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Environmental nitrogen (N) losses (e.g., nitrate leaching, denitrification, and ammonia volatilization) frequently occur in maize ( L.) agroecosystems. Decision support systems, designed to optimize the application of N fertilizer in these systems, have been developed using physically based models such as the Precision Nitrogen Management (PNM) model of soil and crop processes, which is an integral component of Adapt-N, a decision support tool providing N fertilizer recommendations for maize production. Such models can also be used to estimate N losses associated with particular management practices and over a range of current climates and future climate projections. The objectives of this study were to update the PNM model to include an option for simulating soil-water processes in artificially drained soils, and to calibrate the revised PNM model and test it against multiyear field studies in New York and Minnesota with different soils and management practices. Minimal calibration was required for the model. Denitrification rate constants were calibrated by minimizing the error between simulated and observed nitrate leaching for each study site. The normalized root mean squared error of cumulative daily drainage for the validation sets ranged from 10 to 23%. For cumulative daily nitrate leaching, the normalized root mean squared error ranged from 11 to 28% for the validation sets. The minimal calibration required and relatively simple data inputs make the PNM model a broadly applicable tool for simulating water and N flows in maize systems.

Large temporal and spatial variability in soil nitrogen (N) availability leads many farmers across the United States to over-apply N fertilizers in maize (Zea Mays L.) production environments, often resulting in large environmental N losses. Static Stanford-type N recommendation tools are typically promoted in the United States, but new dynamic model-based decision tools allow for highly adaptive N recommendations that account for specific production environments and conditions. This study compares the Corn N Calculator (CNC), a static N recommendation tool for New York, to Adapt-N, a dynamic simulation tool that combines soil, crop, and management information with real-time weather data to estimate optimum N application rates for maize. The efficiency of the two tools in predicting the Economically Optimum N Rate (EONR) is compared using field data from 14 multiple N-rate trials conducted in New York during the years 2011 through 2015. The CNC tool was used with both realistic grower-estimated potential yields and those extracted from the CNC default database, which were found to be unrealistically low when compared with field data. By accounting for weather and site-specific conditions, the Adapt-N tool was found to increase the farmer profits and significantly improve the prediction of the EONR (RMSE = 34 kg ha⁻¹). Furthermore, using a dynamic instead of a static approach led to reduced N application rates, which in turn resulted in substantially lower simulated environmental N losses. This study shows that better N management through a dynamic decision tool such as Adapt-N can help reduce environmental impacts while sustaining farm economic viability.

Leaching loss as nitrate (NO 3 ) is a growing concern because of its potential effect on water resources. Leaching of NO 3 with drainage water from subsurface-drained field plots seeded to maize (Zea mays L.) in 1992, 1993, and 1994 was measured on two soil types (a clay loam and a loamy sand) and for three N fertilization rates (22, 100, and 134 kg N ha -1 ). The 100 kg ha -1 rate was based on the results of a presidedress nitrate test (PSNT). Nitrate nitrogen (NO 3 -N) leaching was similar between fertilizer N treatments at both sites in 1992, the first year after sod plowdown, but concentrations were greater than 10 mg L -1 . For the subsequent two years, losses were similar for the 22 kg N ha -1 and the PSNT-based treatments, but significantly higher for the 134 kg N ha -1 treatment on the clay loam. On the loamy sand, losses increased from the lowest to the highest N rate. Nitrate leaching losses were consistently higher on the loamy sand than on the clay loam. The N budget results showed that the 134 kg N ha -1 rate had the highest residual soil NO 3 -N in the three years at both sites. On the clay loam, significant N losses occurred from denitrification following alfalfa plowdown and the subsequent fall and spring. Results indicate that N use efficiency rapidly decreases with overfertilization, even with N fertilization rates that only slightly exceed (134%) crop requirements. The PSNT-based rate reduced N leaching losses while maintaining maize yields.