Remote Sensing Detection of Cotton and Corn Response to Varying Nitrogen Availability.

Managing N in crop production is difficult due to its transient nature in soils and variability across managed fields. Crop reflectance acquired through remote sensing can be a useful tool for managing variable rate fertilizer N applications. Aerial imagery can provide crop spectral reflectance data in a timely and cost effective manner. The objective of this research was to study relationships between vegetation indices (VI’s) derived from aerial imagery at different plant phenostages and varying N rates. Five VI’s derived from aerial images acquired from a cotton (Gossypium hirsutum L.) crop at early square to peak bloom and a corn (Zea mays L.) crop from V5 to V9 were used to study relationships and determine N effects on canopy and yield responses. The VI’s at early square were less related to varying N rates and yield than VI’s calculated at later stages. The coefficient of determination (r²) between 5 VI’s and yield of cotton ranged from 0.30 to 0.32 at early square and 0.52 to 0.57 at peak bloom. However, VI’s at early bloom were best correlated with fertilizer N rates with r² values from 0.92 to 0.94. For corn, r² values between VI’s and yield at V5 to V6 were from 0.62 to 0.76 compared to 0.79 to 0.86 at V8 to V9. In addition, Green Normalized Difference Vegetation Index was most related to N rates at V5 to V6 and V8 to V9 with r² values of 0.76 and 0.75, respectively. All VI’s, except Ratio Vegetation Index, had a positive relationship to N rates and yield in both corn and cotton. Therefore, VI’s extracted from aerial imagery may be useful for enhancing in-season N application and in-season yield estimation tools.