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Farming systems analysis in Africa RISING. Bernard Vanlauwe - IITA Jeroen Groot - WUR Carl Timler - WUR Lotte Klapwijk – IITA/WUR. 28 May 2013 Lilongwe, Malawi. Contents. Objectives and rationale Steps in the project, timeline Site selection, sample size
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Farming systems analysisin Africa RISING Bernard Vanlauwe - IITA Jeroen Groot - WUR Carl Timler - WUR LotteKlapwijk – IITA/WUR 28 May 2013 Lilongwe, 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)
Functional typology Issues and indicators Evaluation Innovations Explain Selection Fine-tuning Implementation Demonstration Structural typology Describe Explore Scenarios of change Design Diagnosis & design phases Stakeholder interactions Inputs and outputs
Survey Structural typology Extrapolation Potential impact n=500-1000+ Rapid characteriz. Systems (re)design Farm innovations Functional typology n=50-100 Detailed description Exploration innovations Farm diagnoses Tradeoff analysis n=10-50
Exploration of innovations, tradeoffs Housing Intensive grassland Extensive grassland Maize Natural resources Wheat Woodland Gross margin
Farm DESIGN Describe Explain Design Explore Validate 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
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 Babatiand 80 in Kongwa + Kiketo • Malawi • 1 team of 4 enumerators • Surveys: 40 in Dedza and 40 in Ntcheu • Sampling: Y-frame
Survey tool • 8 main sheets: • People • Fields • Crops • Animals • Manures • Imports • Tools • Buildings
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) • ….