Optimizing Maize Agronomic Performance Through Adaptive Management Systems in the Mid-Atlantic United States

Maize (corn) (Zea mays L.)) yield is influenced by complex factors including abiotic and biotic stress and inconsistent nutrient use effi-ciency that challenge optimal yield. Standard management recommendations often fall short, prompting interest in intensive manage-ment strategies within an Adaptive Corn Management System (ACMS). To investigate this, we employed an addition/omission tech-nique within a randomized complete block design (RCBD) to compare standard maize management recommendations with an inten-sive management protocol aimed at identifying yield-limiting factors. Our intensive management approach combined early-season bi-ostimulant applications with mid-season supplementation of phosphorus (P), potassium (K), and nitrogen (N) at the V7 stage, followed by foliar fungicides and additional foliar N at the R1 stage. Field trials spanned five Virginia locations over 2022 and 2023 under both ir-rigated and non-irrigated conditions, yielding ten site-years of data. Analysis via ANOVA in JMP® Version 18 with Dunnett’s test re-vealed that the intensive management approach significantly increased grain yield in 3 of 10 experiments. Under non-irrigated condi-tions, the intensive management practices averaged 5.9% higher yield than the standard management check. We observed a higher re-sponse to irrigation in standard management check (34%) than in intensive management check (8.9%). Site-specific irrigation impacts ranged from 14% to 61%. Results emphasize site-specific input recommendations for yield enhancement.