06 wp5 progresses&results-20130221

WP5 _ Enhancing the knowledge of genetics

underlying novel traits and providing phenotyping methods

Results achieved since the beginning of the project and plans for 2013

Main objectives of the WP5

• Develop tools for novel trait determination

• Investigate novel and complex traits

• Make novel trait analysis high throughput and applicable for the research community and the breeding industry

3 tasks

• Task 5.1 Improve Monilinia resistance in peach

• Task 5.2 Assess fruit quality Jurriaan • Apple

• Peach Remo

• Task 5.3 Select traits important for climate change adaptation Evelyne

Results achieved since the beginning of the project

Task 1. improve resistance to Monilinia in peach

• Protocols for infection tests in lab • Test of artificial infections in orchard • Microscopy analysis of infection • Biochemical analyses of fruit surface • Tests of fungicide activity of some compounds • Spore survey in the orchard



Spray Monilinia laxa suspension

Infection enhancement by humidity increasing: fruit covering

One week incubation Susceptibility score:

% infected fruits

Setup of high-throughput orchard brown-rot phenotyping protocol

CB2 CB3

inoculation

cove

rin

g

no yes

no C I

paper CB2 IB2

plastic CB3 IB3



Spray Monilinia laxa suspension

Infection enhancement by humidity increasing: fruit covering

One week incubation Susceptibility score:

% infected fruits

Setup of high-throughput orchard brown-rot phenotyping protocol

CB2 CB3

IB2 treatment allowed to distinguish between tolerant and susceptible accessions

cell collapse ( ) fungal colonization ( )

Monilinia disease progress : 8 vs. 48 hour after inoculation

Zephir 8hpi Zephir 48hpi

E. Lady 8hpi E. Lady 48hpi

Bolinha 8hpi Bolinha 48hpi

Bolinha: no fungal impact on the analysed samples



Biochemical analyses of fruit surface

40 60 80 100 120 140 160

050

100

150

Jours après f loraison

Masse d

'un fru

it (g

)

A

I

II

III

40 60 80 100 120 140 160

050

100

150


Dem

i-circonfé

rence (

mm

)

B

40 60 80 100 120 140 160

0.0

0.5

1.0

1.5

2.0


Indic

e d

e D

iffére

nce d

'Absorb

ance

C SG

ZE

Fruit growth for 2 cultivars

Days after bloom

Fru

it m

ass

(g)

02

04

06

08

01

00

25-apr 16-may 30-may 20-jun 4-jul 18-jul maturity

Infe

ctio

n p

rob

ab

ility (

%)

* ** *

SG

ZE

Infection probability for 2 cultivars

I II III



Cuticular conductance Biochemical analyses • surface compounds • waxes • cutins • epiderm and flesh phenolics

40 60 80 100 120 140 160

05

10

15

20

total cuticular wax quantities (mg/dm²)

DAB

wa

x a

ccu

mu

latio

n m

g/d

m²

SGZE

Total cuticular waxes accumulation

Wax

(m

g/d

m²)

Days after bloom

0 50 100 150 200 250

20

04

00

60

08

00

10

00

masse du fruit (g)

co

nd

ucta

nce

de

l'é

pid

erm

e (

cm

/h)

SG

ZE

Fruit mass (g)

Cu

ticu

lar

con

du

ctan

ce (

cm/h

)

Cuticular conductance



Correlations between infection probability and

surface compounds

-1-0

.75

-0.5

-0.2

50

0.2

50.5

0.7

51

Proportion d'infection

Acide oléanolique

Acide ursolique

pcoumaroyl di-hexoside penta acétylé

Pic52.5_312

Pic54.6_308

Pic64.6_307

Ole

anolic

acid

Urso

lic a

cid

pcoum

aro

yl

Pic

52.5

_312

Pic

54.6

_308

Pic

64.6

_307

Pic

65.7

_312

-1 -0.75 -0.5 -0.25 0 0.25 0.5 0.75 1

Pro

port

ion d

'infe

ction

Acid

e o

léanoliq

ue

Acid

e u

rsoliq

ue

pcoum

aro

yl di-

hexosid

e p

enta

acéty

lé

Pic

52.5

_312

Pic

54.6

_308

Pic

64.6

_307

Oleanolic acid

Ursolic acid

pcoumaroyl

Pic52.5_312

Pic54.6_308

Pic64.6_307

Pic65.7_312

inhibitory candidates

02

04

06

08

01

00

25-apr 16-may 30-may 20-jun 4-jul 18-jul maturity

Infe

ctio

n p

rob

ab

ility (

%)

