dairy value chain breeding component

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dairy value chain breeding component
CONSULTANCY REPORT ON ACCELERATED VALUE CHAIN
DEVELOPMENT (AVCD), DAIRY VALUE CHAIN BREEDING COMPONENT
– INSEMINATION FOLLOW UP IN HOMA BAY, MIGORI, SIAYA
COUNTIES
SUBMITTED TO: INTERNATIONAL LIVESTOCK RESEARCH INSTITUTE (ILRI)
SUBMITTED BY:
DR. JOSIAH ODHIAMBO
PROF. VICTOR TREVOR TSUMA
LABCO
P.O. BOX 4901-00100 NAIROBI
TELEPHONE: 0722452173/0721395799
EMAIL:
[email protected]/[email protected]
CONTACT PERSON: DR. JOSIAH ODHIAMBO
OCTOBER 2016
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Table of Contents
EXECUTIVE SUMMARY ................................................................................................................................. 3
1.0 INTRODUCTION ...................................................................................................................................... 3
2.0 THE CONTEXT.......................................................................................................................................... 4
3.0 METHODOLOGY...................................................................................................................................... 5
3.1 Re-tooling Veterinarians on bovine early pregnancy diagnosis ....................................................... 5
3.2 Follow-up reproductive cow management ....................................................................................... 5
3.3 Develop, discuss and draft business options on breeding service delivery modelled around
Public-Private partnerships in emerging dairy systems .......................................................................... 5
4.0 FINDINGS, DISCUSSION .......................................................................................................................... 5
4.1 Re-tooling Veterinarians on bovine early pregnancy diagnosis ....................................................... 5
4.2 Follow-up reproductive cow management ..................................................................................... 10
4.3 Business model and options for successful Public-Private partnerships in the emerging dairy
systems ................................................................................................................................................... 11
4.3.1 Identified actors/players to sustain the dairy sector ............................................................... 11
4.3.2 Roles .......................................................................................................................................... 11
4.3.3 Diagram of Business Model & Options..................................................................................... 15
4.3.4 The Operation and Options of the Business Model ................................................................. 16
5.0 CONCLUSION ........................................................................................................................................ 17
6.0 RECOMMENDATIONS ........................................................................................................................... 17
7.0 REFERENCES .......................................................................................................................................... 17
8.0 APPENDICES .......................................................................................................................................... 18
8.1 APPENDIX 1: LIST OF VETERINARIANS RE-TOOLED IN BOVINE EARLY PREGNANCY DIAGNOSIS IN
HOMA BAY, MIGORI, AND SIAYA COUNTIES......................................................................................... 18
8.2 APPENDIX 2: TABLE OF ANIMALS EXAMINED AT DIFFERENT SITES IN DIFFERENT COUNTIES ...... 19
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EXECUTIVE SUMMARY
The dairy sector in Kenya, and the Eastern African region as a whole, is facing a transitional period that
demands an improvement in breeding strategies aimed at availing more appropriate dairy animals.
Human population growth in the region has underlined an emergent “Livestock revolution” that has
resulted in demand for dairy products. This has stimulated a lucrative market-driven opportunity for dairy
farming resulting in a high demand for good quality dairy animals which is a challenge to meet, yet dairy
is a fast growing and major sub-sector of agriculture in the region. In Kenya, dairy farming and dairy
development activities have traditionally been concentrated in the medium to high potential areas of the
country, mainly in the Rift Valley and Central parts of Kenya. Non-traditional dairy areas have been left
out in dairy development activities yet they have substantial land area and biomass that can support a
vibrant dairy sector. Dairy farming in such areas, as in the rest of the country, may be constrained by a
number of challenges, including availability of good quality feeds, diseases such as East Coast fever (ECF),
and inappropriate breeding strategies. In order to address these challenges, the international livestock
research institute (ILRI) in partnership with County governments in selected non-traditional dairy areas of
Kenya and funding from USAID implemented an accelerated value chain development (AVCD) project to
enhance the livelihoods of the targeted communities through enhanced dairy productivity. Through the
breeding component of the project cattle in Homa Bay, Migori and Siaya Counties underwent hormonal
synchronization and fixed time artificial insemination (FTAI). Veterinarians were to be retooled on early
pregnancy diagnosis and the animals that had been recruited for FTAI examined. For animals found not
pregnant, the possible reason and subsequent reproductive management was to be recommended.
