The tour route will travel through fields with uneven terrain. Farm cart transport (e.g. gators) can be available for those who request assistance.
Schedule of Events
Field Tour 11 :00 -11:15 Station 1. Welcome, overview of the program and biostimulant research on Shade-Trees 11:15 – 11:30 Station 2. Plant-based irrigation scheduling: pressure bomb and infra-red thermography 11:30 – 11:45 Station 3. ET-based irrigation scheduling and Flatheaded borer research 11:45 – 12:00 Station 4. Cover cropping and Heat-stress prevention 12:00 – 12:15 Station 5. Boxwood blight control 12:15 – 12:30 Station 6. LiDAR “smart” air-blast sprayer and drone demonstration
12:30 – 1:00 Station 1. Open chat with research team, refreshments and grilled sides.
Open House 1:00 – 2:00 Self guided tour. Researchers will be at each of the six stations to answer questions. Sprayer demos will take place at station 6 every 15 mins.
Shade tree growers need to be prepared for the effects of climate change in Oregon.
In order to equip growers with the tools necessary for production success, we aim to determine critical shade tree stress thresholds, characterize plant responses to drought conditions, and correlate remotely collected spectral images with ground based plant water stress measurements.
Previous studies have sought drought response measurements for Acer rubrum (Red Maple) and Quercus rubra (Red Oak), but never in a nursery production setting.
We aim to disseminate this information to Oregon shade tree growers at the completion of this experiment with the hope to aid growers in making data driven irrigation decisions and demonstrate the use of these technologies in nursery production settings.
In Oregon’s Willamette Valley, the heart of the nursery country, rainfall is scarce during the summer and humidity is low. Oregon’s dry summer conditions can lead to low moisture stress conditions for maples and oaks in normal years. Plant stress resulting from low soil moisture, high heat, and low relative humidity have been exacerbated in recent years with the increasing frequency of heatwaves and drought. Drought and heat stress scorch the maple and oak canopies, which can lead to decreased plant quality and economic losses for shade tree growers. Sensor-based technologies can be used to model plant responses to environmental gradients to develop warning systems to help growers prevent stress and bridge a knowledge gap in the nursery production industry regarding drought responses.
How are we studying plant stress responses?
Starting late June 2022, we will implement two irrigation treatments (well-watered and drought) in our shade tree planting with each row having independent irrigation control. The well-watered rows will be maintained at a soil water potential of >-1.0 mPa. The drought treatment rows will be allowed to naturally dry down to a soil water potential of -4 mPa. If during the experiment, our metrics (stomatal conductance and stem water potential) do not show considerable responses at -4 mPa tension, we will allow the drought treatment to continue to dry down progressively (-1 mPa) until stress is evident.
Why and how do we measure stem water potential?
Plant water status is commonly defined in terms of water potential or the ability of the water to do work. In most cases, well watered plants have “high” water status and drought conditions lead to a “low” water status (Levin and Nackley 2021). Using the pressure chamber, we will take midday stem water potential measurements twice weekly from 12pm-3pm. This time frame is important because it represents the time of day where leaf transpiration is at its maximum.
First, we will cover the leaf and stems to be measured with an opaque bag for at least 10 minutes before pressurization to allow the plant to stop transpiring. Once we excise the sample from the tree it should be placed into the pressure chamber or “pressure bomb” within 30 seconds (Levin 2019). Once the stem is placed into the chamber and pressure is applied, the amount of pressure that it takes to cause water to appear at the cut surface tells us how much tension the stem is experiencing.
Why and how do we measure stomatal conductance?
We measure stomatal conductance using a porometer that measures the degree of stomatal openness and the number of stomata (Licor.com). This indicates the plant’s physiological response to its current environment. If a plant is stressed, it will tend to close its stomata and lower the stomatal conductance rate. We will be using a combination of the LI-6800 Portable Photosynthesis System and the LI-600 Porometer/Fluorometer to make our measurements twice a week from 12pm-3pm.
For more information:
Please stay tuned in the coming months for more blog posts about how we will find plant stress thresholds by measuring the hydraulic conductivity of these shade trees. We will also correlate remotely collected spectral and thermal images with our ground based plant stress measurements to demonstrate how implementing a UAS equipped with a multispectral and thermal camera can be used to detect water stress in nursery production.
Nurseries grow a wide variety of species and use many different crop production methods which can make effectively scheduling irrigation difficult.
Mini-lysimeters are devices that measure evapotranspiration (ET) via a change in weight of a containerized crop.
Mini-lysimeter controlled irrigation has shown to reduce water use and conserve nutrients while producing plants of marketable size and quality.