* ** *

SG

ZE

Infection probability I II I

II

mg/d

m²

01

23

4

Oleanolic acid

mg/d

m²

02

46

810

Ursolic acid

Aire d

e p

ic/d

m²/

10^5

05

10

15

20

25

30

Pic52.5_312


Aire d

e p

ic/d

m²/

10^5

05

10

15

Pic64.6_307

40 60 80 100 120 140 160

05

10

15

20

25

30


Aire d

e p

ic/d

m²/

10^5

Pic65.7_312

40 60 80 100 120 140 160

05

10

15

20

25

Aire d

e p

ic/d

m²/

10^5

p-coumaroyl derivative

SG

ZE

days after bloom

Evolution of fruit surface compounds along fruit growth

Days after bloom

Task5.2 Assess fruit quality

State of progress

Research topic in task 5.2

• Texture/maturation/quality tools evaluation – Compare, use and evaluate common used methods (colour cards, pm, ss, tta,

AWETA, DA) – Acoustic method for crispiness (FC, NZ) – Juice/juiciness analysis by punching and study tissue structure (NZ) – New methods for Fibre content (ML)

• Gene expression based methods for analysing fruit texture trait – Ethylene pathway dedicated approach to unravel ripening and texture trait

biomarkers (DLO) – Differential cultivars for harvest time, storage quality, shelf-life and meatiness

(JP)

• Storage stress test to select and early predict storage performance of new

lines – Standard measurements and inspection (DLO) – Gene expression analysis (JP, DLO)

Texture/maturation/quality tools evaluation

Quality measurements (n=20) • At harvest • After 1 week regime + 1 week shelf life (18°C, 75% RH) • After 1 month regime + 1 week shelf life (18°C, 75% RH) • After 2 months regime + 1 week shelf life (18°C, 75% RH)

Monitored quality parameters: • Fruit weight • Ethylene production (at harvest) • Firmness (FTA automated penetrometer, destructive) • Firmness (AWETA acoustic, non-destructive) • Ground colour (colour chart) • Chlorophyll status (DA-meter, non-destructive) • External and internal disorders (expert visual evaluation)

SensorSense ETD 300 characteristics

• Detection limit 300 ppt (0.3 ppb) • Upper limit 5 ppm (this one up to

100 ppm) • Measurement every 5 sec • Accuracy: <1% of 0.3 ppb (largest

value) • Very specific for ethylene • Calibration yearly

0 20 40 60 800

2

4

6

8

10

12

14

16

18

20

22

24

26

40

45

50

55

60

65

70

0 20 40 60 800

2

4

6

8

10

12

14

16

18

20

22

24

26

40

45

50

55

60

65

70

0 20 40 60 800

2

4

6

8

10

12

14

16

18

20

22

24

26

40

45

50

55

60

65

70

0 20 40 60 800

2

4

6

8

10

12

14

16

18

20

22

24

26

40

45

50

55

60

65

70

TA-XTplus - AED

4 mm flat head probe 5 Kg loading cell

100 mm/min Acquisition at 500 pps Compression strain: 90%

Approach Plant & Food Research

• 6 cultivars

• 10 trained panellists

• 14 sensory texture attributes

• 3 fruit per cultivar

• 3 storage times (scheduled according to softening rate)

• Air storage only

• 1 harvest (using starch and skin colour

Approaches for improved phenotyping technologies – optimising existing technologies

• Destructive

• Tensile • Single edge notch beam • Rheometer (frequency sweep) • Juicer Kinetics • Microphone

• Nondestructive • AWETA • Sinclair

Juiciness potential assoc. with larger cells, higher density and more apoplastic fluid

Scifre

sh

Sciro

s

C.P

ink

R.G

ala

Sciea

rlyCox

0.75

0.80

0.85

0.90

0.95

Cort

ical density (

g/m

L)

Scifresh Sciros RGala C.Pink0

20000

40000

60000

80000

100000

Ce

ll a

rea

m

2

Scifre

sh

Sciro

s

C.P

ink

Roy

al g

ala

0.05

0.06

0.07

0.08

Ap

opla

stic f

luid

(g

/gF

W)

List of tools

Task

Sub-

task Sub-task name Trait or step

Destructive / non Protocol / tool

Tested (1 or 2 years) Species

Conclusions on protocols

available Feasibility Reliability High-

throuput 2 2.1 Maturity

assessment Index of

differential absorbance IAD

1 apple not yet* y y y

Starch D Y 2 " y y y y

Solible solids D Y 2 " y y y y

Titratable acids D Y 2 " y y y y

Streif Index D Y 2 " y y y y

Ethylene production

N Y 1 " y y y y/n

Colour determination

N Y 2 "

y

y

y

y

Chlorophyll ? status (DA-meter)

