Nitrogen (N) mineralized from soil organic matter (SOM) and crop residues is an important source of N to crop nutrition but historically has been difficult to account for in N fertilizer recommendation systems. Here we propose and test relatively simple biogeochemical models that predict the contribution of N mineralization in supporting the yield of corn (Zea mays L.). The models are specifically designed to use soil and cover crop measurements that are easily accessible to farmers and agronomists, including soil carbon (C) concentration, 24-h CO2 respiration of a dried and rewetted soil sample, soil texture, and cover crop biomass N content and C/N ratio. We calibrated the models to explain variation of and predict unfertilized corn yield using a dataset of 73 observations compiled from nine experiments conducted in different sites and growing seasons in Pennsylvania. A model using soil C to calculate contributions of SOM mineralization to N supply predicted unfertilized corn yields more accurately than a model using the 24-h CO2 respiration (r2 =.62 vs.47; RMSE = 1.58 vs. 1.87 Mg ha−1, respectively). Soil sand content played an important role in the models by regulating the humification efficiency, a term that partitions decomposing C and N between microbially assimilated and mineralized pools. These models are prototypes for a new generation of N decision support tools that answer many of the shortcomings of current N fertilizer recommendation systems and offer a novel step forward in N fertility management.
All Science Journal Classification (ASJC) codes
- Agronomy and Crop Science