Leveraging Soil Mapping and Machine Learning to Improve Spatial Adjustments in Plant Breeding Trials
M. E. Carroll, L. G. Riera, B. A. Miller, P. M. Dixon, B. Ganapathysubramanian, S. Sarkar, A. K. Singh
The paper compares spatial adjustment methods in plant breeding trials, finding that XGBoost improves yield estimates by incorporating soil feature modeling at different scales.
bioRxiv · Jan 3, 2024Plant Biology