N Y 1 "

y

y

Not sure to what

quality trait it links

y

List of tools

Task

Sub-task Sub-task name

Trait or step Sub-trait

Protocol / tool

Destructive / non

Tested (1 or 2

years) Species

Conclusions on

protocols available

Feasibility

Reliability

High-throuput

2.2 Fruit texture assessment

Physical paramet

ers

Firmness analysis by penetro measurements

Texture Analyser

D 1 apple y y y y

hand-held penetromet

er

D x " x x <y x

Firmness analysis by confined compression test

D x " x x x x

Firmness analysis by non-destructive acoustic resonance devices

AWETA AFS N 1 " y y y y

Sensor deform at impact sinclair y y y/n y

Firmness analysis combined with crispness analysis

acoustic-mechanical

N x " x x x x

Juice press/spin test D x " x x x x Color determination N 1 " y y y y Bioche

mical paramet

ers

Soluble solids D 1 " y y y y/n

Titratable acidity D 1 " y y y y/n Flavour x " x x x x Molecular characters of

texture 1(sample

s frozen) " n ? ? ?

Water contribution/microstructure on texture (tissue mechanical properties): Evaluation of NMR relaxometry as a screening tool

Achieved

•Water content & compartmentalization were accessed by relaxometry but were not directly related to mechanical properties •Freezing and thawing samples exacerbate relations between mechanical properties & relaxometric variables

On going

•Relate relaxometry & mechanical data with free sugar and cell wall compositions •New assays to evaluate relaxometry of frozen samples vs mechanical/histological/chemical variables

New methods for quality screening assessment

WP5.2

INRA-Nantes Biopolymers, Interactions, Assembly

Dietary fiber content and nature : development of fast screening method by Mid IR analysis of alcohol insoluble tissue material (AIM)

Achieved

•AIM, protein and Mid-IR of 29 genotypes

On going

•DF (AOAC method TDF), cell wall sugar analysis, ash and starch contents •Chemiometric analyses

New methods for quality screening assessment

WP5.2

INRA-Nantes Biopolymers, Interactions, Assembly

Identification of genes and networks controlling major apple quality traits

Materials: 10 varieties (Golden, Gala, Elstar, Greensleave, Cox, Boskoop, Ariane, Jonagold, Fuji, Granny Smith) 4 contrasted hybrids 4 time points: Harvest, 1 month post-harvest, 2 MPH, 4 MPH 2 years of data: 2011&2012 Texture traits: Expert sensory panel (1 to 5 values): Fiber, Grain, Mealiness, Softness, Crunchiness, Juiciness, Acidity, Sugar Physical and Chemical measurements: Acidity, Sugar, Ethylene, Penetrometry, Compression Results: 2011: Phenotypic data completed (contrasted traits, differents kinetics of trait evolution) 2012: Finishing the 4MPH measurements RNA purification completed soon (112 samples) Transcriptomic results with the AryANE chip in June 2013 Bioanalayses and Network buildings during summer

WP5-3

To be completed: material exchange with DLO and PFR (comparison with RNAseq) functional validation of the candidates

R scripts developed for data treatment

24 « .pair » files Raw data

12 « .txt » files Norm. data

normalized intensities per sample, ratios, p.value, localFDR

(Limma & fdrtool packages)

RG_plot.png MA_plot.png

PCAS Clusters

Dendrograms ...

complet-lists.txt

Kjgqdkjlqk Kjgqdkjlqk Kjgqdkjlqk Kjgqdkjlqkghsfhf, Kjgqdkjlqk,gmqldf Kjgqdkjlqk,gmqldf Kjgqdkjlqk,gmqldf Kjgqdkjlqk,gmqldf Kjgqdkjlqk,gmqldf Kjgqdkjlqk,gmqldf







Annotations.txt

MapMan

Dongxia Yao et al Genomics Volume 98, Issue 1 2011 47 - 55

Storage Stress Test Tool

• Success cultivar very much dependent on storage behaviour

• Use commercial pick and commercial storage CA, DCS, mechanical/SF

• Stress test and supporting tools to analyse this behaviour – Does it suffer in-cooling or CA stress

– Is it Low Temp Sensitive

– Firmness during storage

– Sensitive to storage disorders

Experimental setup

Five commercially grown cultivars 1. Cox O.P. 2. Elstar 3. Golden Delicious 4. Jonagold 5. Kanzi Harvested • a week before • at commercial harvest date (for long term ULO-storage) • 1 week after

regime T (°C) %O2 %CO2

1 -1 21 0

2 -1 1 5

3 10 21 0

4 10 1 5

Overview of storage stress test (Y1)

