The Use of Novel, Reversed Physiological Phenotyping Methods in a Continuous High-Throughput Crop–Environment Characterization (Continuous G × E)
Our study demonstrated that continuous quantitative measurements of whole-plant (tomato) physiological traits can explain functional differences in their stomatal density and diurnal aperture, as well as their yield under field conditions. Idiotype lines had highly plastic stomatal-conductance, high ratio of abaxial-adaxial stomatal density and early daily aperture.
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[00:00:00.810]The following presentation
[00:00:02.250]is part of the Agronomy and Horticulture Seminar Series
[00:00:05.830]at the University of Nebraska-Lincoln.
[00:00:08.440]Yeah, good afternoon, everyone,
[00:00:10.160]and maybe good morning
[00:00:12.150]or late evening for some of you who are joining today.
[00:00:16.390]I'm glad to see a good attendance.
[00:00:18.400]It is my pleasure to introduce my colleague and friend,
[00:00:21.898]Professor Menachem Moshelion from the Robert Smith
[00:00:26.150]Faculty of Agriculture, Food and Environment
[00:00:28.740]at the Hebrew University of Jerusalem.
[00:00:31.260]I had the pleasure of interacting with Professor Moshelion
[00:00:34.650]for maybe three years back,
[00:00:36.930]and since that we've on and off been in touch,
[00:00:39.260]including co-advising an excellent student
[00:00:43.740]from his Institute department who was also at Nebraska.
[00:00:47.580]So, Professor Menachem Moshelion
[00:00:50.790]is a Molecular Physiologist.
[00:00:53.070]He has been interested
[00:00:54.660]in studying both the molecular and cellular processes
[00:00:57.880]as well as the whole plant physiology.
[00:01:00.414]Often times, we think that the whole plant physiology
[00:01:04.820]is very simple.
[00:01:05.850]It's the molecules and the genes
[00:01:07.610]and the interaction and the signaling
[00:01:11.250]that's more complicated.
[00:01:13.130]What we sometimes ignore is that they're all integrated
[00:01:16.210]into one big response,
[00:01:17.960]and I think Professor Moshelion has done
[00:01:20.610]an excellent number of research projects on stress,
[00:01:24.760]which is also of great interest,
[00:01:26.900]including your work on aquaporins,
[00:01:29.304]which are small proteins that regulate plant water status
[00:01:35.360]along with Professor Rony Wallach,
[00:01:39.340]who I also had the pleasure of being introduced
[00:01:41.910]when I was visiting Israel a few years ago.
[00:01:44.820]He's developed a really cool,
[00:01:47.320]a whole plant phenotyping system
[00:01:50.420]that provides a boatload of physiological data.
[00:01:55.290]And coming back to my point about the physiology,
[00:01:58.090]or plant physiology being less complex,
[00:02:00.230]I think his work's shown that it's less complex
[00:02:04.680]if you only look once at any given time of the day,
[00:02:08.060]but if you start to make multiple observations over time,
[00:02:12.840]like most biological systems, it's very complicated.
[00:02:16.950]So, today, he's taken some of the advancement
[00:02:21.130]they've done with the phenotyping
[00:02:22.950]into a successful company which has commercialized,
[00:02:26.960]it's called PlantDiTech.
[00:02:29.060]So, I think they're doing very well,
[00:02:31.190]and I think we're gonna learn more about the science
[00:02:35.060]and the technology today.
[00:02:37.020]So, Menachem, over to you,
[00:02:40.010]and thank you for accepting this invitation.
[00:02:42.550]We were hoping to host you in person,
[00:02:44.330]but it is what it is.
[00:02:45.570]We are looking forward to your talk, welcome.
[00:02:49.640]Thank you very much, Harkamal.
[00:02:51.053]I am very glad to be here.
[00:02:54.350]I wish I could be in person,
[00:02:55.920]but this is the status so we just have to live with it.
[00:02:59.810]Maybe next time.
[00:03:01.320]So hello, everyone.
[00:03:03.910]So thank you for this nice introduction, Harkamal.
[00:03:07.747]So, as Harkamal said, I'm a plant physiologist,
[00:03:13.823]my main study are to understand
[00:03:16.640]how plants regulate the water relations
[00:03:20.230]in order to maximize yields.
[00:03:24.080]Let's talk about this concept for a minute.
[00:03:26.780]So, when we look on a wild type,
[00:03:29.260]in nature we can say that this plant
[00:03:31.330]reach some optimal behavior in its own environment.
[00:03:35.967]But when we talk about breeding,
[00:03:38.090]so breeding actually put a lot of pressure on the plant
[00:03:41.500]in order to get much more yield.
[00:03:44.710]Now, when we look on the many years back there,
[00:03:48.150]the literature we see,
[00:03:49.940]mainly the breeding process increases the yield
[00:03:53.410]because it's also increased the size of the plant
[00:03:56.200]and the number of stomata,
[00:03:58.760]but much less of,
[00:04:00.370]because of it's improved the plant efficiency.
[00:04:03.610]So, plants after breeding process
[00:04:06.110]usually are bigger and produce more yield.
[00:04:09.120]But many times we see
[00:04:10.380]that are also less sensitive to ABA or produce less ABA,
[00:04:14.530]which means they open stomata for longer time of the day.
[00:04:18.300]All in all their productivity is much bigger.
[00:04:21.020]We know they have more yield, but also their vulnerability.
[00:04:24.530]In particular, vulnerability to drought.
[00:04:27.340]And when we look about the reason for that,
[00:04:29.880]the reason is, the ratio of water to CO2,
[00:04:33.920]which means during transpiration,
[00:04:38.860]crop plants lose in average 500 molecules of water
[00:04:42.360]in order to fixate one molecule of CO2.
[00:04:45.470]If you look on the whole plant number,
[00:04:48.580]to produce one banana in Israel,
[00:04:50.810]the farmer need to irrigate the plant
[00:04:52.694]about 100 liter per one banana.
[00:04:56.290]If we talk about avocado,
[00:04:58.770]so one kilo of avocado is about 500 liters of water
[00:05:02.310]being irrigated to the plant.
[00:05:04.110]One kilo of avocado is like three to four avocados.
[00:05:07.530]So, these numbers are huge,
[00:05:09.470]crop plants really take a lot of water,
[00:05:11.660]and we can see it in many many other crops.
[00:05:14.290]For example, you can see this wheat-breeding program,
[00:05:17.700]you can see this is the year of release.
[00:05:20.210]So of course as more recent the year is,
[00:05:23.490]the more the yield this crop produce.
[00:05:26.490]This is what we expect from a breeding process.
[00:05:29.700]But when this Richards, the researcher,
[00:05:31.950]this Australian researcher took the same plants,
[00:05:36.430]and this time he measured stomatal conductance,
[00:05:39.160]he find even more linear slope,
[00:05:43.040]which means the higher the plant produce yield,
[00:05:46.950]the higher it's stomata are open, okay?
[00:05:50.560]So, you can see that the high yielder
[00:05:54.520]are almost double in stomatal conductance
[00:05:56.070]than the low yielder.
[00:05:58.158]And this is mainly due to breeding process.
[00:06:00.170]So, when we have really breeding lines,
[00:06:03.071]we can say that the pressure of breeding improve the yield,
[00:06:07.600]this is clearly,
[00:06:08.720]but mainly because of canalizing many key trait
[00:06:11.900]like photosynthesis and transpiration,
[00:06:14.613]but this is in the price of less water-use efficiency
[00:06:18.620]or lower water-use efficiency,
[00:06:20.860]which means higher risk,
[00:06:22.010]because if this plant open stomata for longer time,
[00:06:25.470]they're are more susceptible to drought.
[00:06:27.880]And you can see it every time we have a big drought here,
[00:06:31.240]most of the modern crops
[00:06:32.850]can lose up to 80% of the yield because of drought.
[00:06:37.760]Similar thing with salinity,
[00:06:39.280]but drought is one of the main problems.
[00:06:42.050]So, obviously many breeding programs
[00:06:45.010]are aimed to face this problem of drought and salinity,
[00:06:50.200]but the breeding for drought-resistant plant
[00:06:53.550]can take many years.
[00:06:54.780]You can see it can take more than two decades.
[00:06:57.452]And the reason is not just because of the normal long way
[00:07:03.130]of breeding finding the right trait for performance,
[00:07:08.660]it's also the problem of genetic
[00:07:10.590]by environment interactions,
[00:07:12.770]which mean every year we have different conditions
[00:07:15.650]and the plant respond differently.
[00:07:18.070]So all in all,
[00:07:20.120]we cannot really expect the same result every year,
[00:07:24.615]which in the final results take much more time to breed.
[00:07:32.530]So, what are we breeding for?
[00:07:34.610]There are many terms in literature like drought resistant,
[00:07:37.310]drought tolerance, drought resilience.
[00:07:40.180]I want to talk about
[00:07:42.540]the way I'm looking at this terminology.
[00:07:46.120]So, when we, looking at the plant
[00:07:48.890]usually at the beginning of the season, everything is okay.
