Indian Journal of Agricultural Research
SCOPUSWeb of Science
  • Year: 2025
  • Volume: 59
  • Issue: 4

Assessment of weather parameters on per cent disease incidence and forewarning models of Fusarium wilt in pigeonpea as influenced by different sowing windows

  • Author:
  • D. Nagaraju1,*, S.B. Kharbade2, S.N. Hasabnis3, J.D. Jadhav4, A.A. Shaikh5, R. Balasubramanian6
  • Total Page Count: 5
  • Page Number: 649 to 653

1Department of Agricultural Meteorology, College of Agriculture, Pune-411 005, Maharashtra, India

2College of Agriculture, Nandurbar-425 412, Maharashtra, India

3Division of Plant Pathology, College of Agriculture, Pune-411 005, Maharashtra, India

4Department of Agricultural Meteorology, College of Agriculture, Pune-411 005, Maharashtra, India

5Oilseeds Research Station, Jalgaon-412 005, Maharashtra, India

6Department of India Meteorological, Pune-411 005, Maharashtra, India

*Corresponding Author: D. Nagaraju, Department of Agricultural Meteorology, College of Agriculture, Pune-411 005, Maharashtra, India, Email: dharavathnaga@gmail.com

Online published on 9 July, 2025.

Abstract

Fusarium wilt caused by Fusarium udum (Butler) var. cajani is one of the most important soil-borne diseases of pigeonpea capable of causing 30-100% loss in grain yield. So it is essential to establish the relationship with weather parameters and prediction of per cent disease incidence.

An experiment was laid out in split plot design with three replications and sixteen treatment combinations considering different varieties and sowing windows. Correlation and multiple linear regression equations were elucidated between weather parameters and per cent disease incidence (PDI) of Fusarium wilt on different pigeonpea varieties under different sowing windows during 201718 and 2018-19.

The correlation of weather parameters with PDI of Fusarium wilt indicated that significant and positively correlation with maximum and minimum temperature and negative correlation with evening relative humidity. Among all sowing windows 30th meteorological week (MW) sowing window with the variety ICPH 2740 PDI for two weeks prior was significantly positively correlated with maximum temperature (0.871** and 0.919**) and morning relative humidity (0.727* and 0.056). The prediction of PDI of Fusarium wilt with multiple linear regression equations were recorded the highest R2 valueas 95.5% in case of treatment combination of 30th MW and the variety Vipula.

Keywords

Correlation, Forewarning models, Fusarium wilt, PDI, Sowing windows