Breeding service delivery business options were to be discussed with the animal health service providers
and developed. Nine veterinarians were retooled on early pregnancy diagnosis in cattle. Two thousand
and seventeen cattle were expected to be examined for pregnancy status. There was a low turnout (34%)
of animals to be examined. Of the 686 animals examined, 196 (28.6%) were pregnant. The pregnancy rate
ranged from 0 to 100% at different crush sites. Overall, the pregnancy rate was highest in Migori County
at 35.6%, and was 24.7 and 24.4% respectively, in Homa Bay and Siaya Counties.
1.0 INTRODUCTION
The extent of dairy cattle farming in the western part of Kenya has been low with potential for
improvement. Hindrances to improved production and productivity of the sector include low adoption of
improved breeding practices. Reproductive efficiency is crucial in enhancement of numbers and
productivity of animals kept. This emphasizes an opportunity for increased production through utilization
of assisted reproductive technologies. Of the assisted reproductive technologies applied globally to
improve reproductive efficiency in livestock, artificial insemination (AI) in dairy cattle is the most widely
used and has had the greatest impact in the improvement of dairy cattle productivity. Incorporation of
estrus synchronization protocols into AI programs make AI more efficient and effective. In the region,
uptake of these technologies has been constrained by high cost and where used, poor pregnancy rates.
Estrus detection is required for successful AI, and the efficiency of detection can be low because it is
influenced by animal, human, and environmental factors. In the absence of estrus synchronization, timing
of the optimal time to inseminate is inaccurate and unpredictable, and the numbers of animals to be
inseminated within a specified time frame is low. The AI technician covers long distances to inseminate a
single animal and charges a lot more for the service to recover costs of operation. The result of this is a
more expensive AI service to the farmer, and when this is coupled with low conception rates, it becomes
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untenable. Fixed time AI protocols result in improved reproductive performance as all the animals are
inseminated irrespective of whether they are seen on estrus or not (Colazo and Mapletoft, 2014).
The local level of development of dairy enterprises, the degree of adoption of Artificial Insemination, the
presence of Artificial Insemination Service Providers and the County Government inclination towards
Dairy will determine which options will succeed in sustaining the needed Public Private Partnership to
grow the emerging dairy systems. To arrive at a working Business model and available options for a
particular area one needs to identify the actors/players, their roles, ascertain their level of involvement
to come up with, and then promote the chosen model and available options through stakeholders’ forum.
2.0 THE CONTEXT
As part of its strategy to improve the livelihoods of livestock keepers, the dairy value chain component of
the AVCD project set out to enhance dairy productivity in 9 non-traditional dairy counties in Kenya. Service
providers were refreshed on AI and retooled on estrus synchronization and application of FTAI protocol
to cattle breeding to accelerate the availability of improved dairy cattle in the counties. Within the
breeding component of the project, two consultants were engaged to deliver contractual services to the
project under the following terms of reference:
1. Retool the service providers on early pregnancy detection and follow-up reproductive
management,
2. Supervise and share with the service providers, the post-synchronization and insemination
evaluations, as part of pregnancy diagnosis and post insemination performance monitoring and
report on these,
3. Recommend and undertake immediate follow-up reproductive cow management actions (i.e. reinsemination, synchronization etc.) on cows found to be not pregnant and the pregnant ones to
ensure that overall performance is optimized,
4. Develop, discuss and draft business options on breeding service delivery modelled around PublicPrivate partnerships in emerging dairy systems for further use in engaging the target counties and
key local breeding service delivery stakeholders.
The expected outputs of the assignment were:
1. A pool of 4 retooled and competent service providers on detecting early pregnancy in cows per
county,
2. Certify the pregnancy status of 2,700 cows bred in Migori, Homa Bay, Siaya and Taita Taveta
counties and provide post-insemination management of the cows to ensure that optimum overall
pregnancy rates are achieved,
3. A population of 2,000 mapped, recruited and inseminated and well managed heifers and cows for
continued monitoring and for enhanced achievement of the set breeding program targets and
goals in the three counties, namely, Migori, Homa Bay, and Siaya,
4. Developed and shared business models and options for breeding and general and related input
and farmer education support services to ensure successful Public-Private partnerships in the
emerging dairy systems.
