tli 2012: drought phenotyping for legumes

ICRISAT – CIAT – ISRA – Univ North Carolina

Objective 5: Cross-crop issues

Activity 1: Drought phenotyping

Across crops

Update on Year 2

Hypothesis 1: A “drought tolerant” plant has:

enough water to fill up grains no more water after grain filling

Hypothesis 2: Crop species share same adaptation strategies

Options: • Save water • Tap water • Secure reproduction

Purpose: Looking at similar traits across species

Water use / productivity

Water uptake

Reproduction and partitioning

Modeling

Sub

-Activ

ity 5

: Tra

inin

g

Outputs to TLII

Trait value

predicted

Refined protocols

More tools

Better pheno-

typing data

Phenotyping of cell-based processes – toward gene discovery

FTSW

0.00.20.40.60.81.0

No

rma

lize

d t

ran

sp

irati

on

0.0

0.2

0.4

0.6

0.8

1.0

1.2

Stage I

Stage II

Stage III

How plant manage water when there is water is critical

Basic response of plant exposed to water deficit

Soil moisture thresholds for transpiration decline

Canopy conductance (Tr in g cm-2 h-1)

Tr response to VPD

Leaf area development

To measure:



Groundnut Cowpea Bean Chickpea

Soil moisture thresholds for

transpiration decline x xxx x xxx

Canopy conductance (g cm-2 h-1) x xxx x xx

Tr response to VPD xx xxx x xx

Leaf area development xx x

Zaman-Allah et al., 2011 JXB

Zaman-Allah et al 2011 FPB

Belko et al 2012 - FPB

Belko et al 2012 – Plant Biology

0.000

0.010

0.020

0.030

0.040

0.050

0.060

0.070

0.080

08

:00

09

:00

10

:00

11

:00

12

:00

13

:00

14

:00

15

:00

16

:00

17

:00

18

:00

19

:00

Lea

f co

nd

ucta

nce (

gH

2O

cm

-2h

-1)

Time of the day (H)

LSD ICG 11862 ICG 12235

ICG 13787 ICG 4598 ICGV 12000

ICGV 02189 ICGV 02266 ICGV 11088

ICGV 97182 ICGV 97183

A

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

08

:00

09

:00

10

:00

11

:00

12

:00

13

:00

14

:00

15

:00

16

:00

17

:00

18

:00

19

:00

Leaf

con

du

cta

nce (

gH

2O

cm

-2h

-1)

Time of the day (H)

LSD Bambey-21 IT82E-18

IT97K-556-6 KVX-525 UC-CB46

IT84S-2049 IT93K-503-1 IT93K-693-2

Mouride Suvita 2

B

Groundnut Cowpea

From Issa Faye, Nouhoun Belko, Vadez (in prep)

Sensitive

Tolerant

Sensitive

Tolerant

In cowpea, clear discrimination tolerant/sensitive

In groundnut, Tr differences at high VPD are smaller


y = -13.32x + 2.33

R² = 0.401

P = 0.0113

0.00

0.50

1.00

1.50

2.00

2.50

0.000 0.050 0.100 0.150 0.200

Tra

nsp

irati

on

eff

icie

ncy

(g k

g-1

)

Transpiration rate (g H20 cm-2 h-1)

(C)

WW

Outdoors

y = -17.68x + 2.56

R² = 0.756

P = 0.0000

0.00

0.50

1.00

1.50

2.00

0.000 0.050 0.100 0.150 T

ran

spir

ati

on

eff

icie

ncy

(g k

g-1

)

Transpiration rate (g H20 cm-2 h-1)

(D)

WS

Outdoors

Belko et al 2012 - FPB

High transpiration rates lead to low TE

Work on going to test hypothesis across crops

Water use / productivity Cowpea - WS Cowpea - WW

Drought water use efficiency (g kg-1)

0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6

Dro

ug

ht

see

d y

ield

(g

pla

nt-

1)

2

3

4

5

6

7

8

9

10

BRB 191

PAN 127

SUG 131

VAX 1

BAT 477DOR 364

CAL 143 VAX 3

SEA 5

SEA 15SER 16

SEQ 1003

SEQ 11CAL 96

SEC 16RAA 21

ICA Quimbaya

SER 8

Mean: 7.10LSD0.05: 2.2

Mean: 1.06LSD0.05: 0.41

r = 0.89***

Relationship between water use efficiency and seed yield

Seed yield differences are closely related to TE

Same results in India, but…..