[00:07:51.630]I mean, usually there is not stress
[00:07:54.980]at the beginning of the season.
[00:07:57.320]And then when stress comes,
[00:07:59.280]the plant can respond either by a susceptible,
[00:08:02.220]that means it's very sensitive to the stress, it my die,
[00:08:05.399]or to produce escape mode,
[00:08:08.270]which means plant will flower soon,
[00:08:10.810]would not produce too much fruit.
[00:08:14.710]But what we are very interesting
[00:08:16.440]in the breeding process is, what happen?
[00:08:18.330]What are the mechanism the plant activating
[00:08:21.150]during the stress?
[00:08:22.780]What are the defense mechanism?
[00:08:25.240]What are the biochemical, physiological,
[00:08:27.483]anatomical defense mechanism
[00:08:29.425]that the plant actually activate?
[00:08:32.850]Because this mechanism
[00:08:33.990]can in fact make the plants recover the stress,
[00:08:38.109]for example, longer roots may reach water
[00:08:41.300]at lower part of the soil and then the plant can recover,
[00:08:45.110]or recover could also come by just rain.
[00:08:49.310]Either way, whatever happen during the stress
[00:08:52.280]will help the plant to recover,
[00:08:54.480]and this recovery process,
[00:08:56.750]the terminology is resilience or recovery from the stress.
[00:09:00.410]Now, we must look at it in two phases.
[00:09:03.450]The vegetative phase,
[00:09:04.600]which mean plant biomass recovery,
[00:09:08.210]leaf, roots and so on,
[00:09:10.460]and we have the reproductive recover,
[00:09:13.400]which mean how many flowers and fruit the plant produce.
[00:09:16.720]So, if after the stress the plant is soon to flower,
[00:09:20.980]we talk about low resilience and low tolerance.
[00:09:24.780]Some plants recover nicely in the vegetative part,
[00:09:27.720]so they have more shoot and roots,
[00:09:30.230]but don't have more flowers or fruit.
[00:09:32.560]So, we can say they have higher resilience,
[00:09:34.540]but low tolerance.
[00:09:36.470]And what we're usually looking for
[00:09:38.040]is high resilience and high tolerance.
[00:09:39.950]So, plants that will keep growing
[00:09:41.600]and also make as much as possible yield.
[00:09:44.353]And all these have to be compared
[00:09:47.530]to the control plant or the resistant plant.
[00:09:49.943]What do I mean?
[00:09:50.860]Control is the plant that was not exposed to stress,
[00:09:53.090]so we can say that it actually uses
[00:09:55.036]all of this time to produce.
[00:09:57.910]So, this is what the genetic potential
[00:10:00.970]of the plant might be.
[00:10:02.835]Or resistant, which means it doesn't sense the stress.
[00:10:06.920]Personally, I don't believe there is a resistant to drought,
[00:10:10.250]because plant without water cannot produce that much,
[00:10:13.053]I just showed you the number.
[00:10:15.080]But in other stresses like salinity,
[00:10:16.710]there might be a resistant.
[00:10:19.680]So, this is the terminology
[00:10:20.770]I'm going to use here in my talk.
[00:10:23.090]So, let's go back to the breeding process.
[00:10:25.440]Our research hypothesis was that if we go back,
[00:10:29.500]that mean if we do reverse physiological phenotyping,
[00:10:33.540]and look on plant that are already passed
[00:10:37.221]this breeding process,
[00:10:38.054]and the yield is already known
[00:10:39.160]both under normal condition and stress,
[00:10:41.930]we might study their behavior and find some cellular,
[00:10:45.650]or physiological, or crop physiological traits
[00:10:49.200]that could be used as traits for future breeding.
[00:10:53.440]So what we did, we took the tomato introgression lines.
[00:10:56.900]This is a library developed by Professor Dani Zamir,
[00:10:59.570]my colleague at the university.
[00:11:02.170]This is an M82, it's an all breed line
[00:11:05.630]that was crossed to the wild-type pennellii,
[00:11:08.870]and in each chromosome there of the mother plant, the M82,
[00:11:13.080]there is a piece of the father plant, the pennellii.
[00:11:16.620]So, in every chromosome we have one
[00:11:19.190]or at least one piece of the father insertion,
[00:11:24.450]and we have only one of the whole genome.
[00:11:26.250]So, the plant are very, very similar
[00:11:27.950]except this single unit of chromosome
[00:11:31.970]that were passed from the father.
[00:11:33.310]These are stabilized organisms because of many back crosses.
[00:11:39.540]So, we took this library,
[00:11:41.210]and Dani Zamir was very generous
[00:11:42.890]to give us many yield results from the field.
[00:11:47.400]So, we took the field results and we compare all the lines.
[00:11:52.390]So, there are basically 76 lines,
[00:11:54.810]we narrow it down to 30,
[00:11:57.330]and we look on the M82,
[00:11:58.480]the M82 that you can see here in black.
[00:12:02.080]This is the mother line.
[00:12:04.220]And we checked for the yield
[00:12:05.944]under optimal irrigation and drought condition,
[00:12:09.350]and also we check for the plant biomass
[00:12:12.009]under optimal irrigation and drought conditions,
[00:12:15.550]and we choose plant which are at least 20% higher
[00:12:19.230]than the M82 or similar to the M82,
[00:12:22.630]or 20% lower than the M82.
[00:12:25.750]For example, you can see this line IL12-1-1
[00:12:28.580]when you compare it to the M82,
[00:12:30.550]you can see that he had higher yield
[00:12:33.940]and higher shoot mass under well irrigation condition.
[00:12:38.280]It also had higher yield
[00:12:39.643]than higher shoot weight under drought.
[00:12:42.210]So, this is an ideotype, or we call it high yielder,
[00:12:45.500]high biomass, high tolerance and high-resilient plants.
[00:12:49.930]This is the abbreviation.
[00:12:51.520]We did the same characterization to all the 30 lines,
[00:12:58.152]and all in all we find 20 different behavior patterns.
[00:13:03.130]We select eight out of the seven plus the M82,
[00:13:07.590]and we chose the seven first
[00:13:09.230]because we want to have very different lines.
[00:13:11.180]So for example, we have one ideotype,
[00:13:13.470]two high yielder, one medium yielder and two low yielders.
[00:13:17.580]The color you see here,
[00:13:18.440]I'm going to use for the rest of my talk.
[00:13:20.230]So, green and blue are the high yielder,
[00:13:24.190]and red and yellow are the low yielder.
[00:13:26.619]And we choose this line because we had at least four years
[00:13:30.030]of field experimental data,
[00:13:31.800]so we have to make sure we have a robust data set,
[00:13:35.280]because now we want to study the behavior of this plant.
[00:13:39.460]So, we grow these eight lines.
[00:13:41.660]We started in the greenhouse.
[00:13:42.703]This is a protected greenhouse.
[00:13:44.670]So, the plant growing in the soil,
[00:13:46.830]and we start by using a LI-COR machine,
[00:13:48.910]like gas exchange,
[00:13:51.300]but we didn't find any differences.
[00:13:53.440]It was very disappointing,
[00:13:54.800]neither in the assimilation or stomatal conductance.
[00:13:58.520]And when we thought why we had started,
[00:14:01.400]this is because these machines are a steady-state machine.
[00:14:04.260]So in this chamber here,
[00:14:05.830]you have to wait for a steady state to occur
[00:14:07.940]before you can pick the measurement.
[00:14:10.120]But if you really look on the greenhouse,
[00:14:11.750]this is the temperature in my greenhouse.
[00:14:14.120]You can see every minute, actually,
[00:14:16.610]at each point of the greenhouse,
[00:14:18.100]the temperature are getting very, very different,
[00:14:21.430]and the colors you see are two highs,
[00:14:23.580]close to the surface and one meter above the surface.
[00:14:26.865]So obviously until you move from plant to plant,
[00:14:29.537]all the condition are changed,
[00:14:31.110]so it's very hard to measure a plant under normal sky.
[00:14:34.450]You see, this is the light condition in greenhouse,
[00:14:36.180]and this is the VPD, the Vapor Pressure Deficit.
[00:14:38.959]So, if you just run along with one machine,
[00:14:41.400]it's very, very hard to get to significant data.
[00:14:44.600]Also, the plants are growing,
[00:14:45.790]so if you do this data every few days or weeks,
[00:14:49.530]you get totally different microenvironment of the plants.
[00:14:54.232]Moreover, usually when you work with this manual machine,
[00:14:57.720]you just push the leaf into the chamber
[00:15:00.580]and the leaf assume that you have 1:1 stomata-density ratio
[00:15:04.250]between the adaxial, the upper part,
[00:15:06.440]and the abaxial, the lower part.
[00:15:09.360]This is not a problem if you just measure one plant,
[00:15:13.100]but if you compare many plants,
[00:15:14.410]you actually must make sure that the density
[00:15:15.920]is the same in all the plants, which is not always the case,
[00:15:19.700]and I will talk about it more later.
