Why Using Soil Moisture Sensors for Irrigation Control will Increase Quality and Profit

Dr. Marc Van Iersel discusses drawbacks of excessive irrigation and strategies to reduce nursery water use to increase profits and quality.

In this webinar Dr. Marc Van Iersel presents the highlights of the past ten years of his research using soil moisture sensors for control of greenhouse irrigation.  He discusses the drawbacks of excessive irrigation and teaches specific strategies to reduce nursery water use with the ultimate goal of increasing profits and plant quality.

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Our scientists have decades of experience helping researchers and growers measure the soil-plant-atmosphere continuum.

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Dr. Marc Van Iersel, Professor of floriculture at the University of Georgia.

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Transcript

MARC VAN IERSEL 0:10
I would like to talk today about the evolution of the research I’ve been doing using soil moisture sensors for irrigation control. It basically the highlights of the last 10 years of what I’ve done and where I think this is going to move in the future. But let’s start off with a little bit background. Why am I interested in water to begin with? Most of the Earth is covered with water. And when you look at the total amount of water that we have on Earth it is really a very large amount of water. But unfortunately, only two and a half percent of all the water on Earth is actually fresh water and the water that we use in our daily lives for drinking water, everything around the house, and to grow the crops that we eat. So there is still a large amount of freshwater available, but most of the freshwater on Earth is actually trapped in glaciers and the north and south pole. So even when you look at freshwater, only one half percent of all of the freshwater on Earth is actually available for use by us. So the amount of water that we actually have access to is a tiny fraction from all the water on Earth.

MARC VAN IERSEL 1:23
So when you look at what has been happening with regard to water use around the world, it has been increasing exponentially over the last century. And agriculture is a big part of that water use. On average around the world 60% of all the water that we use is being used for agriculture for irrigation. So the human population is going to keep increasing. And what we need to do is make sure that we use the water as efficiently as we possibly can so that we can maximize production of agricultural crops.

MARC VAN IERSEL 2:03
When you look at water use in different places around the world, that is probably not a big surprise to most people that in the US, we use more water than almost anywhere else in the world. Actually, when you compare all of these countries, the US is using per capita more water than any other country in the world. So what that does mean, in my mind is that there’s a lot of room for improvement. So that is something that I’m very interested in, what can we do to make sure that we use our limited water resources as efficiently as possible?

MARC VAN IERSEL 2:39
So to give you an idea of the use of water for irrigation in the US, this graphic on the right hand side of the screen indicates where we use water in the US, and most water is used for power generation. But that is water that actually isn’t used up. That water is taken generally from rivers and released back in rivers. When you look higher up, you see that irrigation accounts here for 34% of total water use and that is what I call consumptive use. That is water that is being used by agriculture that we cannot use for anything else. When you look at this, if we want to make water go further, we have to focus on irrigation.

MARC VAN IERSEL 3:25
When you look at irrigation, according to the USGS, much of the water that is used, 40% of total water use in the US is being used for irrigation. For irrigation, water use can come either from water that is extracted from surface water, so rivers and lakes, and about 31% of all the surface water that we use is being used for irrigation, or we can pump water from the ground. And almost 70%, about two thirds of all of the water that is being pumped from the ground is being used for irrigation. And in many parts of the US we are pumping water out of the ground faster than that groundwater is getting recharged through rainfall. And what that means is that our aquifers are starting to dry up there. That’s simply not a sustainable approach. And we cannot keep doing this.

MARC VAN IERSEL 4:24
But when we talk about water, it’s not just the quantity that matters. irrigation is closely tied to water quality as well. Because anytime that you apply more irrigation water, then you get leaching or runoff of that excess water that is not needed by the crop that you’re growing. And in many cases that water that may be running off or leaching contains fertilizer, pesticides, and it can create environmental issues. So water quality is an important concern as well. And we cannot forget about that when we talk about irrigation.

MARC VAN IERSEL 5:00
To give you an example of what can happen with regard to water quality, this is a nice neighborhood, I believe in Ohio. And this is what this lake looked like at one point in time. But because of fertilizer runoff into this lake, what this neighborhood turned into was from this, going to this, and you can imagine that this has a great impact just on the value of the homes, the quality of life. This obviously is not a very pleasant situation, and it probably doesn’t smell very good either. So this is the kind of thing that we need to try to prevent by reducing the amount of nutrients that end up in our water sources.