Bean – WS

CIAT)

Relationship between water use efficiency and seed yield

Nitrogen seems to play a central role in that relationship


Bean – WS

ICRISAT)

-5

0

5

10

15

0.00 0.50 1.00 1.50 2.00 2.50 3.00

Po

d Y

ield

- W

S

Transpiration Efficiency 0

2

4

6

8

10

12

0.00 0.50 1.00 1.50 2.00 2.50 3.00

Po

d y

ield

- W

S

Transpiration Efficiency

Post-rainy season Rainy season

Compare the most contrasting lines for the

transpiration response to high VPD


Groundnut – WS

Large variations in leaf development in contrasting chickpea

Leaf and root development closely matches

Possible differences in RUE at early stages

Hydraulic differences?

Sensitive

Tolerant


Leaf area development in chickpea

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

10

30

50

70

90

110

130

150

170

190

210

230

250

270

290

310

330

350

370

390

410

430

450

470

Time (mn)

NT

R

Control

1 mM H2O2Before treatment

Sensitive to

AQP inhibitor

Insensitive to

AQP inhibitor

Transpiration response to 1 mM H2O2 in chickpea

TPLA varying TPLA_inflection_ratio

0

5

10

15

20

25

0 200 400 600 800

TTemerg_to_flag

TP

LA

0.66

0.5

0.33

TPLAmax = 20

TPLA_prod_coef - 0.018

0.33

0.66

The coefficients are used as input to the crop model

Similar work is taking place in groundnut

Similar work needs to be done in cowpea


Lysimetric system

Total water extracted

Kinetics of water extraction

Max rooting depth

Root length density

Relationships RLD vs Water extraction

To measure:

Lysimetric assessments


Total water extraction xxx x x xxx

Kinetics of water extraction xx x x xxx

Root length density (RLD) xxx xx x xxx

Maximum rooting depth xxx xx x xxx

Relationships Roots vs water xxx x xxx

Relationships yield vs water xxx xxx


Ratnakumar & Vadez 2011 FPB

Belko et al 2012 – In preparation



Drought length of the longest root (cm)

70 80 90 100 110 120

Dro

ug

ht

seed

yie

ld (

g p

lan

t-1)

2

3

4

5

6

7

8

9

10

BRB 191

PAN 127

SUG 131

VAX 1

BAT 477

DOR 364CAL 143VAX 3

RCW

SEA 5

SEA 15SER 16

SEQ 1003

SEQ 11CAL 96SAB 259

RAA 21ICA Quimbaya

SER 8

Mean: 7.10LSD0.05: 2.2

Mean: 98.7LSD0.05: 21

r = 0.48***

Relationship between maximum root depth or RLD

and seed yield

Drought root length density (cm cm-3)

0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75D

rou

gh

t s

ee

d y

ield

(g

pla

nt-

1)

2

3

4

5

6

7

8

9

10

BRB 191

PAN 127

SUG 131

VAX 1

BAT 477

DOR 364CAL 143VAX 3

RCW

SEA 5

SEA 15

SER 16SEQ 1003

SEQ 11CAL 96SAB 259

RAA 21 ICA Quimbaya

SER 8

Mean: 7.10LSD0.05: 2.2

Mean: 0.56LSD0.05: 0.13

r = 0.30*

Poor relations between yield under WS and root length or RLD

Similar results in chickpea in India


Beans

Relationship between maximum root depth or RLD and

water extraction

Drought root length density (cm cm-3)

0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75Dro

ug

ht

wate

r extr

acti

on

(kg

pla

nt-

1)

5.5

6.0

6.5

7.0

7.5

8.0

8.5

BRB 191

PAN 127

SUG 131

VAX 1

BAT 477

DOR 364

CAL 143

VAX 3

RCW

SEA 5

SEA 15

SER 16

SEQ 1003

SEQ 11CAL 96

SAB 259

RAA 21

ICA Quimbaya

SER 8

Mean: 0.56LSD0.05: 0.13

SEC 16

Mean: 6.84LSD0.05: 1.53

r = 0.08

Drought length of the longest root (cm)

70 80 90 100 110 120

Dro

ug

ht

wate

r e

xtr

acti

on

(kg

pla

nt-

1)

