In-season optical sensor-based variable-rate nitrogen management in maize production: a meta-analysis

Abstract

Purpose In-season optical sensor-based variable-rate nitrogen application (VRA) is designed to optimize nitrogen (N) management in maize (Zea mays L.) by aligning N inputs with real-time crop demand, yet reports on its performance are inconsistent. This study quantified the effects of VRA relative to fixed-rate management on N inputs, yield, N use efficiency, and profit; assessed VRA’s economic response to market volatility; identified key moderators; tested hierarchical interactions among moderators; and characterized economic and N-efficiency trade-offs. Methods A systematic review through February 2026 yielded 25 studies and 235 paired comparisons. The log response ratio was calculated for total N rate, grain yield, partial factor productivity of N (PFPN), and partial profit. Weighted linear mixed-effects models estimated overall effects, single-moderator analyses identified drivers, and conditional inference trees identified hierarchical interactions. Results VRA reduced total N rate by 18%, increased PFPN by 22%, and produced a 6% profit gain without affecting grain yield. Profitability was significant across all six market scenarios and scaled with the N: Maize price ratio. Agronomic outcomes were governed primarily by pre-plant N strategy, with the greatest benefits when pre-plant N was absent or minimal (≤ 12 kg N ha⁻¹). Economic outcomes were driven by algorithm design and application timing. A quadrant analysis showed simultaneous improvements in profit and PFPN in 57% of comparisons. Conclusion Relative to the uniform-rate treatments reported in the included studies, VRA reduced N inputs and improved efficiency while maintaining yield. Success depends on conservative pre-plant N strategies, appropriate algorithm selection, and early to mid-season timing.

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