The Latest in Vineyard Sensor Technology
December 29, 2019
A "flux tower" equipped with multiple sensors to collect micrometeorological data for the GRAPEX project at a Borden Ranch vineyard in the Lodi AVA.
Photo: Ted Rieger
The National Grape Research Alliance (NGRA) in cooperation with the U.S. Department of Agriculture (USDA) Agricultural Research Service (ARS) held a sensor technology workshop in Sacramento November 13 that presented current sensor knowledge and applications by research scientists working throughout the U.S. representing academia, industry and government agencies.
Much of the current vineyard sensor technology available and in use today is for monitoring meteorological conditions and soil and vine water status for efficient water use and irrigation management. As several speakers pointed out, this will become increasingly important for California vineyard owners as groundwater monitoring and management regulations are implemented under the Sustainable Groundwater Management Act.
Proximal and In Situ Sensors
Dr. Andrew McElrone of the USDA-ARS and the University of California, Davis (UCD) Department of Viticulture and Enology provided an overview of current proximal and in situ sensor technologies used in vineyards and directions for the future. McElrone and his lab have focused on studying water balance in vineyards, and energy balance related to weather conditions and evapotranspiration (ET) that contributes to water flux in vineyards. This led to development of surface renewal monitoring technology, now commercially applied and sold by Tule Technologies for irrigation management.
Soil moisture sensors have been used for many years as indicators of soil water content and water use by plants and vines to assist with irrigation decisions. Examples include the neutron probe, Time Domain Reflectometry (TDR) sensors, capacitance sensors, soil tensiometers, and granular matrix soil sensors.
Vine, or plant, water stress sensors are direct measurement tools and include pressure chambers, leaf porometers and infrared sensors. McElrone mentioned a promising new sensor being field tested--the FloraPulse microtensiometer that can be attached to the vine trunk to continuously measure stem water potential in real time.
Benefits in the current market are that the costs of sensors are going down, sensor manufacturers and service providers have improved designs and pairing techniques, and, McElrone said, “They are doing a better job of data packaging, transmission, processing and delivery so growers can make decisions.” He observed, “The sensors themselves have not changed so much, but there has been more focus on managing data.” Examples of companies that provide integrated sensor and data management systems for vineyards and other crops are WaterBit and Arable. In addition, more work is being done in the areas of machine learning, artificial intelligence (AI), and neural networks to analyze data and do modeling for decision making.
He said a more recent development is the potential use of autonomous vehicles and vineyard monitoring robots to allow the use of mobile proximal sensors to collect data from more sample locations.
Dr. Terry Bates of Cornell University and project director of the national Efficient Vineyard Project (efficientvineyard.com) works with available off-the-shelf sensors and to identify other needs for developing new sensor technologies with the goal of “Measure, Model, and Manage.” However, as Bates explained, “A vineyard is not just a block, it’s a population of individual vines. The problem with vineyard management is that we’re trying to do uniform management in a non-uniform system.” A goal of the Efficient Vineyard Project is to enable variable-rate management. Bates believes technology will be heading toward more direct measurements on vines to enable individual vine to vine management. The Efficient Vineyard Project is working with Bloomfield Robotics, a startup company using prototypes developed by Carnegie Mellon University in Pittsburgh, PA. Bloomfield is developing a self-contained mobile sensor platform to gather vine by vine data to monitor and evaluate vine growth and characteristics, and to take berry counts for crop estimating.
Light Sensors and Imaging Technology
Kaitlin Gold, assistant professor with Cornell University and a National Aeronautics and Space Administration (NASA) researcher, discussed agricultural light sensors (imaging cameras and technologies), used more commonly to monitor canopy growth and stress, but also with potential use for pest and disease monitoring and management. She explained: “How light reflects off leaves and plants can tell us something about plant health and stress before we can see it visually. Sensors can see more types of light than we can see.”
She compiled a “cheatsheet” of five light sensor technologies with their operational light ranges, applications, cost ranges, and practical considerations and uses, summarized below.
