Better lives through livestock
Potential application of lessons from dairy genetics into beef
Lessons from ADGG
Okeyo A.M., Mrode R., Ojango J.M.K., Ekine C., Gebreyohanes G.
CTLGH – ACIAR Convening
Nairobi, Kenya, 30 September 2022

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0
5
10
15
20
25
30
35
40
0 1 2 3 4 5 6 7 8 9 10
Kg
of
milk
per
day
Months in Milk
Figure 1: Realized lactation curves of improved (crossbred or higher) dairy cows achieved by
different farmer types in Kenya
Commercial/Intensive dairy farmers –
~6,500 kg/lactation --- ~2% of farmers
Best smallholder farmers - ~2,500
kg/lactation --- ~5% of farmers
Average smallholder farmers --- ~1,400
kg/lactation --- >90% of farmers
Challenges and opportunities facing the small holder dairy system
• Little or no systematic and sustainable breeding programs
• Limited access to the appropriate genetics that best suit the different production systems
• Inadequate access to various inputs and services,
• Limited access to farmer education and extension
• No sustained productivity gains and profitability

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ADGG is designed to address key challenges facing the smallholder dairy systems
through innovative use of genomics coupled with digital information technology
enabled phenotyping across a wide range of very dispersed smallholder farms
ADGG’s work includes developing breeding values, to drive national breeding
schemes, based on performance data collected in the production environment
to improve productivity and adaptive capacity.
ADDG’s work is enabled by collaboration with key actors including Advanced
research Institutions (ARIs), global and national dairy genetic companies, farmer
organizations, national livestock seed regulators, national agricultural
research and extension systems(NARES) to realize sustained genetic gains and
scaled outcomes, which has been almost impossible to attain prior.
About ADGG

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ADGG’s Objectives • Establish/Revamp National livestock
Performance Recording Centers (DPRCs) or
Platforms for herd and cow data management
• Develop & scale ICT platforms to capture herd,
cow level & other related data & link it to
DPRCs & other databases
• Develop a pipeline for genomic evaluations to
identify genetically superior bulls & cows for
propagation using Artificial Insemination and
natural mating
• Establish a digital farmer extension and
feedback system using genomic and
performance data for improved herd
management
• Establish private-public partnerships to
sustainably resource recording, genetic
evaluation and digital extension at county &
regional levels

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ADGG innovative approach
o Digital platforms for on-farm
performance tracking
o Decision-support and Farmer-to-Farmer
performance benchmarking
o Smart use of records & genomics tools
for selection and AI service delivery
Accelerate on-farm
genetic gains
• Milk Yield
• Milk composition
• Weight
• Reproductive
Performance
• Heat tolerance
• Survival rates
• Lactation persistency
• Mastitis incidences
• Disease tolerance
• Methane emission
• Adaptability Indices
o Target appropriate genotypes to
the agro-ecology
o Use young bulls with a focus on
production & adaptation
o Local feed/fodder resource use
efficiency
Genotypes adapted to
local agro-ecology
Economically and
Environmentally relevant
Traits
Adapted, and
Genetically
superior "seed”
animals for local
production
systems

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Country Access to ADGG Platform: Webpage
The ADGG landing page: https://portal.adgg.ilri.org/

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Overview of the ADGG data platform
Country Data platforms
Data Extraction
API Management
System Administration
Data Validation
User
management
Data
Analytics
Other
Database
integration
Data
feedback
systems
API
API
Mobile
applications
Web
applications
Farm Data
Capture
National governments
Livestock stakeholders
Big Data systems
API
API
API
DATA PLATFORM
API = Application Program interphase
An agile, robust, flexible & scalable system

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ADGG Dashboard: http://18.217.46.219:8088/login/

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Useful data summaries for different stake holders:
Example from Tanzania

Useful data summaries for different stake holders:
Visualization tool for National Artificial Insemination Centers (NAICs)

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Useful data summaries for different stake holders:
Feedback to farmers

Useful data summaries for different stake holders:

Demonstration of evidence for need to support medium scale
farms in supplying genetically superior bulls, evaluated and ranked
in an objective manner to local genetic institutions and small
holder farmers
………many bulls that were evaluated by you are in fact
imported semen and their ancestry, almost all these bulls
have INTERBULL data available or other international
breeding values, many were top ranking bulls in their time.
I have much of their breeding data available…………. It was
very interesting to see that some of the internationally
acclaimed best bulls did not fare so well when
evaluated/performance tested under our challenging
Kenyan coast environment…..
I was truly overwhelmed about all the information you were able to
extract from all the records sent to you, I have still not managed to go
through them all but will give my comments as I proceed over time.
So many thanks for the very comprehensive
data evaluation report! I have not yet had the
pleasure to read such a brilliant summary of
our 30 years of dairying and breeding efforts in
such a compacted and highly accurate format!
What a great effort done by you!!!
Farmer’s
responses
Useful data summaries for different stake holders:

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• ILRI director general, Jimmy Smith (left) and Minister for Livestock and
Fisheries Luhaga Mpina (2nd to left) present the award for best bull at
a special bull and cow show at the Nane Nane exhibition center in
Dodoma, Tanzania, June 2019. Photo ILR
Highlights of
some of ADGG’s
Achievements …
• Ethiopia First dairy animal parade
held on Tuesday March 30, 2020,
Fikiru Regessa, State Minister of
Agriculture (extreme left), Selam
Meseret ADGG Ethiopia National
Coordinator (middle), and Asrat Tera,
Director General of National Animal
Genetics Institute (NAGII) Ethiopia.

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Objective: Evaluate changes in genetic
parameters for milk yield and estimate
breeding values for milk production
under heat stress conditions.
Data –phenotype, genotype, weather
Variance
Components
THI Thresholds
69 71 78
σ2
a 9.83 9.16 7.52
σ2
aht 0.10 1.96 2.15
σa (a, aht) -1.00 -2.10 -0.24
rg(a, aht) -0.99 -0.50 -0.06
Genomic analysis of milk yield and heat tolerance in small holder dairy system of
sub-Saharan Africa
C.C. Ekine-Dzivenu, R. Mrode1, R.D. Oloo, D. Komwihangilo, E. Lyatuu, G. Msuta, J.M. Ojango, A.M. Okeyo
Phenotype
Monthly milk collected,
between Nov 2016
and May 2020
Genotype
Cows and bulls genotyped
on the 50K chip and
imputed to the Illumina HD
chip
Statistical Model
Variance components estimated using a fixed
regression model with random regressions on a
function of THI for additive genetic and
permanent environmental effects
Climate Data
Obtained using GPS coordinates of the
farms, data includes daily maximum
and minimum relative humidity.
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0
1
2
3
4
69 70 71 72 73 74 76 77 78 79 80 81 82
Milk
EBV
THI
65769 55133 59078 63039 51938 59188 59155
Results Antagonistic relationships
between milk yield and thermal
tolerance. Milk production reduced
by 4.16% to 14.42% across THI
groups (heat stress levels).
Reaction norm shows genetic
variations exist between sires,
indicating the possibility to select
animals that perform optimally in
different environments.
Chinyere Ekine-Dzivenu
cekine@cgiar.org

THANK YOU

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Acknowledgment of Partners
Dairy Farmers & Farmer
organizations
National/regional
Institutions/govts.