Efficient resource management is crucial for sustaining maize (Zea mays L.) productivity in semi-arid Indo-Gangetic Plains, where water scarcity and nitrogen-use inefficiency limit yield potential. The present two-year field study (2022–2023) at ICAR-IARI, New Delhi, investigated: (1) the influence of precision sub-surface drip fertigation (SSDF) of N and crop residue management on maize physiological performance and productivity, and (2) relationships between physio-biochemical parameters and grain yield of maize. Treatments included 0–100 % of the recommended dose of nitrogen (RDN) delivered in 3 or 4 splits via SSDF (main-plot treatments), with or without greengram residue (3 t ha⁻¹) incorporation (sub-plot treatments), in comparison to conventional surface fertilization. Data were analysed using analysis of variance (ANOVA) for a split-plot design. SSDF significantly (p < 0.05) improved photosynthetic rate, chlorophyll status (SPAD), intercepted PAR (IPAR), and yield attributes. The treatment with100 % N delivered in 4 splits (100 % N-4S) recorded the highest net photosynthesis (31.9 µmol CO₂ m⁻² s⁻¹), SPAD (50.4), IPAR (1673 µmol m⁻² s⁻¹), and grain yield (6.7 t ha⁻¹), revealing 19.6–27.5 % higher yield over conventional practices. The treatment with 75 % N delivered in 4 splits (75 % N-4S) achieved a comparable yield (6.3–6.4 t ha⁻¹), enabling a 25 % nitrogen saving without loss in productivity. Residue incorporation enhanced stomatal conductance (↑9 %), transpiration efficiency (↑5 %), specific leaf nitrogen (↑5–9 %), and improved grain yield by 5.5 % (during the year 2022) and 9.8 % (during 2023) over no-residue. Additionally, PCA explained 65 % of the total trait variance, with key loadings from specific leaf area (SLA), SPAD, photosynthetic nitrogen-use efficiency (PNUE), and normalized difference vegetation index (NDVI). These findings confirm that integrating SSDF with optimized N scheduling and residue management enhances maize resource-use efficiency and yield, offering a resilient, sustainable strategy in semi-arid agro-ecosystems.
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