[00:15:22.660]So, we look for a high-throughput phenotyping system,
[00:15:28.390]which at the beginning, many years ago,
[00:15:30.110]we start with phenotyping with imaging,
[00:15:32.400]but as Harkamal said,
[00:15:33.970]we develop our own physiological system.
[00:15:36.210]I want to say a few words about the system.
[00:15:39.000]So this system actually,
[00:15:39.907]it's a physiological-based
[00:15:41.850]high-throughput phenotyping system or functional system.
[00:15:46.350]What do I mean by that?
[00:15:48.730]We use the system to measure all the plants simultaneously
[00:15:52.640]when they are randomized in the green house
[00:15:55.960]so we can really build a truly randomized experiment
[00:15:59.110]where each plant being monitored
[00:16:01.960]for its soil, root activity,
[00:16:05.020]whole plant transpiration stomata conductance,
[00:16:07.594]and the environmental.
[00:16:09.090]So, we measure the soil, plants in few measurement
[00:16:12.860]and atmosphere conditions.
[00:16:14.630]So, we can say that each plant is like a resistor
[00:16:18.600]that we measure its conductance
[00:16:20.620]between the atmosphere and the soil.
[00:16:22.470]I would explain more about how we do it.
[00:16:25.220]So, if you take just one plant,
[00:16:27.217]the plant is sitting on a Lysimeter.
[00:16:29.290]It's basically a balance, compensated balance,
[00:16:32.370]that was specially developed to work in a very accurate way.
[00:16:36.750]We also have all these plastic
[00:16:38.570]that help us to measure the plant
[00:16:40.828]and to get very accurate data on the canopy,
[00:16:44.660]the root and the shoot.
[00:16:46.560]Each plant has its own controller
[00:16:48.836]that both measure soil,
[00:16:51.380]water content with the broad atmospheric condition
[00:16:54.930]with the sensors and regulate the irrigation
[00:16:58.140]for each plant separately in a feedback way,
[00:17:01.150]which means I can irrigate each plant
[00:17:03.240]according to its own performances.
[00:17:05.780]This helped me a lot
[00:17:06.860]when I tried to regulate complex traits like drought.
[00:17:11.890]Now, Lysimeter are old technology,
[00:17:15.930]and basically just the old Lysimeter
[00:17:18.960]just measured the whole plant.
[00:17:21.011]The old Lysimeter is like normal human balance
[00:17:23.580]that measure the whole weight of the body,
[00:17:26.470]but cannot separate fluids for fat, for bones, for example.
[00:17:31.320]So what we did, we actually,
[00:17:33.170]in our controller and algorithm,
[00:17:36.180]we cancel the use of data loggers
[00:17:38.400]and we could separate the shoot from the roots,
[00:17:43.360]from the soil and from the water.
[00:17:45.890]So basically we can measure separately,
[00:17:47.960]shoot conductance, root fluxes
[00:17:52.000]under different soil conditions.
[00:17:54.440]The number, sorry,
[00:17:55.890]the measurement we take with the system
[00:17:57.410]is whole-plant biomass gain.
[00:18:00.170]So we can measure the continuous growth of a plant.
[00:18:03.500]We take transpiration,
[00:18:07.530]stomatal conductance of the whole canopy,
[00:18:11.240]and we can also identify the drought point,
[00:18:13.560]the physiological drought point
[00:18:15.700]which tells us exactly what point
[00:18:18.030]the plant become under stress.
[00:18:21.720]all these measurements are absolute numbers,
[00:18:24.320]which mean we have the whole plant
[00:18:25.700]in a very simple numbers like mL per plant per day.
[00:18:30.260]So we can really know the exact amount
[00:18:32.871]which usually we cannot do
[00:18:34.303]when we work with LI-COR, for example,
[00:18:35.960]so it's only for one leaf.
[00:18:37.510]When we work with the pressure chamber,
[00:18:39.570]it's one leaf and also a relative number
[00:18:42.480]like water potential.
[00:18:44.330]But with the Plantarray system,
[00:18:46.860]we can really get the whole plant absolute numbers.
[00:18:49.950]So for example,
[00:18:50.783]transpiration could be mL per plant per day.
[00:18:52.750]How many mL the plant lose.
[00:18:55.080]We also have the tools of,
[00:18:57.830]analytical tools that we can get the raw data,
[00:19:02.540]some basic statistics like ANOVA and T-test, box plots,
[00:19:08.280]Histogram and also heat map
[00:19:11.030]that you can really identify each plant in the array,
[00:19:13.870]and if we need RNA or DNA or something like this,
[00:19:16.360]we can just approach the plant.
[00:19:20.353]the system helped us solve many of the pot effects.
[00:19:23.530]You probably know that when you grow in a pot,
[00:19:26.170]you may very fast be exposed to the pot effect.
[00:19:29.620]For example, big plants would transpire much more
[00:19:33.050]than a small plant.
[00:19:34.060]That means that the smaller pot size
[00:19:36.553]will make your plants to get much faster drought,
[00:19:39.650]which not always what you want.
[00:19:42.540]Or you get a lot of variation between different experiments.
[00:19:47.190]So the system helps solving this problem of the pot effect.
[00:19:52.710]I'm not going to get into too much detail,
[00:19:54.980]but this was published in this paper
[00:19:56.460]if you want to read more.
[00:19:58.990]Also, if you want that,
[00:19:59.823]I will be glad to sending you this paper,
[00:20:01.570]explaining exactly how this pot effect is solved.
[00:20:06.370]So all in all the system enable us
[00:20:08.120]to control each plant separately
[00:20:10.570]to any nutrition and water level we want.
[00:20:14.310]We have all the plants measurement simultaneously
[00:20:18.010]and continuously so we can compare all the plants
[00:20:20.760]to the exact identical conditions,
[00:20:23.590]and we have analytical tool in real time,
[00:20:25.088]so we can very quickly compare these plants.
[00:20:30.280]Old algorithm was published
[00:20:31.270]in this Plant Journal, Technical Advance,
[00:20:34.350]and if you want to see the canopy conductance
[00:20:37.450]which I'm going to talk about more today,
[00:20:40.030]this was recently published
[00:20:42.500]from a group in Buckingham University
[00:20:43.630]that actually tested our stomatal conductance accuracy,
[00:20:50.050]and they found it very good accuracy.
[00:20:53.320]So I'm not going to get to too much details,
[00:20:55.140]but if you have questions later, I would be happy to answer,
[00:20:57.610]or you can see this paper for the answers.
[00:21:02.710]So let's go back to our lines.
[00:21:04.530]So we choose these lines.
[00:21:07.130]We run them on the Plantarray system.
[00:21:09.490]Let's look a bit on the raw data,
[00:21:11.530]so you can see what we measure.
[00:21:14.180]So this is a raw data
[00:21:15.640]of one plant through the whole experiment.
[00:21:17.800]You can intuitively see that the plant is growing with time.
[00:21:22.220]Let's focus a bit to see what exactly we received.
[00:21:24.930]So this is the weight, this is the raw weight,
[00:21:27.310]the increasing weight to mean irrigation
[00:21:29.470]and the decreasing weight to mean transpiration.
[00:21:32.620]So while we define the RDT Morning and RDT Evening,
[00:21:36.700]the data between the two,
[00:21:38.170]the line here is basically the plant water loss
[00:21:40.880]during one day.
[00:21:42.710]So if you just want to see how much the plant lose,
[00:21:44.700]we just need to take this data every day.
[00:21:47.140]And the line here show us
[00:21:48.580]a continuous plant transpiration increase.
[00:21:52.770]Usually it's because of the plant is growing.
[00:21:56.090]Now, this is the IL8-1
[00:21:59.220]to remind you this is the low yielder, this LY.
[00:22:02.940]And this is the daily transpiration of this plant
[00:22:05.530]during well-irrigated condition.
[00:22:07.850]This is about two weeks
[00:22:09.870]or a bit more than almost all of the three weeks
[00:22:12.880]of well-irrigated condition.
[00:22:13.713]Then we expose the plant to drought,
[00:22:17.100]and then we'll put it to recovery, okay?
[00:22:19.580]So we bring back the irrigation.
[00:22:21.200]This was the experimental scenario,
[00:22:24.400]and of course we compare to the other plant.
[00:22:27.400]Each line is the average of at least five different plants.
[00:22:32.210]This is the 5-2,
[00:22:33.043]so this is the high yielder.
[00:22:35.257]You can see that this plant
[00:22:37.300]has much faster development of daily transpiration
[00:22:41.030]with very fast decrease of transportation during drought
[00:22:44.260]and very nice recovery.
[00:22:46.340]And this is the M82 somewhere in the middle, okay?
[00:22:48.963]This is the mother line.
[00:22:51.250]Of course, we compare all the lines together,
[00:22:53.820]and you can see that if,
[00:22:55.430]we start the experiment when the plant were four weeks old.
