Context: Accurate and real-time diagnosis of crop nitrogen (N) status is essential for effective precision N management. Integrating the N nutrition index (NNI) with spectral non-destructive rapid monitoring technologies offers a promising approach to precision N management for field crops. However, applying spectral sensing technologies for providing fertilizer recommendations based on real-time plant N nutrition diagnosis for dripirrigated maize in arid regions remains challenging. Objective: Our study set out to leverage spectroscopic techniques to accurately diagnose maize N status at preand post-anthesis. Our goal was to develop a novel spectral index that could guide site-specific fertigation strategies in arid environments. Methods: The comprehensive field experiments with three maize varieties and different N levels were conducted from 2021 to 2023 in Inner Mongolia, China. Spectral reflectance, biomass, and leaf N concentrations were determined at various layers of maize plants across five growth stages. A Bayesian model to estimate leaf-based NNI was employed to develop leaf-based critical N concentration dilution curves for different ecological sites. The nitrogen nutrient triangle ratio index (NTRI), a key outcome of our research, was constructed using firstorder derivative spectral reflectance between 680 and 750 nm. We then compared the NNI prediction accuracies of NTRI with 29 published spectral indices, ensuring the robustness of our findings. Results: Compared to NNI prediction models based on twenty-nine published spectral indices, our newly developed NTRI demonstrated a superior correlation to NNI (R2 = 0.83). Independent validation confirmed NTRI's robustness, yielding an RMSE of 0.11 % and RE of 9.6 %, surpassing existing indices. Conclusions: Pre-anthesis N diagnosis was most sensitive to spectral diagnosis from the latest fully expanded leaf, while post-anthesis N diagnosis relied on ear leaves. NTRI's accuracy and resistance to varietal and interannual variability highlight its potential application for real-time N monitoring. Significance: Our innovative spectral index NTRI significantly advances spectral N nutrition diagnostics, enabling leaf-layer sensing and smart fertigation systems. This breakthrough paves the way for sustainable, high-yield maize production in arid regions.