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Posts from the ‘Plant Genetics’ Category

Improve Your Plant Study: 3 Types of Environmental Data You May Be Missing

What data are you missing?

The environment plays a large role in any plant study. Ensuring you’re capturing weather and other environmental parameters in the best way allows you to draw better conclusions. To accurately assess plant stress tolerance, you must first characterize all environmental stressors. And you can’t do that if you’re only looking at above-ground weather data.

For example, drought studies are notoriously difficult to replicate and quantify. Knowing what kind of soil moisture data to capture can help you quantify drought, allowing you to accurately compare data from different years and sites.

Get better, more accurate conclusions

It’s important for your environmental data to accurately represent the environment of your site. That means not only capturing the right parameters but choosing the right tools to capture them. In this 30-minute webinar, application expert Holly Lane discusses how to improve your current data and what data you may not be collecting that will optimize and improve the quality of your plant study. Find out:

  • How to know if you’re asking the right questions
  • Are you using the right atmospheric measurements? And are you measuring weather in the right location?
  • Which type of soil moisture data is right for the goals of your research or variety trial
  • How to improve your drought study, why precipitation data is not enough, and why you don’t need to be a soil scientist to leverage soil data
  • How to use soil water potential
  • How accurate your equipment should be for good estimates
  • Key concepts to keep in mind when designing a plant study in the field
  • What ancillary data you should be collecting to achieve your goals

Register now—>

Presenter

Holly Lane has a BS in agricultural biotechnology from Washington State University and an MS in plant breeding from Texas A&M, where she focused on phenomics work in maize. She has a broad range of experience with both fundamental and applied research in agriculture and worked in both the public and private sectors on sustainability and science advocacy projects. Through the tri-societies, she advocated for agricultural research funding in DC. Currently, Holly is an application expert and inside sales consultant with METER Environment.

Webinar: Why Water Content Can’t Tell You Everything You Need to Know

Water content can leave you in the dark

Everybody measures soil water content because it’s easy. But if you’re only measuring water content, you may be blind to what your plants are really experiencing.

Soil moisture is more complex than estimating how much water is used by vegetation and how much needs to be replaced. If you’re thinking about it that way, you’re only seeing half the picture. You’re assuming you know what the right level of water should be—and that’s extremely difficult using only a water content sensor.

Get it right every time

Water content is only one side of a critical two-sided coin. To understand when to water or plant water stress, you need to measure both water content and water potential.

TEROS 21 water potential sensor

In this 30-minute webinar, METER soil physicist, Dr. Colin Campbell, discusses how and why scientists combine both types of sensors for more accurate insights. Discover:

  • Why the “right water level” is different for every soil type
  • Why soil surveys aren’t sufficient to type your soil for full and refill points
  • Why you can’t know what a water content “percentage” means to growing plants
  • How assumptions made when only measuring water content can reduce crop yield and quality
  • Water potential fundamentals
  • How water potential sensors measure “plant comfort” like a thermometer
  • Why water potential is the only accurate way to measure drought stress
  • Why visual cues happen too late to prevent plant-water problems
  • Case studies that show why both water content and water potential are necessary to understand the condition of soil water in your experiment or crop

WATCH IT NOW—>

Presenter

Dr. Colin Campbell has been a research scientist at METER for 20 years following his Ph.D. at Texas A&M University in Soil Physics. He is currently serving as Vice President of METER Environment. He is also adjunct faculty with the Dept. of Crop and Soil Sciences at Washington State University where he co-teaches Environmental Biophysics, a class he took over from his father, Gaylon, nearly 20 years ago. Dr. Campbell’s early research focused on field-scale measurements of CO2 and water vapor flux but has shifted toward moisture and heat flow instrumentation for the soil-plant-atmosphere continuum.

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Download the “Complete guide to irrigation management”—>

How to interpret soil moisture data

Surprises that leave you stumped

Soil moisture data analysis is often straightforward, but it can leave you scratching your head with more questions than answers. There’s no substitute for a little experience when looking at surprising soil moisture behavior. 

Image of orange, yellow, and white flowers in a green house
Join Dr. Colin Campbell April 21st, 9am PDT as he looks at problematic and surprising soil moisture data.

