Maize production in India's Punjab region is crucial for food security but faces challenges in nitrogen (N) use efficiency. Conventional blanket N applications often lead to environmental losses and reduced profitability. This study investigated the efficacy of real-time precision nitrogen management using a leaf color chart (LCC) and chlorophyll content meter (CCM) on the growth, physiology and yield of three maize hybrids (PMH14, PMH13, ADV9293) in the Punjab central plains during the 2024 kharif season. A split-plot design was employed with hybrids as main plots and six N management strategies as sub-plots: LCC-based N application at thresholds 4 and 5, CCM-based application at thresholds 40 and 50, a combination of 50 % nano-N + 50 % inorganic N and a control of 100 % recommended dose of fertilizer (RDF; 120:30:30 kg/ha N:P:K). Results demonstrated that sensor-guided N management, particularly CCM 50, significantly enhanced key parameters compared to conventional methods. The hybrid PMH14 exhibited superior performance, achieving the highest plant height (130.20 cm), leaf area (4317.59 cm²), cob length (23.39 cm), total chlorophyll content (42.00 mg/g FW) and grain yield (8.35 t/ha). Critically, the interaction between PMH14 and the CCM 50 treatment yielded the maximum grain output (10.13 t/ha). These findings conclusively show that synchronizing N supply with crop demand through high-threshold sensor-based management optimizes physiological processes, improves nitrogen use efficiency and significantly boosts productivity, offering a sustainable alternative to fixed-schedule N fertilization for maize in similar agro-climatic zones.
Ayush et al. (Tue,) studied this question.