Purpose <p>Digital technologies have significantly improved nitrogen (N) fertilizer optimization in precision agriculture. A limitation of existing crop N detection approaches is that they primarily focus on above-canopy spectral measurements, overlooking the potential insights from lower canopy levels, which may more accurately reflect N stress through spectral reflectance associated with differential pigment expression.</p> Methods <p>This study introduces high-resolution Red, Green, and Blue (RGB) under-canopy imaging of maize (<i>Zea mays L</i>.) to assess in-season N fertilizer application at high spatial resolution using a 30 frames/sec acquisition rate. Utilizing a purpose-built field robot, developed specifically for this study and equipped with a digital RGB camera, field trials were conducted across Minnesota and New York with varying N rates. Analysis using multiple thresholding methods for the (R-B)/(R+B) index from images captured during day and night revealed a strong correlation between under-canopy images and applied N rates.</p> Results <p>R² values reached up to 0.78 in daytime and 0.92 under nighttime conditions. Semivariogram analysis indicated a range of influence of less than 6 m and showed that N stress spatial patterns are most pronounced with low N levels. Maps were generated based on 6-m field sections to represent field variability of N stress.</p> Conclusion <p>These findings suggest that high-resolution under-canopy RGB imaging is a viable, lowcost method for detecting maize N status with very high spatial resolution, offering a new perspective for precision agriculture.</p>