Understand what’s happening at your site

METER soil scientist, Dr. Colin Campbell has spent nearly 20 years looking at problematic and surprising soil moisture data. In this 30-minute webinar, he discusses what to expect in different soil, environmental, and site situations and how to interpret that data effectively. Learn about:

  • Telltale sensor behavior in different soil types (coarse vs. fine, clay vs. sand)
  • Possible causes of smaller than expected changes in water content 
  • Factors that may cause unexpected jumps and drops in the data
  • What happens to dielectric sensors when soil freezes and other odd phenomena
  • Surprising situations and how to interpret them
  • Undiagnosed problems that affect plant-available water or water movement
  • Why sensors in the same field or same profile don’t agree
  • Problems you might see in surface installations

Watch it now

Learn more

Download the “Complete guide to irrigation management”—>

Chalk Talk: Intensive vs. Extensive Variables

Learn the difference between intensive and extensive variables and how they relate to soil water potential vs. soil water content in our new Chalk Talk whiteboard series. In this video series, Dr. Colin S. Campbell teaches basic principles of environmental biophysics and how they relate to measuring different parameters of the soil-plant-atmosphere continuum.

Watch the video

 

Learn more

To learn more about measuring water potential vs. water content read: Why soil moisture sensors can’t tell you everything.

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

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

Video transcript

Hello, my name is Colin Campbell. I’m a senior research scientist here at METER group. And I teach a class on environmental biophysics. Today I wanted to talk about something we teach in the class: the difference between extensive and intensive variables. I’d like to do this with the goal of relating it to the difference between volumetric water content and water potential. 

Here, I have a picture of a ship moving through the ice and some metal that’s been heated in a furnace. I think we would agree the ship has the highest amount of heat in it compared to this very small piece of metal. And if we placed that piece of metal onto the outside of the ship, despite the fact that there is more heat in the ship, we know the heat would not move from the high amount of heat (ship) to the low amount of heat (metal). It would actually move from the highest temperature to the lowest temperature. Why is that?

The reason is that heat moves because of temperature and not because of heat content or the amount of heat in something. Heat content defines an amount or an extent. And we generally term something that defines an extent or an amount as an extensive variable.An extensive variable depends broadly on the size of something or how much of something there is. 

This differs for temperature. Temperature doesn’t depend on size. The temperature could be the same in a very small room or a very large room, but the amount of heat or heat content in those rooms would be quite different. When we describe temperature, we talk about intensity, which is why we call these types of variables intensive variables. This is because they don’t depend on size or amount. 

Let’s talk about another example. Here’s your heating bill. Maybe it’s natural gas. What you’re paying for is the amount of heat you put into the house. But the question is, are you comfortable in the house? And from this bill, we can’t tell. Maybe you put in 200 heat units, whatever those might be. We can’t tell if that’s comfortable because we don’t know the size of the house or the type of insulation. All those things would influence whether you were comfortable. 

Alternatively, if the temperature is 71 F that’s quite comfortable. That’s equivalent to about 22 degrees Celsius. So the intensive variable, temperature, is different than the extensive variable, heat content, that tells us how much heat we put in. And that’s important because at the end of the day, that leads to cost. 

On this side, we don’t know how much we paid to keep it at 22 C because heat content doesn’t tell us anything about that. But the intensive variable temperature does tell us something about comfort. So both of these variables are critical to really understanding something about our comfort in the house. 

Now let’s talk about the natural environment. Specifically, we’re going to talk about soils. We’ll start with the extensive variable. When we talk about water in soil, the extensive variable is, of course, water content. Water content defines the amount of water. Why would we care about water content? Well, for irrigation or a water balance.

The intensive variable is called water potential. What does water potential tell us? It tells us if soil water is available and also predicts water movement. If this soil had a water content of 25% VWC and another soil was at 20% VWC, would the water move from the higher water content to the lower water content? Well, that would be like our example of the ship and the heated piece of metal. We don’t know if it would move. It may move. And if the soil on either side was exactly the same, we might presume that it would move from the higher water content to the lower water content, but we actually don’t know. Because the water content is an extensive variable, it only tells us how much there is. It won’t tell us if it will move. 

Now, if we knew that this soil water potential was -20 kPa and this soil water potential over here was -15 kPa, we would know something about where the water would move, and it would do something different than we might think. It would move from the higher water potential to the lower water potential against the gradient in water content, which is pretty interesting but nonetheless true. Water always moves from the highest water potential to the lowest water potential.