MARC VAN IERSEL 5:37
So what I’m focused on is improving irrigation management. And this is part of a bigger project where we try to provide real time information to growers about the value conditions on the farm, about how much water the crop needs to help them schedule irrigation applications based on the actual amount of water that is needed by the crops that are growing. So this is the overall goal. And I need to point out, this isn’t just me, this is a big national program with multiple universities and several companies involved. We focus on greenhouses and nurseries, because we feel that we have the biggest challenge and the biggest opportunity there. These are very intensive agricultural production systems with very high fertilizer and water use. And we grow these plants often in containers, where you have a small amount of substrate or soil that is being explored by the roots, and it makes routine irrigation absolutely necessary. As a result, there are potential problems with getting leaching and runoff of water and nutrients from the sides.

MARC VAN IERSEL 6:54
So, this is our goal, but ultimately, the kind of approach that we are developing is going to be applicable to any kind of irrigation system. So the objectives, the grand scale objectives of this project are to first of all develop wireless sensor networks, that is the hardware part of of the project. Then there needs to be a software component to help growers use the hardware. We are working on developing guidelines to help growers make decisions about how they want to irrigate their crops. And we want to look at the social economic impact. What is the value of what we are doing to a greenhouse, to a nursery, but also to society at large?

MARC VAN IERSEL 7:44
So, to just explain to you what a wireless sensor network actually is, let’s say that this diagram here is representing a farm. What you can do throughout your farm displays multiple little boxes, which we refer to as nodes. So these white things are nodes that make up the wireless network system. And each node can have multiple sensors connected to it. In addition, we can connect an irrigation valve to some of the prototype nodes that we have now developed that can turn irrigation on and off automatically depending on the needs of the crop. That node is sending the data that are being collected wirelessly to a computer that you have somewhere nearby. And this computer essentially lets the interface for the grower to control what the nodes are doing. So this is where the software is running. And growers can set up how they want to schedule irrigation, how they want to treat different parts of the farm, if they want to they can use crop models to predict water use and irrigate according to those models. But what we can also do is put that information online so that you can access the information from your wireless sensor network through a browser, no matter where in the world you actually are. So that means you always have access to the irrigation information and you can make changes as needed without having to be present on site. So the spectrum on the left indicates what one of our prototype nodes looks like.

MARC VAN IERSEL 9:29
There’s actually very similar to the EM 50 nodes that are being sold by Decagon which has been modified to be able to control irrigation valves. And then on the right side here, you can see some of the soil moisture sensors that you can interface with that node. The inside of the nodes contains five double A batteries. They can keep that node power for at least several months, sometimes up to a year. At the bottom, here you can see how you connect sensors to this node. It’s very easy, you just plug them in, and the sensors will work. You can configure the setup later on through the software. On the right hand side of this node, this is where the irrigation valve gets connected that allows us now to actually turn irrigation on and off.

MARC VAN IERSEL 10:20
This is the other end of the system. The picture on the left here shows what we call the base station. This is the little radio that is actually communicating with all of the different nodes that you have in your network. And that base station then sends all of that information through a laptop or older computer that can then be used as the user interface. So that gives you an idea of what these wireless networks look like. The idea behind the irrigation control that we are using in my research is very, very simple. You put a soil moisture sensor in the container that is going to send the signal to the node. And when a low substrate water content is detected, basically, then that port is dry. The node can make the decision that the crop needs water and it can then activate that solenoid valve and the plant that’s going to get irrigated based on the actual water requirements of that particular plant. So this can be fully automated. What I want to do now is give you some of the history of how we ended up where we are now.

MARC VAN IERSEL 11:28
We started much of this research in collaboration with a large nursery in Deering, Georgia, McCorkle nurseries. And you can see some of the pictures from the nursery. The greenhouse that you see, on the right hand side, that’s the greenhouse where we have done most of our research. It is a two acre greenhouse. This is just an aerial view of the same facility, the greenhouse that we work on as the white rectangle in the lower left corner. So with our initial work that we did there, we were working with hydrangeas.

