Andries B. Potgieter

This study develops an ensemble model using UAV-derived photogrammetric height data to predict plot-level lodging severity in sorghum breeding trials, achieving high accuracy and robustness across sites.

This paper uses UAV phenotyping and machine learning to predict barley root traits in the field, identifying genetic drivers of root gravitropism.

This study examines the relationship between seminal root angle and root system architecture in durum wheat, showing distinct RSA patterns in wide and narrow genotypes at later growth stages.

This study identifies QTL associated with canopy closure timing in durum wheat that improve yield in rainfed environments without yield penalties.