This helps us understand these variables in terms of plant comfort. We talked about the temperature being related to human comfort. We know at what temperatures we are most comfortable. With plants, we know exactly the same thing, and we always turn to the intensive variable, water potential, to define plant comfort.

For example, if we have an absolute scale like water potential for a particular plant, let’s say -15 kPa is the upper level for plant comfort, and -100 kPa is the lower level of comfort, we could keep our water potential in this range. And the plant would be happy all the time. Just like if we kept our temperature between 21 and 23 Celsius, that would be comfortable for humans. But of course, we humans are different. Some people think that temperature is warm, and some think it’s cold. And it’s the same for plants. So this isn’t a hard and fast rule. But we can’t say the same thing with water content. There’s no scale where we can say at 15% water content up to 25% water content you’ll have a happy plant That’s not true.If we know something about the soil, we can infer it. But soil is unique. And we’d have to derive this relationship between the water content and the water potential to know that. 

So why would we ever think about using water content when we measure water in the soil? One reason is it’s the most familiar to people. And it’s the simplest to understand. It’s easy to understand an amount. But more importantly, when we talk about things like how much we’re going to irrigate, we might need to put on 10 millimeters of water to make the plants happy. And we’d need to measure that. Also if we want to know the fate of the water in the system, how much precipitation and irrigation we put on versus how much is moving down through the soil into the groundwater, that also relates to an amount.  

But when we want to understand more about plant happiness or how water moves, it’s going to be this intensive variable, water potential that makes the biggest difference. And so with that, I’ll close. I’d love for you to go check out our website www.metergroup.com to learn a little bit more about these measurements in our knowledge base. And you’re also welcome to email me about this at [email protected] group.com.

Take our Soil Moisture Master Class

Six short videos teach you everything you need to know about soil water content and soil water potential—and why you should measure them together.  Plus, master the basics of soil hydraulic conductivity.

Watch it now—>

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.

ZL6 Data Logger in a wheat field

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”—>

Download the “Researcher’s complete guide to SDI-12″—>

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.

Grapes being irrigated

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.

Fruit on a tree branch

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.

IoT Technologies Chart

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

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

Download the “Researcher’s complete guide to SDI-12″—>

Get more info on applied environmental research in our

Learn more

Download the “Complete guide to irrigation management”—>

3 Insider Strategies for a More Accurate Soil Moisture Picture (Part 1)

How Do you Know You’re Getting Accurate Soil Moisture?

Researchers and irrigators may wonder if their soil moisture sensors are accurate because probes at different locations in the same field have different water content readings. Different readings in soil moisture sensors are caused by spatial variation in water content. These readings provide researchers valuable information about soil texture, watering patterns, and water use. Here are some ideas and strategies to keep in mind when trying to understand the varying patterns of soil moisture at your research or irrigation site. Click the links for more in-depth information about accurate soil moisture.

Grapes on the vines down isles

One irrigator noticed a few sensors indicating low water content after a heavy rain that had uniformly wetted his vineyard.

Horizontal vs. Vertical Variation

It’s helpful to distinguish variation in the vertical from variation in the horizontal. Most people expect strong vertical variation due to wetting and drying patterns, soil horizonation, and compaction. Water content can vary drastically over distances of only a few centimeters, especially near the soil surface. Horizontal variation is typically less pronounced in a bare or uniformly planted field, and at a given depth, it might be quite small. But surprisingly large variations can exist, indicating isolated patches of sand or clay or differences in topography. One irrigator noticed a few sensors indicating low water content after a heavy rain that had uniformly wetted his vineyard. Knowing that sand has a low field capacity water content, he surmised (correctly) that he had found the sandy areas in the vineyard.

Researcher holding an ECHO EC-5 in front of soil

Soil moisture sensors sometimes measure unexpected things.

Unexpected Readings

Because properly installed dielectric soil moisture sensors lie in undisturbed (and therefore unanalyzed) soil, they sometimes measure unexpected things. One researcher buried a probe in what appeared to be a very dry location and was startled to measure 25 to 30% volumetric water content. Those readings made the soil appear saturated, but obviously it wasn’t. She dug down to the sensor and found a pocket of clay. As she discovered, it is impossible to get much information from an absolute water content measurement without knowing what type of soil the sensor is in.

Since we expect variation, how do we account for it? How many probes are needed to adequately characterize the water content in an application or experiment? There is no simple answer to this question. The answer will be affected by your site, your goals, and how you plan to analyze your data. Here are some things you might consider as you plan.