[00:22:59.350]So you can see that at this age,
[00:23:03.240]no significant difference occurs,
[00:23:05.710]but in few days,
[00:23:07.340]significant different start to occur,
[00:23:09.130]and the higher yielder, like 11-4 and 5-2,
[00:23:13.050]really become very fast,
[00:23:14.673]like in about a week, becomes significant from low yield.
[00:23:19.030]So when we expose them to stress,
[00:23:20.900]you can see that the high yielder
[00:23:22.710]reduced transpiration very fast compared to the low yielder.
[00:23:26.510]We have a transpiration flip-flop.
[00:23:28.758]But this is not because of fast drought,
[00:23:31.030]because if you look at the drought,
[00:23:32.530]this graph here shows you the solely water content.
[00:23:35.740]You can see a similar slope
[00:23:37.723]that we could regulate because of the system.
[00:23:40.520]So all the plant actually exposed to the same drought,
[00:23:44.140]but this plant respond faster, okay?
[00:23:49.880]So I will talk sooner about how can we regulate this drought
[00:23:54.160]so I could be clear,
[00:23:54.993]but let's start before we talk on the drought,
[00:23:56.760]let's talk about normal irrigation.
[00:23:59.520]So let's look at the window here,
[00:24:01.100]when the plant are well watered,
[00:24:03.500]all of them just get full irrigation.
[00:24:08.920]When we just look at the daily transpiration.
[00:24:11.070]So this is the number,
[00:24:12.420]this is the gram of water plant lose in one day,
[00:24:15.570]but it doesn't give us too much resolution.
[00:24:17.980]So if we want to look on higher resolution,
[00:24:20.790]what we do,
[00:24:21.623]we take the momentarily resolution of the plants.
[00:24:25.060]So let's see how we do it.
[00:24:26.120]This is the light in the greenhouse.
[00:24:28.880]This is the VPD, Vapor Pressure Deficit.
[00:24:30.790]This is a very important parameter of the atmosphere,
[00:24:34.830]it's taking account the temperature and relative humidity.
[00:24:37.270]The higher the temperature,
[00:24:39.228]the more demand the atmosphere put on the plant,
[00:24:43.820]and the plant actually start to transpire more.
[00:24:48.650]The black line you see here is the weight.
[00:24:50.530]This is what we get with the Lysimeter,
[00:24:52.490]so you can see like 600 mL decrease in weight of one day.
[00:24:57.150]And when we take the first derivative of this weight,
[00:25:00.930]we actually get transpiration rate.
[00:25:02.860]So this is millimole per mass per second.
[00:25:06.060]So this is the transpiration rate of the plant.
[00:25:11.068]And if you want to take the stomatal conductance,
[00:25:13.110]one of the most important parameters,
[00:25:15.260]basically is how much water the plant lose,
[00:25:18.123]normally it is to its weight,
[00:25:19.850]relative to the VPD, to the demand of the atmosphere.
[00:25:22.760]And this is the green line.
[00:25:24.560]So this is the stomatal conductance.
[00:25:26.697]All of these parameter, we can get directly from the system.
[00:25:29.937]You can see that stomatal conductance
[00:25:32.452]is open wider at early time of the morning here
[00:25:36.390]when the VPD is low and the light is relatively high.
[00:25:39.788]So let's look on our plant,
[00:25:41.240]let's start again with 8-3, the low yielder.
[00:25:44.880]This is the stomatal conductance.
[00:25:46.490]You can think about stomatal conductance,
[00:25:48.170]its how much the stomata is opening, right?
[00:25:50.620]It's the conductance of the stomata to gases.
[00:25:54.130]So we can think of it as stomatal aperture,
[00:25:57.480]you can see it's,
[00:25:58.900]respond very nice with the light and VPD.
[00:26:01.370]When light the VPD goes up
[00:26:03.330]also the stomatal conductors goes up,
[00:26:06.400]and when light goes down at the evening,
[00:26:08.520]this is evening time,
[00:26:09.353]this is the time of the day,
[00:26:10.920]also stomata start to get closed.
[00:26:13.364]Look that the VPD goes up at the same time.
[00:26:16.640]This is because of other atmospheric conditions,
[00:26:19.430]but again the stomata getting closed.
[00:26:22.420]So, although the VPD goes up,
[00:26:24.317]the stomata is responsible to the light.
[00:26:26.820]You can very nicely see this.
[00:26:28.260]But when we now measuring the actual transpiration rates,
[00:26:32.540]which mean how much water the plant really loses,
[00:26:36.020]you can see that while the stomata is getting closed,
[00:26:39.670]the transpiration is staying fixed,
[00:26:42.420]and this is because of the higher demand.
[00:26:44.300]So when the atmosphere demand more water,
[00:26:47.910]although the stomata getting closed,
[00:26:50.350]the transpiration is still fixed
[00:26:52.310]and only later it's getting closed.
[00:26:53.790]This is very nice difference between transpiration rate,
[00:26:58.030]water loss, and stomatal conductance.
[00:27:00.640]Very key important physiological parameters.
[00:27:03.290]Now we compare all the plants together,
[00:27:06.230]and the way we get it,
[00:27:07.450]we pretty much see the same pattern we show before.
[00:27:10.410]You see blue and green,
[00:27:12.640]the 5-2 and 11-4.
[00:27:17.020]There are big here,
[00:27:17.950]and also they invite transportation here.
[00:27:21.450]In the stomatal conductors we see less big difference.
[00:27:24.100]I mean, the 8-3 is always the lower,
[00:27:26.097]and there is also very interesting thing here
[00:27:28.710]with the M82,
[00:27:30.420]you see it's open it's stomata longer time in the day.
[00:27:34.960]This is because this plant was breeding,
[00:27:37.650]past the breeding process.
[00:27:38.880]You remember I told you that breeding process
[00:27:40.420]usually push this stomatal conductance longer during the day
[00:27:44.700]and you can clearly see it here.
[00:27:47.380]But all in all under normal condition,
[00:27:49.100]we don't see something different
[00:27:50.530]than what we already saw in the daily transportation.
[00:27:56.180]What you really want to see
[00:27:57.560]is what they've been under this stress condition.
[00:28:00.370]So, as I said before during the stress,
[00:28:02.830]many mechanism being activated,
[00:28:05.740]and we want to know what happened here.
[00:28:07.810]So one simple way to see is just follow the recovery rates.
[00:28:13.160]So after the drought occurs,
[00:28:14.810]we can say that here,
[00:28:16.960]sorry, during the drought,
[00:28:18.950]all of these mechanism of defense mechanism being activated.
[00:28:24.100]Now, it's very hard to see them
[00:28:25.910]because usually stomata is getting closer
[00:28:27.670]so it's very hard to understand
[00:28:29.520]what happened to the biochemical
[00:28:31.630]and anatomical differences between the plants.
[00:28:36.200]But one very nice way to look at it is the recovery rate,
[00:28:40.060]because if the plants
[00:28:41.820]could survive the drought very nice and recover fast,
[00:28:45.450]that mean that you did something good here,
[00:28:48.600]but if it could not recover after the stress,
[00:28:52.010]that mean that it suffers somehow from the stress.
[00:28:54.580]So one way is just looking at the recovery rate
[00:28:57.150]and compare the different lines in the recovery.
[00:29:00.310]What we do usually it's go back to the recovery
[00:29:03.330]to pretty much what they have before the stress.
[00:29:06.270]This is the resilient slope,
[00:29:07.822]here's the resilient.
[00:29:08.655]And when we look on the recovery rate of the resilience,
[00:29:12.610]we can see that the 5-2,
[00:29:15.540]this line here,
[00:29:16.630]and 11-4, these two lines,
[00:29:18.605]so they were the higher-transpiring plants,
[00:29:21.110]but also fast-recovery plants.
[00:29:23.580]So although they transpire more
[00:29:26.610]and close the stomata sharp, they could also recover fast.
[00:29:30.650]You can see it here, at least compared to the 8-1,
[00:29:32.770]the low yielder.
[00:29:34.670]Also, we finished the experiment here.
[00:29:38.090]So we took the plants and took the dry weight of the plants
[00:29:40.640]and we compared dry weights of the plants.
[00:29:42.870]So, actually, whatever the plants could fixate
[00:29:46.130]during this period,
[00:29:47.130]we took it as a dry weight,
[00:29:49.020]and we compared to the commutative amount of water
[00:29:51.790]the plant transpired.
[00:29:52.710]So we just took everyday transpiration and sum it up.
[00:29:58.490]So the graph you see here is the cumulative transpiration
[00:30:00.980]versus the shoot weight,
[00:30:03.010]and very interestingly this two lines
[00:30:05.300]not only to transpire a lot, but also get a lot of biomass.
[00:30:10.405]And they did it very efficiently.
[00:30:12.860]When you compare the biomass,
[00:30:15.240]the dry biomass to the total water,
[00:30:17.540]we call it agronomic water-use efficiency,
[00:30:20.700]you can see that at least the 11-4
[00:30:24.070]is significantly more efficient than the 8-1.
[00:30:26.870]So not only it transpired a lot and produce a lot,
[00:30:29.550]it's also do it more efficiently.
