Effect of Wheat Cover Crop and Split Nitrogen Application on Corn Yield and Nitrogen Use Efficiency

Abstract

Corn (Zea mays L.) grain is a major commodity crop in Illinois and its production largely relies on timely application of nitrogen (N) fertilizers. Currently, growers in Illinois and other neighboring states in the U.S. Midwest use the maximum return to N (MRTN) decision support system to predict corn N requirements. However, the current tool does not factor in implications of integrating cover crops into the rotation, which has recently gained attention among growers due to several ecosystem services associated with cover cropping. A two-year field trail was conducted at the Agronomy Research Center in Carbondale, IL in 2018 and 2019 to evaluate whether split N application affects nitrogen use efficiency (NUE) of corn with and without a wheat (Triticum aestivum L.) cover crop. A randomized complete block design with split plot arrangements and four replicates was used. Main plots were cover crop treatments (no cover crop (control) compared to a wheat cover crop) and subplots were N timing applications to the corn: (1) 168 kg N ha−1 at planting; (2) 56 kg N ha−1 at planting + 112 kg N ha−1 at sidedress; (3) 112 kg N ha−1 at planting + 56 kg N ha−1 at sidedress; and (4) 168 kg N ha−1 at sidedress along with a zero-N control as check plot. Corn yield was higher in 2018 than 2019 reflecting more timely precipitation in that year. In 2018, grain yield declined by 12.6% following the wheat cover crop compared to no cover crop control, indicating a yield penalty when corn was preceded with a wheat cover crop. In 2018, a year with timely and sufficient rainfall, there were no yield differences among N treatments and N balances were near zero. In 2019, delaying the N application improved NUE and corn grain yield due to excessive rainfall early in the season reflecting on N losses which was confirmed by lower N balances in sidedressed treatments. Overall, our findings suggest including N credit for cereals in MRTN prediction model could help with improved N management in the Midwestern United States.