MARC VAN IERSEL 12:06
And we controlled the irrigation of this crop using the soil moisture sensor that you see inserted into the substrate here. That sensor is connected to this irrigation controller that you see on the right hand side. And by simply turning that dial, you can have the irrigation come on or off, and the substrate is about a dryer so you can adjust the setpoint for irrigation fairly easily. What we wanted to do was see how much water can we save by only watering these plants as needed using the soil moisture sensor? And we compare that to their standard irrigation practices.

MARC VAN IERSEL 12:44
And just to show you the data from the very first 10 days of that study, the red line in this graph shows the amount of water that the nursery was applying to this crop, while the multiple black lines show the different crops that we were controlling using the soil moisture sensor. And what we were seeing within one day is that we were applying a lot less water than the nursery did. So it was clear very quickly that we could save quite a bit of water. But then there was the funny thing, when you look at the line for the different control plots, there are two days where the line is flat right in the middle of this period where the scrub did not get watered. And it took us a while to figure out why would they have not have irrigated for two days in a row. And the answer did not become obvious until I looked at a calendar. And it turned out that May 17 and 18th were a Saturday and Sunday. It was a weekend and whomever was in charge of irrigating that crop simply did not come in on the weekend. And the irrigation never got turned on. The nice thing about automating irrigation using sensors is that they don’t take weekends off and they irrigate whenever the plants actually need it. So this was an interesting difference that we saw very quickly.

MARC VAN IERSEL 14:05
So, at the end of the study, we compared the water use between the control plots that were being irrigated by the nursery and the floods that we controlled using the moisture collect sensor and controller. And it turned out that we use 83% less water than the standard nursery practices. So tremendous water savings. What we also saw was that electrical conductivity and the substrate which is a measure of the amount of fertilizer that is present, was lower in the control plants than in the plants that we were irrigating using the sensor. What that means is that in the control plants, they were leaching out much of the fertilizer that they had applied, meaning that it is not available to the plants and it is going to end up somewhere in the environment. Of course the bottom line is, can you actually grow plants this way? And what we found was that plant growth was very similar, regardless of how these plants were irrigated. So we could grow these plants into the same quality with one seventh roughly of the amount of water that they had been using in this nursery, traditionally. So that was very promising.

MARC VAN IERSEL 15:26
So two years ago, we started a study in the same nursery using gardenia. Gardenia, and especially the cultivo radicans, as a crop that they have a lot of problems with, this crop is very susceptible to root diseases, which we think is generally caused by poor irrigation practices. So we wanted to see if we could grow this crop better if we had better control of irrigation. So this just gives you an overview of the crop that we were working with. We were using the same controllers that we had in the hydrangea study, and we were controlling five groups of plants. And we asked the nursery to irrigate five similar groups of plants, according to their spam bot irrigation practices. So this was one single block. So this is the number of plants that we were controlling using one of these controllers. So one single soil moisture sensor was actually determining when to irrigate all of these plants. So we came back later on to look at how much water we were able to save. And that’s where our first big surprise came in.

MARC VAN IERSEL 16:39
There were no water savings. Water use between our plots, and the plot that the nursery was irrigated was within one half of a percent, essentially identical. This really had us puzzled, we did not understand why we couldn’t get any water savings. While with the hydrangeas, it worked so well. That’s when we talked to the production manager at the facility, it turns out that they had actually asked their irrigation manager to mimic what we were doing with our soil moisture sensor. And it looks like the irrigation manager was very good at actually copying the irrigation that we were applying using the automated control. And he applied the exact same amount of water that we did. Interesting finding from this is that we can actually teach people how to irrigate better. Crop health was absolutely excellent. Not a single plant showed symptoms of disease. This was true in all plots, regardless of who was irrigating these plants. This was a great finding, because they typically may lose 20 to 30% of this crop to disease. So if we can grow this crop without any disease, that means that they have a lot more plants that they can sell. But what was really, really interesting is that we could really shorten the production time. Typically, it takes them on average 14 months to grow this crop. We were able to grow these plans in 8 months rather than 14 months, so about half a year shorter production cycle, meaning that they can sell the crop faster, and they can put another crop into that same space.