The need for sensor-controlled irrigation
Irrigation scheduling for nursery is complex due to the wide variety of species grown, the variety of pot sizes, the differences in growing media, and differences in environmental conditions (i.e. greenhouses, hoop-houses, field nurseries, or use of shade cloths). These factors all influence the specific crop water requirements, making it difficult to determine a generalized irrigation solution. As such, irrigation scheduling is commonly based on grower intuition and experience. For example, it is common for an experienced grower to pick up pots as they walk through a can-yardto get a feel for the weight and irrigation need. With funding support from the ODA-OAN research program, we sought out to develop an automated sensor-controlled irrigation system that is based off container weight, referred to as a mini-lysimeter controlled irrigation system.
What are lysimeters?
Lysimeters are devices that directly measure crop evapotranspiration (ET), which is the transfer of water from the soil to the atmosphere through plants by transpiration, and from the soil by evaporation. Lysimeters consist of a tank filled with soil and crop that is placed on a scale. Any change in weight of the tank is a direct measure of water moving in or out of the system. This provides a direct measurement of water consumption from the tank’s boundary, which can be used to inform irrigation scheduling. Lysimeters have historically been used in agronomic crops like wheat, alfalfa, or legumes. However, they can be scaled down for use in nursery and greenhouse crops, which are often referred to as mini-lysimeters (Fig. 1). You can read more about mini-lysimeters and their many applications in our recent publication.
System Design The mini-lysimeter controlled irrigation system at the NWREC consists of 16 mini-lysimeters. They are suitable for measuring up to 10kg (22 lbs.), which can accommodate up to a 3-gal container (Fig. 2). The mini-lysimeters are hooked up to a Campbell Scientific CR1000X data logger (Campbell Scientific Inc, Logan, UT) using a multiplexer. The system is programmed to trigger irrigation for a zone based on the average container weight. This ensures that the applied irrigation is representative of the variability between containers, such as differences in the water holding capacity of the media, and irrigation uniformity. A guide detailing the design, calibration, and performance of the mini-lysimeter controlled irrigation system and can be found here.
System Performance When mini-lysimeter controlled irrigation is compared to traditional irrigation methods (i.e. irrigation on a timer), it has shown to use less water while producing plants of equal size and quality. Read more about this study here. Mini-lysimeter-controlled irrigation also responds more effectively to the seasonal and daily variations in water demand, increasing irrigation frequency during hot and dry conditions, and foregoing irrigation during cooler days or after rain. This is particularly salient as extreme weather events become more frequent. Having another set of eyes (sensors) looking over your crops can help reduce losses from over- and under-watering.
How we are using low-cost and open-source weather stations for decision support
On-farm weather data can provide valuable information to growers including informing irrigation scheduling, tracking plant growth indices, and mitigating damaging events like frost, heat waves or disease. Weather can vary widely across landscapes, even across a single field, and we have found that there is value in having multiple distributed weather stations on-farm to capture variability across small spatial scales. To do this cost effectively, I developed a low-cost open-source weather station (LOCOS) for my M.S. thesis at the University of Idaho that uses low-cost sensors and an Arduino microcontroller for data logging. By distributing multiple LOCOS across a vineyard, we found that there were distinct micro-climates that had varying susceptibility to grape powdery mildew disease. From calculating a Powdery Mildew Risk Index at each station, we saw that some vineyard blocks could benefit from unique fungicide application schedules. You can read more about this project here.
Since then, the LOCOS have been adapted to study crop water stress. In the summer of 2021, we used LOCOS equipped with infrared thermometers to develop a crop water stress index (CWSI) for hazelnuts. The CWSI is based on leaf temperature and weather data (air temperature, relative humidity, wind speed, and solar radiation). Leaf temperature is a known indicator of plant stress. When a plant is actively transpiring the leaves will be cooler than the surrounding air because of the evaporative cooling effect of transpiration. Whereas a plant that is stressed and not transpiring will have a warmer canopy that is closer to the ambient air temperature. The CWSI varies from 0 to 1, where 1 indicates a stressed, non-transpiring plant, and 0 indicates a well-watered plant transpiring at max potential.
We used the LOCOS to collect canopy temperature of the hazelnut trees from June to September, 2021. The trees were subject to three different irrigation treatments, over watered, moderate water, and no water (dryland) so we could get a range of canopy temperatures to incorporate into our model. We also collected data on leaf water potential, leaf transpiration and leaf conductance to validate the index against. We found that the CWSI we developed was closely correlated with leaf water potential (r2 = 0.84), leaf conductance (r2 = 0.75) and leaf transpiration (r2 = 0.72). These are exciting results because it shows that the LOCOS could provide continuous data on crop water stress that can be used to inform irrigation decision in near real-time. This summer, we will use the LOCOS in another study to develop a CWSI for red maples.