Application of high throughput phenotyping via
PlantScreen System to study early plant stress
responses to progressive drought stress
Klára Šimková, Sharmila Madhavan, Zuzana Benedikty , Diana Santelia and Martin Trtílek
Photon Systems Instruments, Drásov, Czech Republic.
Introduction
Discussion
Drought and salinity in soils are currently one of major problems in agriculture with rapidly growing importance in last few years. The use
of advanced phenotyping that offers application of automated, high-throughput methods for characterisation of plant architecture and
performance, has the potential for improvement of breeding process of different important crops.
Conveyor and robotic PlantScreen System developed in PSI is designed for high throughput plant phenotyping in various species from
Arabidopsis to crop plants. Recently we have used the PlantScreen System to study response of various Arabidopsis starch related
mutants to drought stress conditions. We have optimized the screening conditions and the image processing analysis to obtain quantitative
assessment of plant complex traits such as growth, development and physiological status.
By using combination of chlorophyll fluorescence imaging, thermal imaging and morphology image analysis we have recognized a set of
parameters that could serve as early stress markers for characterization of plant performance under adverse environmental conditions
such as drought.
Analysis of plant performance under water limiting conditions and better understanding of plant responses under drought conditions has in
past years become major a major focus of research and investments. Primary ultimate goal of sustainable farming would be developing crops
with improved water use efficiencies. Here we present rapid high-throughput non-invasive approach to assess numerous phenotypic traits of
soil-grown plants during progressive drought stress treatment.
High-throughput phenotyping platform, the PlantScreen System, was used for automated weighting,RGB morphometric analysis, kinetic
chlorophyll fluorescence assesment and leaf temperature determination via thermal imaging. In addition hyperspectral analysis was used to
determine water content in water-limited plants. Combinatorial statistical analysis was used to discriminate early drought stress marker. Here
we show that the changes in light-adapted photosynthetic parameters during increasing water deficit monitored via chlorophyll fluorescence
imaging can be used as primary marker for the rapid assessment and comparison of the relative viability of Arabidopsis plants during
progressive drought.
Methods
RGB and structural imaging
PlantScreen System was used for the high-throughput automated phenotypic analysis.
Plants were grown in 12h-12h light conditions under cool-white LED illumination of 150
µE in standardized amount of given soil. When plants reached 6th leave stage last
watering was performed. 3 days later the phenotypic analysis in high-throughut
PlantScreen System was initiated. For next 10-11 days RGB structural
imaging, chlorophyll fluorescence and thermal imagigng were monitored twice a day.
Here we present data from one out of 4 biological experiments performed.
Original image
Barrel distortion correction
Mask detection
Chlorophyll fluorescence kinetic imaging
 Area
 Perimeter
 Roundness
 Compactness
Leaf development tracking
 Greening index
 RLGR
PAM light LED panel for kinetic imaging
Fluorescence kinetics measurement
 FO, FM, FV, FO', FM', FV', Ft
 Max quantum efficinecy Fv/Fm
 Photochemical quenching
 Non-photochemical quenching
 Vitality index
 FV'/FM', PhiPSII , qN, qP
PlantScreen Conveyer System
Max light adapted fluorescence (Fp)
Acclimation chamber/
weighing-watering
station
IR imaging station/
Hyperspectral imaging
station
Time (us)
Time (us)
Background subtraction
Time (us)
Time (us)
Time (us)
Time (us)
Time (us)
Time (us)
Time (us)
Time (us)
Time (us)
Time (us)
Mask application and bckgr substraction
Controlled cultivation
environment
Color segmentation
Time (us)
Time (us)
Time (us)
Time (us)
Time (us)
Time (us)
Time (us)
Time (us)
Fluorescence quenching kinetics
RGB imaging/Chlorophyll
fluorescence imaging
station
Weighing and watering
Hyperspectral imaging
Operation
software/PlantScreen
database
Automated weighing
Original image
Plant scale reflectance profile
 Weight of the pot
 Absolute water content
 Nutrient delivery
 Ecotoxicity testing
3D reconstruction
Thermal imaging
 Water content
 NDVI
 PRI
 .....
