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

Abstract

Maize (corn) (<i>Zea mays</i> L.) yield is influenced by complex factors, including abiotic and biotic stress and inconsistent nutrient use efficiency, which challenge optimal yield. Standard management recommendations often fall short, prompting interest in intensive management strategies within an Adaptive Maize Management System (ACMS). To investigate this, we employed an addition/omission technique within a randomized complete block design (RCBD) to compare standard maize management recommendations with an intensive management protocol aimed at identifying yield-limiting factors. Our intensive management approach combined early-season biostimulant 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 irrigated and non-irrigated conditions, yielding ten site-years of data. Analysis via ANOVA in JMP^&reg; Version 18 with Dunnett&rsquo;s test revealed that the intensive management approach significantly increased grain yield in 3 of 10 experiments. Under non-irrigated conditions, the intensive management practices averaged 5.9% higher yield than the standard management check. We observed a higher response 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.