Evaluation of Corn Response to Within-Field Nitrogen Management and the Performance of Tools for In-Season Nitrogen Recommendations in Alabama.

Abstract

Improving nitrogen (N) use efficiency in corn production requires strategies that account for within-field variability and also the availability of precision agriculture technologies. This study evaluated the corn response to different side-dress N rates across field’s management zones (MZs) in six on-farm trials conducted over two growing seasons (2023–2024) in Alabama. Each field was divided into MZs based on yield maps, soil properties, and topography. A strip-trial design testing three nitrogen rates crossing field management zones was implemented. Tools such as Adapt-N and Atfarm were also tested for their accuracy in prescribing within-field in-season N rates under the Alabama conditions. Variables measured included grain yield, ear length, ear diameter, stalk diameter × plant height, N uptake, and economic metrics such as nitrogen productivity and partial profit. The results showed that corn yield response to N varied across MZs and locations. In 2023, higher rates generally increased yield and profitability, particularly in high-yielding zones. In 2024, drought and heat stress during key growth stages reduced corn yield and limited N uptake which resulted in the farmer rate outperforming higher N rates. Yield components, particularly ear length and ear diameter, were positively correlated with yield; however, the correlation was influenced by both N rate and MZ. The evaluation of Adapt N and Atfarm showed that Adapt N could capture and recommend different N rates that address within-field variability. In contrast, Atfarm recommended uniform N rates regardless of within-field differences in soil type or topography. In most fields, the N rate recommended by both tools was close to the N rate treatment that contributed to the field yield average. These results suggest that the tools performance might be influenced by factors such as calibration, site-specific variability, and integration of local field knowledge. This research highlights the value of zone-specific N management and the potential to refine decision-support tools to improve economic and agronomic outcomes. It underscores the importance of integrating spatial variability, crop development, and environmental conditions when making in-season N application decisions to enhance productivity and sustainability in corn production systems of the southeastern U.S.