Madras Agricultural Journal
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Research Article | Open Access | Peer Review

Comparison of Prediction Accuracy of Multiple Linear Regression, ARIMA and ARIMAX Model for Pest Incidence of Cotton with Weather Factors

Volume : 105
Issue: Jul-sep
Pages: 313 - 316
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Abstract


Identifying suitable statistical model for predicting pest incidence have important role in pest management programmes. For this study weekly data of aphid, thrips, jassid and whitefly incidence of cotton at the TNAU region, Coimbatore and the weather factors influencing these pests incidence were used for model development. Rainfall, maximum temperature, minimum temperature, morning humidity, evening humidity were used as the independent variables and MLR, ARIMA, ARIMAX models built for each pests. Comparison of these three models was done and checked the model accuracy using root mean square error value. It was found that for all pests ARIMAX model posses lowest RMSE value compared to ARIMA and MLR. So ARIMAX model was selected as best fit model

DOI
Pages
313 - 316
Creative Commons
Copyright
© The Author(s), 2026. Published by Madras Agricultural Students' Union in Madras Agricultural Journal (MAJ). This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited by the user.

Keywords


Cotton pests Multiple linear regression ARIMA ARIMAX Weather factors
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