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Posts from the ‘Data loggers’ Category

The effects of environmental change on carbon cycling across the semi-arid west

Meet Christopher Beltz: G.A. Harris Fellowship winner

Increased nitrogen availability has the potential to alter many ecosystem functions—and is doing so already. This is due to the widespread response of net primary productivity (biomass) and soil respiration to increased nitrogen inputs into the biosphere.

Increases in nitrogen inputs are responsible for the acidification of soils, streams, and lakes and can affect forest and grassland productivity. Former G.A. Harris Fellowship winner, Christopher Beltz, a PhD student at Yale University, and his research team are examining two major drivers of carbon cycling: water and nitrogen. They want to understand the degree of limitation by both of these factors in the semi-arid ecosystems of the western United States and if that limitation changes by specific function.

Inspired by a mitigation pilot project

Beltz decided to study the effects of increased nitrogen on biomass after learning about the initiation of a major energy development in a sagebrush steppe system which caused declines in a local mule deer herd. He says, “One hypothesis was that the development significantly reduced available winter range forage and also impacted the use of it as the animals moved more quickly through the noisy environment. They wanted to see if the widespread application of fertilizers would potentially offset the loss of biomass and increase the forage quality. In the end, it was clear that the effect of nitrogen fertilization alone would have minimal to no effect. However we also noticed some variability in the results and that this variability seemed to be related to precipitation.”

Beltz thought that if he could control the water in a system in addition to nitrogen, the results might be more consistent. Thus, Beltz and his research team broadcast nitrogen over the soil at three semi-arid grassland and shrubland/sagebrush sites in Colorado and Wyoming. He says, “The three sites essentially have a similar species list, annual precipitation, and annual temperature. However, temperature increases as you go south, and there are some differences in seasonality. The shrublands in the far north are the driest in the late summer which is typical of shrublands, where you see a large amount of precipitation occurring in the spring with a deficit in the summer. Larger taproots are beneficial in this system because they can access deeper water reservoirs.”

Measuring soil moisture improves understanding

The team used METER weather stations, soil moisture sensors, and data loggers to monitor site conditions (i.e., precipitation, air temperature, soil moisture, and soil temperature) with high temporal resolution. Beltz explains, “We monitored soil moisture to understand whether our treatments were having any effect. We needed to know if the treatments actually altered the soil water conditions. With soil sensors in the ground, we could monitor that. We also monitored precipitation at the site level because of the fine scale spatial heterogeneity of precipitation in these systems. We weren’t confident we could obtain this with interpolation or modeling; we wanted site-specific values.”

Beltz uses this and other data to understand the interactive effects of nitrogen and water and also changes in water and nitrogen concentrations. He says, “We do a classic full-factorial manipulation outdoors. We perform the exact same manipulations with the same timing at each site. We measure a whole suite of variables that range from ecosystem structure to ecosystem function. This includes soil respiration, plant community, soil microbial communities (fungal and bacterial) using next-generation sequencing. We look at pools of soil carbon, and we do some fractionation so we can get at more labile and recalcitrant carbon compounds.”

Beltz says that monitoring soil moisture at multiple depths is important. “Our soil samples come from the same depths as the sensors so we can differentiate depth when we look at changes in bacterial or fungal composition. We then try to tie that to temperature and moisture. In 2018, we added an additional set of soil moisture sensors in our water treatment so we could start to quantify the effect in the soil depth that those water treatments were having. This helped explain a lot of what we were seeing.”

Nitrogen or water: which is the driver?

Beltz says the analyses are ongoing, but what they’ve learned so far is that an application of water equivalent to 12 millimeters precipitation penetrates to 10 centimeters of depth, and the effect of that application lasts three to seven days at all of their sites. He says, “Last year, we had an unseasonably large amount of precipitation at our northerly site. So for most of the season, the water treatments and the controls were identical in terms of water availability. That was a very helpful context for us because we started to see things that did not match the expected patterns.”

Looking at the big picture, he adds, “What’s come out of this is not what anybody expected. One major finding, at least in the initial analyses at two of our sites, is that it’s really the combined treatment of increased nitrogen and water that has the effect. This is not necessarily surprising in some ways, however it is the widespread lack of response of any other treatment combination that is extremely interesting.”