MARC VAN IERSEL 18:24
So regarding the finishing time, and when they were able to sell these plants, the yellow bars here indicate when they were expecting to be selling these plants. That was that plan in advance. The wide bars that you see is the time period during which they actually were selling these plants. So you can see that these plans did get sold much, much earlier than they had anticipated.

MARC VAN IERSEL 18:51
So we wanted to look at the economic impact of this. And by shortening that production cycle, that reduced the production costs by about $7,700. So that is a significant amount of money. On top of that, because we did not have the problems with disease that they typically get, they ended up being able to sell 2000 more plants than they thought they would be able to. So that also had a great economic impact. And taking a price of $6.50 per plant, that means that I got a total benefit out of this of almost $21,000 which is basically $1 per square foot in additional profit that I got by using better irrigation practices. So what this shows is that this kind of technique is not just beneficial from the perspective of saving water, that can actually have a tremendous economic impact on a nursery. This price does not include the the opportunity of actually now being able to grow an additional crop in the space where you were producing this gardenia crop that I thought I would have that crop for 14 months, and sold it after eight months instead. So the $1 per square foot is actually a very conservative estimate of the economic impact that we had there. So the last part of my talk, what I want to focus on is how can we implement this in the industry in the future?

MARC VAN IERSEL 20:29
And to get that implementation, we have been working with Decagon Devices on hardware development that could go on, has actually done the hardware development, we’ve been testing it, Carnegie Mellon, has developed software to interface with that hardware. And then several different universities have been doing on farm testing to see how well this kind of irrigation approach is actually going to work. So again, I want to focus on Neals Mill Farm and McCorkle Nursery. This is the same nursery facility. Now in the bottom right you see the two acre greenhouse where we are now controlling irrigation in that whole greenhouse using soil moisture sensors. And then there is a computer 300 meters away in an office that is collecting the data from all the different nodes that we have inside of the greenhouse.

MARC VAN IERSEL 21:22
So again, here we have a picture of what that greenhouse looks like. We are now growing Laura battlelands in this greenhouse, mainly. Inside of this greenhouse, we have eight nR5 nodes and nR5 nodes are the modified nodes that have the ability to control irrigation. These nodes are prototypes at this stage, not commercially available yet, but hopefully they will be in the future. We have connected four or five 10HS sensors to each of these nodes. We are using a single EM 50 logger, the commercially available node from Decagon to collect vital data inside of this greenhouse. We measure light, temperature, and relative humidity.

MARC VAN IERSEL 22:07
So this is a map of what the greenhouse actually looks like. The numbers that you see inside of the boxes are all the different irrigation valves that they have in this greenhouse. So they have a total of 54 different valves. And we are controlling these 54 different valves with eight nodes inside of that greenhouse. The electrical work became a little bit tricky, because one single node can actually only control up to two different solenoid valves. So we had to emphasize the node with a steady state relay, which then in turn was actually controlling the irrigation valves. But we did get it to work. So the black boxes that you see in this diagram, are the different irrigation zones inside of that of this greenhouse. And there’s a picture of what it actually looks like.

MARC VAN IERSEL 22:55
On the left, you see that node there sitting above two irrigation valves. On the right side simply a picture of part of the greenhouse with the node and irrigation valves in the background there. So the different colors here in this diagram indicate the amount of plants that are being irrigated using a single irrigation valve. So if everything works perfectly, then what the soil moisture content looks like is something like this. So the y axis here, they’re showing substrate water content as measured by four different 10HS sensors spread throughout that crop. And on the bottom we have the time. There’s showing one week of data with the yellow background indicating daytime, the gray background indicating nighttime. And what you see is that the substrate water content is pretty stable over time, the different sensors are reading similar. And then you can see that all sensors are spiking up at the same time. That is a sign that the crop got irrigated automatically, using the nR5 nodes that we have in place. I have to admit that things don’t always look this pretty. But at times, we are getting this level of control which really allows us very precise water management. So it’s always very, very promising and rewarding when we get this kind of data coming back from these nodes. They’re also doing work that Evergreen Nursery just outside of Athens, Georgia.

