Journal of Environmental Biology

Temperature influence on leafhopper population and its potential distribution in predicting spread of chickpea stunt disease in India

M.G. Reddy^1,2, G.P. Rao¹*, P. Sinha¹, S.M. Shukla¹ and D. Sagar³ 

¹Division of Plant Pathology, Indian Agricultural Research Institute, New Delhi-110012, India

²Department of Plant Pathology, S.V. Agricultural College, Tirupati, Acharya N. G. Ranga Agricultural University, Guntur-517 502, India

³Division of Entomology, Indian Agricultural Research Institute, New Delhi-110 012, India

*Corresponding Author Email : gprao_gor@rediffmail.com

Received: 04.12.2020                                                                       Revised: 01.03.2021                                                  Accepted: 04.05.2021

Abstract

Aim: To study the influence of temperature on leafhopper population for predicting potential distribution of chickpea stunt disease.

Methodology: Leaf hopper population was sampled at weekly intervals from chickpea experimental plots at Indian Agricultural Research Institute, New Delhi, during Dec-May 2018-2019 and 2019-2020 by using yellow sticky trap. Effect of temperature on leafhopper population was fitted to a non-linear beta model and Briere model by utilizing cardinal temperature for leafhopper growth and reproduction. Daily minimum and maximum temperature data were collected from 146 geo referenced meteorological stations of important chickpea growing states of India. The cumulative temperature indices (MTI) as a measure of monthly leafhopper population was plotted using ArcGis10.0 software.

Results: Temperature index estimated as a measure of leafhopper population based on the beta model potential leafhopper population distribution was predicted. Spatio-temporal pattern of vector population indicated that the entire country is favourable for leafhopper growth round the year, except the Northern parts of India during December to February.      

Interpretation: Since leafhoppers are the natural vectors of virus and phytoplasma pathogens associated with chickpea stunt disease, beta model based prediction of environmental suitability indicates leafhopper as the causative agent for the natural spread of disease in larger geographical area. Spatio-temporal distribution pattern would be useful in predicting the disease spread in different chickpea growing areas for evolving efficient management strategies.

Key words: Leafhopper population, Epidemiological model, Chickpea chlorotic dwarf virus, Phytoplasma

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