What it all means

Beltz sums up the implications of his research like this: “We know water availability and precipitation will shift globally due to climate change, as well as nitrogen deposition and availability. Our research is trying to tease apart the effects of two factors, at least within the western United States, that we know are likely to cause changes to the structure and function of dryland ecosystems. As we start to look at carbon balance or shifts in function or species competition of plant communities, we are finding out that it’s the combined effect of increased nitrogen and water that will cause a more major change as opposed to just one or the other. It’s important that we integrate that combination into models that often do not account for both of these factors.”

Beltz says in the future he’s interested in continuing his work in the carbon/nitrogen cycle world, and he wants to look at integrating nitrogen and water into carbon balance modeling efforts.

You can read more about the first study mentioned, regarding nitrogen fertilization in the sagebrush steppe, which was published in PloS ONE: https://doi.org/10.1371/journal.pone.0206563

Find out about his research here: christopherbeltz.com or via Twitter @BeltzEcology

Now accepting applications: 2019 G. A. Harris Fellowship

The Grant A. Harris Fellowship provides $60,000 worth of METER research instrumentation (six $10,000 awards) to graduate students studying any aspect of agricultural, environmental, or geotechnical science.

Apply now

Learn more

Learn more about measuring soil moisture. Download “The researcher’s complete guide to soil moisture“.

To understand how soil moisture and soil water potential work together, download “The researcher’s complete guide to water potential.”

Data deep dive: why am I seeing diurnal changes in soil moisture?

In the video below, METER soil scientist Dr. Colin Campbell discusses an often-misdiagnosed water content signal that looks like typical diurnal temperature cycling but is actually due to a phenomenon called hydraulic redistribution. He shows how easily these patterns can be seen in ZENTRA Cloud data management software.

Watch the video

 

 

 

Learn more

Learn more about measuring soil moisture. Download “The researcher’s complete guide to soil moisture“.

To understand how soil moisture and soil water potential work together, download “The researcher’s complete guide to water potential.”

Video transcript

Hello, my name is Colin Campbell. I’m a research scientist here at METER Group. And today we’re going to be digging into some water content data that I collected over the last summer. This is a field that’s planted in spring wheat, it’s about 700 meters across. And we’ve set up six measurement sites. At each one of these sites, we’re making several measurements, but the ones we’re going to talk about today are just water content. And while we’ve installed water content sensors at 15, 45, and 65 centimeters, we’re just going to focus on the 65-centimeter water content sensors. These sensors are the METER TEROS 12 soil moisture sensors, so they also measure electrical conductivity and temperature, and we’re going to look at temperature as well because that figures into this discussion. 

So this field was planted in April of 2019. And not a lot interesting goes on at the 65-centimeter depth through April, May, and June. But as we get into July, the wheat is reaching maturity, and they essentially are going to cut off the irrigation water here on July 22. So up to July 22, there’s really not a lot of movement in the water content. One of the sites decreases a little bit, but each line is flat. What I noticed as I was looking at this particular graph is after this long period of very flat data, after June 22 when the irrigation was cut off, we start to see some movement in the water content at this depth Not only is there movement down, but there’s a daily movement of the actual water content signals, all but this top light green line. And it made me wonder, what’s going on? 

Diurnal water content fluctuations are not always due to temperature.

Initially, whenever you see a diurnal movement, you suspect that it’s caused by temperature. It’s been said that every sensor is probably a temperature sensor first, and a sensor of whatever we’re really interested in second. In this case, we can look to see what the temperature is doing at that depth. Here’s soil temperature, at 65 centimeters, and even though there’s just a little bobble in the line, the line is almost completely flat. We see the seasonal trends in temperature, but really no diurnal temperature cycling. And this scale is also fairly small. So back to our 65-centimeter water content. If it’s not temperature that’s affecting these lines, then what is it? 

I’ve seen this before in an experiment that I did years ago in a non-irrigated wheat field. We were measuring down at  150 centimeters, and when the water had been used up in the upper levels of the soil profile, the roots of the wheat plant just simply went down to 150 centimeters and started taking water up. So this is what I assume is also happening here. The wheat has extended its roots down to 65 centimeters, since its irrigated wheat. That’s not too deep, but wheat doesn’t necessarily need to get its roots down super deep. And as the wheat accesses that water, we’re seeing these daily drops in water. But then we’re seeing just a slight increase in water. Here on July 28, we’re seeing that water go up slightly. And so why is this happening? We might understand how the water is being taken out of the soil, but why do we see a slight increase in the water content (just a few tenths of a percent)? 

