Location: Horticultural Crops ResearchTitle: Field testing of an automated canopy-temperature-based water stress index for precision irrigation of wine grape
|King, Bradley - Brad|
Submitted to: American Society of Enology and Viticulture Annual Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 2/1/2018
Publication Date: 6/18/2018
Citation: Shellie, K., King, B.A. 2018. Field testing of an automated canopy-temperature-based water stress index for precision irrigation of wine grape. Abstract for 69th American Society for Enology and Viticulture National Conference 6/18/18-6/21/18 in Monterey, CA.
Technical Abstract: In arid wine grape production regions, irrigation precision is limited by the logistical difficulty of monitoring vine water status. In previous research, we developed a model to predict the canopy temperature of a grapevine under well-watered conditions and used measured and predicted canopy temperatures to calculate a water stress index. The objective of this research was to automate data acquisition, calculation and display of the index and to relate index values with irrigation events, soil moisture and other indicators of vine water status. A sensor network system, which included infrared radiometers, a weather station, soil moisture probe, tipping bucket rain gauge and data logger, was installed in commercial plots of Malbec and Chardonnay at different vineyard sites located in southwestern Idaho. Data were acquired remotely in real-time and a daily crop water stress index was calculated and displayed graphically on a web-based user interface that was accessible for use by vineyard managers. Daily water stress index values decreased after an irrigation event and increased between irrigation events. The depth of water penetration during an irrigation event differed by vineyard and corresponded with irrigation event duration. Values of midday leaf water potential corresponded with water stress index values; however, the water stress index was more responsive to irrigation events than leaf water potential. Results from the first year of this two-year field trial suggest that this methodology can provide a real-time, automated daily indicator of vine water status for use as a decision-support tool in a precision irrigation system.