A crop water stress index based internet of things decision support system for precision irrigation of wine grape
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 impeded by the lack of a smart, decision support system (DSS) to remotely monitor vine water status....
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-08-01
|
| Series: | Smart Agricultural Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375523000321 |
| _version_ | 1827958886816022528 |
|---|---|
| author | Bradley A. King Krista C. Shellie |
| author_facet | Bradley A. King Krista C. Shellie |
| author_sort | Bradley A. King |
| collection | DOAJ |
| description | 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 impeded 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 in situ 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. The CWSI based IoT DSS used a unique combination of neural network modeling, edge computing, and IoT for real-time vine water stress monitoring for precision irrigation. |
| first_indexed | 2024-04-09T15:43:05Z |
| format | Article |
| id | doaj.art-6ec2496f5d984540b820f5df1207602a |
| institution | Directory Open Access Journal |
| issn | 2772-3755 |
| language | English |
| last_indexed | 2024-04-09T15:43:05Z |
| publishDate | 2023-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj.art-6ec2496f5d984540b820f5df1207602a2023-04-27T06:08:51ZengElsevierSmart Agricultural Technology2772-37552023-08-014100202A crop water stress index based internet of things decision support system for precision irrigation of wine grapeBradley A. King0Krista C. Shellie1Research Agricultural Engineer, USDA ARS Northwest Irrigation and Soils Research Laboratory, 3793N 3600 E, Kimberly, ID 83341, USA; Corresponding author.Research Horticulturalist (retired), USDA-ARS Horticultural Crops Research Unit, Corvallis, OR 97330, USAThe 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 impeded 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 in situ 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. The CWSI based IoT DSS used a unique combination of neural network modeling, edge computing, and IoT for real-time vine water stress monitoring for precision irrigation.http://www.sciencedirect.com/science/article/pii/S2772375523000321IrrigationWine grapeCrop water stress indexEdge computingDecision support systemInternet of Things |
| spellingShingle | Bradley A. King Krista C. Shellie A crop water stress index based internet of things decision support system for precision irrigation of wine grape Smart Agricultural Technology Irrigation Wine grape Crop water stress index Edge computing Decision support system Internet of Things |
| title | A crop water stress index based internet of things decision support system for precision irrigation of wine grape |
| title_full | A crop water stress index based internet of things decision support system for precision irrigation of wine grape |
| title_fullStr | A crop water stress index based internet of things decision support system for precision irrigation of wine grape |
| title_full_unstemmed | A crop water stress index based internet of things decision support system for precision irrigation of wine grape |
| title_short | A crop water stress index based internet of things decision support system for precision irrigation of wine grape |
| title_sort | crop water stress index based internet of things decision support system for precision irrigation of wine grape |
| topic | Irrigation Wine grape Crop water stress index Edge computing Decision support system Internet of Things |
| url | http://www.sciencedirect.com/science/article/pii/S2772375523000321 |
| work_keys_str_mv | AT bradleyaking acropwaterstressindexbasedinternetofthingsdecisionsupportsystemforprecisionirrigationofwinegrape AT kristacshellie acropwaterstressindexbasedinternetofthingsdecisionsupportsystemforprecisionirrigationofwinegrape AT bradleyaking cropwaterstressindexbasedinternetofthingsdecisionsupportsystemforprecisionirrigationofwinegrape AT kristacshellie cropwaterstressindexbasedinternetofthingsdecisionsupportsystemforprecisionirrigationofwinegrape |