Epidemiological models based on meteorological variables to forewarn Alternaria blight of rapeseed-mustard

Authors

  • M.S. YADAV ICAR- National Research Centre for Integrated Pest Management, New Delhi, India
  • AMRENDER KUMAR ICAR-Indian Agricultural Research Institute, New Delhi, India
  • C. CHATTOPADHYAY ICAR-Indian Institute of Agricultural Biotechnology, Ranchi, India
  • D.K. YADAVA Indian Council of Agricultural Research, Krishi Bhawan, New Delhi, India

DOI:

https://doi.org/10.54386/jam.v24i1.782

Keywords:

Epidemiological models, meteorological variables, Alternaria blight, forewarning, Brassica

Abstract

Alternaria blight [Alternaria brassicae (Berk.) Sacc.] is one of the most widespread and harmful maladies of rapeseed-mustard, causing yield loss up to 47 per cent. Meteorological parameters especially temperature, relative humidity and bright sunshine hours play major role in the development of Alternaria blight disease. Infection by the pathogen is highly influenced by meteorological conditions. A well-tested model based on meteorological variables is an efficient tool for forewarning this disease. Epidemiology of Alternaria blight of brassicas was investigated based on long term data during 2003-2018 crop seasons on the disease severity and meteorological variables, which was validated with data for two subsequent years. During this study, meteorological variable-based regression model of forewarning was developed for maximum severity (%) of Alternaria blight on leaves and pods for three locations viz., New Delhi, Hisar (Haryana) and Mohanpur (West Bengal)] in India. Validation of the forewarning models for maximum severity (%) of Alternaria blight proved the efficiency of the targeted forecasts.

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Published

11-02-2022

How to Cite

M.S. YADAV, AMRENDER KUMAR, C. CHATTOPADHYAY, & D.K. YADAVA. (2022). Epidemiological models based on meteorological variables to forewarn Alternaria blight of rapeseed-mustard . Journal of Agrometeorology, 24(1), 55–59. https://doi.org/10.54386/jam.v24i1.782

Issue

Section

Research Paper