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3.0 METHODOLOGY
The consultants followed the TORs in the execution of the assignment targeting AI service providers from
Migori, Homa Bay, and Siaya counties.
3.1 Re-tooling Veterinarians on bovine early pregnancy diagnosis
A hands-on refresher training was conducted for veterinarians on early pregnancy diagnosis in cattle.
During the entire duration of the exercise, an animal was first examined by a consultant and then the
veterinarian, or vice-versa, and the findings on the reproductive status of the animal discussed by both to
forge a common interpretation of results. For pregnant animals, the cardinal signs of pregnancy were
evaluated, discussed and reviewed as to when they occur in relation to the stage of gestation. Where
animals were not pregnant, further detailed reproductive examination involving the tubular genitalia and
ovaries was conducted. Prior to reproductive examination of any animal, its body condition was assessed
and scored on a scale of 1 to 5.
3.2 Follow-up reproductive cow management
A discussion was held with each farmer and advice/recommendation made by the consultants together
with the animal service provider on the subsequent management of each animal based on the findings of
its examination.
3.3 Develop, discuss and draft business options on breeding service delivery modelled around
Public-Private partnerships in emerging dairy systems
Discussions were conducted with various dairy stakeholders and Service Providers to arrive at this model
and options after critical analysis.
4.0 FINDINGS, DISCUSSION
4.1 Re-tooling Veterinarians on bovine early pregnancy diagnosis
Nine veterinarians were refreshed hands-on on bovine early pregnancy diagnosis (Appendix 1). Six
hundred and eighty six animals were examined in the three counties (Appendix 2). Of these, 28.6% (196)
were pregnant. The pregnancy rate differed at different sites ranging from 0 to 100%.
Pregnancy rates varied in the three counties as shown in tables 1, 2, and 3 below.
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Table 1. Animals examined for pregnancy following FTAI protocol in Migori County.
SubCounty
Awendo
Kuria
West
Rongo
Total
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Crush Site
No. of
animals
expected
for
examination
Malunga
47
Kuja
63
Manyatta
53
IFAD/Township 10
Kerario farm
11
Naora
43
Kombe
27
Ikerege
37
Lichota
51
Matagaro
37
Kangeso34
Nyandon’g
Chamgiwadu
52
Not identified
No.
examined
No.
pregnant
%
pregnant
%
turnout
21
26
31
5
10
12
23
16
39
10
19
4
15
4
1
6
5
13
7
15
1
5
19
57.7
12.9
20
60
41.7
56.5
43.8
38.5
10
26.3
44.7
41.3
58.5
50.0
90.9
27.9
85.2
43.2
76.5
27.0
55.9
27
8
247
10
2
88
37
25
35.6
51.9
Table 2. Animals examined for pregnancy following FTAI protocol in Homa Bay County.
SubCounty
Crush Site
Kasipul
Koyoo
Kasimba
Kwoyo
Mathenge
Sino
Soko Adongo
Karabok
Nyahera
Karoko
Oriang
Nyaluru
Kaduke
Kokwanyo
Kakelo
Nyangiela
Anjech
Kolundo Alela
Othoro
Kabondo
Kasipul
No. of
No.
animals
examined
expected
for
examination
4
11
4
6
4
26
17
21
16
11
35
16
53
41
24
50
7
50
30
14
31
16
No.
pregnant
%
pregnant
0
2
3
2
2
2
4
4
12
7
7
6
3
0
50
75
11.8
9.5
18.2
25
9.8
50
100
23.3
42.9
18.8
14
67
4
7
1
1
67
40
16.7
14.2
33.3
24.7
10
42
7
3
271
19
Total
%
turn
out
36.4
66.7
65.4
68.8
45.7
77.4
14.0
60.0
51.6
71.4
62.7
15.8
Table 2. Animals examined for pregnancy following FTAI protocol in Siaya County.
