Comparison of AONR, EONR, and yield-goal methods reveals significant variability for corn crops in Florida, suggesting refined practices are needed.
Corn ( Zea mays L.) plays an important role in human and animal nutrition, biofuel production, and international economics. It is essential to fulfill the nitrogen (N) requirements to attain high yield potentials, provided that a recommended optimum N rate (ONR) is both economically and environmentally sustainable. The agronomic and economic ONR (AONR and EONR, respectively) and the yield‐goal‐based N rate (YGR) are benchmarks used in N recommendation systems. However, edaphoclimatic conditions, crop physiology, and field crop history might influence ONR estimations. This study aimed to compare AONR, EONR, and YGR in 3 years (2022, 2023, and 2024) and two fields. Response curves were created for different groupings: field‐year (six levels), year (with fields combined, three levels), field (with years combined, two levels), and complete dataset (one level). The AONR, EONR, and YGR were calculated from the best model for each level of grouping and ranged between 229 and 412, 229 and 351, and 219 and 318 kg ha −1 , respectively. Eight out of 12 levels were best regressed to linear‐plateau curves, while four followed quadratic curves. The EONR was either lower or equal to the AONR. The YGR did not adequately detect field‐year variability, meaning that growers might over‐ or under‐fertilize corn in Florida, applying 32 kg ha −1 more to 46 kg ha −1 less N than the EONR. These findings raise the question of which is the best approach to determine an ONR in Florida: regression or arithmetic. Further research needs to be addressed to improve estimation methods and account for field‐ and/or year‐specific variability.
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Leitão et al. (2025) studied this question.
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