Using Soil Moisture Sensors in Plant-Water Relations Studies

Dr. Jongyun Kim explains why soil moisture sensors help control substrate water contents, estimate plant water use, and understand drought physiology.

In this webinar, Dr. Jongyun Kim describes how he used soil moisture sensors and data loggers to get real time substrate volumetric water contents during his research on plant-water relations. The use of METER soil moisture sensors gave him the ability to control substrate water contents, estimate plant water use, and understand drought physiology.

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Dr. Jongyun Kim, University of Maryland Department of Plant Science and Landscape Architecture


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Hi everyone, I’m Jongyun Kim from University of Maryland. And I’m so glad to have my presentation here for Decagon Devices virtual seminar. So, I’ll present some of my research that I have done during my PhD at University of Georgia, and my research interest is mostly on the plant water relationship, physiology. So I use soil moisture sensors and data logger very much and I could get very good analysis from that. So I would like to share some of that. So I use soil moisture sensors a lot with my research, because they could give very good idea about the substrate water contents or soil moisture contents of the soil environment of the plants. So I could use the data logger to monitor and control the substrate water contents with a soil moisture sensor. So I could get the estimation of the plant water use per day or per hour and it could also give very well described the soil moisture content. So, with that, I could get a much better idea about the drought physiology of the plant. So I would share on what I have done.

So this is the system that I used with a soil moisture sensor. As you see in this chart, in this graph, this is the soil moisture sensor that Decagon has. This is called EC-5 soil moisture sensor and this can measure the dielectric properties of the substrate. So it could give the volumetric water contents of the substrate and it is connected to the data logger. So we program the data logger— okay, the data logger is kind of a small computer that can collect and record and process the data. So whenever the sensor read the substrate water contents less than the setpoint, when the substrate goes dry and when the measurement is less than the setpoint, the data logger which is a small computer will process to turn on the switch for the irrigation. So through this relay driver, it will turn on the power to the solenoid valve and it will irrigate to the plant. So it will maintain that setpoint substrate water contents throughout the experiment. So we could maintain this specific setpoint all the time. So it has this powerful ability. So this gave me very good research capability. So at the same time he gave us how much irrigation happened by programming the data logger and it also gave how the substrate water content changed throughout my experiments. So I will share some of data now.

And also at the same time, I also measured the temperature and relative humidity to get to know the environment of the plants. And also the light sensor photosynthetically active radiation light sensor gave me also a very good idea about the light environment of the plant, because light is one of the most important factors for plants, for waterers of the plants. So this graph shows on the x-axis, it shows the days after planting and y-axis it shows how much water the plant used. So in this graph, it shows the daily water use of the petunia. So I used the data logger to collect how much irrigation happened per day, and it shows these lines and the more water use has been done from the bigger pots. So it has three pots, but what I want to show you is we could get, we could quantify the daily water use of the plant through the soil moisture sensor and data logger programming. And at the same time by measuring the environmental factors of the plants, we could get to see the correlation between the environment and plant the water use, so it shows the DLI, which is the daily light integral, the total amount of the light per day. It has very good fit between the water use and light environment, and at the same time the vapor pressure deficit, which is how much water vapor the relative— something like the humidity, relative humidity, but vapor pressure deficit is kind of direct effect to the transpiration. So it shows very good fit between good correlation between the vapor pressure deficit and daily water use of the plants. So using those kind of environmental factors and plant factors, I could get very good regression model predicting estimating the daily water use of the Petunia.

And also for drought study. So this is a little different study that I have done. Plant feel thirsty whenever they have less water in the substrate. So most people have— many people has been done, where the drought physiology, and this graph shows very good overview of drought physiology. But the problem I have had was this mostly on the water potential, which is a little bit hard to measure during the plant growth, and for mostly horticulture people, it may be much easier to use the sensor for substrate water contents, and it will be much easier to understand what happened for the substrate and just to think about the plant, what will happen? So I try to explain what happened when the substrate water content is at a certain point. So this is what I have done. So I try to have that drought study and at the same time, drought might be very beneficial for some plant, such as sometimes a mild drought can slow plant growth. So sometimes some people want to have some marketing time a little bit later, then he can just make a little drought, but plant will still grow but slowly, and he can make right marketing time. Or sometimes some post production benefits can be done by the mild drought, such as, when they’re very well irrigated, they can not do well on the shelf at the big shops like garden center. They will just dry up very quickly, and they’re very weak. So it can give a longer shelf life if can they have some mild drought. And also some better landscape performances can be happened through this mild drought by a hardening of the plant because we people, we can also have some exercise and it will make you stronger, right? So some mild drought can make plants stronger. And this is mostly from the acclimation part of the plant.

