Hyperspectral Indices for Predicting Nitrogen Use Efficiency in Maize Hybrids

Enhancing the nitrogen (N) efficiency of maize hybrids is a common goal researchers, but involves repeated field and laboratory measurements that are laborious costly. Hyperspectral remote sensing has recently been investigated for measuring predicting biomass, N content, grain yield in maize. We hypothesized vegetation indices (HSI) obtained mid-season through hyperspectral could predict whole-plant biomass per unit taken up by plants (i.e., conversion efficiency: NCE) plant internal NIE). Our objectives were to identify best HSI end-of-season NCE NIE, rank selected HSI, evaluate effect decreased spatial resolution on values hybrid rankings. Analysis 20 from imaging at V16/18 R1/R2 manned aircraft UAVs over three site-years using mixed models showed two indices, HBSI1 HBS2, predictive NCE, HBCI8 HBCI9, NIE actual data collected five nine maturity. Statistical differentiation their or performance was possible based with greatest accuracy NIE. Lastly, decreasing changed values, an not evident.