Tanzania Dairy Genetics: Highlights of progress
James Rao
Maziwa Zaidi review & planning meeting
31March – 1 April 2015 at Giraffe Ocean View Hotel, Dar es Salaam,
Tanzania
tdg.ilri.org

The Problem
 Many Smallholder dairy farmers are milking losses.
 Use of inappropriate dairy breeds leading to low
productivity
 Inadequate application of productivity enhancing
technologies
 The potential contribution of appropriate genetics and
new technology in increasing yields is largely
undocumented.

This Animal
This EnvironmentWhat farmers have been
trying to do
MOVE
Crossbreed
Adapt
Optimize
Upgrade

Environment
To this
Animal

Smart choices can only be made where
performance data is available!
I am Better I am much Better
Ngobe Zerida II
H234 73% 4.9
ltr/day
Rank:
209/285
11.06
ltr/day
W046 77% Rank: 1/285

• Characterization of current
dairy cattle genotypes in
use
• Determination of most
appropriate genotypes for
smallholder dairy farmers
in Rungwe and Lushoto
• Understanding what dairy
technologies are most
desired (lacking) by
smallholder dairy farmers
in Rungwe and Lushoto
TDG Project Objectives

How are we doing this?
 Apply emerging NGS technologies to determine breed
composition of dairy animals
 Samples are already taken from animals
 Undergoing analyses
 Correlate breed-type with performance & systems data
obtained through participatory appraisal, in-situ
 Baseline household survey conducted
 Longitudinal surveys on-going
 Listen to farmers…continuously and incorporate their
concerns and views in design of on-going interventions

Project Study Sites
Selection Criteria
 On-going ‘Maziwa
Zaidi’ Activities
 Emerging Dairy
industries with high
potential
 Range of breed types
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Farmer and Animal Selection
 Household selection
criteria
 Have more than 1
animal meeting
selection criteria OR
 Have an active bull
 Have a variety of breed
types
 Animal Selection Criteria
 Be either a calf less
than 3 months old
 Be a bull in active use
 Be a lactating cow
 Be in-calf, 3rd trimester

Progress so Far: Activities
completed
• Animal selection: A total
of 1200 animals recruited
• Bio-sampling: Blood and
hair samples collected
from 1200 animals; Most
of the animals ear tagged
• Baseline survey: Systems
data collected from 670
households

Preliminary results: Household survey
6%
30%
20%
17%
16%
11%
Proportion of animal types in study
households visited
Incalf
Heifers
Lactating
Cows
Incalf Cows
0
100
200
300
400
500
Lushoto Rungwe
NumberofFarmers
District
Mobile Network Operator Subscription amongst
farmers
AirTel Tigo Vodacom
0
500
1000
Phone Type
NumberofHouseholds
Phone types distribution amongst participating
farmers
Basic Null Smart

Animal Dynamics: Baseline
0
20
40
60
80
100
120
Animal Dynamics: Entry and
exit
Number_bought Number_sold
Numberof
animals
Animal Type
0.00
50.00
100.00
150.00
200.00
250.00
300.00
350.00
400.00
450.00
Animal Dynamics: Sale and
purchase price
Purchase_price(US$) Sale_price (US$)
Price(USD)
Animal Type

Progress so Far: Ongoing activities
 1000 animals to be genotyped
for breed composition
 Collection of performance data
ongoing, to last 9 months
 Farmer feedback: Two sessions
planned
 ICT system deployment:
Training materials being
developed

Challenges
 Lack of USSD platform to
deploy paperless data
collection
 Delays in start of field
activities
 Increase in costs of data
collection

Successes
 So far have trained 47
individuals in field data
collection, survey
administration and bio-
sample collection
 Leveraged collaborations with
RDA and ILRI Health team to
investigate husbandry and
health issues
 Integrated the national
extension system to be part
of project activities and
planned feedback delivery
network

Mechanisms for output dissemination and
scaling
Focus group discussions
Online Training tool*
Mobile phone content delivery*
Individual Farmer feedback

The Team
Students
Work Package Leads
Project Management Team
Site Enumerators
tdg.ilri.org

The presentation has a Creative Commons licence. You are free to re-use or distribute this work, provided credit is given to ILRI.
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