[00:30:32.101]So these are a very three important characteristic
[00:30:36.470]that you can just easily take.
[00:30:40.110]So, more importantly is, what happened during the stress?
[00:30:44.860]What does the plants do during the stress?
[00:30:47.770]So, first of all,
[00:30:48.603]when you compare all the plants under stress,
[00:30:50.450]you must make sure
[00:30:51.580]that they are really facing similar stress.
[00:30:54.910]What do I mean by that?
[00:30:56.750]So this stress here,
[00:30:58.760]if we would not regulate it very efficiently
[00:31:02.460]using the Plantarray system, we will get this.
[00:31:05.893]This is the same IL lines when we just let them dry.
[00:31:09.920]When we just close the tab here and let them dry,
[00:31:12.936]the fast-transpiring plants lose water very fast
[00:31:17.200]while the low-transpiring plants lose water much slower.
[00:31:22.010]So let's say after a week,
[00:31:24.030]the high-transpiring plants will be under much severe stress
[00:31:26.310]than the low-transpiring plant,
[00:31:28.700]so you cannot really compare them based on time.
[00:31:31.730]So (clears throat)this is why
[00:31:33.500]when you want to compare apples to apples,
[00:31:35.620]you must make sure that all your plants
[00:31:37.620]are under similar stress level.
[00:31:40.410]Otherwise you really compare the time and not the stress.
[00:31:44.051]So, how can you determine the stress level?
[00:31:47.284]So the Plantarray system have a very unique controller
[00:31:51.240]with two valves, A and B,
[00:31:53.770]that first of all it can make a cocktail of solution,
[00:31:56.720]but more importantly, for this experiment,
[00:31:59.407]they can irrigate the plant
[00:32:01.540]based on all previous day transpiration.
[00:32:04.810]So if a plant, for example loses 100 mL
[00:32:07.940]and you want to expose it to 90% drought,
[00:32:10.370]you would just give him back 90 mL.
[00:32:13.030]And because each plant has its own controller,
[00:32:16.800]you can see it here,
[00:32:18.380]we can regulate the droughts for each plant separately
[00:32:22.910]based on its own physiology.
[00:32:25.406](Moshelion clears throat)
[00:32:26.239]We can also do automatic dehydration rate.
[00:32:28.450]So we can just do what you saw before.
[00:32:31.140]You can just get the drought in a very similar rate,
[00:32:35.650]as I showed you before.
[00:32:37.950]And these drought is basically what they showed before
[00:32:41.086]as you can see here,
[00:32:46.014]has a very similar rate.
[00:32:49.380]Now, when we control the,
[00:32:54.250]some people use a,
[00:32:55.083]the system can also control the drought using a sensor.
[00:32:59.470]What do I mean by that?
[00:33:00.570]The system can be hooked to all kinds of soil sensor
[00:33:04.920]and regulate the water based on the sensor,
[00:33:07.740]but this could be sometime misleading.
[00:33:09.630]Let me explain why.
[00:33:10.780]Let's look on these to plant, tomato and sunflower.
[00:33:14.440]You can see both transpire the same,
[00:33:17.150]on the x-axis,
[00:33:19.730]here is the soil water content measuring by a plant.
[00:33:23.810]Now, the tomato plants, when we start dry the soil,
[00:33:29.380]we close stomata at around 60% of soil water content.
[00:33:33.293]This terminology for this is theta crit.
[00:33:36.560]Theta crit means the drought point
[00:33:40.110]or the soil water content,
[00:33:41.920]which become limiting factor for the plant transpiration.
[00:33:47.030]This is a physiological point,
[00:33:49.190]that actually under this point
[00:33:50.660]the plant being exposed to stress.
[00:33:53.581]At the meantime,
[00:33:56.360]sunflower is only being limited
[00:33:59.290]under 40% soil water content.
[00:34:01.610]This is because of the sunflower root system.
[00:34:03.960]So if I would regulate the drought
[00:34:05.730]based on a soil profile,
[00:34:06.840]for example let's say I would choose
[00:34:08.510]to put the soil on 50%,
[00:34:10.810]it's not a big deal, it's very easy to do with the system,
[00:34:14.130]but in this case without knowing
[00:34:17.150]the theta crit of each plant,
[00:34:19.460]I might put the tomato on the stress
[00:34:22.920]while the sunflower won't be under stress, okay?
[00:34:27.580]So controlling drought treatment based on soil prob
[00:34:30.300]could be misleading.
[00:34:32.310]The reason, by the way,
[00:34:33.410]for the sunflower to have a lower theta crit
[00:34:35.500]is because of its much larger root system
[00:34:40.132]that actually reach more water in the same pot.
[00:34:43.575]So although both of them exposed
[00:34:45.000]to the same depletion of water,
[00:34:48.190]sunflower can reach to more water
[00:34:50.550]and actually reduce it's low,
[00:34:53.940]it's theta crit to a lower values.
[00:34:57.460]So in our case, we took the theta crit
[00:34:59.570]to each one of our plants, of course,
[00:35:02.090]and we choose the drought point to be below theta crit
[00:35:05.310]at about 50% of the transpiration rate of the whole plant.
[00:35:10.290]So we choose the stress to be easy or logical-stress level.
[00:35:15.240]Now, again, we compare all the plant continuously
[00:35:19.430]under the same light and VPD condition.
[00:35:22.240]So let's start with stomatal conductance.
[00:35:24.500]You can see again that the stomata is opening,
[00:35:26.800]first of all the values are much lower
[00:35:28.580]than what I showed before.
[00:35:29.943]But also you can see that although the light and VPD
[00:35:33.237]are pretty fixed during the noon,
[00:35:35.910]the conductance is getting lower
[00:35:37.670]because this plant is already exposed to stress
[00:35:40.340]and this is because of ABA.
[00:35:42.950]But when we compare the 8-1 line to the 5-2,
[00:35:48.300]we can see very interesting results.
[00:35:50.740]You can see that 5-2,
[00:35:52.988]this is the high yielder, we call it ideotype,
[00:35:55.790]has much faster opening of stomata early time of the day
[00:36:00.020]and later on close the stomata
[00:36:02.840]getting much lower water loss.
[00:36:05.250]So it can open stomata wider,
[00:36:07.830]meaning getting more CO2 at this time of the day
[00:36:10.796]while paying a lower price of water loss.
[00:36:13.900]You can see it here.
[00:36:15.650]So this is a very nice difference
[00:36:17.270]between the high yielder and low leader.
[00:36:19.400]Why does stomata conductance
[00:36:20.670]at the same time lower water loss?
[00:36:22.980]Because of the different time of the day
[00:36:24.880]and the different VPD.
[00:36:26.219]The VPD as I told you before, this is the demand.
[00:36:27.993]This is what actually push the water,
[00:36:30.390]pull the water out of the plant.
[00:36:32.390]So of course we compare on the plants simultaneously.
[00:36:36.170]You can see nice patterns,
[00:36:38.810]a bit different between the lines,
[00:36:40.410]and we wondering, why is this differences?
[00:36:43.310]I mean, how come these different plants,
[00:36:45.120]all of them look almost identical, the tomato plants,
[00:36:48.855]why do we get these patterns?
[00:36:50.530]And we saw these paper by Henry et al.
[00:36:52.901]that talk about the stomata safety-efficiency trade-offs.
[00:36:58.830]So they claim that the difference
[00:37:01.830]in between the stomatal density and stomatal aperture
[00:37:04.626]might have a role in their responsive
[00:37:07.270]of the stomata to the environment.
[00:37:09.400]And we were wondering,
[00:37:10.590]could it be really that the stomatal density
[00:37:13.040]is different between our line?
[00:37:15.660]So what we did,
[00:37:17.070]we use these special stomatal printing method.
[00:37:23.440]It's a special glue that you can just fix to the leaves,
[00:37:26.677]its very fast dry, so we can get the printing of your leaf.
[00:37:30.870]And we want to have both the abaxial and adaxial,
[00:37:33.610]and we want to have this printing
[00:37:35.980]at different times of the day,
[00:37:37.610]at least six times of the day to all of the lines.
[00:37:40.950]To have these simultaneously
[00:37:42.310]you really have to have an army of people
[00:37:44.130]running around in the greenhouse and gluing this material.
[00:37:47.820]By the way, if you want to see the protocol,
[00:37:49.230]you just log into the bioRxiv,
[00:37:50.910]it's now under revision.
[00:37:52.600]And what we could take out of this measurement
[00:37:56.210]is both the stomatal aperture and stomatal density,
[00:38:00.020]which mean how many stomata we have in 0.1 millimeter.
[00:38:05.170]Now, when we look at the results,
[00:38:06.660]and of course we did it both to the abaxial and adaxial,
[00:38:09.890]the upper and the lower part of the leaf.
[00:38:12.200]So if we look on the total density,
[00:38:14.160]we don't see significant difference between the lines.
