Phenotyping plant and organisms interactions in the context of sustainable agriculture

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Phenotyping plant and organisms interactions in the context of sustainable agriculture

Christophe Salon

To cite this version:

Christophe Salon. Phenotyping plant and organisms interactions in the context of sustainable agri- culture. Photo-Physiology Phenotyping Workshop, UK Plant Phenomics Network., Dec 2013, Essex, United Kingdom. �hal-02802432�

Christophe SALON

UMR 1347-AgroSup/INRA/uB

17 rue Sully - BP 86510 - 21065 Dijon - France

Plant architecture, flowering, senescence, … Pods and seeds

Roots and interactions with micro organisms

Bacteria Mychoriza

Valorise soil beneficial biological interactions

Understand plant response to environmental factors, identify genes.

Select the best performing crops..

..“better” yield, environmental « efficiency ».

Context Approach Phenotypic tools Examples Models Conclusion

Context Approach Phenotypic tools Examples Models Conclusion

Tools and methods

CONCEPTION of PLANT IDEOTYPES

Genetic variability

Characterizing mechanisms and molecular basis

PPPN, ESSEX, 17/12/2013

Context

PPHD Fluxomic Rhizotrons

Approach Phenotypic tools Examples Models Conclusion

Growth pouches, hydroponics

Labeling chamber

C/

N/

S N

adapted Isotopic split root

Characterizing root development C, N, S flux measurement

Rhizobox

High Throughput Phenotyping Platform

Building,

Phenotyping facilities Lemnatec

greenhouses (240+110m

),

climatic chambers (80m

)

Context

PPHD Fluxomic Rhizotrons

Approach Phenotypic tools Examples Models Conclusion

Shoot roots etc…

Facilities

Spielberg’s masterpiece Rhizobox

PPPN, ESSEX, 17/12/2013

100 units/h

Phenotyping cabins equiped with cameras and robots

VIS NIR FLUO

Aerial architecture

Root system

120 units/h

6 units/h 20 units/h

2 units/h

Small plants

Organs (seeds…)

Germination

Plant from the agrosystems

Context

PPHD Fluxomic Rhizotrons

Approach Phenotypic tools Examples Models Conclusion

Spielberg’s masterpiece Shoot roots etc…

Facilities

Rhizobox

Context

PPHD Fluxomic Rhizotrons

Approach Phenotypic tools Examples Models Conclusion Facilities

Spielberg’s masterpiece Shoot roots etc…

Rhizobox

PPPN, ESSEX, 17/12/2013

Rhizothrones

(EU Patent INRA-Inoviaflow,

1300 units planed) ^Rotating _device

Traits :

projected

root area

projected

nodule

number

nodule size

total root length….

High resolution T0

T1 Tn RBG Image Context

PPHD Fluxomic Rhizotrons

Approach Phenotypic tools Examples Models Conclusion

Rhizobox

2013

Context

PPHD Fluxomic Rhizotrons

Approach Phenotypic tools Examples Models Conclusion

Rhizobox

2014 2015 2016 2011 2012

2010

Date

1000 1300

2017

500

2018

200

500

1.V1 1.V2 3.V3 10.V3 25.V4

1000

1300

RhizoBox (INRA-Inoviaflow

Context

PPHD Fluxomic Rhizotrons

Approach Phenotypic tools Examples Models Conclusion

Rhizobox

Linear Sensor 12MP, 3 LEDs RVB, precision 50µm

Camera : BASLER racer (Adapter F-Mount V01)

Examples Legumes

Context Approach Phenotypic tools Models Conclusion

But…

Fluctuating yields

•  Symbiotic fixation and durability :

ê  fertilizers, fossil energy, GHG emissions, irrigation

Regulation of symbiotic N

fixation and NO

assimilation: determinism, plasticity constituents, optimal root / nodules for maximizing yield?

Genetic diversity Objectives

Identify a strategy Genotype ranking

Sensitivity of symbiotic N

fixation to environmental

conditions

•  Two ways of nitrogen nutrition

PPPN, ESSEX, 17/12/2013

Examples Legumes

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking

Tools and methods

CONCEPTION of PLANT IDEOTYPES

Genetic variability

Characterizing mechanisms

and molecular basis

French national collections of pea, fava and lupin (10000 accessions)

Context Approach Phenotypic tools Models Conclusion

Natural genetic variability

Bourion et al. Annals Bot. 2007

Genetic diversity on root architecture

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

PPPN, ESSEX, 17/12/2013

Context Approach Phenotypic tools Models Conclusion

Recombinant inbred lnes (1400 RILs)

Bourion et al. TAG 2010

Nodules:

Number Surface Biomass Roots:

