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Assessing factors influencing maize yield response to nitrogen using remote sensing technologies
Abstract
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.
https://digitalcommons.unl.edu/dissertations/AAI3738927