Sub-County
Alego Usonga
Crush Site
Kamagoye
Ndere
Nyalgunga
Gem
Nango
Omindo
Kodero
Kosoro
Ugenya/Ugunja Awendo
Jera
Murumba
Uria Magoya
Total
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No. of
animals
expected
for
examination
14
39
24
21
26
22
15
29
38
No.
examined
No.
pregnant
%
pregnant
%
turn
out
8
30
14
5
10
16
18
19
14
16
18
168
4
4
2
2
0
6
6
5
5
2
5
41
50
13.3
14.3
40
0
37.5
33.3
26.3
35.7
12.5
27.8
24.4
57.1
76.9
58.3
47.6
61.5
86.4
93.3
55.2
47.4
Migori had the highest pregnancy rate at 35.6, with Homa Bay and Siaya having 24.7 and 24% respectively.
Fixed-time AI protocols, as that used in the current project, in lactating dairy cattle have resulted in
pregnant rates similar to those of AI after estrus detection (Pursley et al., 1997; de La Sota et al., 1998).
However, conception rate may be lower when such protocols are used, as ovulation may not be
adequately synchronized in about a third of treated animals, a small proportion (11%) may ovulate before
the FTAI, few (15%) may not respond to PGF2α, whereas some (9%) may not ovulate after the second
GnRH (Colazo et al., 2009). Cumulatively, the synchronization rate is thus about 68% (Colazo and
Mapletoft, 2014). Considering a services to conception rate of 1.6 (the recommended interference level
reproductive index) together with a synchronization rate of 68%, a 42.5% conception rate would be
expected on animals on FTAI. In the current project the pregnancy rate ranged from 0 to 100%. Various
factors may account for the differences seen. Most critical in the current project was the nutritional status
of the recruited animals (Pictures 1, 2 and 3). Migori County had a more established dairy culture with
more awareness on AI compared to the other two counties. The animals in the county were better fed
and managed than in the other counties. Indeed, one of the sites used in Migori was an upcoming dairy
farm (Kerario), where the animals were semi-intensively raised with adequate forage and mineral
supplementation. On this farm, the turn out rate of the animals was 90.9% with a pregnancy rate of 60%.
One of the animals had even conceived on sexed semen, which the owner had insisted on during
insemination, which has lower conception rates compared to conventional semen. The one animal that
was not examined had been seen on heat and taken to a bull for service. A number of the non-pregnant
animals were cycling as evidenced by a corpus luteum on one of the ovaries. Overall, the animals in Homa
Bay and Siaya Counties were in a poor nutritional status as evidenced by the body condition score. None
of the crush sites in Siaya even achieved a pregnancy rate of 42.5% or above. Many farmers indicated that
feed was a challenge and that they did not supplement the animals with balanced mineral salts. Most of
these animals were found to be anestrous on ovarian palpation, with many having small ovaries. Such
ovaries are unlikely to respond to ovarian stimulation. It is unlikely animals in poor body condition and
small ovaries responded to the FTAI, thus accounting for the low pregnancy rate in these counties.
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Picture 1. A cow in good nutritional status (BCS 3.5) that was found to be pregnant after FTAI.
Picture 2. A cow in good nutritional status (BCS 3.0) that was found to be pregnant after FTAI.
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Picture 3. A cow in poor body condition (BCS 2) that was found non-pregnant after FTAI
A low animal turnout for examination was also of concern as it blurred the accurate outcome of the FTAI.
Some farmers (for example in Kirind, Siaya) indicated that they did not avail their animals because they
were sure that they had conceived to the FTAI, whereas others (for example Murumba, Siaya) indicated
that the animals had come on heat and were taken to the bull for service. According to most farmers, the
protocol resulted in animals that had previously not been seen on heat manifesting heat signs. It is thus
plausible that the hormones jump-started cyclicity in a number of animals, besides the protocol
establishing a keenness in the farmers to observe for heat.
4.2 Follow-up reproductive cow management
The general advice to the farmers was that dairy animals require sufficient input (good quality and
quantity of feed) to give outputs (calf and milk). Farmers were advised to ensure that their animals were
well fed with good quality feed and water and supplemented with balanced mineral salts. It was impressed
upon the farmers that only animals in good body condition would come on heat, conceive to insemination,
carry the resulting pregnancy to term, calf with little problems, and produce sufficient milk.