What I think is happening, in this case, is that it’s not temperature, but actually, roots are growing down into this area, and they’re probably growing around the sensor. As we change from day to night, we see a release in the elasticity of the water in the xylem, and maybe just a little bit more water down in the roots as they’re the transpiration pull of the day is lessened and stops overnight. The stomates are closed, and we see just a little bit of water coming back into the roots and possibly into the soil. 

Now there was a big discussion many years ago about whether this was something called hydraulic lift where trees could take up water from deep in the soil profile and essentially give it back to plants near the surface. And although it was a great debate, it was never proven that this actually happened: water being spread from deeper locations to more shallow locations by roots. But this is probably hydraulic redistribution where we just have roots filling with water, and when they are filled, we see a little bit in the water content sensor.

Soil moisture sensors aid forensic science in time-of-death estimates

Extending time of death estimates

Forensic scientists are looking at better, more accurate ways of determining the post-mortem interval, or time of death. When a human body decomposes, microbes and nematodes become abundant in the soil surrounding the body. The types and maturity of these organisms may be a means of determining the time of death, but thus far most studies have focused on short post-mortem time frames.

Scientists look for ways to increase the accuracy of long-term post-mortem interval estimates

That’s why Stacy Taylor, her advisor, Dr. Jennifer DeBruyn, and their research team at the University of Tennessee are using cutting-edge molecular techniques and classical microscopic techniques to try and extend the time frames over which this approach could be used to determine how long it’s been since victims have died. 

Monitoring dramatic soil changes   

Taylor, a winner of the National Institute of Justice Graduate Research Fellowship in STEM, working in conjunction with the UT Anthropology Research Facility, is measuring biological and chemical changes in soil composition brought about by long-term human decomposition. She says, “We are looking at a combination of soil chemistry, microbial ecology, and some of the soil animals, particularly the nematodes, to get an entire food web approach in understanding all of the nutrient cycling that is occurring in these systems. We want to look at the soil chemistry patterns and microbial/nematode succession to see if these cross-inform each other.” 

Taylor explains some of the changes in soil composition that occur during both vertebrate and invertebrate decomposition, “Basically, any time you have a decomposition event that is not composed of plant litter, it creates what’s called a “hot spot” of nutrient enrichment. Unlike plant litter, which decomposes very slowly, with a vertebrate system you have a tremendous amount of protein and fat. You also have a lot of calcium, magnesium, sodium, and potassium. And when you put a large load of these things into the soil, you get a huge change in soil organic composition, nutrient availability, and soil moisture. So you’re essentially dealing with massive changes in a very localized soil environment.”

Decomposition also changes the soil water

Taylor and her adviser Dr. Debruyn had the fairly new idea to insert METER soil moisture, temperature and electrical conductivity sensors connected to data loggers into the soil in these hot spots, to see what kind of interesting data would turn up.

The TEROS 12 is an updated version of the sensor Taylor used in her research

She says they’ve been surprised at how informative and eye-opening this has been. She explains, “These hot spots change the ionic strength of the soil water. And that is highly correlated to electrical conductivity, which is measured by the soil moisture sensors. A change in ionic strength potentially impacts the salinity of the soil. Some of those changes have been shown to persist for well over a year, which is what these soil sensors are showing. I take an hourly reading, and the sensors are producing the most amazing data.”  

Taylor says the sensors were inserted into the soil surface, so they could measure the impact the decomposition produced immediately on the upper layer of soil. They took soil cores at 16 centimeters to measure soil pH and EC, and they also used RT-1 air temperature sensors to track accumulated degree days which are based on ambient air temperature and correlate with maggot growth and development rates. 

