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Optimizing corn yield prediction: Integrating multi-temporal UAS data and machine learning
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DOI：10.1016/j.atech.2025.101344.png)
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Abstract
En 中文
• RF and GB outperform LASSO for yield prediction using RGB. • LWIR improves yield prediction, especially in water-stressed fields and using GB. • Early yield prediction possible with reflectance data as early as the V9. • RGB poorly predicts corn yield during the reproductive stage. • Combined Ref & LWIR optimize yield prediction in deficit conditions across stages.
Keywords:
Time-series
Random forest
Gradient boosting
LWIR
Thermal
Water deficit
NDVI
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