Improving wheat yield prediction through variable selection using Support Vector Regression, Random Forest, and Extreme Gradient Boosting
Plant breeding centers, in their relentless pursuit of more productive and resilient wheat varieties, have generated vast data repositories that are fundamental to ensuring global food security. This study uses these data to develop a wheat grain yield (GY) prediction model, using machine learning t...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Smart Agricultural Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375525000255 |
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