141 004, Punjab, India

*Corresponding Author: N.R. Bhardwaj, ICAR-Indian Grassland and Fodder Research Institute, Jhansi-284 003, Uttar Pradesh, India, Email: nitish.rattanbhardwaj@gmail.com

Online Published on 09 February, 2024.

Abstract

Background

Stem rot caused by Sclerotinia trifoliorum is the most damaging disease of Egyptian clover (popularly called as berseem), which is widely grown as a leguminous, winter season fodder crop in India. Stem rot management currently relies on fungicides which have negative effect on livestock and environmental health. In this study, in order to rationalize the fungicide use for stem rot management, a prediction model which assesses the high risk of stem rot (>20% incidence) was developed.

Methods

The disease and weather data was collected from week-50 (second week of December) to week-14 (first week of April) during 2010-11 to 2019-20. The model was developed using logistic regression modeling approach.

Result

The model included increasing weekly average temperature (between 8-25°C) and wind speed (between 1-7 km/hr) as key predictor variables. Goodness of fit statistics such as number of concordant pairs (83.8%), discordant pairs (16.1%), Somers’ D (0.68), Gamma (0.68) and Tau-a (0.33) indicates high accuracy of the model. The model had high area under receiver operating characteristic curve value of 0.84 during development and 0.82 on cross validation indicating that it will perform fairly well on an independent dataset. Thus, these macro climatic-weather variables can be used to predict high risk (>20% incidence) of stem rot, which ultimately will rationalize use of fungicides for stem rot management. This is the first model to predict Sclerotinia stem rot in Egyptian clover based on weather variables in India and probably around the world.

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Keywords

Clover rot, Egyptian clover, Prediction model, Sclerotinia, Weather.

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