But we have a question here, what is this mild drought? So we have not well described this mild drought well, so I tried to show what is the mild drought in substrate water content level. So this was my objective of study. So what specific substrate water content level is mild drought? So I tried to look at their physiological responses, to look at their acclamation level, do they really acclimate and how they acclimate to that substrate water contents. And I also looked at the gene expression level, because most people, many people have working on the molecular study nowadays. So the soil moisture sensor actually can work with this gene expression study as well. And find out which substrate water content level will be beneficial to give plant a better sight like longer the shelf life or make them stronger. So I tried to look at the acclimation and what is the severe drought level. So I use the Petunia plant which is common breeding plants. So I planted a plant in a litter tray and we use common greenhouse mix, was 60% peat and 40% perlite, was slow release fertilizer and we had the irrigation with this irrigation grid, the customized grid drip irrigation pipes. And we had 10%, 20%, 30%, 40% substrate water contents in volumetric water content. So we had four different treatments, and we use these two EC-5 soil moisture sensors. So it’s just the same as what I showed you in previous slide. So the soil moisture sensor monitored the substrate water contents of the tray. So whenever the substrate water contents reading is less than the setpoint, which was 10%, 20%, 30%, 40%. So each treatment has their own setpoint, so whenever the substrate water contents of the tray is less than the setpoint, it will turn on the solenoid valve to irrigate that tray. So we could maintain that specific substrate water content throughout the experiment. So that happened in the treatment.

And this graph shows how it happened. So on the x-axis, it shows the time, and y-axis, it shows substrate water content. So, as you see here, each 40%, 30%, 20%, 10% shows very different treatment. It shows very clear treatment effect on substrate water content because it’s the treatment, I just wanted to show in this slide that it effective, it was very effective to have this treatment with substrate water content. And at this treatment I also measured how they acclimate or how they respond to this kind of substrate water content level. So I use the CIRAS-2 from PP Systems to measure the stomatal conductance and photosynthesis level of the plant. And I also measured the water potential, leaf water potential through the psychrometer. So I also wanted to this, the compare between the water potential and substrate water content, and also leaf relative water contents, which can show a little bit of turgor of the plant. And I measured it every two or three days at noontime. The reason why I measure every two or three days is I didn’t know when it will reach the setpoint and what will happen during the drying period. So I try to have more often measurement to see how they changed over time.

So actually, I have very nice story about this. So I’ll talk about this in a few next slide. And at the same time when I sampled the physiological responses, I also sampled the gene expression for, I also sampled the leaves for the gene expression. So I also use the similar methods of previous Petunia study has done with trizol method. I extracted RNA and I use the real time PCR, which is quantitative PCR, but it would take a lot of time to explain all of the pathway, so I will just skip it. But what I wanted is just show you that the soil moisture sensor can work with all the molecular biologist as well who are very interested in the substrate water content level drought physiology in molecular level as well. And what I was very interested in was ABA, the abscisic acid, the plant hormone. This is very closely related to the drought stress of the plant. So what happens when the substrate goes dry, there will be a lot of synthesis of ABA in the roots and in the leaves as well. So this abscisic acid, ABA, will translocate to the leaves, and this ABA will affect the stomata, which is kind of gate for the plant to have some kind of water movement. It will close this ABA will close the stomata, and when the stomata will be closed, there will be less transpiration of the plant. So from that, plant can keep the water inside of the plant. That’s how the plants survived in some drought condition with this kind of plant hormones. So this is very important hormone in plants. So I wanted to quantify how much this plant hormone affected by this drought. So I use that ELISA method which is Enzyme Linked Immunosorbent Assay. So it worked pretty nicely and I will share this result as well.