For the animals that were not pregnant but cycling, it was agreed between the farmers, consultants, and
service providers that:


Where such animals showed overt signs of heat and AI services were accessible to the farmers,
an AI technician would be contacted to inseminate the animals based on the conventional am/pm
rule,
Where a significant number of such animals had a corpus luteum on the ovaries and the farmers
wanted to reduce the days open, such animals would be synchronized using PGF2α and be
inseminated on observed heat (48 to 72 hours later) to increase the number of animals that an AI
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
technician would inseminate within the scheduled time to reduce the number of injections and
cost per insemination,
Where a number of animals were acyclic or cycling and were in good body condition, a number
of farmers would come together and have their animals put on the FTAI protocol by a group of AI
technicians for an increased service rate while eliminating the need for heat detection to schedule
the AI and cut down on the cost of AI.
4.3 Business model and options for successful Public-Private partnerships in the emerging
dairy systems
4.3.1 Identified actors/players to sustain the dairy sector
 Farmers
 AI Services Providers
 The County Government
 Agro Vets (Inputs Producers and Suppliers)
 Kenya veterinary Board (KVB) and its Agents
 Kenya Livestock Breeders Organization(KLBO)
 Kenya Dairy Board
 Transporters
 Consumers/Market
 Financial Institutions
 Cooperative Societies and Self Helps Groups
 Coolers (Cooling Services Providers)
 Processors
4.3.2 Roles
4.3.2.1 Farmers
 Proper maintenance and management of the cows
 Call the Technician promptly
 Pay the Technician promptly
 Be able to provide required inputs e.g. Hormones, ear tags, supplements, dewormers etc. for
their animals
 Link the Technician to other farmers
 Avail the animals that need AI service for service
 Provide infrastructure (crushes) for serving the cows
 Avail themselves for training to acquire knowledge (extension messages)
 Keep proper cow pertaining to health, breeding, management and production
 Invest in Dairying as a Business
4.3.2.2 Technician (vets, AHA/AI services providers)
 Be available to offer services promptly and professionally
 Offer extension services to the farmers
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





Know and understand the market, type of farmers, their breeding objectives, type of cows, semen
from which bulls would achieve the goals.
Upgrade himself/herself continuously professionally
Keep records for his business (farmers, cows, semen used, financial etc.)
Offer his/her services as a business
Deliver reports to relevant authorities as required
Solicit for business from the farmers/cooperatives on contractual basis and seek to work as a team
for maximum impact and coverage
4.3.2.3 County government
 Provide Infrastructure and amenities
o Roads
o Milk coolers
o Electricity
o Water
 Laws and Policies that support business environment
 Policies to promote private sector growth
 Collaborate with actors/Development Partners and others that promote livestock business i.e.
Promote and nurture Public Private Partnerships
 Provide seed capital to jump start some identified areas in dairy business e.g. Provision of liquid
nitrogen, liquid nitrogen tanks, AI kits and semen.
 Promote formation of(dairy)Cooperatives
 Promote Dairying as a Business
 Capacity building/extension services
 Disease control
o Vaccinations
o Control of livestock movement
o Administration of livestock auctions
4.3.2.4 Agrovets/inputs producers & suppliers
 To stock good quality and relevant inputs (semen, drugs, implements, feeds, minerals)
 Offer extension services
 Maintain records/inventory of products and services delivered-verifiable on demand
 Offer quality services (AI clinical, herd health etc)
4.3.2.5 Kenya Veterinary Board (KVB) and its agents
 Monitor and ensure quality services are provided
 Monitor and ensure quality products are offered
 License Services Providers and their premises
 Eliminate quacks(unqualified service providers)
 Organize supportive continuous professional development ( CPD) workshops
 Regulate training institutions
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4.3.2.6 Kenya Livestock Breeders Organisation (KLBO)
 Promote and actively register animals according to their breeds
 Avail more Breeds Inspectors to offer registration services
 Promptly provide registration certificates and milk records in liaison with Livestock Recording
Centre
 Embark on training more inspectors in the Counties to devolve this service.
4.3.2.7 Transporters
 To provide prompt and appropriate transportation services to maintain quality and animal
welfare.
