Plant Disease Research
Year : 2023, Volume : 38, Issue : 1
First page : ( 116) Last page : ( 122)
Print ISSN : 0970-4914. Online ISSN : 2249-8788.
Article DOI : 10.5958/2249-8788.2023.00012.4

Cotton leaf curl virus disease and weather interaction at Faridkot under south western region of Punjab

Kumar Ashok^*, Mishra Sudhir Kumar

Punjab Agricultural University, Regional Research Station, Faridkot-151203

^*E-mail: ashokkumar@pau.edu

Online Published on 28 August, 2023.

Abstract

Cotton an important fiber crop is source of the livelihood and income of cotton growers of India and world. Growth and productivity of the cotton crop is dependent on the edapho-climatic and management factors. Weather conditions also favour and control the occurrence as well as the spread of various plant diseases. The cotton leaf curl disease (CLCuD) caused by the group of begomoviruses and transmitted by the whitefly is major cause for low cotton productivity in cotton growing regions of India. Present study was aimed to understand the role of environmental factors on development of this disease and to develop weather based CLCuD forewarning models. The relationship between CLCuD and weather variables was determined using the correlation coefficient analysis while the stepwise regression was done for the development of disease prediction models. Results of the present study revealed that maximum and minimum temperatures, afternoon relative humidity and total rainfall were negatively related but, morning relative humidity and bright sunshine duration had positive relation with CLCuD. Minimum temperature 24-28 °C, mean temperature 29-32 °C, morning relative humidity 70-90 % and bright sunshine 5-7 hours were optimum range of the weather parameters for the CLCuD incidence. Among three models developed for CLCuD prediction, Y= - 27.1-7.5 × Tmin + 13.6 × BSS + 2.3 × RHmax was the best model having -14.1 and +14.5% error. The models may be used as decision making tool for effective management of the CLCuD.

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Keywords

Cotton leaf curl virus disease, Forewarning model, Weather parameters, Punjab.

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