- Digital cameras: Operate with visible light range (red, green, blue), and serve as “eye extenders.” They have relatively low cost, are readily available, easy to use, small yet powerful, but provide limited information. They are best for looking at properties we see over a wide range: greenness, growth, weeds, pests, visible disease. They have potential integrated pest management (IPM) uses for vine training, crop/canopy management, and disease management.
- Multispectral sensors: Operate using discrete segments of visible and near infrared (NIR) light and are good for general crop stress detection and indirect problem identification. They can be imprecise, provide limited information, and are budget flexible, available in a range of prices. They can be used for normalized difference vegetation index (NDVI), and general crop stress from multiple causes: nutrient deficiency, water stress, weeds, pests, and diseases. Potential IPM uses are vine training, crop/canopy management, vine nutrition, irrigation, disease management.
- Hyperspectral sensors: Operate with a light range of continuous visible to shortwave infrared (SWIR). Have potential applications for direct problem identification and trait quantification. They are currently very expensive, need more commercial development, and require expert interpretation. They can be used for specific biotic and abiotic stress detection and quantification.
- Thermal sensors: Operate using longwave infrared light with applications for temperature monitoring and properties that change plant temperature. Are available at moderate to high cost. High-resolution technologies are heavy, and data collected can become “noisy.” Used for properties that change plant temperature including water content, water stress and diseases that impact plant vascular activity. Potential IPM uses are soil management, vine nutrition, irrigation, and disease management.
- LiDAR: Operate in a very specific light region, either NIR or SWIR. Applications include laser, plant structure, plant height and biomass. These technologies can be high cost, they are best for use in the sky rather than on the ground. They can be used for measuring elevation, plant height, leaf volume and canopy density. Potential IPM uses include site selection, vine training, and crop/canopy management.
Gold advised, “Decide what information is important to you, then look for a sensor that can get you that. Much like fungicides, knowing how sensors work or don’t work is crucial to using them effectively.” She noted that commercially available sensors, most commonly digital and multispectral, are currently useful in vineyards for crop growth stage determination and general crop health, and available as services through companies such as Vine View and Ceres Imaging. Research, validation and development is still needed for other sensor uses and technologies. Specific stress detection and differentiation is not yet commercially available. Hyperspectral sensors still need major commercial development before they are ready for real-time, in-field use.
The Grape Remote sensing Atmospheric Profile & Evapotranspiration eXperiment (GRAPEX) is a project coordinated by the ARS Hydrology & Remote Sensing Lab (HRSL) based in Beltsville, MD in cooperation with E & J Gallo Winery to develop irrigation scheduling tools for California vineyards.
Providing background, ARS research hydrologist Dr. Bill Kustas of HRSL noted that California vineyards are increasingly being scrutinized for water use and groundwater regulation, in addition to experiencing variable precipitation and water availability related to drought conditions. “Our goal is to evaluate and refine a multi-scale remote sensing evapotranspiration (ET) model and integrate these tools and data into a vineyard irrigation scheduling and water management tool for improving water use efficiency,” Kustas said.
Using a wide range of sensor technologies, data have been collected since 2013 from two vineyard blocks at Borden Ranch near Galt, CA, within the Lodi American Viticultural Area (AVA), each planted to Pinot Noir—an older block of about 60 acres planted in 2009, and a 40-acre block planted in 2011. The project has collected micrometeorological and biophysical data during the growing seasons. In addition, ground, airborne and satellite remote sensing data were collected during intensive observation periods (IOPs) by the GRAPEX team at different vine phenological stages.
Continuous measurements of surface fluxes, including ET and environmental conditions, using eddy covariance micrometeorological systems with sensors on 8-meter high “flux towers” in each vineyard block are collected. Each tower is instrumented with a Campbell Scientific infrared gas analyzer and a three-dimensional sonic anemometer to measure concentrations of water, carbon dioxide and wind velocity. During the growing season three additional sonic anemometers are mounted at different heights on the tower to investigate the effects of canopy structure on near-surface turbulence. Other tower measurements and sensors include: the full radiation budget using a four-component net radiometer; incident and reflected photosynthetically active radiation (PAR) measured with quantum sensors from LI-COR; air temperature and water vapor pressure measured using three temperature and humidity probes; and precipitation measured using a tipping-bucket rain gauge from Texas Electronics. Both vine canopy and inter-row surface temperatures are measured using a pair of Campbell Scientific thermal infrared thermometers.
