Technical Abstract: Ground-based, active light sensing relies upon the Normalized Difference Vegetation Index (NDVI) for assessing crop nitrogen (N) response and applying N fertilizer. However, NDVI may not work well in semiarid environments where biomass and yields depend upon plant water. This study evaluated the Canopy Chlorophyll Content Index (CCCI) for predicting leaf chlorophyll and N contents while minimizing non-N related crop variation. Ground reflectance was measured on wheat (Triticium aestivum L.) in a small plot experiment using an active sensor with sensitivity in red, red edge, and near infrared wavebands. Relative chlorophyll and N were measured in flag leaf samples. The CCCI was calculated from the Normalized Difference Red Edge (NDRE) index and NDVI in ratio. Index CCCI was more highly correlated with chlorophyll (r^2=0.46) and leaf N (r^2=0.31) than NDRE (r^2<0.17) or NDVI (r^2<0.10). Chlorophyll and leaf N were well described by CCCI in two farm fields (r^2<0.80), but NDRE or NDVI performed well in only one field. The CCCI shows promise over NDVI for predicting N status. A simple N response index is proposed using CCCI to base late-season topdressing for increasing grain protein in hard red wheat.