Weather Based Pest Forewarning Model for Major Insect Pests of Rice – An Effective Way for Insect Pest Prediction

Narayanasamy, Manikandan and Kennedy, J. S. and Geethalakshmi, V (2017) Weather Based Pest Forewarning Model for Major Insect Pests of Rice – An Effective Way for Insect Pest Prediction. Annual Research & Review in Biology, 21 (4). pp. 1-13. ISSN 2347565X

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Abstract

Weather parameters viz., Temperature, rainfall, relative humidity, sunshine hours and wind speed are the major weather elements determining the insect pests’ occurrence. Weather based forewarning models are widely utilized in the integrated pest management system as a tool which do not cause any harm to the predators and also cuts down environmental pollution. Considering this, an attempt was made to predict the population occurrence of Yellow Stem Borer (YSB), Brown Planthopper (BPH) and Rice Leaffolder (RLF). Generalized Linear Model (GLiM) was developed for YSB, BPH and RLF for predicting the population at a given time. The results of chi square test revealed that, there are many other factors which affect the amount of light trap catches of the insects apart from weather parameter. The predictability of the equation can be increased if the weather factors are combined with the other factors (variety, soil, fertilizer application, etc.,) in developing the model.

Item Type: Article
Subjects: Institute Archives > Biological Science
Depositing User: Managing Editor
Date Deposited: 05 Oct 2023 08:13
Last Modified: 05 Oct 2023 08:13
URI: http://eprint.subtopublish.com/id/eprint/2817

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