Identifying time markers

Taylor says that soil changes (in particular EC and temperature) are not just general deviations but show clear stages as decomposition progresses through time, indicating they might be useful as time markers. She explains, “We are tracking a succession of events. These events happen at particular time points and are associated with certain decomposition stages (i.e, bloat, active decay, advanced decay, or skeletonized remains). For example, you might see traces of increased electrical conductivity followed by a drop. If that drop happens at the same stage of decomposition, over and over, then you know that you have a time marker. And when you gradually accumulate some of these time markers, that can potentially inform some of the existing estimates of how long something has been there.”

Taylor’s study is about bringing better justice and more peace to the families of crime victims.

What’s the future?

Taylor says the implications of this study will help nail down many of the intrinsic controls on the decomposition process. And once they understand that, they’ll have a better idea how to employ these estimates of post mortem interval, which will bring better justice and more peace to the families of crime victims. About the future of the research, she says, “This is the kind of study that you want to replicate at other human decomposition facilities that vary by altitudes, weather, soils, and more. You need to be able to look at a variety of environments just to see what happens.”

You can read more about Stacy’s project here.

To learn more about measuring soil moisture, download “The researcher’s complete guide to soil moisture“.

To understand how soil moisture and soil water potential work together, download “The researcher’s complete guide to water potential.”

Freshwater shrimp grown in Korean rice paddy boost grower income

In South Korea, falling rice prices threaten the livelihood of many rice growers. Recently our Korean reps told us about an experiment performed in Jinju city, Gyeongsangnam-do, South Korea, by GNARES (Gyeongsangnam-do Agricultural Research & Extension Services) to increase grower income through simultaneous freshwater shrimp, lotus plant, and rice cultivation in a paddy field.

RT-1 water temperature sensors were installed along with METER data loggers to monitor the water temperature, ensuring it was optimal for shrimp growth. Through this experiment, GNARES found that environmental conditions were good for cultivating freshwater shrimp in this area. 

Download the “Researcher’s complete guide to water potential”—>

Download the “Researcher’s complete guide to soil moisture”—>

Engineers Without Borders alleviates Panamanian village water security issues

Engineers Without Borders (EWB) at Washington State University in Pullman, WA has partnered with a small indigenous village located in the Comarca Ngäbe-Buglé region of Panama. The relationship between this village and EWB at WSU began in 2016 when WSU alumna Destry Seiler began living in the village as a Peace Corps volunteer hoping to help solve the community’s water security needs.

A view of the Comarca Ngäbe-Buglé taken from the village in Panama.

During the rainy season in this village, approximately 20 households have access to water through a two-inch PVC pipe that operates by gravity. It runs approximately 1.5 kilometers through the jungle from a spring source higher in the mountain to small hose spickets located close to the homes on the distribution line. The other ~80 households do not have access to the distribution line and walk to the closest river or creek up to five times a day to find water. However, during the dry season, most spring sources dry up, leaving all households in the community to walk to the diminished supply of rivers to find their water.

A view of the water line currently serving ~20 homes in the village during the rainy season.

The village initially requested assistance from the Peace Corps in order to find a year-round source of clean water. But, after living in the village for 1.5 years, Ms. Seiler could not locate spring sources that both survived through the dry season and could also reach the homes in need through a gravity fed system.

Then Ms. Seiler began thinking of groundwater as a possible new water source for the community. Unfortunately, groundwater data for the Comarca Ngäbe-Buglé was not available from the local government agency. So she decided to reach out to WSU professor, Dr. Karl Olsen, to ask for assistance with a groundwater research project, and the EWB club was formed.

The club visited the village for the first time along with Ms. Seiler and faculty mentor Dr. Karl Olsen in August 2018 to do an initial survey of water use and needs, as well as to create a first-ever map of the area. EWB will return to Panama this June 2019 to implement a solar-powered water pump requested by a section of the community to deliver water from a spring source to approximately 20 homes on the nearest ridgeline. The club will also install latrines in a nearby community. They will continue the groundwater survey of the area through more extensive mapping and perform a more advanced analysis with the support of a local hydrologic company.

EWB members and WSU students Patrick Roubicaud, Kristy Watson, Destry Seiler, Perri Piller, Rene McMinn, and Kevin Allen during their visit to Panama, August 2018.

