Applications of Machine Learning in Agrometeorological Forecasting and Modeling: A Short Review from the Journal of Agrometeorology

Authors

DOI:

https://doi.org/10.54386/jam.v28i1.3320

Keywords:

Machine learning, Weather forecasting, agrometeorological model

References

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Kureshi, A. M., Pathak, V. N., Kardani, D. B., Dave, J. A., Shah, D. B., Turakhia, T. P., Gujrati, A., Pandya, M. R., & Trivedi, H. J. (2025). Machine learning approaches for clear-sky Land Surface Albedo (LSA) retrieval using OCM-3 data over diverse Indian landscapes. Journal of Agrometeorology, 27(4), 454–463. https://doi.org/10.54386/jam.v27i4.3174

Mahadeva, M., & Sriram A. V. (2025). Adaptive Neuro-Fuzzy inference system (ANFIS) based models for estimation of reference evapotranspiration (ET0). Journal of Agrometeorology, 27(3), 381–384. https://doi.org/10.54386/jam.v27i3.3008

Naidu, D., & Chandniha, S. K. (2025). Hybrid SARIMA–Bi-LSTM model for monthly rainfall forecasting in the agroclimatic zones of Chhattisgarh. Journal of Agrometeorology, 27(3), 332–337. https://doi.org/10.54386/jam.v27i3.3010

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Naranammal, N., S. R. Krishna Priya, & K. Naveena (2025). Enhanced hybrid CEEMDAN-GMDH regression model for forewarning sucking pests in cotton crops of Coimbatore, Tamil Nadu. Journal of Agrometeorology, 27(4), 447–453. https://doi.org/10.54386/jam.v27i4.3099

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Rao, A. S., & Krishnan, A. (2025). Rice yield prediction in Dakshina Kannada district using ensemble machine learning. Journal of Agrometeorology, 27(4), 518–521. https://doi.org/10.54386/jam.v27i4.3148

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Published

01-03-2026

How to Cite

PANDEY, V. (2026). Applications of Machine Learning in Agrometeorological Forecasting and Modeling: A Short Review from the Journal of Agrometeorology. Journal of Agrometeorology, 28(1), 106–109. https://doi.org/10.54386/jam.v28i1.3320

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Short Communication

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