progress of the milkit project in tanzania (july – november 2012)
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PROGRESS OF THE MILKIT PROJECT IN TANZANIA (July – November 2012). Component 2. Productivity Enhancement – Tanzania . 2a.Strategies for implementing local feed-related innovations emerging from stakeholder platforms with the potential to enhance dairy incomes. - PowerPoint PPT PresentationTRANSCRIPT
PROGRESS OF THE MILKIT PROJECT IN TANZANIA
(July – November 2012)
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
FEAST training and DVC Assessment in Pemba (MilkIT 7th – 14th July 2012)
Kisiwani Chake Chake and Mkoani
FEAST training in Pemba
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
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
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
Baseline/HH Survey (More-MilkiT, MilkIT and SFFF Nov. - Dec. 2012)
Magamba, Lushoto Teams taking off in the morning
Detailed Site Selection in Tanzania
Process of Detailed Site Selection Sites for interventions in Tanzania DVC so far identified up
to district levelMorogoro 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
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
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
Detailed Village SelectionProcess:
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
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 teamProduce quarterly technical reports Write annual report Lessons synthesized, assessed and applied
Innovation PlatformsInnovation Platforms Meeting:
Stakeholders’ analysis in Tanga and Morogoro to be done by partners
Tanga Dairy Platform already in placeTanga 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
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
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
Tanzania
Morogoro Tanga
KilosaMvomero Handeni
Lushoto
a b c
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
a b c a b c a b c
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 ruralRural to urban
Production systemsIntensive/semi-intensiveExtensive
Accessibility
Knowledge Sharing
Characteristics of selected villages District Village Cattle
population (no. hds)
HHs with cattle (no.)
Marketing channels
Farming system
Altitude Access-ibility
Tanga
Lushoto Kwang’ wenda
308-Improved
102 Rural-urban
Intensive High Good
Magamba 1330-Improved
330 Rural- urban
Intensive High Good
Handeni Sindeni 4996-Local 86 Rural-rural Extensive Low Good
Kabuku 121-Local + 60-Improved
10-Local + 32-Improved
Rural-rural Extensive + Intensive
Low Good
MorogoroMvomero
Manyinga 298-Improved
42 Rural- urban
Extensive Low/high Good
Kambala 8,614-Local + 354-Improved
562-local + 76-Improved
Rural-urban
Extensive + Intensive
Low Good
Kilosa Twatwatwa
60,317-Local 191 Rural-rural Extensive Low Good
Mbwade 3745-Local 47 Rural-rural Extensive Low Good
Knowledge Sharing
X
Mvomero (left), Kilosa (right)
Morogoro Region
Detailed Site Selection in Tanzania
Sindeni
Lushoto Handeni
Tanga Region
Detailed Site Selection in Tanzania