The team will use a METER-donated ATMOS 41 weather station along with a ZL6 data logger and ZENTRA Cloud software to assist in the data collection necessary to begin mapping groundwater in the area. The weather station will record precipitation, solar radiation, vapor pressure, temperature, wind, and relative humidity data that will enable EWB to begin to quantify environmental conditions and available water supply. When combined with streamflow data from rivers in the area, groundwater availability can also begin to be estimated. Because of ZENTRA Cloud, EWB will be able to view this information near-real time as well as share it with the village to help guide their design decisions. EWB plans to install the ATMOS 41 at a nearby village school to ensure weather station security and to provide an opportunity for local students to learn about their surrounding environment in a way they have not been able to do before.

To learn more about the Panamanian village or the work EWB from WSU is doing, visit ewb.wsu.edu.

See performance data for the ATMOS 41 weather station.

Download the “Researcher’s complete guide to soil moisture”—>

Download the “Researcher’s complete guide to water potential”—>

How to get started with ZENTRA Cloud

Researchers need to optimize funding and maximize peer-reviewed paper output. ZENTRA Cloud’s powerful data management software works with the new ZL6 data logger to make it easier to succeed at both.

ZENTRA Cloud reduces workload by speeding up analysis, streamlining workflow, and simplifying data sharing.

Try ZENTRA Cloud now

Want to explore how ZENTRA Cloud works? Request access to a live test account.

Take a ZENTRA Cloud guided tour

Get a comprehensive look at ZENTRA Cloud’s capabilities and learn how to get started here.

Download the “Researcher’s complete guide to soil moisture”—>

Data collection: 8 best practices to avoid costly surprises

Every researcher’s goal is to obtain usable field data for the entire duration of a study. A good data set is one a scientist can use to draw conclusions or learn something about the behavior of environmental factors in a particular application. However, as many researchers have painfully discovered, getting good data is not as simple as installing sensors, leaving them in the field, and returning to find an accurate record. Those who don’t plan ahead, check the data often, and troubleshoot regularly often come back to find unpleasant surprises such as unplugged data logger cables, soil moisture sensor cables damaged by rodents, or worse: that they don’t have enough data to interpret their results. Fortunately, most data collection mishaps are avoidable with quality equipment, some careful forethought, and a small amount of preparation.

Before selecting a site, scientists should clearly define their goals for gathering data.

Make no mistake, it will cost you

Below are some common mistakes people make when designing a study that cost them time and money and may prevent their data from being usable.

  • Site characterization: Not enough is known about the site, its variability, or other influential environmental factors that guide data interpretation
  • Sensor location: Sensors are installed in a location that doesn’t address the goals of the study (i.e., in soils, both the geographic location of the sensors and the location in the soil profile must be applicable to the research question)
  • Sensor installation: Sensors are not installed correctly, causing inaccurate readings
  • Data collection: Sensors and logger are not protected, and data are not checked regularly to maintain a continuous and accurate data record
  • Data dissemination: Data cannot be understood or replicated by other scientists

When designing a study, use the following best practices to simplify data collection and avoid oversights that keep data from being usable and ultimately, publishable.

Read more

Download the “Researcher’s complete guide to soil moisture”—>

Download the “Researcher’s complete guide to water potential”—>

IoT Technologies for Irrigation Water Management (Part 2)

Dr. Yossi Osroosh, Precision Ag Engineer in the Department of Biological Systems Engineering at Washington State University, continues (see part 1) to discuss the strengths and limitations of  IoT technologies for irrigation water management.

Informed irrigation decisions require real-time data from networks of soil and weather sensors at desired resolution and a reasonable cost.

LoRaWAN (a vendor-managed solution see part 1) is ideal for monitoring applications where sensors need to send data only a couple of times per day with very high battery life at very low cost. Cellular IoT, on the other hand, works best for agricultural applications where sensors are required to send data more frequently and irrigation valves need to be turned on/off. Low-Power Wide-Area Networking (LPWAN) technologies need gateways or base stations for functioning. The gateway uploads data to a cloud server through traditional cellular networks like 4G. Symphony Link has an architecture very similar to LoRaWAN with higher degree of reliability appropriate for industrial applications. The power budget of LTE Cat-M1 9 (a network operator LPWAN) is 30% higher per bit than technologies like SigFox or LoRaWAN, which means more expensive batteries are required. Some IoT technologies like LoRa and SigFox only support uplink suited for monitoring while cellular IoT allows for both monitoring and control. LTE-M is a better option for agricultural weather and soil moisture sensor applications where more data usage is expected.

