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<p>Fall armyworm (FAW), <i>Spodoptera frugiperda</i> (J.E. Smith), spread rapidly across maize - growing regions due to its high-flying ability, affecting the crop extensively within a short period. The infestation percentage of FAW on maize was recorded for a period of four years from 2020 to 2023. The highest infestation percentage were observed in the 35th and 36th Standard Meteorological Weeks (SMW) with 75.2% in 2023, 58.6% in 2022, 55.6% in 2020, and 51.5% in 2021. An ARIMAX (1, 0, 0) model was utilized to analyze and forecast FAW infestation percentage. The ARIMAX model’s parameter estimates indicate significant coefficients for maximum temperature and morning relative humidity, emphasizing their impact on FAW infestation. In terms of climatic factors, there is a positive correlation (<i>r</i> = 0.1) between morning relative humidity and FAW infestation percentage. However, maximum temperature (<i>r</i> = -0.11), minimum temperature (<i>r</i> = -0.10), evening relative humidity (<i>r</i> = -0.01), and rainfall (<i>r</i> = -0.03) showed negative correlations with the FAW infestation. Integrating these climatic variables into predictive models enhances the ability to forecast and manage FAW outbreaks effectively. The study provides a quantitative analysis showing how climatic factors, particularly maximum temperature and morning relative humidity, influence the infestation levels of fall armyworm in maize crops. This approach not only helps in understanding the dynamics of FAW outbreaks but also aids in developing strategies to minimize crop damage through timely interventions based on weather forecasts and agronomic practices.</p>

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Harnessing the power of weather-based forecasting ARIMAX model for predicting fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith), and infestation in maize

  • 期刊论文

  • 发表日期：

    2025年1月9日

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  • T. Srinivasan,
  • V. Sadhana,
  • P. S. Shanmugam,
  • V. Baskaran,
  • M. Shanthi,
  • M. Murugan,
  • K. Prakash,
  • S. Sivakumar

摘要

Fall armyworm (FAW), Spodoptera frugiperda (J.E. Smith), spread rapidly across maize - growing regions due to its high-flying ability, affecting the crop extensively within a short period. The infestation percentage of FAW on maize was recorded for a period of four years from 2020 to 2023. The highest infestation percentage were observed in the 35th and 36th Standard Meteorological Weeks (SMW) with 75.2% in 2023, 58.6% in 2022, 55.6% in 2020, and 51.5% in 2021. An ARIMAX (1, 0, 0) model was utilized to analyze and forecast FAW infestation percentage. The ARIMAX model’s parameter estimates indicate significant coefficients for maximum temperature and morning relative humidity, emphasizing their impact on FAW infestation. In terms of climatic factors, there is a positive correlation (r = 0.1) between morning relative humidity and FAW infestation percentage. However, maximum temperature (r = -0.11), minimum temperature (r = -0.10), evening relative humidity (r = -0.01), and rainfall (r = -0.03) showed negative correlations with the FAW infestation. Integrating these climatic variables into predictive models enhances the ability to forecast and manage FAW outbreaks effectively. The study provides a quantitative analysis showing how climatic factors, particularly maximum temperature and morning relative humidity, influence the infestation levels of fall armyworm in maize crops. This approach not only helps in understanding the dynamics of FAW outbreaks but also aids in developing strategies to minimize crop damage through timely interventions based on weather forecasts and agronomic practices.