Cultivar

Max storage period

(optimal conditio

ns)

Low Temp Sensitivity flesh

browning Texture issues

Low O2/high CO2 tolerance

Disorder sensitivity

practice

test practice test practice test practice test

Cox 5-6 m +++

Can develop mealiness

before softening

- Bitter pit,

brown core, Softening

Kanzi 12 m +++ Very firm, tough peel

? bitter pit, lenticel

breakdown

Jonagold 9 m - Greasiness ++ Scald, flesh browning

Golden 8 m -

++ Scald

Elstar 7 m + Rapid softening after storage

+ Softening, skin spots

Overview of storage stress test (Y1)

Cultivar

Max storage period

(optimal conditio

ns)

Low Temp Sensitivity flesh

browning Texture issues



practice

test practice test practice test practice test

Cox 5-6 m +++

+++

(-1°C + CA, late harvest, ≥1 month)

Can develop mealiness

before softening

Mealiness , rapid

softening (air, ≥1 month)

- - Bitter pit,

brown core, Softening

-

Kanzi 12 m +++

++++

(-1°C + CA, late harvest, 2 months)

Very firm, tough peel

Very firm indeed

?

++

(-1°C + CA, last harvest, ≥1 month)

bitter pit, lenticel

breakdown -

Jonagold 9 m - - Greasiness Greasiness (10°C, air, ≥1

month)

++

+ (-1°C + CA,

3 harvest, ≥1 month)

Scald, flesh browning

-

Golden 8 m - -

Greasiness (10°C, air, ≥1

month)

++

++

(-1°C + CA, 1+3 harvest, ≥1 month)

Scald -

Elstar 7 m + - Rapid softening after storage

Confirms practice

+ - Softening, skin spots

Skin spots (all treatm)

Samples for microarray

Cultivar

Genetic background

Max storage period

(optimal conditions)

Texture issues Low Temp

Sensitivity flesh browning



practice test practice test practice test

Cox

5-6 m Can develop

mealiness before softening

+ +++ ++ - - Bitter pit, brown core, Softening

Golden 8 m +/- - - ++ + Scald

Kanzi

12 m Very firm, tough

peel - +++ + ++(?) ++

bitter pit, lenticel

breakdown

Task5.2 Assess fruit quality (peach) State of progress

Cultivar Texture Type Pulp Institution

Cultivar Texture Type Pulp Institution

UMIL IRTA ARO UMIL IRTA ARO

Oro A NM Pc Y √ BO 05030142 SH P G √

BO 94007020 NM Pc Y √ BO 05030149 SH P G √

Dixired M P Y √ BO 05030081 SH P G √

Iride NM Pc W √ Elegant lady M P G √

Alice Col NM Pc Y √ IFF 331 SH P B √

Ambra M N Y √ √ Sweet dream M √

Big Top SM N Y √ √ Dulcebo SM P G √

Honey Kist SM N Y √ SRG M N G √

Redhaven M P Y √ Honey Royale SM √

Rich Lady SM P Y √ Nectaross M √

Vista Rich SM P Y √ BO 10120182 NM √

Ghiaccio SH P W √ √ Bolero M P G √

Glohaven M P Y √ BO 89010005 M N B √

Durado NM Pc Y √ Fei Cheng NM Pc B √

Alipersie M P Y √ Maria delizia M P B √

BO 00020006 NM Pc Y √ Dulciva M N G √

Swelling M P W √ Summer snow SM P W √

September Snow SM P W √ Fairlaine SM N Y √

1881 SM P W √ Hermoza SM P W √

Plant material & Experimental Design

Harvest

Co

ld S

tora

ge (

21

d a

t 4

ºC)

14d

1d

3d

21+1d

21+3d

0d

21d

21+5d

5d

Postharvest trial

2d

21+2d

Classification

M1 M2 M3

2011, 2012: M1, M2, M3

Summary (I)

Trait Sub-trait Technique Years Comments

Physical parameters Firmness analysis by

penetro measurements

Texture Analyser 1&2 Differentiate between fruit with different texture types through storage

hand-held penetrometer

1&2 In some cases, differentiate between fruit with different texture types through storage

Firmness analysis by confined compression test

Texture Analyser 1 No additional information if compared to other physical firmness techniques

Firmness analysis by non-destructive acoustic sensor

AWETA AFS 1&2 Differentiate between stone fruit type but not different textures

Compression to penetration ratio

Texture Analyser 2 Interesting results in Y1 but not in Y2

Juice press & spin test Expressible juice 1&2 Differenciates fruit with different textures through storage

Color determination & Portable

spectrophotometer Minolta CR2600d 1&2

No suitable for differentiating fruit with different textures

NIR Bruker MPA Multi

Purpose FT-NIR Analyzer

0 Data currently being analyzed

Summary (II)