NB-IoT is more popular in EU and China and LTE Cat-M1 in the U.S. and Japan. T-Mobile is planning to deploy NB-IoT network in the U.S. by mid-2018 following a pilot project in Las Vegas. Verizon and AT&T launched LTE Cat-M1 networks last year and their IoT-specific data plans are available for purchase. Verizon and AT&T IoT networks cover a much greater area than LoRa or Sigfox. An IoT device can be connected to AT&T’s network for close to $1.00 per month, and to Verizon’s for as low as $2 per month for 1MB of data. A typical sensor message generally falls into 10-200 bytes range. With the overhead associated with protocols to send the data to the cloud, this may reach to 1KB. This can be used as a general guide to determine how much data to buy from a network operator.

Studies show there is a potential for over 50% water savings using sensor-based irrigation scheduling methods.

What the future holds

Many startup companies are currently focused on the software aspect of IoT, and their products lack the sensor technology. The main problem they have is that developing good sensors is hard. Most of these companies will fail before batteries of their sensors die. Few will survive or prevail in the very competitive IoT market. Larger companies who own sensor technologies are more concerned with the compatibility and interoperability of these IoT technologies and will be hesitant to adopt them until they have a clear picture. It is going to take time to see both IoT and accurate soil/plant sensors in one package in the market.  

With the rapid growth of IoT in other areas, there will be an opportunity to evaluate different IoT technologies before adopting them in agriculture. As a company, you may be forced to choose specific IoT technology. Growers and consultants should not worry about what solution is employed to transfer data from their field to the cloud and to their computer or smart phones, as long as quality data is collected and costs and services are reasonable. Currently, some companies are using traditional cellular networks. It is highly likely that they will finally switch to cellular IoT like LTE Cat-M1. This, however, may potentially increase the costs in some designs due to the higher cost of cellular IoT data plans.

Download the “Researcher’s complete guide to water potential”—>

Download the “Researcher’s complete guide to soil moisture”—>

Get more info on applied environmental research in our

IoT Technologies for Irrigation Water Management

Dr. Yossi Osroosh, Precision Ag Engineer in the Department of Biological Systems Engineering at Washington State University, discusses where and why IoT fits into irrigation water management. In addition, he explores possible price, range, power, and infrastructure road blocks.

Wireless sensor networks collect detailed data on plants in areas of the field that behave differently.

Studies show there is a potential for water savings of over 50% with sensor-based irrigation scheduling methods. Informed irrigation decisions require real-time data from networks of soil and weather sensors at desired resolution and a reasonable cost. Wireless sensor networks can collect data on plants in a lot of detail in areas of the field that behave differently. The need for wireless sensors and actuators has led to the development of IoT (Internet of Things) solutions referred to as Low-Power Wide-Area Networking or LPWAN. IoT simply means wireless communication and connecting to some data management system for further analysis. LPWAN technologies are intended to connect low-cost, low-power sensors to cloud-based services. Today, there are a wide range of wireless and IoT connectivity solutions available raising the question of which LPWAN technology best suits the application?

IoT Irrigation Management Scenarios

The following are scenarios for implementing IoT:

  1. buying a sensor that is going to connect to a wireless network that you own (i.e., customer supplied like Wi-Fi, Bluetooth),
  2. buying the infrastructure or at least pieces of it to install onsite (i.e., vendor managed LPWAN such as LoRaWAN, Symphony Link), and
  3. relying on the infrastructure from a network operator LPWAN (e.g., LTE Cat-M1, NB-IOT, Sigfox, Ingenu, LoRWAN).

This is how cellular network operators or cellular IoT works. LPWAN technology fits well into agricultural settings where sensors need to send small data over a wide area while relying on batteries for many years. This distinguishes LPWAN from Bluetooth, ZigBee, or traditional cellular networks with limited range and higher power requirements. However, like any emerging technology, certain limitations still exist with LPWAN.

Individual weather and soil moisture sensor subscription fees in cellular IoT may add up and make it very expensive where many sensors are needed.

