Enhancing off-season maize production through tailored nitrogen management and advanced cultivar selection techniques - Oliveira, Bruno Rodrigues de; Ratke, Rafael Felippe; Steiner, Fábio; Al-Askar, Abdulaziz A.; Aguilera, Jorge González; Hashem, Amr H.; Sheteiwy, Mohamed S.; Sobrinho, Renato Lustosa [UNESP]; El-Tayeb, Mohamed A.; AbdElgawad, Hamada; Morales-Aranibar, Luis; Marques, Luciano Façanha; et al. (Elsevier, 2025)
Context: Climate change can trigger excessive rainfall, making mechanized soybean harvesting unfeasible. The off-season maize cultivation can benefit from soybean-maize rotation system, inoculated with Bradyrhizobium spp. strains, as a potential biological source of nitrogen (N). To meet the nutritional demand of maize crops, N fertilization management is essential. Recent research has sought to understand how maize cultivars respond to mineral N application. Objective: In this work, we used a modern methodology to select maize cultivars with greater response to different application inputs of mineral N fertilizer, including N derived from soybean crop residues. Methods: We used the Manhattan distance to verify the similarity between the responses of four maize cultivars (30F53VYHR, AG8700 PRO3, B2433PWU, and SYN7G17 TL) that were either unfertilized or fertilized with 40, 80, 120, and 160 kg N ha−1. The Technique for Order of Preference by Similarity to the Ideal Solution method was applied to select the most responsive cultivar. Results and conclusions: Among the four maize cultivars, SYN7G17TL and AG8700PRO3 are more responsive to N fertilizer application in medium and high-fertility agricultural soils, respectively. When soil fertility levels are disregarded, the AG8700PRO3 cultivar has greater potential response to N fertilization, agreeing with previous studies. Significance: The proposed approach is easy to use and adapt and provides an appropriate mechanism for selecting maize cultivars sown in areas with soybean residues, thus contributing to more sustainable planting as it adequately assesses nitrogen management.
Keywords: Decision making modeling; Land use systems; Multi-criteria assessment; Off-season maize; Zea mays L