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

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. 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 (Pennisetum purpureum), Brachiaria spp and Guinea grass (Panicum maximum) SARI- Arusha and TALIRI- Tanga are the proposed sites where multiplication plots will be established under different ecological conditions. Productivity Enhancement

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

8. Process of Detailed Site Selection  Sites for interventions in Tanzania DVC so far identified up to district level Morogoro Region (Kilosa and Mvomero districts) Tanga Region (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  Kilosa and Handeni districts represent pre-commercial rural production-to-rural consumption  Mvomero and Lushoto stand for more commercial rural production-to-urban consumption Detailed Site Selection in Tanzania

9. 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 Detailed Site Selection in Tanzania

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

11. 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 Detailed Site Selection in Tanzania

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. 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 Knowledge Sharing

16. 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 Knowledge Sharing

17. Sampling Villages in a District  Reducing 150 – 200 villages in a District to 35  MoreMilkIT research 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 Knowledge Sharing

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

19. 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 Knowledge Sharing

20. Characteristics of selected villages DistrictVillage Cattle population (no. hds) HHs with cattle (no.) Marketing channels Farming system Altitude Access- ibility Tanga Lushoto Kwang’ wenda 308-Improved102Rural-urbanIntensiveHighGood Magamba1330-Improved330Rural- urbanIntensiveHighGood HandeniSindeni4996-Local86Rural-ruralExtensiveLowGood Kabuku 121-Local + 60-Improved 10-Local + 32-Improved Rural-rural Extensive + Intensive LowGood Morogoro MvomeroManyinga298-Improved42Rural- urbanExtensiveLow/highGood Kambala 8,614-Local + 354-Improved 562-local + 76-Improved Rural-urban Extensive + Intensive LowGood KilosaTwatwatwa60,317-Local191Rural-ruralExtensiveLowGood Mbwade3745-Local47Rural-ruralExtensiveLowGood Knowledge Sharing

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

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