Number Length Biomass

Aerial part : Height Biomass Leaf surface area

STRUCTURE FONCTION

C use efficiency

N uptake efficiency

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Context Approach Phenotypic tools Models Conclusion

Induced genetic variability

Total plant growth rate during the week following nodule initiation (g.day^-1)

0,00 0,02 0,04 0,06 0,08 0,10 0,12

Number of nodules formed during the first nodulation wave

0 100 200 300 400 500 600 700 800 900

R² = 0.97 P = 0.0004 Sym28

Sym29 nod3

Frisson

Plant  growth  rate  

Nodule  number                

Wild   Hypernodula7ng  

Nodule development

Voisin et al. Plant Soil 2010 Salon et al. Agr 2001

Duc et al. 1998

0 2 4 6 8 10 12 14 16

0 200 400 600 800 1000 1200

Somme de dégrés-jours depuis le semis Accumulation de matière sèche (g.plante-1)

Degree  days  a:er  sowing   Nitrogen  accumula7on     (g/plant)  

Cazenave et al. Plant Soil 2013

Porceddu et al. BioMed 2008 Coll . KK Sidorova

Wild   Long  roots   Ramified  ++   Nod++  

Ramified ++

Nod++ x Ramified++

Nod++

Wild

Root architecture

Medicago truncatula, induced by Tnt1

Pea, induced by EMS

Identify/characterize genes involved in nodulation control or root architecture

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Context Approach Phenotypic tools Models Conclusion

TILLING mutant collections

Research mutant in a target gene, analyze the mutation effect Medicago truncatula Jemalong A17 (9000 M2) and pea (Pisum sativum) var. Caméor (5000 M2)

Le Signor et al. Plant Biotechnol 2009 Dalmais et al. BMC Genome Biol 2008

ü  HTP TILLING platform: ABI 3730 (Contact: lesignor@dijon.inra.fr)

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Tools and methods

CONCEPTION of PLANT IDEOTYPES

Genetic variability

Characterizing mechanisms and molecular basis

PPPN, ESSEX, 17/12/2013

What is the strategy of legume plants faced to a N constraint ?

Roots Dry Weight (g) 0,04 0,06 0,08 0,10 0,12 0,14 0,16 0,18

Nodules Dry Weight (g)

0,004 0,006 0,008 0,010 0,012 0,014 0,016 0,018 0,020

Number of nodules counted on the scan

0 200 400 600 800

Real number of nodules

0 200 400 600 800 1000

Surface area

20 30 40 50 60 70

Root Dry Weight (g root/plant) 0,04 0,06 0,08 0,10 0,12 0,14 0,16 0,18

y = 0.0106 ln(x) + 0.0369, R≤ = 0.78 y = 0,000041x² - 0,001530x + 0,087432, R≤ = 0,839

y = 1.1645 x - 9.45, R≤ = 0.90

Nodules number and size, appearance

NH4NO3 10 mM

-N KNO3 0.5

mM 14 days after inoculation

Split roots

Ruffel et al. (2008), Plant Physiol. 146: 2020-2035.

Salon et al. (2009), CRAS, 332 :1022-1033.

Jeudy et al. (2010), New Phytol, 185:817-828.

Morphometry versus functional

strategy identifcation

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

“Low” throughput characterization of nodulated roots

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Young plant

Thèse Simeng Han (unpublished)

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Binary image and

threshold

Young plant

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Smooth the image

Young plant

Get rid of unused

areas

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Count nodules with the

« circle » form

Young plant

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Original image + superposed

nodules

Young plant

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Young plant some days later…

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Enlarged image

PPPN, ESSEX, 17/12/2013

Hybrid space (color + texture)

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Green band of the RGB image

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

PPPN, ESSEX, 17/12/2013

Binary image with squared nodules

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Nodules automatically detected

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

95%  detec7on  efficiency    

PPPN, ESSEX, 17/12/2013

Context Approach Phenotypic tools Models Conclusion

Genetic diversity Objectives

Identify a strategy Genotype ranking Examples

Legumes

Original image + superposed nodules

Context Approach Phenotypic tools Examples Models Conclusion Legumes

Genetic diversity Objectives

Identify a strategy Genotype ranking

Ranking pea genotypes: Pea core collection Hydroponic versus rhizotron Shoot biomass

Genotype

ranking does not vary

Dry Matter (g/plant)

