Research Soil Scientist
Dr. Curtis Ransom is a Research Soil Scientist within the Cropping Systems and Water Quality Research Unit of USDA-ARS in Columbia, Missouri. He is focusing on leveraging precision agriculture and data science to sustainably manage nutrients, thereby enhancing yields and mitigating environmental impact.
He earned advanced degrees in Environmental Science from Brigham Young University (MS, 2014) and University of Missouri (PhD, 2018). Both of which explored quantifying nutrient 4-R management practices (fertilizer types, placement, application timing, and rates) in horticulture and agricultural crops.
Prior to beginning with USDA ARS as a Research Soil Scientist in 2023, Dr. Ransom worked as a post-doctoral student with the University of Missouri and USDA ARS. There he worked on methods to improve corn nitrogen fertilizer rate recommendation tools.
My research integrates agronomic, soil, and data science methodologies to innovate and optimize tools for the management of nitrogen and carbon in diverse cropping systems. My primary goal is to identify precision agriculture technologies that can effectively assist farmers in enhancing both profitability and sustainability across dynamically varying soil and weather conditions. Presently, my research initiatives include:
- Assessment and enhancement of existing corn nitrogen recommendation tools throughout the US Midwest.
- Identification of data layers, including remote sensing, proximal soil sensors, and chemical and biological soil measurements, crucial for comprehending corn responses to fertilizers.
- Application of machine learning techniques to establish correlations between proximal soil sensing measurements and profile soil carbon stocks.
- Development of high throughput methods for characterizing pedogenic soil characteristics with spectroscopy.
Why am I doing this research
For decades, substantial research efforts have been dedicated to formulating fertilizer recommendations. Nevertheless, traditional small-plot studies, which are both costly and labor-intensive, have not proved adequate for widescale use. Addressing this uncertainty necessitates additional research conducted under diverse combinations of growing conditions. With current precision agriculture technologies, we are now able to acquire high-quality data across a broad spectrum of growing conditions. Access to such comprehensive and quality data is instrumental in empowering farmers to effectively manage every acre sustainably and profitably.
How my research is conducted
My research centers on the application of precision agriculture technology to systematically gather extensive datasets spanning both spatial and temporal dimensions. This includes a range of research activities, from small plots to field-wide response plots and participating in regional collaborative efforts. My primary focus in data collection involves grain crop yield monitors, remote sensing imagery, active canopy reflectance sensors, proximal soil sensors, computer simulation models, and soil samples.
Notable findings
- Many fertilizer recommendations are geographically specific and are often inaccurate across much of the growing conditions present in the US Midwest. However, many publicly available N recommendation tools can be improved (up to 54% increase in R2) by including site-specific weather and soil information in the decision aid process.
- Levels of active carbon (a prominent soil health measurement) below 400 to 450 mg C kg soil-1 were associated with reduced corn yields. This novel benchmark can help farmers understand when they need to implement remedial practices (e.g., manure, no-till, cover crops) to improve soil health and yield.