Trait Sub-trait Technique Years Comments

Biochemical parameters

Soluble solids

Standard

1&2 No relationship with texture

Titratable acidity 1&2

Ethylene production 1&2 Not directly related to fruit texture, some interesting results that need to be further

confirmed

Antioxidant capacity FRAP assay 1&2 No direct relationship with fruit texture

Summary (III)

Trait Sub-trait Protocol Years tested Comments

Fruit structure and imaging

TRS Instrument developed by

Politecnico of Milano 1&2

Discriminate 3 out of 4 texture type (M, Sm and SH)

Nuclear Magnetic resonance

Esaote Airis II field intensity of 0,3 Tesla

1 No difference in texture (abandoned)

Echography Multimage Aloka ssd-500

scanning frequency of 3,5-5,0-7,5 MHz

1 No difference in texture (abandoned)

Computerized tomography

Stratec Medizintechnik XCT Research SA+

1&2

Gene expression RNA seq Illumina HiSeq 2000 2 Data currently being analysed

Sensory evaluation

Firmness perception 3 texture attributes and

likeness 2

No capability to distinguish between texture types but differentiate through storage

Phenotyping tools

Standard quality (TSS, TTA)

Firmness (Penetrometry, Texture Analyser and Acoustic Firmness sensor)

Expressible juice

Objective colour (L*, a* and b*; Spectrophotometer 360-740nm)

Fruit ethylene production

Sensory Analysis (Consumer tests)

Biochemical analysis (Antioxidants, MDA…)

Fmax

F(5% Def.)

P&D ratio

F

Stiffness Frecuency Impact Force

Phenotyping tools

Time Resolve Reflectance Spectroscopy (TRS)

Computerised tomography (CT)

Near Infrared Spectroscopy (NIR)

Echography

Nuclear Magnetic resonance(NMR)

Gene expression analysis

Transcriptomics

cytokinesis cell stretching

time

Fase I Fase II Fase III Fase IV

t0 t1

t2

t3

Results Fruit firmness: penetration

Days at 20ºC

0 1 2 3 4 5 6

Fir

mn

es

s (

Kg

)

0

1

2

3

4

5

6

7

Days at 20ºC

0 1 2 3 4 5 6

Fir

mn

es

s (

Kg

)

0

1

2

3

4

5

6

7

Fir

mn

es

s (

Kg

)

0

1

2

3

4

5

6

7

Fir

mn

es

s (

Kg

)

0

1

2

3

4

5

6

7

Ambra (M)F

irm

ne

ss

(K

g)

0

1

2

3

4

5

6

7

8

After CS

Before CS

Fir

mn

es

s (

Kg

)

0

2

4

6

8

Big Top (SM)

Honey Royale (SM) Nectaross (M)

Rome Star (M) Sweet Dream (SM)

S

M

-> No clear differences among different texture types -> Values from IRTA much lower than those from ARO (Impact of Agroclimatic conditions?)

Am

bra

Big

Top

Honey

Roya

le

Nec

taro

ss

Rom

e Sta

r

Swee

t Dre

am

Oded

Swel

ling

1881

Septe

mber

Snow

Fairla

ne (N

ecta

rine)

Her

moza

Summ

er S

now

P/D

ra

tio

0

1

2

3

4

IRTA ARO

Slow melting

Melting

Results Fruit firmness: deformation

*

*

*

a a

0

10

20

30

40

50

60

70

80

0 1 2 3 4 5

Exp

ress

ible

Ju

ice

(%

)

Day at 20°C

Melting

Non Melting

Slow Melting

a

a

a

b b b

b

b ab

c

0

10

20

30

40

50

60

70

80

0 1 2 3 4 5

Exp

ress

ible

Ju

ice

(%

)

Day at 20°C

Melting

Non Melting

Stony Hard

Slow Melting

a a

a a a ab

bc

ab

b b

c b

c

b

c

2012

2011

Results Expressible juice

Mie theory

b

s a )('

Stony Hard Slow Melting Melting

Results TRS

Mie theory

b

s a )('


Results TRS

Mie theory

b

s a )('


Results TRS

Mie theory

b

s a )('


