Developing a crop based strategy for on-the-go nitrogen management in irrigated cornfields

Traditional nitrogen (N) management schemes for corn production systems in the Corn Belt have resulted in low N use efficiency (NUE), environmental contamination, and considerable debate regarding use of N fertilizers in crop production. The major causes for low NUE of traditional N management practices are: (1) poor synchrony between soil N supply and crop demand, (2) field uniform applications to spatially-variable landscapes that commonly have spatially-variable crop N need, and (3) failure to account for temporal variability and the influence of weather on mid-season N needs. Therefore, the objective of this work was to develop a reflectance-based technology for in-season and on-the-go nitrogen (N) fertilizer management in irrigated cornfields. First, a series of experiments were conducted to answer relevant questions pertaining to sensor positioning and orientation to maximize sensitivity for biomass and N status estimation. The second objective was to assess chlorophyll (Chl) status in cornfields using active crop canopy sensor readings by means of comparing the results with relative chlorophyll meter data (SPAD) units. Sensor and SPAD readings were collected in three cornfields in central Nebraska from V9 to R4. Finally an algorithm for in-season N management based on active sensor readings was developed using ancillary data from a long-term study. The results indicate that sensor readings provide information not only about relative Chl content but also about plant distribution and biomass. The four vegetation indices evaluated were linearly related with relative SPAD readings during vegetative growth stages. RWDRVI, RChl index, and RAR showed more sensitivity than RANDVI to variations in relative Chl content. It also was found that (1) sensors can be used to predict N availability to the crop, (2) N deficiencies can be corrected depending on the degree of stress, (3) A SISENSOR \u3c0.78 during the period V11-115 may indicate irrecoverable yield loss. Active sensor technology can be used for on-the-go assessment of N status in irrigated cornfields. At this point the model developed is site-specific and needs to be tested in other environments