Digital Phenotyping of field crops under field conditions
Stefan Schwartz Business Development stefan.schwartz@lemnatec.com
LemnaTec founded May 1998 in Aachen, Germany
interdisciplinary team (biology, physics, engineering) 14 years of experience with image based biological measurement (phenotyping, ecotoxiology)
in-house development of image processing software in-house development of hardware
Speaker: Stefan Schwartz
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LemnaTec
Speaker: Stefan Schwartz
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LemnaTec
200
Speaker: Stefan Schwartz
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The human eye
How many legs does this elephant have?
The human eye
Count the number of black dots‌
The human eye The circles in the centers‌
‌are exactly the same size
scanalyzerField
Field Phenotyping System
scanalyzerField
Speaker: Stefan Schwartz
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scanalyzerField – movable arm System width up to 10 m System length up to 40 m System height up to 6 m
Speaker: Stefan Schwartz
Customised to application Based on concrete foundation
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scanalyzerField – movable arm Support for movable cameras, scanners and sensors Height range X-y m Movement speed Precision
Speaker: Stefan Schwartz
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scanalyzerField – movable arm Key element sensor platform
High precision movement of the camera and sensor unit (reproducibility 5 mm) up to 4 top cameras and scanners
Movable arm to mount side cameras or adjustable scanners Optional addition of environmental monitoring sensors Option for irrigation Maximum load 60 kg Speaker: Stefan Schwartz
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scanalyzerField – Cameras Cameras are shielded against dust and heat Top cameras in different wavelength Multiple side images are possible for different height levels Height scanning Speaker: Stefan Schwartz
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scanalyzerField HTS – Crops Wide application range for nearly all crops: Small trees even in containers High density crops to be imaged from top only (cereals, rape)
Crops growing in rows or plots with intermediate space (corn, potatoes, beets, legumes, pulses) All field crops in natural soil or containers Speaker: Stefan Schwartz
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Phenotyping the Data
Interpreting the numbers
The experiment Different species have been grown on the PhenoFab system in Wageningen Each species had 10 different genotypes in a fivefold replicat The plants have been screened daily for 35 days with 5 images each day ( 4 side images and a top image ) All images have been analysed to extract projected area
Speaker: Stefan Schwartz
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Overview
Speaker: Stefan Schwartz
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Growth Movies
Speaker: Stefan Schwartz
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Growth Plot
Significant difference after the first 5 days
LemnaTec scanalyzer Field
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Growth Plot Begin of drought stress
Increased amount of water
LemnaTec scanalyzer Field
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Correlation to manual measurement Last day of experiment plants have been harvested Height and fresh weight was measured manually Correlated to images of last day before harvesting
R²=0.9563 Speaker: Stefan Schwartz
R²=0.9857 Slide 21
Growth Modeling  Each replicate growth curve has been averaged over the different views and then been modeled  Woods incomplete gamma function (3 parameters) đ?‘Ś đ?‘Ą = đ?‘Ž đ?‘Ą đ?‘? đ?‘’ −đ?‘?đ?‘Ą
đ?‘Ž: inital size đ?‘?: inital growth đ?‘?: secondary growth
 An average parameter with confidence intervals was then created for each genotype out of the ten replicats for side and top view  Result: 6 Parameters for each Genotype Speaker: Stefan Schwartz
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Plant Growth Fingerprint Tobacco - BAAA Initial growth side -2 0 2
Secondary growth top x40
4
Initial size side
6 8 10
Initial size top
Secondary growth side x40
Lower 95% confidence limit
Initial growth top
Mean value Upper 95% confidence limit
Speaker: Stefan Schwartz
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Comparing different Genotypes BBAA
BBAA
BCAA
-2
-2
-2
-2
-2
3
3
3
3
3
8
8
8
8
8
BFAA
BGAA
BHAA
BDAA
BEAA
BJAA
BIAA
-2
-2
-2
-2
-2
3
3
3
3
3
8
8
8
8
8
High similarity Speaker: Stefan Schwartz
Big difference Slide 24
Comparison Metric  
The 6 parameters that describe can be considered as a 6 dimensional vector that describes growth behaviour Similarities between those vectors can be expressed by an angle measure such as <đ?&#x2018;&#x17D; ,đ?&#x2018;&#x17D; > đ?&#x153;&#x192; = đ?&#x2018;&#x17D; 1 đ?&#x2018;&#x17D;2 1
ď&#x201A;§
2
A matrix that compares all genotypes to each other can then be created giving a similarity of the matching phenotypic fingerprint between 0 and 1 (1 maximum similiraty)
BAAA BBAA BCAA BDAA BEAA BFAA BGAA BHAA BIAA BJAA
BAAA BBAA BCAA BDAA BEAA 100,0% 86,9% 88,5% 77,7% 85,1% 100,0% 99,0% 81,6% 97,7% 100,0% 88,6% 96,1% 100,0% 74,1% 100,0%
Speaker: Stefan Schwartz
BFAA BGAA BHAA 91,0% 82,5% 91,0% 92,1% 96,9% 96,9% 96,3% 98,8% 99,1% 93,5% 92,4% 92,2% 89,8% 92,0% 92,1% 100,0% 95,2% 97,7% 100,0% 98,4% 100,0%
BIAA 87,3% 99,0% 99,1% 86,6% 94,0% 93,4% 98,3% 98,6% 100,0%
BJAA 87,2% 89,9% 87,1% 59,1% 95,4% 83,0% 79,1% 83,2% 84,7% 100,0%
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Comparison Metric BAAA BBAA BCAA BDAA BEAA BFAA BGAA BHAA BIAA BJAA
BAAA BBAA BCAA BDAA BEAA 100,0% 86,9% 88,5% 77,7% 85,1% 100,0% 99,0% 81,6% 97,7% 100,0% 88,6% 96,1% 100,0% 74,1% 100,0%
BFAA BGAA BHAA 91,0% 82,5% 91,0% 92,1% 96,9% 96,9% 96,3% 98,8% 99,1% 93,5% 92,4% 92,2% 89,8% 92,0% 92,1% 100,0% 95,2% 97,7% 100,0% 98,4% 100,0%
-2
-2 3 8
BBAA BCAA BGAA BHAA
BIAA
3 8
BIAA 87,3% 99,0% 99,1% 86,6% 94,0% 93,4% 98,3% 98,6% 100,0%
BJAA 87,2% 89,9% 87,1% 59,1% 95,4% 83,0% 79,1% 83,2% 84,7% 100,0%
BAAA BBAA BCAA BDAA BEAA BFAA BGAA
BHAA BIAA BJAA
Speaker: Stefan Schwartz
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Comparing selected Genotypes Tobacco BDAA
Initial growth side -2
BJAA
0 2
Secondary growth top x40
4
Initial size side
6
BJAA shows in Top and Side view a high secondary growth BDAA shows the exact opposite behaviour and Initial size top has a high initial growth with low secondary growth
8 10
Secondary growth side x40
Initial growth top
Speaker: Stefan Schwartz
BJAA (Lower 95%) BJAA Mean Value BJAA (Upper 95%) BDAA (Lower 95%) BDAA Mean Value BDAA (Upper 95%)
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Conclusions excelent reproducibility of measurements (95% confidence intervals per genotype) high sensitivity to distinguish between different genotypes already after 5 days of growth
high correllation between „real“ phenotype and digital phenotype It works!
Speaker: Stefan Schwartz
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Thank you for your attention! Visit our website www.lemnatec.com