[00:38:17.450]But if we look on the differences
[00:38:19.136]between the abaxial and adaxial,
[00:38:20.980]we see that in 5-2 and 11-4,
[00:38:23.153]these are the high yielder,
[00:38:25.670]there's much more stomata
[00:38:26.670]on the lower part of the leaf than on the upper part.
[00:38:30.110]Some plants are neutral,
[00:38:31.470]so they have the same,
[00:38:33.740]and some of the low,
[00:38:36.120]so some of low line like 8-1-3
[00:38:38.270]also have similar to the high yielder,
[00:38:43.090]that's mean that this is not enough
[00:38:44.640]to have this difference in density.
[00:38:48.100]So what we did,
[00:38:50.030]which we also look on the aperture, okay?
[00:38:53.750]This time, a different time of the day.
[00:38:56.620]So we look at the aperture,
[00:38:58.304]a different time of the day,
[00:38:59.538]and you can see that 8-1, the low yielder
[00:39:02.533]has its maximum aperture at the mid day.
[00:39:06.270]Now, this is Israel,
[00:39:07.620]mid day is very hot.
[00:39:09.590]So, opening stomata to its wider peak at noon
[00:39:15.244]might be not the smarter thing to do,
[00:39:18.350]especially when you look at the 5-2
[00:39:19.757]and you see the peak is really at the same time
[00:39:21.970]we saw the stomatal conductance peak.
[00:39:23.510]So relatively early in the morning
[00:39:25.877]at the lower part of the leaf,
[00:39:27.620]and in the upper part it's a bit later,
[00:39:29.820]but also before noon.
[00:39:32.090]And the M82 is sour in the middle.
[00:39:34.346]And we did the same to all the plants,
[00:39:36.770]and we find very interesting trend of maximum peak
[00:39:41.130]of the stomatal aperture.
[00:39:44.490]We were wondering if this density differences
[00:39:46.860]is related to the SPEECHLESS gene.
[00:39:49.410]SPEECHLESS is a gene that involve
[00:39:51.150]in the regulation of stomata in the leaf,
[00:39:53.980]and we also were wondering
[00:39:55.810]if some of these time of the days
[00:39:58.740]is related to some stress gene
[00:40:01.010]like these zeaxanthin epoxidase which is related to stress.
[00:40:06.150]So we took the Chitwood paper
[00:40:08.790]that actually take the same library of tomatoes
[00:40:11.810]and measure these genes,
[00:40:13.730]and we saw a very nice correlation
[00:40:15.460]with the SPEECHLESS to the abaxial style.
[00:40:19.730]So, SPEECHLESS is very nicely correlated
[00:40:23.830]with the stomatal density at the abaxial side.
[00:40:26.310]So the gene express much more,
[00:40:30.290]where we see much more stomata,
[00:40:33.066]and at adaxial we have much less.
[00:40:34.790]So at the lower part,
[00:40:35.950]we think that the SPEECHLESS is very much important.
[00:40:38.607]The ZEP1, the Zeaxanthin,
[00:40:41.260]just show us a mirror image,
[00:40:43.380]which means that the 8-1,
[00:40:45.890]although it was not on the stress at this condition,
[00:40:49.123]show high level of this gene,
[00:40:50.700]which is like this plant is under constant stress.
[00:40:54.190]This is like what seems from these gene.
[00:40:57.030]Again, with a very nice correlation.
[00:41:00.370]So to sum up this part,
[00:41:03.250]when we measure the aperture,
[00:41:04.620]aperture is very important, right?
[00:41:06.580]Very hard to take, but it's very important,
[00:41:09.010]but measuring the aperture of the stomata is not enough.
[00:41:13.050]You also have to know the density and distribution
[00:41:16.650]of the stomata between the adaxial and abaxial.
[00:41:19.387]You have to know your VPD,
[00:41:20.790]which is the temperature and humidity
[00:41:22.550]at every time of the day,
[00:41:24.460]and only when you have these three,
[00:41:26.610]this actually sum up to what I showed you before,
[00:41:29.900]the canopy conductance and the transpiration rate.
[00:41:33.580]So, we saw very nice fitting of what we took manually
[00:41:38.950]to what the system gave us automatically.
[00:41:41.770]Now, of course, when we come back to the manual machine,
[00:41:44.880]if you really want to measure it manually,
[00:41:46.668]you have to work with probably few machine
[00:41:49.600]and do a very tedious work.
[00:41:50.950]People did it.
[00:41:51.870]You can see this very nice work
[00:41:54.040]of Brodribb and Holbrook showing the same,
[00:41:57.110]we call the peak by the way, Golden Hour.
[00:41:59.875]Seeing these Golden Hour, different lines,
[00:42:03.910]again, as we said before, when the VPD is low,
[00:42:06.630]if the VPD is low the stomata conductance is high.
[00:42:09.760]They did it here manually,
[00:42:11.330]and they could also show
[00:42:12.650]very nice increase early in the morning.
[00:42:14.920]Some plant almost totally closed the stomata at noon.
[00:42:19.510]We also measure it in other paper,
[00:42:21.270]we show with the Lysimeter, the same high peak at morning.
[00:42:24.930]Again, it was highly correlated to yield.
[00:42:27.893]Another work by Bacher et al.,
[00:42:30.670]a student of Professor Peleg and Harkamal
[00:42:34.100]from your Institute,
[00:42:35.698]show the wheat cultivar into regression lines
[00:42:40.350]with better yield,
[00:42:41.640]better resilience also have this nice peak in the morning.
[00:42:46.380]So we can see these trends coming from several plants.
[00:42:51.730]So, to conclude my main take home messages.
[00:42:58.300]So high transpiration is a very good trait for yield.
[00:43:02.330]We saw it in all the high-producing lines,
[00:43:04.440]very high transpiration.
[00:43:06.510]But under drought,
[00:43:08.493]a fast response or plastic response of the stomata
[00:43:12.240]is also very important.
[00:43:13.320]So as faster the plant respond the better.
[00:43:17.800]High abaxial to adaxial stomatal density.
[00:43:20.750]So the more stomatal level, the low part the better.
[00:43:25.620]Dynamic water-use efficiency in particular, the Golden Hour.
[00:43:28.950]It's a very nice trait to stress response.
[00:43:31.490]So the plant that opens stomata wider
[00:43:34.186]under stress earlier in the morning is better.
[00:43:39.290]So we call dynamic water-use efficiency.
[00:43:41.890]And rapid recover, what you see here from stress.
[00:43:45.233]So also if the plant transpire a lot,
[00:43:49.030]and it's really reach high transpiration before stress,
[00:43:52.470]during stress it's probably exposed to more stress
[00:43:55.470]because this plant is physically bigger,
[00:43:58.225]but if you can still recover fast,
[00:44:00.223]this is a very good trait.
[00:44:02.830]This fast recovery, it's very important trait as well.
[00:44:06.581]As I show you,
[00:44:08.300]we saw the SPEECHLESS gene is probably important
[00:44:12.030]in regulation to the gene expression,
[00:44:14.390]and the zeaxanthin also important there
[00:44:17.560]probably as a stress response.
[00:44:21.510]So, obviously if you can measure,
[00:44:24.200]the stomatal aperture is very important,
[00:44:26.030]but both manually as I show you,
[00:44:28.680]or using steady-state, gas exchange is very tedious,
[00:44:32.590]and very low throughput.
[00:44:35.470]What I show you is the Plantarray system that you get,
[00:44:38.480]first of all, the whole plant measurement,
[00:44:42.190]and you compare it continuously and simultaneously.
[00:44:46.490]So, we think that in breeding
[00:44:48.240]or a similar functional project,
[00:44:50.960]this is very, very important.
[00:44:54.313]So we are now developing several simulations
[00:44:58.480]with many other functional phenotyping tools
[00:45:03.270]to help us actually breed to several scenarios of stresses
[00:45:07.950]to limit the nutrient and so on.
[00:45:10.170]And the idea is like choosing the winning horse
[00:45:12.360]based on its real race and not based on its genetic,
[00:45:15.510]or other measurements.
[00:45:17.570]So we always compare our plants together.
[00:45:22.670]When you choose a phenotyping system,
[00:45:24.420]actually as you know there are many phenotyping system.
[00:45:27.800]What we recommend, is if you're doing a stress response,
[00:45:31.880]you should take in account these ten key challenges.
[00:45:36.940]First of all,
[00:45:37.940]remember the plant respond very fast to the environment,
[00:45:40.830]so you better measure the shoot, the roots,
[00:45:44.530]the water in the soil, the atmosphere, light, VPD,
[00:45:49.550]and if possible also the rhizosphere.
[00:45:51.680]Because all of those traits
[00:45:53.680]are cross-interacting with each other.
[00:45:56.670]It's better to measure several traits
[00:45:58.570]like stomata conductance and transpiration,
[00:46:00.870]and root fluxes, biomass,
[00:46:02.940]again, simultaneously under well irrigated
[00:46:06.400]and drought conditions.
[00:46:08.730]Continuous and simultaneous measurements are crucial
[00:46:12.380]because of this momentary changes.