5.5

6.0

6.5

7.0

7.5

8.0

8.5

BRB 191

PAN 127

SUG 131

VAX 1

BAT 477

DOR 364

CAL 143

VAX 3

RCW

SEA 5

SEA 15

SER 16

SEQ 1003

SEQ 11

CAL 96

SAB 259

RAA 21

ICA Quimbaya

SER 8

Mean: 98.7LSD0.05: 21

SEC 16

Mean: 6.84LSD0.05: 1.53

r = 0.25*

No relation b’ween water extraction (WS) and root length / RLD

Similar results in chickpea in India


Beans

Relationship between drought seed yield and water

extraction

Seed yield differences are related to higher pre-flowering water extraction

“ “ to lower grain filling water extraction

Nitrogen seems to play a central role in these relationships

Trend is different in chickpea

Pre-Flowering stage Grain-Filling stage

Beans


Vegetative and pod yield under high / low nitrogen and

under well-watered and water stress conditions

Nitrogen supply seems to be a more critical factor

than drought for seed yield

Beans

Cowpea

Relationship between drought seed yield and water

extraction

Similar results in cowpea and chickpea


Plant trait Irrigated Drought

Day to flowering 0.03 -0.33**

Days to maturity 0.08 -0.62***

Water use efficiency (g kg-1) 0.63*** 0.89***

Stem biomass (g plant-1) 0.43*** -0.30*

Pod harvest index (%) -0.01 0.23

Maximum rooting depth (cm) 0.16 0.48***

Total root length (m plant-1) 0.17 0.30*

Root length density (cm cm-3) 0.17 0.30*

Root length density at the 0-15 cm soil layer (cm cm-3) 0.01 -0.29*

Root length density at the 30-45 cm soil layer (cm cm-3) 0.18 0.30*

Root length density at the 45-60 cm soil layer (cm cm-3) 0.12 0.44***

Root length density at the 60-75 cm soil layer (cm cm-3) 0.08 0.12

Root length density at the 75-90 cm soil layer (cm cm-3) 0.09 0.28*

Total root biomass (g plant-1) 0.26* 0.22

Correlation coefficients between seed yield and plant attributes of

20 common bean genotypes grown in lysimeters at CIAT-Colombia

Modeling of critical traits


Model availability xxx xxx xxx xxx

Parameterization of key cultivars xx xxx

Modelling water use traits x x

Modeling root traits xxx

Developing maps (India) x NA NA x

Developing maps (ESA – WCA) xx xx


Ratnakumar & Vadez 2011 FPB

Belko et al 2012 – In preparation


-15

-10

-5

0

5

0 50 100 150 200 250

Pe

rce

nta

ge y

ield

incr

eas

e

Baseline Yield at locations

Faster root growth

Faster root growth in Chickpea

Negative effect of faster root growth (= faster water depletion)

Decreased depth of water extraction

Increased depth of water extraction

-45

-35

-25

-15

-5

5

15

0 50 100 150 200 250

Pe

rce

nta

ge y

ield

incr

eas

e


Altered depth of water extraction in Chickpea

Water extraction at depth is what really matters

RLD and water extraction seldom correlate

Decreased depth of water extraction Decreased depth of water extraction

+ Faster root growth Increased depth of water extraction Increased depth of water extraction

+ Faster root growth

-45

-35

-25

-15

-5

5

15

0 50 100 150 200 250

Pe

rce

nta

ge y

ield

incr

eas

e


Altered depth of water extraction +/- faster rooting

Increased leaf area Increased leaf area

+ Faster root growth -25

-20

-15

-10

-5

0

5

10

15

20

25

0 50 100 150 200 250

Pe

rce

nta

ge y

ield

incr

eas

e


Again, faster rooting brings a negative effect

Faster leaf development +/- faster rooting

30 mm irrigation at R5

-10

0

10

20

30

40

50

0 50 100 150 200 250

Pe

rce

nta

ge y

ield

incr

eas

e


Irrigation at key time during grain filling

The effect is larger than the best genetic effect

Predictions from Marksim weather deviate from

those obtained from observed weather

So far, few locations

Can Marksim-generated weather be used??

Marksim weather can be used to test trait effects

Modeling & mapping the benefits of particular trait in the targeted regions

Probability of yield

increase after introduction

of trait X into standard

genotype

Region with low probability of yield increase

Region with high probability of yield increase

Capacity to test trait effects acrossWCA and ESA)

Work on-going in chickpea and groundnut

Soon will start with soybean

Training on drought phenotyping

Long term training

Year 2 trainees:

Vincent Vadez – Crop modeling

Year 3 plans: Abalo Hodo TOSSIM (Groundnut CSSL???)

Omar Halilou (Groundnut) – Crop modeling

Nouhoun Belko (Cowpea) – Trait mapping – Crop

modeling

Jose Polania (Bean) – Trait mapping – Crop modeling

Training

Thank you

tli 2012: drought phenotyping for legumes

Technology