17 May 2016 Strategies for soil-based precision agriculture in cotton
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Abstract
The goal of precision agriculture is to increase crop yield while maximizing the use efficiency of farm resources. In this application, UAV-based systems are presenting agricultural researchers with an opportunity to study crop response to environmental and management factors in real-time without disturbing the crop. The spatial variability soil properties, which drive crop yield and quality, cannot be changed and thus keen agronomic choices with soil variability in mind have the potential to increase profits. Additionally, measuring crop stress over time and in response to management and environmental conditions may enable agronomists and plant breeders to make more informed decisions about variety selection than the traditional end-of-season yield and quality measurements. In a previous study, seed-cotton yield was measured over 4 years and compared with soil variability as mapped by a proximal soil sensor. It was found that soil properties had a significant effect on seed-cotton yield and the effect was not consistent across years due to different precipitation conditions. However, when seed-cotton yield was compared to the normalized difference vegetation index (NDVI), as measured using a multispectral camera from a UAV, predictions improved. Further improvement was seen when soil-only pixels were removed from the analysis. On-going studies are using UAV-based data to uncover the thresholds for stress and yield potential. Long-term goals of this research include detecting stress before yield is reduced and selecting better adapted varieties.
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Haly L. Neely, Haly L. Neely, Cristine L. S. Morgan, Cristine L. S. Morgan, Scott Stanislav, Scott Stanislav, Gregory Rouze, Gregory Rouze, Yeyin Shi, Yeyin Shi, J. Alex Thomasson, J. Alex Thomasson, John Valasek, John Valasek, Jeff Olsenholler, Jeff Olsenholler, } "Strategies for soil-based precision agriculture in cotton", Proc. SPIE 9866, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping, 98660K (17 May 2016); doi: 10.1117/12.2228732; https://doi.org/10.1117/12.2228732
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