[00:46:14.250]If you really want to see the difference,
[00:46:15.640]you must know they are really simultaneously measured.
[00:46:19.670]You need to, if you're doing drought,
[00:46:21.330]it's better to control the drought and not just let it dry.
[00:46:24.670]Also probe-based regulation is not always good.
[00:46:29.460]It's good, but you have to know what you're doing.
[00:46:32.090]So standardization is very important
[00:46:34.340]in order to repeat the experiment again and again.
[00:46:38.530]Solving the pot effect is crucial.
[00:46:41.400]Smaller pot will just make the plants dry much faster
[00:46:45.150]than you want.
[00:46:47.460]And working in a randomized way,
[00:46:51.200]so the controller help us
[00:46:53.100]actually measure all the plants simultaneously
[00:46:56.640]by controlling each one separately.
[00:46:59.370]So true randomization
[00:47:00.744]and real-time analytical tools
[00:47:02.600]are also very, very important.
[00:47:06.041]I don't have time
[00:47:07.170]to talk about two other functional projects we did
[00:47:10.203]like biostimulant and early detection of plant disease.
[00:47:13.530]So I would just skip it.
[00:47:15.960]In few words, we could screen for biostimulant effect,
[00:47:19.450]so you can use the same genotype,
[00:47:21.670]but use different chemicals like biostimulant,
[00:47:25.220]again using the same principle
[00:47:26.720]and really understand the difference
[00:47:28.650]between different chemicals.
[00:47:29.970]You can really understand what they're doing,
[00:47:32.580]this saves a lot of time before going to the field.
[00:47:35.860]And recently we started to work a lot with biotic stresses,
[00:47:40.070]like plant diseases.
[00:47:41.210]This is in collaboration with Shay Covo my colleague.
[00:47:44.280]For example, this Fusarium
[00:47:46.440]that could very easily show phenotypic,
[00:47:49.690]I'm sorry if I'm jumping,
[00:47:50.770]but I don't want to take more time,
[00:47:53.060]you can see that we can see differences in transpiration
[00:47:56.257]of infected plants after five or six days,
[00:48:01.410]while to see it in your eyes it take like three weeks.
[00:48:04.970]And the more severe the stresses,
[00:48:07.650]the faster you can see the differences.
[00:48:10.370]So, biotic stresses like this Fusarium or,
[00:48:15.960]sorry that I'm jumping,
[00:48:17.040]but we did it in several,
[00:48:18.760]or this viruses also on the Lysimeter system,
[00:48:21.520]you can see differences in the plant,
[00:48:24.210]whole plant behavior much, much before you see
[00:48:26.800]anything with your eyes.
[00:48:28.570]So, we think these functional phenotyping
[00:48:31.520]could be also very nicely implemented
[00:48:33.610]in biological stresses like diseases.
[00:48:37.580]I would like to thank Sanbon,
[00:48:39.675]he is the PhD student who did most of the research tutorial,
[00:48:43.440]Professor Dani Zamir that gave us all the IL lines
[00:48:45.920]and all the field results,
[00:48:47.950]Bogale, Ravitejas and Ramon,
[00:48:49.120]master student that's also part of the paper,
[00:48:51.600]and Shani Fridman that did disease research
[00:48:54.510]that unfortunately I could not explain it well.
[00:48:58.010]And thank you very much.
[00:49:03.079]Thank you, Professor Moshelion.
[00:49:05.181]That was an excellent and very insightful talk.
[00:49:08.410]So there's a question.
[00:49:09.740]Thank you for the very nice presentation,
[00:49:12.010]I'm curious about the significance
[00:49:13.720]of calling these recombinant inbred lines ideotypes.
[00:49:19.060]So we chose this name because the,
[00:49:22.990]maybe I will share again,
[00:49:26.040]we chose this name because of this table here.
[00:49:29.550]So basically when you look at this plant,
[00:49:33.580]we compare them always to the M82, okay?
[00:49:36.407]M82 is the breeding line,
[00:49:37.890]so it's like the line that was released.
[00:49:42.550]But this plant were high in yield, high in shoot weight,
[00:49:45.850]high in fruit under drought and high in weight.
[00:49:48.600]So actually there were better in all measurements.
[00:49:52.020]So this is why we call it ideotype.
[00:49:53.470]Is just something you can say we decided to call it.
[00:49:58.175]There is another one,
[00:49:59.008]have you by chance compared results
[00:50:01.160]of ideotype assessments against folio damage,
[00:50:05.700]falling lethal drought treatments?
[00:50:08.210]If so, did you see strong correlations?
[00:50:11.620]And Aaron is asking this because,
[00:50:15.160]I have an interest in plants survival in wild populations.
[00:50:19.170]Yeah, it's very good question.
[00:50:20.400]So, we did something similar with barley cultivar.
[00:50:26.830]Let me find,
[00:50:29.839]it was actually published.
[00:50:31.210]So we collected barley from different zones in Israel,
[00:50:34.810]from the South till the North,
[00:50:37.140]and we compare the barley behavior, this is wild type,
[00:50:40.800]exactly for this kind of behavior.
[00:50:44.570]We did put it to a little stress, and I explain why.
[00:50:48.270]When you work with ecological stress,
[00:50:51.030]so what you do, what we did,
[00:50:53.200]we actually took six years back of these regions,
[00:50:56.867]and we measure what is the average time
[00:50:59.490]between two rain events, okay?
[00:51:02.220]We call it drought duration.
[00:51:03.974]So, average drought duration
[00:51:06.100]was the time period between two rain events.
[00:51:09.900]We also took soil samples
[00:51:13.430]and calculated the water content in the soil.
[00:51:17.100]And we built in the system two simulation
[00:51:20.710]of severe drought and less severe drought
[00:51:24.150]to all the barley's together
[00:51:26.160]based on the actual ecological data that we got.
[00:51:29.960]So, we are building the scenarios
[00:51:32.460]based on what we expect the plant
[00:51:34.320]should be exposed to in the field.
[00:51:37.860]So, usually we never just close the tab and let them die,
[00:51:41.500]but try to keep the stress
[00:51:43.400]to be similar to the desired scenario.
[00:51:48.680]Hey, yeah, thank you for the presentation.
[00:51:50.386]I'm curious after seeing the slide
[00:51:53.410]with like your variation in stomatal
[00:51:56.750]kind of peak opening and transpiration,
[00:51:59.860]those points in a controlled environment situation,
[00:52:03.180]do you think we could manipulate light intensity, VPD,
[00:52:07.556]to kind of capitalize on staying more
[00:52:11.120]at that peak level during the day?
[00:52:13.520]Yes, I'm sure we can.
[00:52:15.550]We do it with cannabis plant.
[00:52:20.200]It's, well, you cannot fully control it,
[00:52:22.530]but it's for sure, much more easy.
[00:52:25.140]And this peak is really not the morning.
[00:52:27.906]The reason it's in the morning,
[00:52:30.439]because this is the right combination of VPD and light.
[00:52:32.620]But if you can mimic it,
[00:52:33.906]for example, if you take the same tomatoes
[00:52:36.790]during the winter,
[00:52:38.060]the peak shifted toward the noon in Israel,
[00:52:41.000]because you have much less light
[00:52:42.300]and all the other condition changes.
[00:52:43.680]So this is really depend on the environment,
[00:52:46.280]not exactly the time of the day.
[00:52:49.890]So I think, yes, I think that in a controlled growth room,
[00:52:53.840]you can just follow it
[00:52:55.000]and each time try to improve it based on the plant feedback.
[00:53:00.040]Looking at the transpiration rates,
[00:53:02.350]is that what you would look at as a metric for that?
[00:53:05.660]So I would compare both transpiration and conductance.
[00:53:08.780]So transpiration is the actual water loss.
[00:53:13.124]In the growth room it might be enough
[00:53:16.110]because usually you can control very nice the VPD,
[00:53:19.184]and this is the main thing, the VPD,
[00:53:24.610]but both, I would look both on the conductance
[00:53:26.870]and the transpiration rate.
[00:53:29.700]Great, thank you.
[00:53:31.130]There's also a question about,
[00:53:33.570]identifying any genes that you think
[00:53:35.620]could be associated with some of these phenomena,
[00:53:37.710]you mentioned SPEECHLESS.
[00:53:40.100]Yes, I mentioned.
[00:53:41.410]So, we didn't do the genes,
[00:53:43.810]we took it from a known,
[00:53:45.490]so this, our library has many papers on it.
[00:53:48.597]One of them was this expression profile that they did.
[00:53:53.520]So we found this SPEECHLESS,
[00:53:54.990]which is taking part in the regulation
[00:53:57.767]of the stomatal density
[00:53:59.360]was highly correlated with the high number of the stomata
[00:54:04.667]in the lower part of the leaf.
[00:54:08.600]We didn't go too much to it
[00:54:10.250]because this is more physiological-based study.
[00:54:12.330]But these two genes that I show you
[00:54:13.620]was really nicely correlated.
[00:54:14.990]So, of course there are probably more genes
[00:54:17.560]that are involved.
