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Algorithm for variable-rate nitrogen application in maize based on active crop canopy sensor
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DOI：10.1016/j.atech.2026.102469.png)
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Abstract
En 中文
Spatial variability in maize nitrogen demand requires decision-support systems that can translate mid-season crop status into accurate, real-time fertilizer recommendations. This study developed and validated a sensor-based nitrogen management algorithm for maize by integrating active optical sensing, in-season estimated yield (INSEY), and response index (RI) concepts within a computationally efficient polynomial framework suitable for real-time application. Field experiments were conducted under four nitrogen rates (0, 75, 100, and 125 kg N ha⁻¹) and at four sensing stages (35, 45, 65, and 75 days after sowing) to calibrate yield prediction and nitrogen response models. Normalized difference vegetation index (NDVI) data acquired using a GreenSeeker sensor were combined with growing degree days to estimate baseline and nitrogen-enriched yield potential. Strong exponential relationships were observed between INSEY and grain yield, with the highest prediction accuracy at 45 days after sowing (R² = 0.97). The response index effectively captured crop responsiveness and supported estimation of attainable yield under additional nitrogen supply. The quadratic model accounted for 72–84% of the variation in nitrogen requirement (R² = 0.72–0.84), while INSEY-based prediction reached R² = 0.98 at 65 days after sowing. Algorithm-guided nitrogen management achieved a maximum yield of 7.9 t ha⁻¹ while reducing nitrogen input by 20–30% compared with conventional practice. The novelty of this work lies in combining RI-based yield response with INSEY-derived baseline yield in a simplified polynomial model suitable for on-the-go variable-rate nitrogen application under Indian agro-ecological conditions. This framework provides a practical pathway for real-time and sustainable nitrogen management in maize.
Keywords:
Variable rate applicator
Sensor-based algorithm
In-season estimated yield (INSEY)
Response index (RI)
Nitrogen use efficiency Precision agriculture
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