Farming systems analysisin Africa RISING

Bernard Vanlauwe - IITAJeroen Groot - WURCarl Timler - WUR

Lotte Klapwijk – IITA/WUR

28 May 2013Lilongwe, Malawi

Contents

• Objectives and rationale• Steps in the project, timeline• Site selection, sample size• Project organization, teams, roles• Training: Tanzania + Malawi• First results

Objectives

• To find options for sustainable intensification and targeted innovations at farm-level

– Diagnose current whole-farm performance (RO1)– Explore trade-offs and synergies among ‘services’,

or objectives, identifying farm performance gaps– Interactive re-design of farming systems, to close

gaps– Inclusive project and stakeholder approach

Rationale (1)

• Based on household surveys, characterizations and previous engagements with farmers …

• … model-supported diagnosis and exploration of whole-farm options for sustainable intensification …

• … informing interactive adaptation and learning cycles conducted with farmers and other stakeholders.

Rationale (2)

• A farm-level approach allows to embed proposed and tested innovations

• Exploration, presentation and discussion of sets of options is needed to:– Analyze trade-offs and synergies (among

objectives, etc.)– Support adoption processes by providing choices– Avoid lock-in onto undesirable development paths

(= provide pathways out of poverty)

Describe

Explain

Design

Explore

Issues and

indicators Evaluation

Innovations

Selection

Fine-tu

ning

Implementation

Demonstration

Structural typology

Functional typology

Scenarios of change

Stakeholder interactions

Diagnosis & design phases

Inputs and outputs

Survey

Rapid characteriz.

Detailed description

Explorationinnovations

Functional typology

Structural typology

Systems(re)design

Extrapolation n=500-1000+

n=50-100

n=10-50Farm

diagnosesTradeoff analysis

Farm innovations

Potentialimpact

Exploration of innovations, tradeoffs

Naturalresources

Gross margin

HousingIntensive grasslandExtensive grasslandMaizeWheatWoodland

Farm DESIGN

Describe

Design

Explore

Explain

Validate

Groot et al., 2012. Agricultural Systems.

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Operating profit (k€)

Soil

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Labor balance (h)

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Organic matter balance (kg/ha)

f.

Groot et al., 2012. Agricultural Systems.

Site selection, sample size

• Tanzania, Malawi– Next growing season: Nov. 2013– Results by: Sep. 2013

• Ghana, Mali– Next growing season: Apr./May 2014– Results by: Dec. 2013

• Samples (dependent on capacity)– Rapid characterization 50-100– Detailed diagnosis 10-50

Milestones, products per stage

• Rapid characterization functional typology• Detailed description diagnosis per farm• Exploration T-S and promising options,

discussions with farmers a.o.

• Re-design implementation and demo plan for farm

innovations

Timeline

Timeline

Timeline

Timeline

Teams and roles• National teams (NT’s)

– Local recruitment (Number? Capacities?)• Data collection, entry, checks• Process with farmers

• Scientific team (ST)– 2 PhD students, 1 per region– 1 post doc researcher

• Instruct and train NT’s• Data analysis typologies• Perform modeling (diagnosis and exploration)

• Scientific supervision (SP)– Wageningen team

• Support trainings and all activities of ST

Training sessions

• On-farm data collection (ST NT)• Characterization, description (SP ST)• Exploration and re-design (SP ST)

First results

• Training: April 2013• Tanzania

– 2 teams of 4 enumerators– Surveys: 96 in Babati and 80 in Kongwa + Kiketo

• Malawi– 1 team of 4 enumerators– Surveys: 40 in Dedza and 40 in Ntcheu

• Sampling: Y-frame

Tittonell et al., 2013

Survey tool

• 8 main sheets:– People– Fields– Crops– Animals– Manures– Imports– Tools– Buildings

Household size

0 2 4 6 8 10 12 14 160%

5%

10%

15%

20%

25%

30%

35%

Babati Kongwa Dedza Ntcheu

Farm size (acre)

0 10 20 30 40 50 600%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Babati Kongwa Dedza Ntcheu

To do:• Check + clean 256 surveys • Collect secondary data• Build basic farms in FarmDESIGN• Model runs and analysis of results• Farm typologies (per country and region)• Plan detailed characterization (sample = 10%)• Inventory of ‘Innovation-Basket’• Cooperate: talk, meet, discuss, etc. (today)• Identify entry-points (later)• ….

Thanks for your attention!