Original thermal image
3D model reconstruction
Reflectance histogram
Binary image from RGB camera
Watering in relative and absolute amount
Temp (°C/K)
 Leaf Count
 Area
 Perimeter
 Orientation
 Plant Width
 Plant Height
 Bounding box
Specific reflective indices
 Leaf temperature
 Leaf temperature change
kinetics
IR edge
Days
3D model single leaf analysis
Pattern recognition for mask matching
IR image with overlaid RGB mask
Results
Morphometric analysis
Days upon stress initiation
Chlorophyll fluorescence imaging
12
1000
D1
800
1000
Series1
800
600
500
600
400
500
Control plants
27
28
29
31
32
33
Days upon germination
4
3
2
1
0
11
Area
Normalised a.u.
5
3
4
RFD
2
900
1
800
9
10
8
1
700
0
0
2
4
6
8 10 12
Days upon stress initiation
600
11
9
3
4
Control
Drought
3
30010000000
15000000
20000000
0
50000000
10000000
Time (us)
Time (us)
D5
RFD
700
0
DryF4
6
Control
4
Drought
100
9
4
0
8
10
6
Fig.5 Rapid rehydration stress was used to asses rate of water content
loss by water absorption measuremnt with SNIR hyperspectral
camera. Blue color refers to water content as detected by absorbance
at 1440 nm and 1920 nm.
1
2
DryF3
RFD
400
DryF2
0
DryF3
DryF2
300
Time (us)
7
9
4
8
0
Fig.2 Among all parametres analysed
area, compactness, perimetr and SOL
0
50000000
10000000
15000000
20000000
wereselected as useful early discriminants between control
Time and
(us) stressed group.
Acknowledgements
This work was carried out at Photon System Instruments (Czech Republic), with
the financial support through HARVEST , FP7 Marie Curie Initial Training Network.
1
1
0h
0.9
300
200
2
20000000
D8
DryF4
1000
6
900
4
800
2
DryF3
15000000
100
Fig.4 Fp derived parametres can be used
as primary discriminants between stressed
0
and control group already 7-8 days upon
stress50000000
initiation. 10000000 15000000 20000000
0
0.5
7
50000000
0.5h
0.9
0.8
0.8
0.7
0.7
0.7
0.6
0.6
0.6
0.5
0.4
0.5
0.4
0.5
0.4
0.3
0.3
0.3
0.2
0.2
0.2
0.1
0.1
0.1
1000
1200
1400
1600 1800 2000
wavelength [nm]
2200
2400
0
800
2600
1
1000
1200
1400
1600 1800 2000
wavelength [nm]
2200
2400
0
800
2600
1
2h
0.9
4h
0.9
0.8
0.7
0.7
0.7
0.6
0.6
0.6
0.5
0.4
0.3
0.2
0.2
0.2
0.1
0.1
0.1
1000
1200
1400
1600 1800 2000
wavelength [nm]
2200
2400
2600
1600 1800 2000
wavelength [nm]
2200
2400
2600
1000
1200
1400
1600 1800 2000
wavelength [nm]
2200
2400
2600
5h
0.4
0.3
0
800
1400
0.5
0.3
0
800
1200
0.9
0.8
0.4
1000
1
0.8
0.5
1h
0.9
0.8
0
800
200
1
11
0
400 10
8
1.5
0
500
DryF2
SOL
0.5
500
0
7
Perimeter
0
600
4
1000
20000000
2
0
7
15000000
4
1
10
3
10000000
Time (us)
DryF4
6
4
1
100
400
D1
3
2
11
200
Fig.3 Time course of chlorophyll fluorescence
transients signatures in control and
200
stressed plants measured by quenching
protocol .After 7-8 days maximum
100
fluorescence in light adapted state 0(Fp) differed between stressed and control
0
50000000
10000000
15000000
20000000
group.
Time (us)
50000000
Compactness
3
0.5
300
0
Fig.1 Time course of plant development and stress response. Binary image
is further used for morphometric analysis.
Area
0
400
500
100
0
25
500
200
0
Drought
Control D8
600
600
300
100
Control D8
700
700
400
200
23
800
Control
D8
1000
Series1
900
Series2
800
700
300
22
900
900
Series2
700
D5
reflectance
11
reflectance
10
reflectance
8
reflectance
7
reflectance
6
Reflectance
4
reflectance
2
Stressed plants
1
Hyperspectral analysis
2200
2400
2600
0
800
1000
1200
1400
1600 1800 2000
wavelength [nm]
Wavelenght (nm)
Fig.6 Rapid rehydration stress was used to asses rate of water content
loss by water absorption measuremnt with SNIR hyperspectral
camera.