IoT Strengths and Limitations

The average data rate in cellular IoT can be 20 times faster than LoRa or Symphony Link, making it ideal for applications that require higher data rates. LTE Cat-M1 (aka LTE-M), for example, is like a Ferrari in terms of speed compared to other IoT technologies. At the same time, sensor data usage is the most important driver of the cost in using cellular IoT. Individual sensor subscription fee in cellular IoT may add up and make it very expensive where many sensors are needed. This means using existing wireless technologies like traditional cellular or ZigBee to complement LPWAN. One-to-many architecture is a common approach with respect to wireless communication and can help save the most money. Existing wireless technologies like Bluetooth LE, WiFi or ZigBee can be exploited to collect in-field data. In this case, data could be transmitted in-and-out of the field through existing communication infrastructure like a traditional cellular network (e.g., 3G, 4G) or LAN. Alternatively, private or public LPWAN solutions such as LoRaWAN gateways or cellular IoT can be used to push data to the cloud. Combination of Bluetooth, radio or WiFi with cellular IoT means you will have fewer bills to pay. It is anticipated that, with more integrations, the IoT market will mature, and costs will drop further.

Many of LPWAN technologies currently have a very limited network coverage in the U.S. LTE Cat-M1 by far has the largest coverage. Ingenu, which is a legacy technology, Sigfox and NB-IOT have very limited U.S. coverage. Some private companies are currently using subscription-free, crowd-funded LoRaWAN networks to provide service to U.S. growers: however, with a very limited network footprint. Currently, cellular IoT does not perform well in rural areas without strong cellular data coverage.

In two weeks: Dr. Osroosh continues to discuss IoT strengths and limitations in part 2.

Download the “Researcher’s complete guide to soil moisture”—>

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Irrigation Curves—A Novel Irrigation Scheduling Technique

This week, guest author Dr. Michael Forster, of Edaphic Scientific Pty Ltd & The University of Queensland, writes about new research using irrigation curves as a novel technique for irrigation scheduling.

Growers do not have the time or resources to investigate optimal hydration for their crop. Thus, a new, rapid assessment is needed.

Measuring the hydration level of plants is a significant challenge for growers. Hydration is directly quantified via plant water potential or indirectly inferred via soil water potential. However, there is no universal point of dehydration with species and crop varieties showing varying tolerance to dryness. What is tolerable to one plant can be detrimental to another. Therefore, growers will benefit from any simple and rapid technique that can determine the dehydration point of their crop.

New research by scientists at Edaphic Scientific, an Australian-based scientific instrumentation company, and the University of Queensland, Australia, has found a technique that can simply and rapidly determine when a plant requires irrigation. The technique builds on the strong correlation between transpiration and plant water potential that is found across all plant species. However, new research applied this knowledge into a technique that is simple, rapid, and cost-effective, for growers to implement.

Current textbook knowledge of plant dehydration

The classic textbook values of plant hydration are field capacity and permanent wilting point, defined as -33 kPa (1/3 Bar) and -1500 kPa (15 Bar) respectively. It is widely recognized that there are considerable limitations with these general values. For example, the dehydration point for many crops is significantly less than 15 Bar.

Furthermore, values are only available for a limited number of widely planted crops. New crop varieties are constantly developed, and these may have varying dehydration points. There are also many crops that have no, or limited, research into their optimal hydration level. Lastly, textbook values are generated following years of intensive scientific research. Growers do not have the time, or resources, to completely investigate optimal hydration for their crop. Therefore, a new technique that provides a rapid assessment is required.

How stomatal conductance varies with water potential

There is a strong correlation between stomatal conductance and plant water potential: as plant water potential becomes more negative, stomatal conductance decreases. Some species are sensitive and show a rapid decrease in stomatal conductance; other species exhibit a slower decrease.

Plant physiologist refer to P50 as a value that clearly defines a species’ tolerance to dehydration. One definition of P50 is the plant water potential value at which stomatal conductance is 50% of its maximum rate. P50 is also defined as the point at which hydraulic conductance is 50% of its maximum rate. Klein (2014) summarized the relationship between stomatal conductance and plant water potential for 70 plant species (Figure 1). Klein’s research found that there is not a single P50 for all species, rather there is a broad spectrum of P50 values (Figure 1).

