A brief history of remote sensing of soybean

The last 20 years have been a period of significant advancement in the tools available for remote sensing of soybean [Glycine max (L.) Merr.] in terms of price, ease of use, quality of information provided, and range of available research applications. This review article posits that now is an appropriate time to reflect on the previous two decades of research effort devoted to remote sensing of soybean to gain an appreciation for how far the field has come, while also acknowledging how much work remains to be performed. Structured by field management activities, this review is based on selected works culled from a broad search. These works contributed meaningful knowledge specific to soybean or elucidated key points not presented in those more intentionally focused on soybean. While there were many successes in the varied applications of remote sensing in soybean research, taking this 20-year perspective also exposed areas of unmet expectations. Advances in knowledge are hampered by systemic challenges with inconsistent results and confounding factors imposed by research settings. There is potential to address these challenges by tempering expectations for what is possible and addressing reporting standards and data needs, specifically related to machine learning. The future is bright, but a concerted community effort is needed to continue to advance the state of knowledge into the next 20 years.