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Analyses of Yield Response with Subsurface Drip Irrigation Strategies and Remote Sensing with UAVs
Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org
Citation: 2018 ASABE Annual International Meeting 1801152.(doi:10.13031/aim.201801152)
Authors: Travis Ford, Christopher Hartman, Abhijit Nagchaudhuri, Madhumi Mitra
Keywords: drone, corn, crop water stress index, irrigation water use efficiency, thermal imaging
Abstract. Subsurface drip irrigation (SDI) is a judicious irrigation technique that is being used to irrigate crops in a cost effective way. This paper will outline research conducted at the University of Maryland Eastern Shore(UMES), on a 15 acre field where a 20 zone SDI set up was recently installed which allowed 4 irrigation treatment that were replicated 5 times within separate blocks. The four irrigation strategies that were tested in the 2017 growing season were 1/4 in, 3.18 mm.in, 1.59 in, and a control of 0 inches of irrigation per day. Irrigation was not applied on days in which rainfall saturated soil field capacity. The seeding rate was 28,000 per acre and a split-plot experimental design was implemented. The field was planted with a 12 row planter and harvested with a 6 row combine retrofitted with an Ag leader yield monitor. Data was analyzed with SMS Ag leader software. A FLIR thermal camera was flown above the corn canopy on an unmanned aerial vehicle (UAV) to record thermal imagery at predefined way points over crop canopy at appropriate stages of growth. These images are being stitched and processed to calculate water stress of the crop. Initial yield data show that SDI can significantly increase yield as compared to non-irrigated plots that received on average approximately 18 inches of rain during the growing season. Analyses of various irrigation strategies and UAV based thermal imagery will be continued in the future. Irrigated water use will be calculated to evaluate consumption differences among irrigation strategies.
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