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Identifying drivers of soil nitrogen mineralization dynamics in cover-cropped agroecosystems using machine learning
Journal article   Peer reviewed

Identifying drivers of soil nitrogen mineralization dynamics in cover-cropped agroecosystems using machine learning

K. C. Rabin, G. Philip Robertson and Sieglinde Snapp
Soil Science Society of America journal, Vol.90(2), p.n/a
03/01/2026
DOI: https://doi.org/10.1002/saj2.70246
url
https://doi.org/10.1002/saj2.70246View
Published (Version of record) Open

Abstract

Agriculture Life Sciences & Biomedicine Science & Technology Soil Science
Nitrogen (N) supply from cover crops to subsequent crop primarily depends on cover crop biomass production. Questions remain on how cover crop biomass interacts with abiotic factors to affect soil inorganic N and when N availability is highest following cover crop termination. This study identified key variables influencing N mineralization dynamics in cover crop systems, including air temperature, precipitation, gravimetric water content, cover crop biomass, weed biomass, and days after cover crop termination (DAT). Using random forest modeling with leave-one-year-out cross-validation, we analyzed 30 years (1990-2020) of bi-weekly soil N measurements in two corn (Zea mays L.)-soybean (Glycine max)-wheat (Triticum aestivum L.) rotations with a legume cover crop (Trifolium pratense L.) to identify key drivers of soil inorganic N release. Models explained 35% of variability in soil NO3--N and 15%-32% variability in soil NH4+-N in the two systems. Variable importance analysis revealed that DAT was the most important driver affecting soil inorganic N availability, with air temperature as a close second. Partial dependence plots showed that soil NO3--N increased rapidly following cover crop termination and peaked at approximately 50 DAT. Two-dimensional partial dependence plots revealed interactions among DAT, temperature, and cover crop biomass in affecting soil NO3--N. Temperature >12 degrees C and cover crop biomass above 4000 kg ha(-1) were associated with high soil NO3--N levels. There were productivity differences between the management systems studied, yet both systems showed similar N dynamics, suggesting this approach was robust for understanding underlying drivers concerning N mineralization.

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