Systems research and modelling

in Agri-Food research

Dr. Martin Kropff, CIMMYT Director General

Prof. Wageningen University

Berlin, 17 March 2016

Thank you to Kai Sonder, Matthew Reynolds, Bruno Gerard, Isaiah Nyagumbo,

Kindie Tesfaye, Balwinder Singh, Peter Carberry, V Valdez, A. Jarvis, Rao, …

…This presentation…

• AgriFood central to all challenges

• Developments in the CGIAR

• Systems research and modelling in AgriFood

• Model development vs applications

• Future needs and opportunities: an invitation!

The 9 Billion Person Question

AgriFood systems

Food security

Climate change

Diseases

Urbanization

Resources

Diets

More Less

Better

Food System Shocks

Ug99 (windborn)

Lloyds Emerging Risk Report – 2015

Price

increase

s

x4

x5

Stock market

losses

Food riots

Humanitarian

crisis

Human cost

10% in EU

5% in US

Wheat

Maize

Rice

Soybean

7%

10%

11%

Global production

losses

7%

Impacts

Lloyds workfloor: Global insurance:

managing risk

CIMMYT Around the World Key Office

Field Station

Project

China

Zimbabwe

Kenya

Ethiopia

Mexico, HQ

Guatemala

Colombia

Kazakhstan Iran

Turkey

Bangladesh

Nepal

India Pakistan

Afghanistan

Impact: Spring bread wheat releases by region and

origin 1994-2014: Annual return of 2-5 billion $

-

10

20

30

40

50

60

70

80

90

100

China EU and otherhigh income

countries

FormerSoviet Union

Countries

LatinAmerica

South Asia Sub-SaharanAfrica

West Asiaand North

Africa

World

Pe

rce

nta

ge o

f re

leas

es

(%)

Direct CGIARlines

CGIAR parent

CGIARancestry

Non-CGIAR

Unknownvarieties

Unknown Varieties Non-CGIAR parents CGIAR Ancestry CGIAR Parent CGIAR Line

Source: Lantican et al., 2015

Working Within Agri-food Systems Site integration

AFS: From germplasm-breeding-sustainable intensification to value chains

Modeling 1980’s

data in

search of

a system

Prof. C.T. de Wit (1924-1993));

My Dream 25 Years Ago

Today:

Progress

Research tool?

Applications? +

scaling up

DSS

Capacity/Training? -

SYSTEMS APPROACHES AND CROP MODELLING IN AGRIFOOD RESEARCH

Research tool

analysing data

hypothesis generation

study emerging behaviour

SI and Breeding

Value chains

Applications

Decision support

Yield Gap Analysis

Climate change regional scenario studies

Assisting breeding GxExM

Capacity building ???

Examples systems research: Was there a yield decline? Model as reference

S. hamata and C -

C. cajan C ++

in rice

Akanvou, Kropff, Bastiaans

Examples systems research: Understanding rice-legume relay cropping

Shenggen Fan, October 2013

Examples systems research: Rice-legume relay cropping

Introduction more competitive variety:

• later introduction

• faster growth after removal rice

• better use water reserves

Ecophysiological model INTERCOM:

0.0

0.2

0.4

0.6

0.8

1.0

0 2 4 6 8 10 12 14

Ric

e g

rain

yie

ld lo

ss

Legume biomass (t ha-1)

4 DARS

8 DARS

12 DARS

16 DARS

20 DARS

24 DARS

28 DARS

32 DARS

C. cajan in V4

C. cajan in Wab56-50

S. hamata in Wab56-50

S. hamata

in V4

Examples systems research:

Methane emissions in rice

Serendipity

v d Gon, Kropff,

v Breemen, PNAS

y = -61x + 558

R2

= 0.94

0

50

100

150

200

250

300

350

400

450

0 2 4 6 8 10Yield (t/ha)

Seasonal C

H4 e

mis

sio

n (

kg C

H4

-C / h

a)

Dry season

Wet season

Linear WS and DS

y = -61x + 558

R2

= 0.94

0

50

100

150

200

250

300

350

400

450

0 2 4 6 8 10Yield (t/ha)

Seasonal C

H4 e

mis

sio

n (

kg C

H4

-C / h

a)

Dry season

Wet season

Linear WS and DS

Sink limitation was

process in the model…

Otherwise???.

Examples systems research:

Scenario analysis with APSIM in Bangladesh CIMMYT-CSIRO incl. training!

