PLANT DISEASE RESEARCH
  • Year: 2020
  • Volume: 35
  • Issue: 2

Effect of different dates of planting and weather parameters on early blight disease of tomato

  • Author:
  • Ravinder1, Narender Singh2, N.K. Yadav3*, Ashwani Kumar4, Rakesh Sangwan5
  • Total Page Count: 5
  • Page Number: 127 to 131

1Krishi Vigyan Kendra, Bhiwani, CCS Haryana Agricultural University, Hisar-125004

2Krishi Vigyan Kendra, Mohindergarh, CCS Haryana Agricultural University, Hisar-125004

3Cotton Research Station, Sirsa, CCS Haryana Agricultural University, Hisar-125004

4College of Agriculture, Kaul, CCS Haryana Agricultural University, Hisar-125004

5Agricultural Technology Information Centre, Hisar, CCS Haryana Agricultural University, Hisar-125004

*E-mail: narendersingh7627@yahoo.com

Online published on 30 May, 2021.

Abstract

Field trials were conducted to study the effect of different dates of sowing on the per cent disease intensity of early blight disease at experimental area of Department of Plant Pathology, CCS HAU, Hisar during Rabi season, 2017–18. The treatments included three dates of sowing (November 15th, November 30th and December 15th) and three replications for each treatment were taken. Observations on development of early blight disease of tomato were recorded in relation to weather factors viz., temperature (maximum and minimum), relative humidity (morning and evening) and rainfall. The quantitative relationship between the disease progress (per cent disease intensity) and weather variables for all three dates of sowing obtained by performing correlation matrix and regression equation analysis. The results showed that temperature (maximum and minimum) were positive and significantly correlated with per cent disease intensity. Relative humidity (morning and evening) were negatively correlated with the per cent disease intensity. Rainfall was non-significant but positively correlated with the disease progression in all dates of sowing. Multiple regression equations were developed on data of per cent disease intensity and weather variables. These regressions equations explained variability of disease progression from 90% to 94% in different dates of sowing. The prediction equations explained that 90 to 94 per cent disease development was influenced by the temperature (maximum and minimum) and relative humidity (morning and evening) from one date of sowing to another date of sowing.

Keywords

Early blight, Dates of sowing, Correlation matrix, Regression equation, Relative humidity