Figure 1. The relationship between stomatal conductance and leaf water potential for 70 plant species. The dashed red lines indicate the P80 and P50 values. The irrigation refill point can be determined where the dashed red lines intersect with the data on the graph. Image has been adapted from Klein (2014), Figure 1b.

Taking advantage of P50

The strong, and universal, relationship between stomatal conductance and water potential is vital information for growers. A stomatal conductance versus water potential relationship can be quickly, and easily, established by any grower for their specific crop. However, as growers need to maintain optimum plant hydration levels for growth and yield, the P50 value should not be used as this is too dry. Rather, research has shown a more appropriate value is possibly the P80 value. That is, the water potential value at the point that stomatal conductance is 80% of its maximum.

Irrigation Curves – a rapid assessment of plant hydration

Research by Edaphic Scientific and University of Queensland has established a technique that can rapidly determine the P80 value for plants. This is called an “Irrigation Curve” which is the relationship between stomatal conductance and hydration that indicates an optimal hydration point for a specific species or variety.

Once P80 is known, this becomes the set point at which plant hydration should not go beyond. For example, a P80 for leaf water potential may be -250 kPa. Therefore, when a plant approaches, or reaches, -250 kPa, then irrigation should commence.

P80 is also strongly correlated with soil water potential and, even, soil volumetric water content. Soil water potential and/or content sensors are affordable, easy to install and maintain, and can connect to automated irrigation systems. Therefore, establishing an Irrigation Curve with soil hydration levels, rather than plant water potential, may be more practical for growers.

Example irrigation curves

Irrigation curves were created for a citrus (Citrus sinensis) and macadamia (Macadamia integrifolia). Approximately 1.5m tall saplings were grown in pots with a potting mixture substrate. Stomatal conductance was measured daily, between 11am and 12pm, with an SC-1 Leaf Porometer. Soil water potential was measured by combining data from an MPS-6 (now called TEROS 21) Matric Potential Sensor and WP4 Dewpoint Potentiometer. Soil water content was measured with a GS3 Water Content, Temperature and EC Sensor. Data from the GS3 and MPS-6 sensors were recorded continuously at 15-minute intervals on an Em50 Data Logger. When stomatal conductance was measured, soil water content and potential were noted. At the start of the measurement period, plants were watered beyond field capacity. No further irrigation was applied, and the plants were left to reach wilting point over subsequent days.

Figure 2. Irrigation Curves for citrus and macadamia based on soil water potential measurements. The dashed red line indicates P80 value for citrus (-386 kPa) and macadamia (-58 kPa).

Figure 2 displays the soil water potential Irrigation Curves, with a fitted regression line, for citrus and macadamia. The P80 values are highlighted in Figure 2 by a dashed red line. P80 was -386 kPa and -58 kPa for citrus and macadamia, respectively. Figure 3 shows the results for the soil water content Irrigation Curves where P80 was 13.2 % and 21.7 % for citrus and macadamia, respectively.

Figure 3. Irrigation Curves for citrus and macadamia based on soil volumetric water content measurements. The dashed red line indicates P80 value for citrus (13.2 %) and macadamia (21.7 %).

From these results, a grower should consider maintaining soil moisture (i.e. hydration) above these values as they can be considered the refill points for irrigation scheduling.

Further research is required

Preliminary research has shown that an Irrigation Curve can be successfully established for any plant species with soil water content and water potential sensors. Ongoing research is currently determining the variability of generating an Irrigation Curve with soil water potential or content. Other ongoing research includes determining the effect of using a P80 value on growth and yield versus other methods of establishing a refill point. At this stage, it is unclear whether there is a single P80 value for the entire growing season, or whether P80 shifts depending on growth or fruiting stage. Further research is also required to determine how P80 affects plants during extreme weather events such as heatwaves. Other ideas are also being investigated.

For more information on Irrigation Curves, or to become involved, please contact Dr. Michael Forster: michael@edaphic.com.au

Reference

Klein, T. (2014). The variability of stomatal sensitivity to leaf water potential across tree species indicates a continuum between isohydric and anisohydric behaviours. Functional Ecology, 28, 1313-1320. doi: 10.1111/1365-2435.12289

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