Statistical and machine learning models for location-specific crop yield prediction using weather indices
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00484-024-02763-w.pdf
Reference196 articles.
1. Abbas F, Afzaal H, Farooque AA, Tang S (2020) Crop yield prediction through proximal sensing and machine learning algorithms. Agronomy 10(7):1046. https://doi.org/10.3390/agronomy10071046
2. Abbas S, Kousar S, Khan MS (2022) The role of climate change in food security; empirical evidence over Punjab regions, Pakistan. Environ Sci Pollut Res 29(35):53718–53736. https://doi.org/10.1007/s11356-022-19315-7
3. Abdi H (2003) Partial least square regression (PLS regression). Encycl Res Methods Soc Sci 6(4):792–795
4. Abdi H (2010) Partial least squares regression and projection on latent structure regression (PLS Regression). Wiley Interdiscipl Rev: Comput Stat 2(1):97–106. https://doi.org/10.1002/wics.51
5. Agrawal R, Mehta SC (2007) Weather based forecasting of crop yields, pests and diseases-IASRI models. J Ind Soc Agril Statist 61(2):255–263
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