PROGRESS OF THE MILKIT PROJECT IN TANZANIA (July – November 2012)

1. PROGRESS OF THE MILKIT PROJECT IN TANZANIA (July – November 2012)

2. Component 2. Productivity Enhancement – Tanzania 2a. Strategies for implementing local feed-related innovations emerging from stakeholder platforms with the potential to enhance dairy incomes. • Training on the FEAST tool – in Pemba • Characterize feeding systems with FEAST assessments • Plan site-specific interventions with platforms • Compile inventory of feed agents/types/sources around sites

3. FEAST training in Pemba FEAST training and DVC Assessment in Pemba (MilkIT 7th – 14th July 2012) Kisiwani ChakeChake and Mkoani

4. Component 2. Productivity Enhancement – Tanzania 2b. Methods for enhancing diffusion of local feed-related innovations among dairy smallholders with the potential for income benefits through productivity increases. • Test strategies to engage local decision makers • Identify workable interventions at project sites – TechFit • Innovation platforms develop a process to change feeding practices 2c. Strategic lesson learning on appropriate dairy feeding strategies and technologies. • Design and implement baseline study • Document current feed-related development activities (successes + failures) • Develop framework to assess likelihood of technology uptake

5. Productivity Enhancement Technical activities planned • Forage Germplasm Establishment: • A base towards conducting trials and seed distribution to farmers during the project. • Few forage spp. already proposed and agreed, namely; • Varieties of Napier grass (Pennisetumpurpureum), Brachiariaspp and Guinea grass (Panicum maximum) • SARI- Arusha and TALIRI- Tanga are the proposed sites where multiplication plots will be established under different ecological conditions.

6. Component 2. Productivity Enhancement – Tanzania 2b. Methods for enhancing diffusion of local feed-related innovations among dairy smallholders with the potential for income benefits through productivity increases. • Test strategies to engage local decision makers • Identify workable interventions at project sites – TechFit • Innovation platforms develop a process to change feeding practices 2c. Strategic lesson learning on appropriate dairy feeding strategies and technologies. • Design and implement baseline study • Document current feed-related development activities (successes + failures) • Develop framework to assess likelihood of technology uptake

7. Detailed Site Selection in Tanzania Baseline/HH Survey (More-MilkiT, MilkIT and SFFF Nov. - Dec. 2012) Magamba, Lushoto Teams taking off in the morning

8. Detailed Site Selection in Tanzania Process of Detailed Site Selection • Sites for interventions in Tanzania DVC so far identified up to district level • MorogoroRegion (Kilosa and Mvomero districts) • TangaRegion (Handeni and Lushoto districts) • Based on mixture of spatial map overlays, stakeholder consultation, scoping visits and R&D partner preferences • Spatial mapping mainly relied on socio-economic data • Human population & poverty, market access and consumption • Livestock density and • Livestock production systems • Kilosaand Handeni districts represent pre-commercial rural production-to-rural consumption • Mvomeroand Lushotostand for more commercial rural production-to-urban consumption

9. Detailed Site Selection in Tanzania Detailed (intervention) site selection • Objective • to identify specific sites where specific interventions will be carried out • Checklist and participatory scoping procedures will be applied to identify sites for implementation based criteria, e.g. • Target groups, • Impact indicators, • Ease of assistance and access to markets/ inputs/services • Potential for collective action, and • Availability of related development activities

10. Detailed Site Selection in Tanzania Detailed village selection in Kilosa and Mvomero, Morogoro Region; Handeni and Lushoto, Tanga Region (More-MilkiT and MilkIT September 2012) In Lushoto .

11. Detailed Site Selection in Tanzania Detailed Village Selection • Process: • 25 Villages surveyed by visiting District Offices • GPS-coordinates and village details gathered • Some key findings: • Poor organization of data/information. • Most of the improved cattle were obtained through projects (e.g., Heifer International and SECAP, Soil Erosion Control Agroforestry Project) • Fred to expand

13. Component 3. Knowledge Sharing – Tanzania 3a. Mechanisms for sharing knowledge at local and regional levels. • Identify key existing knowledge pathways • Identify communication barriers along value chain • Establish steering group 3b. Mechanisms for sharing knowledge across project countries and among global R4D projects. • Annual planning meeting of project team • Produce quarterly technical reports • Write annual report • Lessons synthesized, assessed and applied

14. Knowledge Sharing Innovation Platforms • Innovation Platforms Meeting: • Stakeholders’ analysis in Tanga and Morogoro to be done by partners • Tanga Dairy Platform already in place • Tanga model will be the basis of establishing other platforms in Morogoro. • The IP activities start from November in Tanga • Dairy Platform Meeting in Tanga • Julius to expand on meeting November 2012

16. Knowledge Sharing Approaches: Innovation Platforms (IPs) and site selection • Alan (28.08.2012): “Chronology in MilkIt would be to form IP’s, agree on feed interventions among IP members and then select sites for those interventions based on agreement with IP members.” • Actual process: • Site selection by • Regional IP • Village IPs • FEAST training + assessments already planned for January’13

17. Knowledge Sharing Sampling Villages in a District • Reducing 150 – 200 villages in a District to 35 • MoreMilkITresearch villages (20 – 25 per district) represent the majority of the cattle population and cattle-keeping population in the area • The initial selection of 35 villages was based on local authority official figures for villages where there were ‘some’ cattle • Upon reduction from 35 to 25 villages a few ‘very remote’ villages were dropped and villages with little/no cattle as per ground-truthing activity • Among these 25 villages, there are villages with few cattle keepers, but these keep large herds, so in terms of cattle population, it's not negligible

18. Knowledge Sharing Tanzania Country Tanga Region Morogoro Mvomero Lushoto Handeni District Kilosa Ward Village a a a a b b b b c c c c MilkIT feed activities in village types a and c. Overarching IP at Regional level and local feed IP’s at District level.

19. Knowledge Sharing Considerations concerning village selection • Cattle numbers + number of cattle-keeping households • Improved cattle + number of households with improved cattle • Market channels: • Rural to rural • Rural to urban • Production systems • Intensive/semi-intensive • Extensive • Accessibility

20. Knowledge Sharing Characteristics of selected villages

21. Detailed Site Selection in Tanzania Morogoro Region Mvomero (left), Kilosa (right)

22. Detailed Site Selection in Tanzania Tanga Region Sindeni Lushoto Handeni