Results TRS

Days at 20ºC

0 1 2 3 4 5

Aco

usti

c F

irm

ness

0

10

20

30

40

50

Days at 20ºC

0 1 2 3 4 5

Aco

usti

c F

irm

ness

0

10

20

30

40

50

Aco

usti

c F

irm

ness

0

5

10

15

20

25

30

Aco

usti

c F

irm

ness

0

5

10

15

20

25

30

Aco

usti

c F

irm

ness

0

5

10

15

20

25

30

35

40

Aco

usti

c F

irm

ness

0

5

10

15

20

25

30

35

40

After CS

Before CS

Ambra Big Top

Honey Royale Nectaross

Rome Star Sweet Dream

Acoustic firmness changes did not reveal different softening behaviors among the different cultivars investigated Significant differences in the fruit acoustic firmness were observed between different stone fruit types (Nectarine vs Peach)

Results Acoustic firmness

Before cold storage

After cold storage (21 d 4°C)

(M)

(M)

(M) (SM)

(SM)

(SM)

Results CT

Results CT

Big Top Oro A

Redhaven Alipersie

Rich Lady

IFF 331

BO 94007020

Ghiaccio

SM

M

NM

SH

0

50

100

150

200

250

300

Canning peach Peach Nectarine

De

nsi

ty g

cm

-3

Texture within peach group

Preliminary results average density

0

50

100

150

200

250

300

SM M SH

De

nsi

ty g

cm

-3

NGS raw data

Quality trimming and filtering (erne-filter)

Alignment to reference genome (Bowtie2)

Hits raw count

T1 T2

M SM SH NM M SM SH NM

T1

M – Redhaven – Rep 1 1 0 0 0 0 0 0 0

M – Bolero – Rep 2 1 0 0 0 0 0 0 0

SM - Big Top – Rep 1 0 1 0 0 0 0 0 0

SM - Rich Lady – Rep 2 0 1 0 0 0 0 0 0

SH - IFF 331 – Rep 1 0 0 1 0 0 0 0 0

SH - BO05030081 – Rep 2 0 0 1 0 0 0 0 0

NM - Oro A – Rep 1 0 0 0 1 0 0 0 0

NM - BO010120182 – Rep 2 0 0 0 1 0 0 0 0

T2

M – Redhaven – Rep 1 0 0 0 0 1 0 0 0

M – Bolero – Rep 2 0 0 0 0 1 0 0 0

SM - Big Top – Rep 1 0 0 0 0 0 1 0 0

SM - Rich Lady – Rep 2 0 0 0 0 0 1 0 0

SH - IFF 331 – Rep 1 0 0 0 0 0 0 1 0

SH - BO05030081 – Rep 2 0 0 0 0 0 0 1 0

NM - Oro A – Rep 1 0 0 0 0 0 0 0 1

NM - BO010120182 – Rep 2 0 0 0 0 0 0 0 1

Differential expression analysis (R, Limma and EdgeR)

Results Transcriptomic

For each type, the two time points group together.

Only SH flesh type groups tightly together

NM groups together at least in one axis, while M and SM samples group separately in both dimensions

Results Transcriptomic

Conclusions and prespectives

It is feasible to differentiate between fruit with different textures using time-course postharvest experiments with certain techniques.

Task5.3 Adaptative traits

State of progress

INRA Montpellier and Bordeaux UNIBO

Objectives

• Is it a genetic adaptation to ongoing climatic changes?

• Setting protocols easy to perform on populations for genetic studies and to be duplicated in different sites

• Chilling and heating requirements – Changes in temperature (during winter and spring) influences tree

phenology – Can we phenotype for selecting cultivars with desired chilling and heating

requirement ?

• Water scarcity – Identification of physiological parameters, potential candidates for

phenotyping tolerance and/or resilience to root water stress

Planned actions: CR et HR apple and peach

• In apple: 3 cultivars (Golden Delicious, Gala, Granny Smith)

• In peach: 9 cultivars (Fantasia, Ferjalou Jalousia, Flavorcrest, Mayglo, Redhaven, Summergrand, Summer Lady, Sunred, Tasty Free).

chosen from bibliographical data on their respective temperature requirements (contrasting CR from 200 to 1000 CH).

• Common methods performed in autumn 2011 and 2012 to estimate dates of dormancy release for floral and vegetative buds

• Samples of shoots collected from October year n to february year n+1 (collection every week at each site from december to february)

• Prospect other tests, search for new descriptors

Two biological tests:

forcing of ‘one-bud cuttings’ (vegetative buds)

forcing of floral primordia (Tabuenca’s test) from paradormancy period (summer in year n-1) to ecodormancy period (winter year n)

Characterization of genetic and annual influences both in Southern France and Southern Brazil (bilateral Project Capes Cofecub)

Observation of ‘green-tip’ stage: average time and percentage of budburst

VEGETATIVE BUD FORCING

FLORAL PRIMORDIA FORCING

(within floral bud)

Weighting of primordia before (in orchard ) and after forcing (fresh and dry weights)

Results: CR et HR apple

Results CR in apple

1 – Apple: Soil water restriction characterised by FTSW (Fraction of Total Soil Water)

- Bologne: Same protocol than in 2011: Leaf T° and fluorescence - Mtp: with a volumetric control of water in the soil (Volumetric Humidity assessment experiment);

* with mild root water restriction, applied during 3 weeks at 50% FTSW followed by 3 weeks at 20% FTSW, at morphological Measurements: (leaf area, shoot length and number of nodes) and eco-physiological (stomatal conductance) levels, • the ability to resume growth after a severe root water restriction, ie

provoking apex growth arrest, and possibly death, for most genotypes, applied during 3, 4 and 5 weeks (resilience).

