Plant breeding programs demand efficient and accurate methods for crop phenotyping, especially for economically important crops like soybeans. High-resolution satellite and drone imagery are alternatives to ground data collection to monitor crops in a time, cost, and labor efficient way. Drone imagery offers localized and high-resolution data but has limitations in coverage and operator skills. In contrast, high-resolution satellite imagery provides broad-scale views of research sites without the need of a human data collector or pilot.    Our study investigates the potential of high-resolution satellite imagery (50 cm GSD) as an alternative to drone imagery for assessing soybean physiological maturity and monitoring the crop condition in a small plot breeding program. We compare the efficacy of satellite against UAV by generating various multi-spectral vegetation indices (VI) to predict maturity and assessing crop canopy characteristics (green cover and NGE) . Eleven satellite derived VI were compared to UAV derived values, with NDVI (R2= 0.84), EVI2 (R2= 0.83), TVI (R2= 0.83) and IPVI (R2= 0.83) displaying the highest correlation between the two methods. Satellite-derived NDVI was also efficient in distinguishing the maturity of varieties among and across maturity groups when compared against UAV imagery. Within location heritability was high with values ranging between H2= 0.77 and H2= 0.93.    With advances in spatial resolution, satellites can now provide detailed insights into crop health, productivity, and resource management. Our findings reveal the promise of high-resolution satellite imagery as a valuable tool in small plot phenotyping with the potential to further scale breeding programs.

Plant breeding programs demand efficient and accurate methods for crop phenotyping, especially for economically important crops like soybeans. Traditional manual assessment methods are labor-intensive and prone to errors. The emerging field of phenomics leverages advanced technologies, including high-resolution satellite and drone imagery, to monitor crops in a time, cost and labor efficient way. Drones offer localized, high-resolution data but have limitations in coverage and operator skills. In contrast, high-resolution satellite imagery provides broad-scale views of the vegetation with increasing improvements in spatial and temporal resolution.Our study investigates the potential of high-resolution satellite imagery as an alternative to drone imagery for assessing soybean maturity and monitoring the crop condition in a small plot breeding program. We compare the efficiency of these two technologies and we explore the utilization of various vegetation indices (VIs) derived from satellite-based multispectral imaging sensors for maturity estimation, indirect assessment of essential plant traits and identification of the growing patterns of different maturity groups.Our findings reveal the promise of high-resolution satellite imagery as a valuable tool in soybean phenotyping, addressing the spatial scale challenges in breeding programs. With advances in spatial resolution, satellites can provide detailed insights into crop health, productivity, and resource management. This research contributes to the evolution of precision agriculture, offering a cost-effective and scalable solution for monitoring soybean maturity and enhancing crop adaptability and yield.

Phenotypic trait measurements have enabled breeders to link genomic information to phenotypic information and through this enhance crop performance by breeding for superior germplasm. Progress in this area has been hindered by the limited ability to capture agronomic traits of importance at a large field-based scale since traditional methods for measuring phenotypic traits in field are time and labor intensive and are limited in accuracy and consistency when implemented on large scale. Precision phenotyping efforts have enabled researchers at Corteva Agriscience to collect high quality datasets for important traits that programs had been unable to measure accurately or safely in the past. Specific applications of phenotyping technologies and how these have influenced data collection within Corteva breeding programs around the world will be presented. Technology is rapidly evolving, and by using this technology to develop novel precision phenotyping solutions, breeders are able to capture more high-quality data and gain unique insights.