MARC VAN IERSEL 24:33
So this is an aerial picture of that facility. This is a map. The blue rectangles on this map indicate parts of that facility where we are monitoring the substrate water content in the crop. Right now we are controlling irrigation in two parts of the facility. Those are indicated here using the red rectangles and we have a single battle station. That’s the little blue dot. So this is a software interface that we are using to communicate with these nodes. And the interface basically has a homepage that shows a map of the facility, and the different green, orange, yellow and red pictures that you see there, those indicate the different location of the nodes. And the color is indicative of the water content measurements that we are getting from different parts of this nursery.

MARC VAN IERSEL 25:35
So that Evergreen, we have four nR5 nodes that are capable of controlling irrigation. And then three EM50 radio nodes that are only capable of measuring data and sending that to the computer but not capable of actually controlling irrigation, turning irrigation on and off. All of the sensors that we are using here, EC-5 soil moisture sensors a little bit smaller than the 10 HS sensors that we used at McCorkle. And just like McCorkle, the irrigation here is by overhead sprinklers. So this is a picture of what we’re doing at Evergreen.

MARC VAN IERSEL 26:15
The note that you see in the center of this picture is the nR5 node that is in control of irrigation for the ukhrul coral bells that you see in this picture. One of the challenges that we have in this nursery is that they grow different crops that get planted at different types, all within the same irrigation zone. And when you have a situation like that, you have to be very careful in choosing which plants you want to monitor to actually turn irrigation on and off. And generally what we try to do is to find the highest water users, and those plants are going to be determining when the irrigation gets done on or off.

MARC VAN IERSEL 26:52
So this is the irrigation scheduling page a little bit. On the bottom half, you see there the drop down menu to select a particular irrigation node. So right now we have selected node G6. Below that, we can select which sensors we want to use for irrigation control. So in this case, we have selected all of the five sensors that are connected to port one through five. And then you see the low set point here set at 27%. That means that whenever the average of soil moisture sensor readings from these five different sensors drops below 27%, that is when the irrigation is going to come on, but only during the time period that are actually shown at that bar at the very bottom. You can see in blue a time period highlighted from 9 am till about 9:30 and from 3 pm till about 3:30. So the irrigation will only come on during that particular time period, no matter how dry the crop is. This helps the nursery to schedule all of the different irrigation procedures that they have to have throughout the entire nursery. So this is an example of data that we’re getting from EverGreen from this Heuchera crop.

MARC VAN IERSEL 28:18
Again, good uniformity among the sensors. The red bars that you see in this diagram right here actually indicate when and for how long the crop got water. So you can see the first irrigation was 15 minutes, two days later, the plants got water for 10 minutes. And the irrigation controller will not irrigate on Sundays when the plants don’t need water. And it can automatically adjust the duration of irrigation also based on how much water the plants have actually used. So this too, seems to be working very, very nicely.

MARC VAN IERSEL 28:54
So overall, the type of benefits that I think we can get from this approach to irrigation is that we can reduce water use that is good for the environment, it is good for society, and it helps grow us to save money. But what may be more beneficial for the environment is that we can actually greatly reduce the amount of leaching and runoff of nutrients and pesticides that would otherwise potentially get into the environment, so we can really have a big impact there. We also hypothesize that because we are leaching less water out of the spots is that we can reduce the amount of fertilizer that growers need to apply and fertilizer is very expensive. So this is large potential savings for the growers. We can give growers better control over plant growth and quality including disease suppression that too can be financially very, very beneficial. We have seen at McCorkle’s that we do think disease pressure could have a major impact on the bottom line of that operation. So we’re very excited to see that happen. But I don’t think we will actually know what all the possible benefits are until we have more experience in the different nurseries. And growers sparked learning how to really use this technology. It’s going to be very interesting to see that they are going to tweak all of the settings that they can control to really optimize the way that they are going to produce the crops. So we still have a lot left to learn in this project.

MARC VAN IERSEL 30:39
I’m not going to list all of the people who have been instrumental in this research, but I would like to thank the United States Department of Agriculture for funding this project. You can see the various collaborators that we have in this work. And if you would like to get more information about what we’re doing, please visit the website www.smartfarms.net where you can read all about everything that we’re doing. Thank you. And with that, I would like to take any questions you might have.

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