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This study investigates the use of UAV imaging and machine learning to enhance phenotyping efficiency in faba bean breeding by estimating plant height, yield, and chlorophyll content. Utilizing Support Vector Regression (SVR) and Random Forest (RF) models, the research identifies optimal stages for predicting yield and SPAD values, achieving high correlation coefficients. The findings suggest that integrating UAV technology with machine learning offers a practical solution for rapid and efficient high-throu

Author

clevermukuz

Language

EN