Optimizing Corn and Cotton Performance with Adaptive Management Systems and Subsurface Drip Irrigation in the Mid-Atlantic USA

Corn (Zea mays L.) and cotton (Gossypium hirsutum) are globally important crops for food, feed, fuel, and industrial feedstocks. In Eastern Virginia, achieving optimal yields is challenging due to unpredictable environmental conditions which impact overall crop growth and nutrient use efficiency. More data are needed on adaptative corn management strategies that focus on increasing nutrient use efficiencies and crop yields (i.e., 4R nutrient management, biostimulants, and in-season crop protection chemicals). With less than 5% of Virginia's corn and cotton fields irrigated, increased irrigation adoption could stabilize/increase crop production outcomes in this region. Three studies were conducted to evaluate these management strategies with the following objectives:

1. To compare standard farmer practices with the Adaptive Corn Management System (ACMS) using a treatment omission/addition approach.
2. To analyze subsurface drip irrigation (SDI) effects on corn grain yield under different seeding and nitrogen (N) application rates in drought-prone soils of Eastern Virginia.
3. To evaluate SDI strategies in cotton, assessing the effects of dripline spacing, plant growth regulator (PGR) rates, irrigation strategies, N rates, and variety on yield. The first study integrated irrigation, in-season nutrient supplementation (soil and foliar applied), foliar fungicides, and biostimulants to enhance corn yields. Field trials conducted across five Virginia locations (2022 to 2023) with irrigated and non-irrigated sites showed yield improvements with supplemental nutrients, biostimulants, and fungicides in 4 of 10 experiments. The yield increase resulting from irrigation in intensive and standard management strategies ranged from -3 to 61%, averaging 8.9 and 34% for intensive and standard management practices, respectively. The second study (2022-2024) evaluated six SDI management strategies, four seeding rates (59,280 to 103,740 plants ha-1), and four N application rates (133 to 333 kg N ha⁻¹). Main effects of irrigation, seeding, and N rates significantly impacted yields. Irrigation and N interactions were significant across years for grain yield. Corn grain yield was greater by 102% with irrigation in 2022 compared to only 13%, and 51% in 2023 and 2024. Averaged over the three years the 0.91 m dripline and 0.91 m with volumetric water content (VWC) sensors increased revenue by $985 and $885 ha-1, respectively, above non-irrigated. Grain yield increased up to a seeding rate of 88,920 plants ha-1 and N rates up to 267 kg N ha-1. The third study utilized two experim¬¬¬¬¬ents evaluating SDI management strategies in cotton from 2019 - 2021. Experiment 1 of the third study tested three irrigation systems with various dripline spacings (0.91 m, 1.82 m, non-irrigated), four PGR rates (0%, 100%, 150%, 200% of current Virginia recommendations, and four cotton varieties. Experiment 2 examined three irrigation strategies (irrigation, fertigation, and non-irrigated), three N rates (89, 133, 178 kg ha-1), three PGR rates (0, 100 and 200%), and two cotton varieties. Results from experiment 1 showed that dripline spacing significantly influenced lint yields in 2 of 3 years. The PGR application rates significantly influenced lint yield in 2021 growing season only. Lint yield varied by variety in 3 of 3 years of the study. The 1.82 m dripline and 100% PGR rate produced the highest economic gains of $158 and $162 ha-1 respectively above check. In Experiment 2, the lint yield varied by irrigation all three years, while PGR rates, N application rates, and variety each influenced lint yield in 2 of 3 years. The highest rates of lint yield increase were achieved at 133 kg N ha-1. Irrigation implementation was more effective in increasing corn grain yields than cotton lint yields during the six-year study period. Corn grain yields were increased on average 60% with SDI compared to non-irrigated treatments over the three-year study. Inputs for adaptative corn management systems were not consistent for increasing grain yields. Although various PGR rates were evaluated, current PGR recommendations for cotton are sufficient with the varieties evaluated in maximizing lint yields. The current N applications for Virginia were in-line with those of the current study which identified 133 kg N ha-1. These studies provide the first data for corn and cotton management with SDI in Virginia and the Mid-Atlantic USA.