Predicting Corn Yield with a Soil Organic Matter Test and Cover Crop Nitrogen Credits.

Nitrogen (N) mineralized through the microbial decomposition of soil organic matter and cover crop residues is an indigenous source of N that can meet crop growth demands and offset external N fertilizer inputs. Predicting the extent to which indigenous N sources support the yield of a crop could be used in an adaptive N management process.  Here we develop models to predict the absolute yield (Mg ha^-1) of an unfertilized corn (Zea mays L.) crop based on either the 24h flush of carbon dioxide (CO₂) soil test or total soil carbon (C) concentration and a previoulsy developed cover crop N crediting model.  A dataset of 120 plots where corn was grown without N fertilizer following various cover crop treatments in 6 fields in Pennsylvania was used to calibrate the models.  Predictive accuracy improved when silt and clay concentration were integrated into the model as regulators of N supply.  The best fitting model to predict N supply from soil organic matter (r²=0.68) was theoretically derived from a linear sorption isotherm, where total soil C concentration is fractionated into adsorbed and soluble pools by a distribution coefficient regulated by silt and clay concentration.  Alternative model formulations, where silt and clay concentration instead regulated C saturation dynamics, were slightly less accurate (r²=0.62-0.65).  Using the 24h flush of CO₂ test as a predictor of unfertilized corn yields had the lowest accuracy (r²=0.60).  Based on these results, a model that accounts for the interactions between organic matter and mineral surfaces has potential to be used in an adaptive N management process where knowledge of the indigenous N supply capacity of a soil is accounted for when estimating the N fertilizer requirements of a crop.