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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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-04-01
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| Series: | Discover Agriculture |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44279-025-00215-6 |
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