0,00   0,50   1,00   1,50   2,00   2,50  

Hydroponic   Rhizotrons  

Rhizotron

y  =  0,9052x  -­‐  0,3116  

0,0   0,2   0,4   0,6   0,8   1,0   1,2   1,4   1,6   1,8  

0,0   0,5   1,0   1,5   2,0   2,5  

Hydroponic and substrate R²=0,88

PPPN, ESSEX, 17/12/2013

Nodule biomass

Context Approach Phenotypic tools Examples Models Conclusion Legumes

Ranking pea genotypes: Pea core collection Root biomass

Genetic diversity Objectives

Identify a strategy Genotype ranking

Dry Matter (g/plant) Rhizotron

Hydroponic and substrate 0,00  

0,05   0,10   0,15   0,20   0,25   0,30   0,35  

0,40   Hydroponic  

Rhizotrons  

y  =  1,1576x  -­‐  0,0451  

0,0   0,1   0,1   0,2   0,2   0,3   0,3   0,4   0,4  

0,0   0,1   0,2   0,3   0,4  

0,00   0,02   0,04   0,06   0,08   0,10   0,12   0,14  

Hydroponic   Rhizotrons  

y  =  0,7358x  -­‐  0,013  

0,0   0,0   0,0   0,0   0,0   0,1   0,1   0,1   0,1  

0,0   0,0   0,0   0,1   0,1   0,1   0,1   0,1  

R²=0,80 R²=0,95

Ongoing rhizothrone validation

Estimate integrative variables :

- compare measured/observed variables

Form recognition : nodule and roots number Root and nodule surface and biomass

Robustness of traits:

- intraspecific (X genotypes), - interspecific (Y species),

- modulating the abiotic environment (Z env.)

Context Approach Phenotypic tools Examples Models Conclusion Legumes

Genetic diversity Objectives

Identify a strategy

Genotype ranking

Understand process and their interactions

-  C and N multiple interaction, -  Root architecture

Naudin et al. Plant & Soil 2011 Agrophysiologie du pois 2010 Voisin et al. Plant & Soil 2010 Salon et al. CR Biologies 2009 Voisin et al. Annals Bot 2007

Mecanistic models : PEA NOD (coll. L Pagès)

Modèles Conclusion

Contexte Approche Outils Exemples

Context Approach Phenotypic tools Examples Models Conclusion

Leaf area

Total plant biomass Biological efficiency

Total nitrogen amount

Specific nitrogen acquisition Efficiency of N conversion to

leaf area

Microbial communities Rhizodeposition

Respiration

Stimulating root development Improving soil N availability

Nodulated roots

Root biomass over plant biomass ratio

Root Nodules

Integrative Model: Medicago

Decomposing  integraCve  variables  in  physiological  processes  

Moreau et al. Plant Cell Env 2006 Moreau et al. JExp Bot 2008 Zancarini Plos One 2013 Soil acidification

Preferential selection of microbial communitues

Organic carbon Organic acids

CO2

Disolved Inorganic Carbon

Models  need  a  reduced  number  of  parameters  for   phenotyping  gene7c  variability  

Provides  characteriza7on  of  phenotypic  

traits  into  models  

Approach Phenotypic tools Examples Models Conclusion

Analytical approach

Modelisation Phenotyping Approach

Combine approaches

Identifying differences among genotypes

Interpreting the detected difference

+ +

Food for thoughts…

Ø  Towards functional phenotyping (NAAS System)

Ø  Validate to/from the field : Pheno Field Platform in Dijon

Context

NO3- NO3- N₂

CO₂

CO2

N

Starring…

Christian JEUDY

Céline BERNARD

Jean-Claude SIMON

Frédéric COINTAULT

Simeng HAN

Marielle ADRIAN

Steven S.

Christophe BAUSSARD

Agrosystems Adaptation Team Medicago truncatula team

And also …

PPHD’s addicts

Proteaginous target crop team

Data acquisition and management wizards

Ecophysiology team

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

Rhizothrones (EU Licence INRA- Inoviaflow, 1300 units

planed

Context

PPHD Fluxomic Rhizotrons

Approach Phenotypic tools Examples Models Conclusion

Rhizobox

Roots Membrane 32µm

Substrate

Compressed gaz (20-100mbar)

Valve Before inflating

Plant

After inflating

Examples Models Conclusion Legumes

Grapevine Context Approach Phenotypic tools

Major problems in viticulture è cryptogamic diseases (oïdium, grey mould) of grapevine

Desease detection Objectives

Detecting desease in viticulture

Approaches:

1) ê number of fongicides

treatments and ê applied quantity (decision tools) + images (thermography IR…)

2) alternative strategies to fongicides

Examples Models Conclusion Context Approach Phenotypic tools

Microplates, dishes HTS (small biological unit phenotyping)

Detection/evaluation of the intensity of diseases on grapes/berries

Legumes Grapevine

Desease detection Objectives

Colour/texture hybrid spaces

-RGB images in colorimetric spaces that integrates texture,

- object with similar colors may have different textures (so need to practice with biological

objects)

PPPN, ESSEX, 17/12/2013