Optimizing Nitrogen Fertilization in Maize Production to Improve Yield and Grain Composition Based on NDVI Vegetation Assessment

Árpád Illés, Csaba Bojtor (), Endre Harsányi, János Nagy, Lehel Lengyel and Adrienn Széles
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Árpád Illés: Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi Street, 4032 Debrecen, Hungary
Csaba Bojtor: Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi Street, 4032 Debrecen, Hungary
Endre Harsányi: Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi Street, 4032 Debrecen, Hungary
János Nagy: Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi Street, 4032 Debrecen, Hungary
Lehel Lengyel: Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi Street, 4032 Debrecen, Hungary
Adrienn Széles: Institute of Land Use, Engineering and Precision Farming Technology, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 138 Böszörményi Street, 4032 Debrecen, Hungary

Agriculture, 2025, vol. 15, issue 21, 1-19

Abstract: Nitrogen fertilization is essential for balancing maize yield, grain composition, and environmental sustainability. This study aimed to evaluate the relationship between nitrogen (N) supply, grain quality traits, and yield potential using UAV-based Normalized Difference Vegetation Index (NDVI) monitoring in a long-term fertilization field experiment in Eastern Hungary. Six N levels (0–300 kg ha −1 ) were tested during two consecutive growing seasons (2023–2024) under varying climatic conditions. The obtained results showed that moderate N doses (120–180 kg ha −1 ) provided the optimal nutrition level for maize, significantly increasing yield compared to the control (+5.086 t ha −1 in 2024), while excessive fertilization above 180 kg ha −1 did not result in any substantial yield gains; however, it significantly modified grain composition. Higher N supply enhanced protein content (+0.95% between 0 and 300 kg ha −1 ) and reduced starch percentage, confirming the protein–starch trade-off, whereas oil content was less affected by nitrogen fertilization, similarly to previous results. The strongest correlation between NDVI values and yield was measured at the post-silking stage (112 DAS; R = 0.638 in 2023, R = 0.634 in 2024), indicating the suitability of NDVI monitoring for in-season yield prediction. Overall, NDVI-based monitoring proved effective not just for optimizing N management but also for supporting site specific fertilization strategies to enhance maize productivity and nutrient use efficiency.

Keywords: maize; NDVI; nitrogen supply; nutrient replenishment; remote sensing; yield composition (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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