Off-campus UNL users: To download campus access dissertations, please use the following link to log into our proxy server with your NU ID and password. When you are done browsing please remember to return to this page and log out.

Non-UNL users: Please talk to your librarian about requesting this dissertation through interlibrary loan.

Assessing factors influencing maize yield response to nitrogen using remote sensing technologies

Brian Theodore Krienke, University of Nebraska - Lincoln


Nitrogen (N) is a limiting nutrient in maize that is an environmental issue; the result of over or asynchronous application with respect to crop N uptake. Rates are largely determined by a yield goal, which fails to account for spatial and temporal variability in N supply and grain yield. Crop canopy sensors that monitor N status of maize have been validated as a way to increase nitrogen use efficiency (NUE), and maintain yield potential by applying N in-season. Such methods are not immune to the effects of temporal variability that occur beyond the time of application, such as intense rainfall events that are conducive to N loss. To identify potential factors that influence the temporal stability of hybrid respond to N, two different experiments carried out. In the first, blocks represented a range of soil organic matter (OM) and mean relative yield (MRY) values, and received split N application at different timings. Nitrogen, OM, MRY, and timing were evaluated across years for temporal stability and influence on yield. Results showed only MRY was temporally stable; although all factors influenced yield. Sidedress application beyond V14 lost yield. In the second experiment, temporal stability of hybrid response to N (RTN) was evaluated. Hybrids selected represented a broad range of RTN. Hybrid x N interaction was significant across site years, which indicated an inability to classify hybrids based on RTN. A final experiment compared crop canopy sensors from an unmanned aerial vehicle (UAV), to collect more frequent N status of maize, and established best management practices of how to utilize an active crop canopy sensor mounted to a UAV. Results showed that an active crop canopy sensor mounted on a UAV is a suitable platform to replace or augment current methods of acquiring N status of maize canopies. The collective result of experiments showed a lack in temporal stability that exists in terms of N management that is largely influence by local site and seasonal weather. Future research is needed to investigate the interplay of crop canopy reflectance, soil environment, and weather monitoring on a frequent basis to guide N management. ^

Subject Area

Agronomy|Soil sciences|Remote sensing

Recommended Citation

Krienke, Brian Theodore, "Assessing factors influencing maize yield response to nitrogen using remote sensing technologies" (2015). ETD collection for University of Nebraska - Lincoln. AAI3738927.