Table 2_Field-scale evaluation of satellite-derived vegetation indices and image timing for in-season nitrogen management in corn.docx

IntroductionTraditional methods to determine the agronomic optimum nitrogen rate (AONR) for corn (Zea mays L.) rely on grain yield data, limiting in-season decision-making for nitrogen (N) management. Vegetation indices (VIs) derived from satellite imagery can serve as proxies for grain yield and help estimate in-season AONR, enabling timely sidedress applications. This study aimed to (1) quantify how VI–yield relationships vary during the vegetative period across fields with different tillage systems and crop residue; (2) determine whether VI–N response curves can be used to estimate AONR (AONRvi); and (3) assess the accuracy of AONRvi relative to yield-based AONR (AONRy).
MethodsThree rainfed on-farm field trials with contrasting tillage systems and four to five N rates were conducted in Indiana in 2021. PlanetScope imagery (3-m resolution) was used to calculate 16 VIs (8 NIR-based and 8 RGB-based) across multiple growth stages. Linear regressions between yield and VIs were used to assess strength of their relationship, followed by VI–N response curves to estimate AONRvi.
Results and DiscussionDuring the vegetative period, VI–yield relationships were generally weak (R2 ≤ 0.31) and varied across fields, with fewer significant relationships under higher crop residue conditions. Of the VI–N response curves evaluated, 17% met selection criteria for estimating AONRvi, with lower proportions observed in higher-residue systems. Mid-vegetative period imagery (V10–V11) produced the smallest deviations from AONRy for NIR-based indices, although no single VI consistently performed best across fields and timings. These results indicate that 3-m satellite imagery has potential to detect crop N response under commercial field conditions, but its reliability for estimating in-season AONR depends on management context, image timing, and spectral domain.