Aerial phenotyping for sugarcane yield and drought tolerance

Sugarcane breeding is resource-intensive and time-consuming, and could benefit substantially from the integration of aerial phenotyping (AP) for rapidly identifying genotypes with superior yield traits. The study aimed to assess the feasibility of using AP to enhance sugarcane breeding by rapidly identifying genotypes with superior yield traits. The specific objectives of the study were to: (1) assess the impacts of canopy cover and stomatal conductance on stalk dry mass yield (SDM); (2) assess the feasibility of estimating these traits with aerially sensed normalized difference vegetation index (NDVI) and canopy temperature (Tc); (3) evaluate the potential for predicting SDM from NDVI and Tc; (4) formulate best AP procedures. The study comprised a replicated field trial near Komatipoort, South Africa, with 54 genotypes grown under well-watered and water deficit conditions. Traits were measured on the ground (canopy cover and stomatal conductance) and remotely sensed from the air with a drone (NDVI and Tc) throughout the plant and first ratoon crops, and SDM was measured at harvest. Measurements were categorized by crop water status and extent of canopy cover, and phenotypic trait correlations were analyzed for these different categories. The study confirmed canopy cover and stomatal conductance as influential traits for determining SDM. Canopy cover could be used as a proxy for identifying high- and lowyielding genotypes early on in water stress-free crops. Findings suggest that high stomatal conductance benefits well-watered crops, while relatively low conductance could be advantageous in dry environments, though further investigation is needed. Canopy cover was predicted well from NDVI at partial canopy for well-watered crops, while the prediction of stomatal conductance from Tc lacked reliability. It was concluded that NDVI and Tc could be used to identify high- and low-yielding genotypes when measured earlier on in the growth cycle for well-watered crops. Results also showed potential for using water treatment differences in Tc and SDM to identify drought tolerant genotypes. Lastly, the study highlighted methodological challenges and insights for future agronomic trait prediction using AP techniques. The findings of this study will be used in further testing in the early stages of the breeding programme along with the breeding populations, ultimately helping to manage breeding strategies for target environments. This has the potential to enhance breeding efficiency and ultimately genetic gains towards productive sugarcane cultivars for the future.