So as a result, excuse me. So as a result, I previously showed this substrate water content change over time. And because I measured every two or three days, this arrow shows when I measured the physiological responses and when I sampled the leaves for gene expression and ABA complication. And this solid dot shows when they are drying. So I tried to measure between during the drying period and after they reached a setpoint because I thought about Yeah, they maybe have some acclamation after they reached the setpoint. So I just distinguish between during the drying period and after the setpoint. So after the setpoint as you can see it’s open. So solid dots represent during the drying period and open circle shows after the setpoint. So this is what it shows in physiological responses. On the left slide it shows stomatal conductance, how stomata opens, and on the right graph, it shows the photosynthesis. And each graph shows on the x-axis is substrate water content. So when it’s on the left, it’s lower subsrate water contents. And as you might expect, as substrate water contents goes down, the stomatal conductance and photosynthesis decreased. And this was during the drying period. And what happened after they reached the setpoint it will show you in open circle. So after they reach the setpoint 20% and 30%, substrate water contents treatments increased, a little mostly recovered their stomatal conductance and photosynthesis back after they reached the setpoint which showed the acclamation of the plant at the substrate water contents levels. But 10% substrate water contents treatment, it didn’t show any acclamation, and it seems like they have very severe drought at this level of substrate water contents.

And I can also show you the water potential level. So this red line. So on the left graph, it shows the water potential and on the right graph, it shows the ABA concentration. So on the left graph, the water potential, the red which is 10% substrate water contents, it also decreased the water potential but it recovers back the water potential because previous slides showed that drought responds to the water potential, but actually based on the substrate water contents, the water potential also changes over time and 20% and 30% substrate water contents treatment, it just maintained a little decreased water potential throughout the experiment. And more interesting story was on the ABA concentration. So on the x axis as time goes by, after two days after the treatment started, that 30%, 20%, 10%, which were the drought stress treatment, increased the ABA concentration of the leaf. So that was very interesting. So even little drought stress gave the ABA increase inside the leaf, but 20% and 30%, they maintain that increase the ABA level throughout the experiment until the end of the experiment. But 10% which was most likely to see the drought stress, it increase faster the APA concentration inside the leaf and it was about nine fold of the control, which is very high concentration of ABA. So it showed very interesting, severe drought response of 10% substrate water content treatment. And we found out it has very interesting comparison between stomatal conductance because ABA is mostly controlling stomata.

So I try to compare between stomatal conductance and ABA concentration. So as you see on the left graph and right graph, it shows a little similarity. You can now see I will show you if you will flip the stomatal conductance graph so the 10% will be at the top and 40%, which was the control, is at the bottom. So they should very pretty similar pattern. So I plotted the graph to show the stomatal consequence and ABA concentration on the next slide. So on the x-axis, it shows leaf ABA concentration, and on y-axis, it shows stomatal conductance. And you can see they have very good correlation. There might be a very good line. Let’s see it. So this is very good line like this and it is r score .85. We were very surprised. We actually expected some of this, but more important, more interesting thing that I had, it was regardless of treatment or time. So they have very good correlation between leaf ABA concentration and stomatal conductance, and it has been done with very good treatment of substrate water contents. And at the final, at harvest, I measured the leaf water contents, so how much turgor it could have by visual. So I measured those and only 10% substrate water contents, which is very severe that we thought only that 10% has significantly lower leaf water contents. And other than 10% substrate water content treatment, 20% and 30% and 40% substrate water contents has same, not significantly different relative water contents. So it shows that 10% has visually as well, it shows very severe drought stress.

So in conclusion, what I have shown here in this study, I showed there was substrate water content specific physiology, and it showed some partial recovery at 20% and 30% substrate water contents. But there was no recovery at 10% substrate water content treatment. So from that, I could say, the 10% substrate water content might be severe drought for Petunia. And from looking at the acclimation that 20% and 30% substrate water contents for Petunia, it might be mild drought, and it could help to have a better ability to kind of longer shelf life or having a better landscape purposes for Petunia. 20% or 30% might be good to have the mild drought.

So in summary, I really liked the soil moisture sensor to have a better idea about the soil environment of the plant. So from that I could get a very good idea of what substrate water contents gave which plant response to that drought stress. So they gave me very good power. And from monitoring and controlling substrate water content, I could have very good control maintaining substrate water contents very well. So it was pretty nice. I really liked that. And from that, I could understand that environment, the soil environment much better. And if you can use other sensors like temperature, relative humidity sensor, and light sensor, then you can get a better idea about what environment you had for all the plant physiological studies to understand what environment affects them. So from that I could get the substrate water content specific physiology, and I really like to have further research for those kinds of responses to different kinds of environments, especially for water deficits. So I’d really like to thank you. And thank you for Decagon Devices to having me for this wonderful seminar. And if you have any questions, I would like to take any. Thank you very much.

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