Enhancing rapeseed biomass and yield estimation with ensemble learning and synergistic multidimensional features.

Key Points

• The aim is to improve the accuracy of rapeseed biomass and yield estimation using advanced modeling techniques.
• Implemented an ensemble learning approach utilizing multidimensional features.
• Conducted analyses across various planting patterns to assess model performance.
• Evaluated prediction accuracy with metrics such as rRMSE and R².
• Achieved a prediction accuracy of R²=0.68 with rRMSE=13.67%.
• The model provided stable predictions across different varieties and density interactions.
• Presented a generalizable approach that enhances biomass yield estimation for precision harvesting.