Abstract
Farmers' interest in precision nitrogen (N) fertilization has grown in the inland Pacific Northwest due to significant within-field spatial variability in yield and protein content. Mapping the spatial variability of yield, protein content, and total grain N uptake (N-g) can be a useful tool for post-harvest evaluation of N sufficiency that, in turn, can guide precision N fertilization. We evaluated the applicability of combining RapidEye satellite imagery-derived vegetation indices with topographic variables derived from high-resolution data obtained from proximal sensors to estimate winter wheat yield, protein content, and N-g. Results indicate that the normalized difference vegetation index (NDVI), the normalized difference red edge index (NDRE), terrain curvature, slope, aspect, topographic wetness index, and solar radiation are the most relevant co-variables that contribute to spatial variability of yield and N-g. Yield and N-g exhibited strong relationships with NDVI and NDRE from late June through early July during grain filling stage, with nearly all R-2 > 0.6. We found greater yield and N-g values in concave-shaped terrain; 0-5 degrees and 10-20 degrees slopes; and flat, eastern, or northern aspects. In contrast, protein content exhibited weak relationships with vegetation indices and nearly all terrain factors. Prediction models demonstrated that these variables can provide good estimations of yield and N-g, with R-2 of 0.848 and 0.864, respectively, and RMSE of 48.47 and 0.0136, respectively. Combining RapidEye-based NDRE with proximal sensor-based topographical factors shows great potential for accurately and efficiently estimating winter wheat yield and N-g, which can help guide N fertilizer management.
NSTL
Elsevier