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ARS Home » Pacific West Area » Kimberly, Idaho » Northwest Irrigation and Soils Research » Research » Publications at this Location » Publication #393131

Research Project: Improving Water Productivity and Quality in Irrigated Landscapes of the Northwestern United States

Location: Northwest Irrigation and Soils Research

Title: A crop water stress index based internet of things decision support system for precision irrigation of wine grape

Author
item King, Bradley - Brad
item SHELLIE, KRISTA - Retired ARS Employee

Submitted to: Smart Agricultural Technology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/17/2023
Publication Date: 2/19/2023
Citation: King, B.A., Shellie, K.C. 2023. A crop water stress index based internet of things decision support system for precision irrigation of wine grape. Smart Agricultural Technology. 4. Article 100202. https://doi.org/10.1016/j.atech.2023.100202.
DOI: https://doi.org/10.1016/j.atech.2023.100202

Interpretive Summary: Irrigation of wine grape in arid and semiarid regions is used as crop management tool, requiring precision irrigation management, as well as to sustain vine survival and growth. Precision irrigation management is hindered by the lack of an automated irrigation scheduling tool. The objectives of this study were to: develop and deploy an internet-of-things (IOT) system for monitoring vine water stress based on a thermal crop water stress index (CWSI), install the IOT system on commercial vineyards for use by irrigation managers, evaluate vine water stress monitoring using CWSI, and evaluate success of system use by vineyard irrigation managers. The CWSI IOT system was installed on two small commercial vineyards in southwestern Idaho USA for vineyard managers/owners to use for irrigation scheduling at their discretion. Daily CWSI was significantly (p < 0.001) correlated with midday leaf water potential available soil water confirming the daily CWSI effectively provided automated monitoring of vine water stress. Both vineyard managers reported daily use of the information for making irrigation scheduling decisions. Over a four-year study, each vineyard manager was able to maintain consistent seasonal average CWSI daily values and irrigation application amounts, despite yearly differences in climatic conditions. The results of this study demonstrate that an CWSI based IOT system can readily be adopted by commercial vineyards managers as a precision irrigation management tool.

Technical Abstract: The goal of irrigation for wine grape grown in arid or semiarid regions is to sustain vine survival and to optimize berry attributes for quality wine production. Precision irrigation of wine grape is hindered by the lack of a smart, decision support system (DSS) to remotely monitor vine water status. The objectives of this study were to: develop and field test an Internet of Things (IoT) DSS system for precision irrigation of wine grape. The IoT system was comprised of a suite of insitu sensors used to monitor real-time weather conditions, grapevine canopy temperature, soil moisture, and irrigation amount. Sensor data were collected and stored on a field deployed data logger that calculated a daily thermal Crop Water Stress Index (CWSI) for grapevine using a neural network model with real-time sensor data model inputs. The data logger also hosted, via a cellular modem, webpages showing a running, 12-day history of daily CWSI, fraction of available soil moisture (fASW), irrigation amount, and other sensor data. The webpages were accessible to vineyard managers via cell phone or computer. The CWSI based IoT DDS system was installed at two small acreage, commercial estate vineyards in southwestern Idaho USA over four growing seasons. At each vineyard site, the DSS was used daily by the vineyard irrigation manager to schedule irrigation events. Neither vineyard manager used any other quantitative vine water status monitoring tool for irrigation management decisions. The midday leaf water potential (LWP) of grapevines was routinely measured by research project personnel. Data collected over the study period at each vineyard showed a significant (p < 0.001) correlation with LWP and fASW, providing evidence that, under the conditions of this study, the daily CWSI based IoT provided automated, remote monitoring of vine water status. Both vineyard managers reported daily use of the DSS for irrigation scheduling decisions. Over the four-year study, each vineyard manager was able to maintain consistent seasonal average CWSI daily values and irrigation application amounts, despite yearly differences in climatic conditions. The results of this study demonstrate that a CWSI based IoT DSS can be used for precision irrigation of wine grape in a commercial vineyard under semiarid growing conditions.