2 – Peach: 2 cvs grafted on a F1 rootstock progeny 2012 was the first year of water stress (field experiment)

OBJECTIVES FOR WATER SCARCITY

2. Identification of a cluster of physiological parameters, potential candidates for phenotyping

Scatterplot (DATASHEET FATTORI pca STRESSED.sta 10v*17c)

F2FLUOTL = -8.8167E-16+0.6582*x

7S

23S

26S35S

37S

38S

40S

41S

48S

54S

70S

96S

117S

121S

125S

gsS

stkS

-4 -3 -2 -1 0 1 2 3 4

F2ALL

-3

-2

-1

0

1

2

3

F2

FL

UO

TL

F2ALL:F2FLUOTL:

r = 0.8153; p = 0.00007;

y = -8.4004E-16 + 0.6582*x

Scatterplot (DATASHEET FATTORI pca STRESSED.sta 10v*17c)

F1FLUOTL = 6.1837E-16+0.6678*x

7S

23S

26S

35S

37S

38S

40S

41S

48S54S

70S96S

117S

121S

125S

gsS

stkS

-6 -4 -2 0 2 4 6 8 10

F1ALL

-4

-3

-2

-1

0

1

2

3

4

5

F1

FL

UO

TL

F1ALL:F1FLUOTL:

r = 0.9387; p = 0.00000002;

y = 4.3311E-16 + 0.6678*x

PCA ALL vs. PCA FLUO_TL (2011)

2. Identification of a cluster of physiological parameters, potential candidates for phenotyping

PCA ALL vs. PCA FLUO_TL (2012)

Scatterplot: F1_ALL vs. F1_FLUO_TL (Casewise MD deletion)

F1_FLUO_TL = 0.0000 + .61268 * F1_ALL

Correlation: r = .91001

7

23

26

35

37

38

40

41

48

54

57

70

96

106

111

117

121125

gs

stk

-8 -6 -4 -2 0 2 4

F1_ALL

-5

-4

-3

-2

-1

0

1

2

3

4

F1

_F

LU

O_

TL

95% confidence

Scatterplot: F2_ALL vs. F2_FLUO_TL (Casewise MD deletion)

F2_FLUO_TL = 0.0000 + .86070 * F2_ALL

Correlation: r = .92362

7

2326

35

37

3840

41

48

5457

70

96

106111

117

121

125

gs

stk

-3 -2 -1 0 1 2 3 4

F2_ALL

-2

-1

0

1

2

3

4

F2

_F

LU

O_

TL

95% confidence

Projection of the cases on the factor-plane ( 1 x 2)

Cases with sum of cosine square >= 0.00

Labelling variable: trt

Active

7s

23s26s

35s

37s

38s40s

41s

48s

54s57s

70s

96s

106s111s

117s

121s

125s

GSs

STKs

-6 -5 -4 -3 -2 -1 0 1 2 3 4 5

Factor 1: 53.19%

-3

-2

-1

0

1

2

3

4

5

Fa

cto

r 2: 3

1.5

5%

Projection of the cases on the factor-plane ( 1 x 2)

Cases with sum of cosine square >= 0.00

Labelling variable: trt

Active

7S

23S

26S35S

37S

38S

40S

41S

48S54S

70S

96S

117S

121S

125S

gsS

stkS

-8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5

Factor 1: 65.47%

-5

-4

-3

-2

-1

0

1

2

3

4

Fa

cto

r 2: 2

4.9

3%

41 Stk 38 26 35 54 48

41 Gs 106 96 111 54

Gs 23 96 125 70 40 7 117 37 121

37 38 Stk 121 70 40 26 48 125 35 117 57 7 23

3. A tentative discrimination

2012

2011

As expected gs of 50% FTSW WS plants was higher than gs of 20% FTSW WS plants, with a decrease of ca. 80% and 35% compared to gs of WW plants, respectively.

