The widespread adoption of smartphones and unmanned aerial vehicles (UAVs) has the potential to ease collection of in-season cotton nitrogen (N) status. Subsequently, in-season cotton N status could be used to drive management decisions. The utility and limitations of these new platforms must be assessed and compared to current in-season measurements. The objectives of this study were to evaluate the ability of early- and late-season ground-based measurements to provide insight into cotton N status and to evaluate the ability of aerial-based measurements to correlate to ground-based measurements. Although measurements failed to correlate strongly across seasons to leaf N, moderate relationships (R2 = 0.453) between chlorophyll meter readings and the dark green color index (DGCI) measured from a smartphone were observed in late-season measurements. Poor relationships were found between early-season UAV-acquired vegetation indices (VIs) and leaf N. Analysis of a subset of the data indicated relationships between chlorophyll meter readings and chlorophyll concentrations predicted by DGCI were strong for ground-based measurements and moderate for UAV-based measurements. (R2 = 0.711 and R2 = 0.511, respectively). Although additional site-years including aerial-based data are needed, this study demonstrates the usefulness of UAV-based reflectance data and VIs in predicting in-season cotton N status. Furthermore, it appears handheld DGCI measurements have the potential to replace chlorophyll meter readings for late in-season measurements of cotton N status.