[00:54:18.790]So do you think that the response or store mix
[00:54:23.070]for especially for the high yielding,
[00:54:24.670]like the steeper decline under drought,
[00:54:28.650]and then of course you have a better recovery,
[00:54:32.930]intuitively do you think that they are related?
[00:54:36.183]There same phenomena of more responses domain,
[00:54:39.430]but have you seen any lines
[00:54:41.590]where they are actually disconnected?
[00:54:44.593]So we start with rice plant,
[00:54:46.620]we talked a bit before about it.
[00:54:48.450]So, rice are highly productive.
[00:54:50.610]They have huge amount of transpiration,
[00:54:52.440]so they're very nicely productive,
[00:54:54.770]but guess the lines we check,
[00:54:56.460]it was Japonica and Horizontal I think,
[00:55:00.120]they had a very bad recovery rate.
[00:55:03.030]So they had a very nice transpiration
[00:55:06.250]and fast-increasing transpiration,
[00:55:08.247]but very bad recovery.
[00:55:11.809]This is one example I can recall,
[00:55:15.480]but I think it's different rates.
[00:55:18.770]I mean, I think many times it does correlate,
[00:55:23.330]but it's not necessarily so.
[00:55:25.210]Does time matter to get results?
[00:55:27.450]My question is,
[00:55:28.820]how long does it take for stoma to stay open?
[00:55:32.290]Stomata respond very quickly.
[00:55:34.160]So in few minutes, it will change.
[00:55:36.690]So if you look on the continuous,
[00:55:39.300]this is for example, you see, this is like two hours.
[00:55:42.120]So, from I dunno, 6:30 to seven, you get very fast response
[00:55:50.980]and then a very fast respond out.
[00:55:52.710]Now you can see all these curves up and down.
[00:55:55.490]This is an average,
[00:55:56.323]but it's all respond to this changes in the environment.
[00:55:59.530]This is naturally occurring changes
[00:56:01.110]because it's in a controlled greenhouse.
[00:56:04.370]So this is this the stomata respond,
[00:56:05.710]you see the transpiration is much more smooth,
[00:56:09.200]but it conducted itself, it's much more jumpy.
[00:56:12.970]Now in the literature,
[00:56:13.810]you can see that the stomata responds in few minutes.
[00:56:16.492]We've all kinds of papers,
[00:56:17.670]I'm talking about five minutes,
[00:56:18.830]I'm talking about 15 minutes,
[00:56:21.030]but it's in order for minutes this response.
[00:56:23.930]How can the Plantarray,
[00:56:25.691]or can the Plantarray system differentiate
[00:56:27.950]the transpiration and evaporation early development stages?
[00:56:33.000]In other words, is there a threshold-
[00:56:35.440]Yes, yes of course.
[00:56:38.643]So, yes, it's much harder.
[00:56:41.410]So it's called signal-to-noise ratio.
[00:56:44.120]So what we recommend is to work with about 80 or 100 mL.
[00:56:50.410]It's not too much you can look at this tomato,
[00:56:54.140]you can see they start transpiration
[00:56:55.770]from about 50 or 100 mL and it's going very fast.
[00:56:58.630]But if you work with the seedlings,
[00:57:01.190]or very small plants, like we work with Arabidopsis.
[00:57:05.170]So we just put more plant per pot.
[00:57:07.230]You don't have to put single plant like I show you here.
[00:57:11.960]In fact what you can do
[00:57:13.220]and this is what we do also,
[00:57:14.640]if you want to work with wheat on a very early stage
[00:57:18.170]what we do instead of putting one plant per pot,
[00:57:22.830]we can put five, six, or even 10
[00:57:25.910]just to reach this higher level of signal.
[00:57:30.550]So the signal-to-noise will improve,
[00:57:34.870]and we also reduce the pots.
[00:57:36.220]So for example, Arabidopsis,
[00:57:38.568]we put four to five plants in one-liter pot.
[00:57:41.380]What you see here,
[00:57:42.213]this is four liter pots,
[00:57:43.930]and we also have,
[00:57:46.520]if we want to work with much bigger plants,
[00:57:49.670]let me see if I have it here,
[00:57:50.970]we can also work with 25-liter pots.
[00:57:55.440]So the idea is just to play with the number of your plants
[00:57:58.300]just to get to the minimum signal
[00:58:03.550]that you need for the measurement.
[00:58:05.465]But it just the matter of pot size
[00:58:07.420]and number of plants in the pot.
[00:58:09.000]So the data you showed had so many,
[00:58:12.780]the vegetation was quite extensive
[00:58:14.570]and they were also very close to each other.
[00:58:17.130]Have you looked at the effect of an isolated,
[00:58:20.960]set of isolated pots, like either distant apart,
[00:58:23.420]so you don't have more of the canopy dynamics of VPD
[00:58:27.620]and temperature playing as opposed to in a,
[00:58:31.160]isolated versus like in a canopy,
[00:58:34.620]have you seen those differences?
[00:58:37.300]So, of course, there are differences.
[00:58:39.620]Let me show you two confirmation.
[00:58:41.080]This is the dense confirmation.
[00:58:43.150]We choose this
[00:58:43.983]because this is really simulation of a greenhouse.
[00:58:47.330]If we run it a bit,
[00:58:49.200]you will see the plants getting pretty big.
[00:58:51.890]You can see it here.
[00:58:54.283]This is the density that are really going to be in the field
[00:58:57.440]or in a greenhouse.
[00:58:58.480]This is how they're going to look
[00:58:59.313]in the field, very crowded.
[00:59:01.830]So, of course, you get,
[00:59:03.938]so there is no noise or something,
[00:59:06.590]but there is a different of cross-interaction
[00:59:09.190]because of shading and humidity.
[00:59:12.040]But this is a real-life situation
[00:59:14.240]where we work with diseases.
[00:59:15.910]You can see it here in this greenhouse.
[00:59:18.940]We put it to much more apart,
[00:59:21.980]let me, you see,
[00:59:22.920]here they're much more apart,
[00:59:24.295]but this is very functional
[00:59:26.250]because we didn't want them to contaminate one another.
[00:59:30.010]Of course, the plant when it's more exposed,
[00:59:32.410]you will get more transpiration
[00:59:34.390]and less impact of shading.
[00:59:37.470]Again, this is part of the scenario you need to design,
[00:59:41.160]because it's very easy to move this system.
[00:59:44.160]So your just need to know what is your scenario
[00:59:46.570]and just design your table accordingly.
[00:59:49.580]When plants cope with drought stress,
[00:59:51.680]how is the fruit number per plant changing?
[00:59:59.200]Yeah, this is an important question.
[01:00:01.440]We need to separate these, okay?
[01:00:03.360]Most of the crop plants,
[01:00:05.260]what we do, we judge them by two different ways.
[01:00:08.920]One is the vegetative growth,
[01:00:10.990]what I showed you here today,
[01:00:12.870]it's growth rate,
[01:00:16.520]water efficiency and so on and so forth.
[01:00:19.770]This is still your flowers, okay?
[01:00:23.670]So this is very important part of the growth spirit,
[01:00:28.050]where the plant establish its factory,
[01:00:30.587]its leaf number, its biomass.
[01:00:34.190]Now, as soon as the plant start to flower,
[01:00:37.600]this is the reproductive phase,
[01:00:39.732]and here its totally different questions.
[01:00:43.870]For example, some flowers are sensitive to the drought
[01:00:46.760]and just fall down.
[01:00:48.160]Maize is a great example,
[01:00:49.710]maize is a C4,
[01:00:51.740]pretty resilient plant,
[01:00:53.580]but highly sensitive to drought, why?
[01:00:56.940]Because of the flowering period.
[01:00:58.680]So if a maize plant
[01:01:01.460]will face the drought while its flowering,
[01:01:04.220]the chances you will lose most of the yield,
[01:01:07.040]although the plant will look nice.
[01:01:09.460]So we have what I call before,
[01:01:12.430]high resilience, low tolerance,
[01:01:15.640]big plants without too many fruit.
[01:01:18.100]So when you judge, when you test your plants,
[01:01:20.660]you need to separate these vegetative part
[01:01:22.790]from the reproductive part.
[01:01:24.840]On the system, on the PlantDiTech system what I show you,
[01:01:28.240]we usually measure the physiological parameters
[01:01:31.370]which are extremely important during the vegetative part.
[01:01:35.140]The reproductive have to,
[01:01:36.960]you have to use different kinds of tools
[01:01:39.030]because it's mainly flower, pollen and so on.
[01:01:42.130]Well, I think,
[01:01:42.990]please join me in thanking Professor Moshelion.
[01:01:46.047]It's been a really thought-provoking seminar,
[01:01:50.810]and a good lot of questions and discussions.
[01:01:53.670]So, we really are thankful for this opportunity
[01:01:57.340]to interact with you and learn about your work.
[01:01:59.890]So, thank you very much.
It's a pleasure.
[01:02:02.450]Thank you all, thank you for inviting me.
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