Maize and soybean yield prediction using machine learning methods: a systematic literature review

Maize and soybean yield prediction using machine learning methods: a systematic literature review

Abstract Today’s agronomy is data-rich, and machine learning (ML) provides the ability to efficiently predict crop yields, utilizing high-volume data to optimize agricultural decision-making. Numerous ML models are used, yet systemized framework guiding the crop-targeted selection of models, feature...

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Bibliographic Details
Main Authors: Ramandeep Kumar Sharma, Jasleen Kaur, Gary Feng, Yanbo Huang, Chandan Kumar, Yi Wang, Sandhir Sharma, Johnie Jenkins, Jagmandeep Dhillon
Format: Article
Language:English
Published: Springer 2025-04-01
Series:Discover Agriculture
Subjects:
Machine learning in agronomy
Deep learning
Crop management
Precision agriculture
Artificial intelligence
Online Access:https://doi.org/10.1007/s44279-025-00215-6
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https://doi.org/10.1007/s44279-025-00215-6

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