Predicting the severity of Spodoptera litura on groundnut in relation to climatic variability using ordinal logistic model

Authors

  • GIRISH K. JHA ICAR-Indian Agricultural Research Institute, New Delhi- 110 012
  • GAJAB SINGH ICAR-Indian Agricultural Research Institute, New Delhi- 110 012
  • S. VENNILA ICAR-National Research Centre for Integrated Pest Management, New Delhi-110 012
  • M. SRINIVASA RAO ICAR-Central Research Institute for Dryland Agriculture, Santosh Nagar, Hyderabad-500059, India.
  • H. PANWAR ICAR-National Research Centre for Integrated Pest Management, New Delhi 110012
  • M. HEGDE University of Agricultural Sciences, Dharwad, Karnataka -580 005

DOI:

https://doi.org/10.54386/jam.v18i2.951

Keywords:

Trend analysis, Mann-Kendall test, Ordinal logistic model, proportional odds model, Spodoptera litura

Abstract

In this paper, an ordinal logistic regression model was developed for predicting the severity of tobacco caterpillar, Spodoptera litura (Fabricius) on groundnut using the pest dynamics vis a vis climatic data of twenty five years (1990-2014) pertaining to Kharif (26 to 44 standard meteorological weeks (SMW)) season of Dharwad (Karnataka). Trend analysis of climatic data using Mann-Kendall non
parametric test showed that mean and minimum temperatures, and rainfall to be increasing while morning and evening relative humidity and their mean to be decreasing over time. The weekly male moth catches of S. litura (nos./trap/week) during maximum severity period (34 SMW) was modeled with climatic variables lagged by two weeks. The developed model indicated that the maximum temperature and morning relative humidity prior to two weeks contributed significantly to the occurrence of high level of pest attack. Results suggested that for each degree increase in maximum temperature during 32 SMW, the odds of being high pest attack (as opposed to lower or medium) increased by a multiple of 8.6 as compared to the odds of being high or medium (as opposed to low) increasing by 6.4 times for each per cent rise in the morning relative humidity.

Downloads

Published

01-12-2016

How to Cite

GIRISH K. JHA, GAJAB SINGH, S. VENNILA, M. SRINIVASA RAO, H. PANWAR, & M. HEGDE. (2016). Predicting the severity of Spodoptera litura on groundnut in relation to climatic variability using ordinal logistic model. Journal of Agrometeorology, 18(2), 282–287. https://doi.org/10.54386/jam.v18i2.951

Issue

Vol. 18 No. 2 (2016): December

Section

Research Paper

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

This is a human-readable summary of (and not a substitute for) the license. Disclaimer.

You are free to:

Share — copy and redistribute the material in any medium or format

Adapt — remix, transform, and build upon the material

The licensor cannot revoke these freedoms as long as you follow the license terms.

    Under the following terms:

    Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

    NonCommercial — You may not use the material for commercial purposes.

    ShareAlike — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original.

    No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

    Notices:

    You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation.

    No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.

    Most read articles by the same author(s)