Sucking pest population dynamics of cotton crop in relation to agrometeorological parameters and spectral indices

Authors

  • NARESH KUMAR Department of Agricultural Meteorology, CCS Haryana Agricultural University, Hisar-125 004 India
  • RAM NIWAS Department of Agricultural Meteorology, CCS Haryana Agricultural University, Hisar-125 004 India
  • M. L. KHICHAR Department of Agricultural Meteorology, CCS Haryana Agricultural University, Hisar-125 004 India
  • R. K. SAINI Department of Agricultural Meteorology, CCS Haryana Agricultural University, Hisar-125 004 India
  • BARUN BISWAS Department of Agricultural Meteorology, CCS Haryana Agricultural University, Hisar-125 004 India

DOI:

https://doi.org/10.54386/jam.v14i2.1419

Keywords:

Cotton, leafhopper, whitefly, correlation, weather, multiple regressions

Abstract

Present study was designed to reveal the impact of different meteorological factors on sucking pest population dynamics and to work out multiple regression equations using different weather parameters and spectral indices. Leafhopper population was positively correlated with Tmax (Maximum temperature), Tmin (Minimum temperature), RHM (Morning RH) and RHE (Evening RH) and negatively associated with VPD (Vapour pressure deficit). However, whitefly population was negatively correlated with Tmax, Tmin and VPD and positively related with RHM and RHE. In case of leafhopper, regression equation consisting all the weather variables were more suitable to predict their population (R2 = 0.79). But for whitefly population, equation with only temperature variables explained more variability (R2 = 0.89). Multiple regression analysis with spectral indices showed variable performance for these pests.

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Published

01-12-2012

How to Cite

NARESH KUMAR, RAM NIWAS, M. L. KHICHAR, R. K. SAINI, & BARUN BISWAS. (2012). Sucking pest population dynamics of cotton crop in relation to agrometeorological parameters and spectral indices. Journal of Agrometeorology, 14(2), 170–172. https://doi.org/10.54386/jam.v14i2.1419

Issue

Vol. 14 No. 2 (2012): December

Section

Research Paper

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