Examine on farm and on station trials in terms of:

– Changing from conventional to conservation agriculture (water

conservation)

– Increasing mechanisation (reducing labour for production)

– Comparing different rabi crops: e.g. boro vs. maize vs. wheat vs. lentil

– Examining the feasibility of including a third crop between rabi and kharif

Examples systems research

Using APSIM to optimise cropping

systems in Cooch Behar

1

9

|

0

10

20

30

40

50

60

70

Jun

Jul

Au

g

Se

p

Oct

Nov

Dec

Jan

Fe

b

Ma

r

Ap

r

Ma

y

Avera

ge r

ain

fall

(mm

)

Examples systems research

Scenario analysis with APSIM in Bangladesh

STARS: Model for irrigation scheduling in

the Delta region of Bangladesh

Ground Cover (%) from remote

sensing

Daily Weather

• Tmax

• Tmin

• Solar

radiation

• Precipitation

Forecasted

irrigation need

(yes/no)

Water table depth

MODEL

Example of small scale spatial

variability measured on farmers fields

in Bangladesh Dry Wet Intermediate

Dry

Dry

Wet

Wet

Intermediate

Intermediate

Examples systems research

Groundnut pigeonpea intercrop

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

1.8

2.01

96

2

19

63

19

64

19

65

19

66

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67

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68

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71

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19

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19

96

19

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19

98

19

99

20

00

Syst

em

LER

, Re

lati

ve y

ield

to

tal

Year

Md pigeonpea intercrop

Sole crops Yield LER iPnMdPp RYT iPnMdPp

(ICRISAT) Rao Nageswara, Meinke and Kropff, 2016 APSIM

Examples systems research:

Cassman and van Ittersum et al

Weather based scheme since

2007operational since 2007

• 15 million farmers covered

• 67 crops covered

• Subsidized; linked to credit

Yet dissatisfied stakeholders

• Farmers due to poor weather

triggers for yield loss estimates

• Industry due to limited profits

• Government due to subsidy load

Examples systems research:

Crop insurance in India: Reaching the Unreached

Examples systems research

Improvement by using crop models and optimization Farmer’s satisfaction with new rainfall triggers: Example from

Maharashtra, India

0

1

2

3

4

5

6

7

Paddy Pearl Millet Cotton SoybeanFarm

er'

s S

ati

sfa

cti

on

In

dex

Current Index New Index

More than a million farmers used this product in 2015 in one crop season alone

Systems research: Examples

Modelling at different scales? • Multi-scale and

• Multi-dimensional analysis

Global

Continental

National

Regional

Farm

Field

Global

Continental

National

Regional

Farm

Field

Ewert et al., 2006

Economic

Social

Natural Institutional

Economic

Social

Natural Institutional

Example systems approaches

Using crop models to look at crop yields

under future climate (CIAT)

Gourdji et al. (in prep.)

Percent change in yields by 2030s and RCP4.5

Modelling: a New Era 2016’s

data in

search of

a system

Examples Systems research:

Breeding predicting G x E x M

Genotype (QTL)

Physiological

trait

Eco-

physiological

model

Yield

G x E x M

Yin, Kropff, Stam 2004, TIPS

FUTURE NEEDS AND OPPORTUNITIES: AN INVITATION

Ravi Singh and Norman Borlaugh

Ravi Singh CIMMYT:

Can modellers explain and

help identifying the parents

for crosses

Targeting G to E and M

Data: 700 lines x 70 locations

CIMMYT operates a global breeding

platform

2001

2008

2002

2007

1999

2011

2006

1998

2010

1987 2000

1990

2009

2004

2003 1979

1996

1990

1982

1987

1984

1989

1988 1994

1985

1980 1991

1983

1986

1981

1993

1992

2013

2012

2014

2015

4.0

4.5

5.0

5.5

6.0

6.5

7.0

7.5

7.5 8.5 9.5 10.5 11.5 12.5Wh

eat

yie

ld Y

aq

ui V

alley (

To

n/H

a)

Adapting to Climate Change: Heat Tolerant Wheats prove their Value in Farmers’ Fields in Mexico:

Explain?

1C increase = 700 Kg lower yield

January-April Average min. Temperature C

Y=11.55 – 0.65 X R2=0.75

Source: H.-J. Braun, I. Ortiz-Monasterio CIMMYT

CIRNO

CIMMYT and others in The CGIAR:

A dream collaboration for modellers • 10000 people studying crops worldwide!!!

• Modelling expertise scattered: data in search of modellers

• G x E x M: Models should be a standard tool next to statistical models (improving G component)

• Large multilocation datasets: all sorts of treatments: agronomy-modelling

• Model improvements

• Platform big data: Community of Practice modellers

• Understanding the model principles!!! Training

• Modeling in the value chain

…Conclusion… • AgriFood central to all challenges

• Modelling has to become a standard tool in AgRes

• A revival with new approaches and open innovations?

• The CGIAR : a dream for modellers

• Capacity building: understanding the models (no misuse)

• An invitation! Data in search of models 2016!

• New intensive collaboration with modelling groups

• Enhancing impact of science!

Diego Rivera Tlatelolco Market Mural

Thank you

for your

interest!