The Use of Novel, Reversed Physiological Phenotyping Methods in a Continuous High-Throughput Crop–Environment Characterization (Continuous G × E)

Menachem Moshelion, professor of The R.H. Smith Institute of Plant Sciences and Genetics in Agriculture, The R.H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot, Israel Author

01/31/2022 Added

40 Plays

Description

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,
[00:04:37.260]plant actually,
[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,
[00:18:05.550]water-use efficiency,
[00:18:07.530]stomatal conductance of the whole canopy,
[00:18:09.930]root fluxes,
[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.
[00:18:20.840]More importantly,
[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.
[00:19:19.520]Very importantly,
[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,
[00:44:40.650]absolute 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.
[00:44:53.480]What next?
[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?
[00:54:35.350]Right?
[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?
[00:54:43.760]Yes, yes.
[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.
[00:56:36.510]For sensitivity?
[00:56:37.810]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,
[01:00:15.010]transpiration conductance,
[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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The Use of Novel, Reversed Physiological Phenotyping Methods in a Continuous High-Throughput Crop–Environment Characterization (Continuous G × E)

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