7

2326

35

37

38

4041

48

54

57

7096

97

106

111

117

121

125

GS

SK

7

23

26

35

37

3840 41

48

54

57

7096

97106

111

117121

125

GS

SK

y = 0.1361x + 276.38R² = 0.0464

ns

y = 0.09x + 102.6R² = 0.1802

P=0.05

0

50

100

150

200

250

300

350

400

450

0 100 200 300 400 500 600

20

12

-gs

in W

S p

lan

ts (

mm

ol.

m-2

.s-1

)

2012- gs in WW plants (mmol.m-2.s-1)

X12_gs_WS50

X12_gs_WS20

2012 results – Apple Mtp

BUT the ranking of genotypes relative to each other for the three traits in either WW or WS between the two periods was different (example of the number of nodes). This would suggest that apart from the proper effect of the water regime, a plant development effect (growth dynamics varying along the growing season) and/or other environmental factors likely different between the two measurement periods, affected the development of the shoot.

Number of nodes developed during the period, either 50% or 20%

Pearson coefficient / Rank

correlation (Kendall’s t) WW - 50% FTSW vs WW - 20% FTSW R=0.32, ns; t=0.17, ns

WS - 50% FTSW vs WS - 20% FTSW R=0.21, ns; t=0.15, ns

2012 results – Apple Mtp

The combination leaf temperature and fluorescence provides a very good compromise between rapid and effective assessment of the drought resistance of a given phenotype.

WS protocol seems to be effective, simple for Leaf T° and fluorescence (and duplicable ??)

Summary-APPLE

Ranking was different between the two years and between stress conditions.

Ongoing discussions and analyses

0,0

5,0

10,0

15,0

20,0

25,0

0,0

20,0

40,0

60,0

80,0

100,0

120,0

140,0

1 2 3 4 5 6 7 8 9 10 11 12

tem

pe

ratu

re (°

C)

Rai

nfa

ll (m

m)

month 2012

rainfall temperature

2012 Results on peach

Harvest date

Surprised: 19 and 23 July 2012

Summergrand: 31 July 2012

No rootstock effect on fruit growth

But, fruit weight impacted …

In the same year or from n-1 year effect?

Publications

• Water scarcity

– Unibo communication at ISHS symposium on « orchard management »in South Africa, Dec. 2012

– Joint statistical analyses between Unibo & Mtp:

1 common publication planned in 2013

• CR:

– Statistical analyses of 2011 and 2012 results currently carriet out and publication planned, at least for apple results

linked to other projects

technical improvements on forcing tests, and application to a segregant progeny (genetic determinism of chilling requirement trait)

Validation of chilling models previously selected in apple by AFEF Team, based on the forcing test results obtained in the two hemispheres

Apply of ‘one-bud cuttings’ test Research of new alternative methods as NIRS Technology, based on the forcing test results in France (French Project Perpheclim ACCAF)

Main challenges for 2013 (CR, Apple)

Apple: 1 – Joint analyses between Bologna and Montpellier 2 - Same protocoles and observations in 2013, as in 2011 and 2012. No resilience experiment. Need to better study the ranking of genotypes in the various water conditions and years 3 –Comparison of 1YO shoots between plants in a greenhouse and plants in nearby outside conditions in Montpellier + possibly, at least for some of the variables, comparison with adult-fruiting trees of the same genotypes in the field. Peach: New experiment in 2013 in Bordeaux (2nd year) and in Bologna (1st year)

Main challenges for 2013 (Water scarcity)

Interactions WP5.3 and the rest of the project

• Interactions with other WPs of the project:

– Apply of ‘one-bud cuttings’ test to an apple segregant progeny (genetic determinism of chilling requirement trait)

– Apply water restriction to an apple core collection from WP4

Publications

• Communications in different meetings in 2012 and planned for 2013

• Publication plan has to be discussed during this meeting

Main challenges for 2013

• Complete sample analyses

• Analyze all data acquired

• Make synthetic analyses between years

• Merge results between partners

• Give conclusions on methods and tools

• Complete D5.2 (due February 2013)

Interactions between WP5 and the rest of the project

• From WP5 to WP2, WP3, WP4 – phenotyping tools for WP2, WP3 and WP4 Ex: Monilinia resistance on peach ; crispiness and water scarcity

on apple

– provide interesting genitors to WP2

• Interactions planned with the stakeholders of the project Test the phenotyping protocoles when available

Action Plan for 2013

To be discussed during this meeting

Should include many exchanges between partners via mels, phone calls, visio conf or workshop meetings

WP5 workshops

This afternoon:

• Task 5.2 _ 15:30 to 18:30 _ sala delegacions

• Task 5.3 _ 17:00 to 18:30 _ room 2.06

Tomorrow morning:

8:30 to 10 : 3 tasks separately