Random forest model that incorporates solar-induced chlorophyll fluorescence data can accurately track crop yield variations under drought conditions
Timely and reliable crop yield estimation is vital for ensuring both global and regional food security. Previous studies have primarily used process-based crop models or statistical regression-based models for crop yield estimates. However, these model types possess limitations, particularly in acco...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Ecological Informatics |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1574954124005144 |
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