Modeling of winter wheat yield prediction based on solar-induced chlorophyll fluorescence by machine learning methods
Timely and accurate prediction of large-scale crop yields is critical for national food security. Solar-induced chlorophyll fluorescence (SIF), an indicator of photosynthesis, has emerged as a promising predictor of crop yields. However, it remains unclear to what extent satellite-based SIF data can...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | European Journal of Remote Sensing |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/22797254.2025.2455940 |
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