Subsurface measurements have included soil heat flux measured with a cross-row transect of five plates buried at a depth of 8 cm, soil temperatures measured with thermocouples, and soil moisture content measured with soil moisture probes. Profiles of soil water content and temperature have also been measured under the vines at different locations using HydraProbe and Decagon sensors.
Flowmeter sensors were placed in the irrigation driplines to monitor irrigation to estimate the amount of water applied in both vineyards during the growing season.
Vine canopy and cover crop development is visually tracked and recorded using a “phenocam”--a digital camera mounted along the road on the east side of each block that takes a daily photo.
Aerial imagery and remote sensing data are collected through three different methods at different heights: imagery from NASA Landsat satellites; through fix-winged aircraft flyovers using commercial vineyard imaging service providers; and unmanned aerial vehicle (UAV) imagery provided by AggieAir from Utah State University, a GRAPEX team member.
Kustas said, “Satellites give us snapshots of conditions at different times during the season—budbreak, bloom, fruit set, pre-veraison, veraison and harvest. UAVs could complete the picture for times when we don’t have satellite data.”
During the IOPs, at the different phenological stages, ground measurements were collected of leaf area index (LAI), leaf stomatal conductance, and photosynthesis using multiple sensor technologies, and of leaf water potential using a pressure chamber. These measurements were taken along transects across the vineyard to determine variability in vine biomass, water use and stress. In addition, ground level micrometeorological measurements were taken during the IOPs to evaluate conditions between vine canopies and below canopy turbulence.
More recently, two other GRAPEX vineyard sites have been established using similar sensor systems in Gallo managed vineyards: the Ripperdan site planted with Chardonnay and Merlot in Madera County; and the Barrelli Vineyard, a North Coast site near Cloverdale, Sonoma County, with Cabernet Sauvignon. The Borden Ranch GRAPEX vineyard blocks are scheduled to be grafted over from Pinot Noir to Cabernet Sauvignon in 2020. While this will result in an interruption in data collection for at least one year while the new scion vine material becomes established, it should benefit the project over the long-term with additional data for another variety at this site.
Forrest Melton is a senior research scientist at the NASA Ames Research Center at Moffett Field, CA and a faculty member at California State University, Monterey Bay. In addition to being a member of the GRAPEX team, Melton is working with the NASA Applied Sciences Program and the Western Water Applications Office to develop another agriculture irrigation tool, OPEN ET. The goal of OPEN ET is to produce reliable ET data at field scale in real time and make it available online at low cost and easily accessible for irrigated agricultural operations in the western U.S.
Melton noted that 10 percent of NASA’s budget is devoted to earth science applications, and part of this is focused on understanding, measuring and monitoring the water cycle including precipitation, snow properties, ET, soil moisture, groundwater, and plant chlorophyll. He said 35 years of Landsat imagery and data is freely and publicly available.
The OPEN ET project development team of government agencies and industry representatives includes NASA Earth Sciences, California Department of Food and Agriculture (CDFA), California Department of Water Resources, University of California, E & J Gallo Winery, California Almond Board, and others. Project development began in 2018 to develop user requirements and as Melton explained, “Everything we’ve done is driven by input from users.” Melton said beta testing of the OPEN ET website is planned for 2020, and the final phase of the project in 2021-2021 will be to refine custom website applications and provide user training, outreach and training materials.
Information and data management is collected and integrated from Landsat satellites, ground stations, NASA/U.S. Geological Survey/European Space Agency (ESA) Data Centers, Google Earth Engine, and other databases and models. Melton is also integrating work he has been involved with from NASA Satellite Irrigation Management Support (SIMS), and the UC-developed CropManage system (https://cropmanage.ucanr.edu/).
More info is available at www.etdata.org
(Ted Rieger, CSW, is a wine journalist based in Sacramento, California and a writer for wine industry media since 1988.)