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.