Translation of ditial phenotypic traits: from promise to commercial relevance

Translation of digital phenotypic traits: from promise to commercial relevance

Dr. Shital Dixit

Presentation outline • Challenges in plant phenotyping • Novelty of PhenoFab® projects

• Journey of PhenoFab® (2011-2012) • Phenodays 2011 offer projects

• Game changing role of data analysis • Conclusions Shital Dixit

11-10-2012

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Challenges in plant phenotyping Cold

Salt

Drought

• • •

Objective phenotyping Digital Phenotyping High-throughput

Abiotic agents

Biotic agents

Subjective/bias scoring Shital Dixit

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Digital Phenotyping

Objective data collection from digital images to measure morphological and physiological characteristics through image analysis is known as digital phenotyping

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Novelty of PhenoFab facility

Agri Food Biotech company

Automation of scientific images

Software/hardware development

Value creation for Customer

Traits/genes/genomics/bioinformatic

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PhenoFab® – the facility

3D Conveyor Scanalyzer

•Greenhouse setup with climate control •Moving pots/trays: capacity: 1200 pots

•GMO authorized Shital Dixit

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3D Image stations Capacity: Plant Height 2.6 mts.

Visible light -Shape - Color

NIR - internal structure - Water content

Fluorescence -Chlorophyll analysis

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CottonDrought, WUE Tobacco

NUE Flowering time Crop architechture Height, width Canopy structure Heavy metal toxicity Effect of growth substrate Crop growth rate Fruit shape, color and shelf life

Lettuce

Grass

Sorghum

Taraxacum

Pepper

Maize

Miscanthus

Canola

Rice

Ficus

Sugarbeet

Wheat

Cabbage

Grass

Tomato

Cucumber

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PhenoFab 速 project workflow

Idea

PhenoFab 速

to workplan

5 weeks

From image to digital phenotyping

Statistical correlation study

Conclusions

4 months Shital Dixit

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The PhenoDay 2011 offers Evaluate the power of digital phenotyping • Growth curve evaluation between genotypes – – – – –

Sorghum Sugarbeet Tobacco Grasses Miscanthus

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Project 1: Phenoday 2011 offer project GOAL: Phenotype biomass development in sugarbeet hybrids

 Experimental set-up  5 sugarbeet hybrid seeds  GAA, GBA, GCA, GDA & GEA

 8 repetitions  Phenotyped for 5 weeks  4 side + 1 top camera images

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Growth model analysis GEA is the smallest, fastest in the initial growth and • Initial size of genotype slowest in growth the secondary growth • Initial rate of genotype GCA is the biggest, • Secondary growth rate of genotype Slowest in the initial growth and Fastest in the secondary growth

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GDA

GBA

GCA

GAA

GEA

GAA

GDA

GBA

GCA

GEA

Secondary growth per genotype

Initial growth per genotype

GCA

GDA

GBA

GAA

GEA

Initial size per genotype

Growth curve analysis for 5 week period

No significant difference between genotypes

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Discussion of the results with the client    

Genotypes were treated with seed priming treatment GEA and GCA with treatment-A GAA with treatment-B GBA and GDA control treatment-C

 Effect on growth expected in 2-3 weeks after germination  Seedling delivered to PhenoFab 2 weeks after germination  Zoom into the first 11 days of the experiment

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Growth curve analysis for first 11 days

No significant difference between genotypes

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Growth curve analysis for first 11 days

Treatment A shows 5% boost in the growth of the plant compared to its non-treated control

GCA GEA GAA GDA GBA

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Conclusions for project 1  Research question must be clearly addressed to design the right experiment  Parameters measured some times might not be correlated to the desired trait/effect but can be additional effects measured on the plants  Digital phenotypic data analysis is very dynamic and can be very trait specific

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Project 1: Commercial relevance  Seed priming treatment A showed 5% higher growth compared to its control and counter standard treatment.  (1-1.5% in root yield in field is of commercial relevance)

 Image analysis of the first 2-3 weeks after germination in sugarbeet might even show higher differences between treatments.  Uniform and faster germination (>30%) is of commercial relevance

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Project 2: PRS company project

GOAL: PRS (gel-based growth medium) enhances plant growth

PRS gel at the bottom of the pot

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PRS system tested on Pepper and Ficus

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PRS system tested on Pepper and Ficus Plant type 1. Fast growing= Pepper 2. Slow growing = Ficus Watering regimes 1. W1= sub-optimum 2. W2= Optimum Design 1. Pepper grown with gel = PG 2. Pepper grown without gel = PN 3. Ficus grown with gel =FG 4. Ficus grown without gel =FN

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Growth curve analysis in pepper

Sub-optimum water Optimum water

Sub-optimum water Optimum water

Missing data

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Growth curve analysis in Ficus Sub-optimum water Optimum water Sub-optimum water Optimum water

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Growth rate analysis in pepper

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Growth rate analysis in Ficus

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Biomass development in ficus and pepper Does PRS system enhances plant growth?

Biomass comparison of plants

FGW1 FGW2 FNW1 FNW2 PGW1 PGW2 PNW1 PNW2

Shoot Average (g) 9.0 11.0 10.3 13.4 220.6 262.3 242.5 267.9

Shoot Stdev 2.4 2.0 2.9 2.4 32.8 33.6 23.7 38.5

Root Average (g) 7.4 9.9 6.7 10.9 42.5 52.1 70.5 66.1

Root Stdev 4.6 1.5 1.3 2.3 8.6 13.8 15.4 17.3

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Water and Nutrition use efficiency Water Water (ml) and Nutrition average per plant/treatment (ml * EC) (ml)

FGW1 FGW2 FNW1 FNW2 PGW1 PGW2 PNW1 PNW2

375 604 574 925 3978 4560 4320 4936

Ficus grown on gel-based medium needs 35% 35% less water to produce 35% similar amount of biomass produced by plant grown On a non-gel medium

8%

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Conclusions for project 2 • PRS gel based system does not enhances plant growth

• Plant growth speed variation: Observed only in pepper but only in combination with water regime • PRS system allows plants to use both water and nutrients more efficiently (35% less water in ficus) • Digital phenotyping data allows to study the problem in dynamic manner.

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Commercial relevance of PRS system  PRS system can claim that plants grown on their medium are more water and nutrient efficient (35% in ficus and 8% in pepper)  System can be used to grow plants where water is a scarce resource e.g in dry and arid regions Water quality is poor to grow plants  Maintaining plants longer without watering, thereby reducing manual costs for watering

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PhenoFab® summary  PhenoFab® has: 1. gained experience in different crops and relevant traits 2. overcomed image analysis and data analysis challenges to greater extent, hence speed up the project duration.

3. generated output towards creating commercial value in crops

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PhenoDays 2012

Wanna try PhenoFab in 2012 ?

Just let us know shital.dixit@keygene.com

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Acknowledgements      

Gert-Jan Speckmann Jose Guerra Koen Huvenaars Marco van Schriek Anker Sørensen Arjen van Tunen    

Dirk Vandenhirtz Joerg Vandenhirtz Kevin Nagel Ralph Schunk Shital Dixit

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PhenoFab: The plant phenotyping facility in Europe

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