Artificial subsurface drainage is essential to sustain crop production in many areas but may also impair water quality by exacerbating nitrate (NO 3 )-nitrogen (N) delivery downstream. Cover crops and split-N application have been promoted as key conservation practices for reducing NO 3 -N losses, but few studies have simultaneously assessed their effect on water quality and crop productivity. A field study was conducted to evaluate the effects of N application timing and cover crops on subsurface drainage NO 3 -N losses and grain yield in continuous corn (Zea mays L.). Treatments were preplant-N: 224 kg N ha -1 split-applied with 60% fall + 40% preplant in 2018, or as single preplant applications in 2019 and 2020; split-N: 40% preplant + 60% side-dress (V6-V7); split-N + cover crop (CC): Split-N + cereal rye (Secale cereale L.); and a zero N plot as the control. Across the 3-yr study period, split-N + CC significantly reduced flow-weighted NO 3 -N concentration and NO 3 -N loss by 35 and 37%, respectively, compared with preplant-N. However, flow-weighted NO 3 -N concentration (4.3 mg L -1 ) and NO 3 -N loss (22.4 kg ha -1 ) with split-N were not significantly different from either preplant-N (4.8 mg L -1 and 26.4 kg ha -1 , respectively) or split-N + CC (3.1 mg L -1 and 16.7 kg ha -1 , respectively). Corn yield was significantly lower in the control treatment but did not differ among N fertilized treatments in any year. These results indicate that combining split-N application with cover crops holds promise for meeting the statewide interim milestone NO 3 -N reduction target of 15% by 2025 without negatively impacting crop productivity.

Grain sorghum growth and development was affected by cover crop and N management. Sorghum–sudangrass cover crop prior to grain sorghum required N to maintain yield. Late maturing soybean cover crop increased grain sorghum yield at suboptimal N rates. Late maturing soybean cover crop, N fertilizer replacement value of 44 kg N ha–1. Cover crops (CCs) can affect N fertilizer management by influencing nutrient cycling and N fertilizer requirement. Cropping systems with different CCs were established in 2007 to examine the response of sorghum [Sorghum bicolor (L.) Moench]. Four CC treatments {summer legume, late‐maturing soybean [LMS; Glycine max (L.) Merr]; summer non‐legume, sorghum–sudangrass (SS; Sorghum bicolor × Sorghum bicolor var. sudanese); winter legume, crimson clover (CL; Trifolium incarnatum L.), and winter non‐legume, daikon radish (DR; Raphanus sativus L.)} as well as double‐crop soybean (DSB) and chemical‐fallow (CF) treatments were imposed after wheat (Triticum aestivum L.) harvest in a wheat–sorghum–soybean cropping system. Five N rates (0, 45, 90, 135, and 180 kg N ha–1) were applied to sorghum within 2 wk of planting. Aboveground sorghum biomass was collected after physiological maturity to determine total N uptake and grain yield. The cropping system managed with LMS increased grain yield (>9%), compared to other CCs and CF with zero N application. Cropping systems including CL, DR, and DSB had similar effects on grain yield relative to CF when N fertilizer was applied. Increasing N rates significantly increased grain yield and N uptake of grain sorghum following SS, indicating that soil N was limited in this cropping system. The addition of LMS as a summer legume CC has the potential to contribute N and replace CF, thus improving management of N resources.

Nitrogen (N) losses from cropping systems in the U.S. Midwest represent a major environmental and economic concern, negatively impacting water and air quality. While considerable research has investigated processes and controls of N losses in this region, significant knowledge gaps still exist, particularly related to the temporal and spatial variability of crop N uptake and environmental losses at the field-scale. The objectives of this study were (i) to describe the unique application of environmental monitoring and remote sensing technologies to quantify and evaluate relationships between artificial subsurface drainage nitrate (NO 3-N) losses, soil nitrous oxide (N 2 O) emissions, soil N concentrations, corn (Zea mays L.) yield, and remote sensing vegetation indices, and (ii) to discuss the benefits and limitations of using recent developments in technology to monitor cropping system N dynamics at field-scale. Preliminary results showed important insights regarding temporal (when N losses primarily occurred) and spatial (measurement footprint) considerations when trying to link N 2 O and NO 3-N leaching losses within a single study to assess relationship between crop productivity and environmental N losses. Remote sensing vegetation indices were significantly correlated with N 2 O emissions, indicating that new technologies (e.g., unmanned aerial vehicle platform) could represent an integrative tool for linking sustainability outcomes with improved agronomic efficiencies, with lower vegetation index values associated with poor crop performance and higher N 2 O emissions. However, the potential for unmanned aerial vehicle to evaluate water quality appears much more limited because NO 3-N losses happened prior to early-season crop growth and image collection. Building on this work, we encourage future research to test the usefulness of remote sensing technologies for monitoring environmental quality, with the goal of providing timely and accurate information to enhance the efficiency and sustainability of food production.

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New process‐based tools for predicting in‐season soil nitrogen (N) levels has the potential to provide timely information for N management decisions for corn (Zea mays L.) production systems in the U.S. There is, however, little published data supporting the assumption that soil mineral N (SMN, NH4‐N + NO3‐N at 0–60 cm) is correlated with yield response at different vegetative growth stages. Moreover, the degree to which changes in SMN influence the risk of N losses is uncertain. Data from 32 site‐years of field experiments in Illinois (2015–2018)—that included 12 combinations of N fertilizer rate, timing, and source—were used to evaluate the relationship between SMN concentration and grain yields across vegetative growth stages and estimate the exceedance probability of N losses. Overall, SMN across vegetative growth explained 46–61% of the variation in grain yield. Critical level of SMN that optimized yield decreased from 23.4 mg kg−1 at V5‐V7 to 9.1 mg kg−1 at VT‐R1 growth stage, but it was consistent, ranging from 14.7 to 16.3 mg kg−1, among sampling periods between V8 and V16 stages. While increasing SMN from deficiency (below critical levels) to sufficiency (at critical levels) increased yields by 22% (11.8 vs. 14.4 Mg ha−1), it also increased the probability of environmental N losses throughout vegetative growth, indicating a clear tradeoff between production and sustainability goals. These results help guide the development of sustainable in‐season N management strategies by illustrating the importance of incorporating risks of environmental N losses when trying to reach optimum grain yield levels.