17 May 2016 Remote sensing based water-use efficiency evaluation in sub-surface irrigated wine grape vines
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Increased water demands have forced agriculture industry to investigate better irrigation management strategies in crop production. Efficient irrigation systems, improved irrigation scheduling, and selection of crop varieties with better water-use efficiencies can aid towards conserving water. In an ongoing experiment carried on in Red Mountain American Viticulture area near Benton City, Washington, subsurface drip irrigation treatments at 30, 60 and 90 cm depth, and 15, 30 and 60% irrigation were applied to satisfy evapotranspiration demand using pulse and continuous irrigation. These treatments were compared to continuous surface irrigation applied at 100% evapotranspiration demand. Thermal infrared and multispectral images were acquired using unmanned aerial vehicle during the growing season. Obtained results indicated no difference in yield among treatments (p<0.05), however there was statistical difference in leaf temperature comparing surface and subsurface irrigation (p<0.05). Normalized vegetation index obtained from the analysis of multispectral images showed statistical difference among treatments when surface and subsurface irrigation methods were compared. Similar differences in vegetation index values were observed, when irrigation rates were compared. Obtained results show the applicability of aerial thermal infrared and multispectral images to characterize plant responses to different irrigation treatments and use of such information in irrigation scheduling or high-throughput selection of water-use efficient crop varieties in plant breeding.
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Carlos Espinoza Zúñiga, Carlos Espinoza Zúñiga, Lav R. Khot, Lav R. Khot, Pete Jacoby, Pete Jacoby, Sindhuja Sankaran, Sindhuja Sankaran, "Remote sensing based water-use efficiency evaluation in sub-surface irrigated wine grape vines", Proc. SPIE 9866, Autonomous Air and Ground Sensing Systems for Agricultural Optimization and Phenotyping, 98660O (17 May 2016); doi: 10.1117/12.2228791; https://doi.org/10.1117/12.2228791

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