Sun rising behind a wheat field

If a field will be irrigated as a unit, it should be monitored as a unit at one representative spot.

Strategy #1: Irrigation—Use Soil Moisture as an Indicator

What information do you have when you know a field’s volumetric water content? That number independently tells an irrigator very little. Soil moisture can be used like a gauge to show when a field is full and when it needs to be refilled, but the “full” and “empty” are only meaningful in context.

The goals of irrigation are to keep root zone water within prescribed limits and to minimize deep drainage. Understanding and monitoring the vertical variation lets you correlate a real-time graph of water use data with above-ground field conditions and plant water needs. It makes sense to place probes both within and below the root zone.

By contrast, measuring horizontal variation—placing sensors at different spots in the field—is not very helpful. If a field will be irrigated as a unit, it should be monitored as a unit at one representative spot. Because there’s no way to adjust water application in specific spots, there’s no benefit to quantifying spatial variation in the horizontal. Like a float in a gas tank, a set of soil moisture sensors in the right spot will adequately represent the changing soil moisture condition of the whole field.

We recommend a single probe location in each irrigation zone with a minimum of one probe in the root zone and one probe below it. Additional probes at that site, within and below the root zone, will increase the reliability of the information for the irrigation manager, at minimal additional cost.

In two weeks: Learn two more techniques researchers use in crop studies and ecology studies to account for variability in order to obtain an accurate soil moisture picture.

Get more info on applied environmental research in our

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

A comparison of water potential instrument ranges

Water potential is the most fundamental and essential measurement in soil physics because it describes the force that drives water movement.

Tomatoes on a plant

Water potential helps researchers determine how much water is available to plants.

Making good water potential measurements is largely a function of choosing the right instrument and using it skillfully.  In an ideal world, there would be one instrument that simply and accurately measured water potential over its entire range from wet to dry.  In the real world, there is an assortment of instruments, each with its unique personality.  Each has its quirks, advantages, and disadvantages.  Each has a well-defined range.

Below is a comparison of water potential instruments and the ranges they measure.

Water potential instrument ranges diagram

A comparison of water potential instrument ranges

To learn more about measuring water potential, see the articles or videos below:

How to Create a Full Soil Moisture Release Curve

Two Old Problems

Soil moisture release curves have always had two weak areas: a span of limited data between 0 and -100 kPa and a gap around field capacity where no instrument could make accurate measurements.

Plant sprouting from the soil

Using HYPROP with the redesigned WP4C, a skilled experimenter can now make complete high-resolution moisture release curves.

Between 0 and -100 kPa, soil loses half or more of its water content. If you use pressure plates to create data points for this section of a soil moisture release curve, the curve will be based on only five data points.

And then there’s the gap. The lowest tensiometer readings cut out at -0.85 MPa, while historically the highest WP4 water potential meter range barely reached -1 MPa. That left a hole in the curve right in the middle of plant-available range.

New Technology Closes the Gap

Read more

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

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

Stop Hiding Behind a Shield

Get better air temperature accuracy with this new method

ATMOS 41 weather station standing in a field

Accurate air temperature is crucial for microclimate monitoring

The accuracy of air temperature measurement in microclimate monitoring is crucial because the quality of so many other measurements depend on it. But accurate air temperature is more complicated than it looks, and higher accuracy costs money. Most people know if you expose an air temperature sensor to the sun, the resulting radiative heating will introduce large errors. So how can the economical ATMOS 41’s new, non-radiation-shielded air temperature sensor technology be more accurate than typical radiation-shielded sensors?

We performed a series of tests to see how the ATMOS 41’s air temperature measurement compared to other sensors, and the results were surprising, even to us. Learn the results of our experiments and the new science behind the extraordinary accuracy of the ATMOS 41’s breakthrough air temperature sensor technology.

In this brief 30-minute webinar, find out:

  • Why you should care about air temperature accuracy
  • Where errors in air temperature measurement originate
  • The first principles energy balance equation and why it matters
  • Results of experiments comparing shielded sensor accuracy against the ATMOS 41 weather station
  • The science behind the ATMOS 41 and why its unshielded measurement actually works

Watch the webinar

See weather sensor performance data for the ATMOS 41 weather station.

Explore which weather station is right for you.

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