- For inputs
- For livestock(poultry, dairy cattle, beef cattle, shoats etc)
- For livestock products(milk, milk products, beef, mutton ,eggs, hides and skins etc)
4.3.2.8 Consumers/market


Demand/purchase/consume products of known quality and standards at prices that sustain the
dairy industry in the area.
Be constantly aware and conscious of quality and product standards.
4.3.2.9 Financiers


To offer livestock /dairy friendly and affordable credit
Training on Financial Management skills to Cooperatives and other farmer groups
4.3.2.10 Cooperatives/self-help dairy groups etc.












Recruit more members for sustainability
Provide required services and products on check-off system
Contract for services and products on check off system to the members
Organize farmers trainings or provide extension services
Provide affordable credit to farmers
Offer collection and cooling services to farmers.
Provide appropriate containers for collection and transportation of milk.
Do product marketing for the members
Carry out Value Addition
Pay farmers promptly and fairly
Operate as a Business Hub to attract and retain members due to variety of inputs, services leading
to increased productivity and value for money.
Maintain records: Membership ,Transactions, products, inputs, services, minutes, financial
reports and activities for transparency
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4.3.2.11 Processors








Provide processing facilities
Pay farmers/Cooperatives promptly and fairly
Pay for milk not only on volumes but also based on quality
Provide cooling facilities
Provide transport from cooling facilities to factory
Offer extension services
Provide milk quality testing services
Engage actively in breeding objectives in line with what the market demands
4.3.2.12 Cooler services



Offer cooling service at a fair fee
Provide transport from farm gate to Cooler
Provide transport from Cooler to processing Plant
4.3.2.13 Kenya Dairy Board




Provide regulatory policies to the industry
License transporters,cooling plants and processors
License milk traders and milk outlets
Offer training for milk handlers, plant operators and processors
4.3.2.14 Development partners






Provide seed investment for sustainable business
To catalyze extension services
Develop capacity for good corporate governance
Promote sustainable business conduct and culture
Offer assistance and support which do not create dependency syndrome.
To have a platform among themselves to harmonize their approaches to avoid confusion, mixed
messages, duplicity and donor fatigue.
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4.3.3 Diagram of Business Model & Options
FARMERS
KLBO
TECHNICIANS
VETS, AHAS,
LPO, AI,SPS
KDB
COUNTY
GOVERNMENT
DAIRY
COOPERATIVE
SOCIETY OR
SELF HELP
GROUP
Development
partners
AGROVETS & AI
SERVICE
PROVIDERS
FINANCIERS
KVB
TRANSPORTERS
CONSUMER
/
MARKET
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PROCESSOR
COOLING PLANT
4.3.4 The Operation and Options of the Business Model
In Migori, Siaya and Homa Bay Counties, the identified actors play their roles to varying levels and different
intensities. There is general lack of appreciation of each other’s role which needs to be addressed at
special stakeholder forums within designated localities.
The presence or absence of a Dairy Cooperative Society or a Dairy Group in a Sub location ,Location, Ward,
Sub county or County will determine the entry point and amount of effort required to get the Business
model working.
It is our considered view that the business model which will work should be around a functional and
effective Dairy Cooperative Society or Dairy Group. The Society or Group will gather the farmers together
for training and help them access inputs in bulk, services in groups and collect their milk, cool it, process,
value add in any other way and then market jointly to benefit from economies of scale and benefit from
their sheer numbers and being organized.
The inputs and services can be obtained from the providers through an arrangement negotiated by the
Cooperative Society or Dairy Group paid for via a check off system from the members. This will ensure
availability of inputs and services all the time to the members hence improving efficiency and productivity.
The Cooperatives or Dairy Groups also have an option of offering the inputs and services directly having
employed Service Providers, acquired stores and inputs to have the Society or Group operate as a one
stop Business Hub providing bundled services paid for by retaining part of farmers’ dues from their milk
earnings.
The Cooperative Society or Dairy Group may also offer cooling, transport and other value addition services
at a fee deductable from their earnings at the end of the month.
Other options would be to contract the various Service Providers for breeding services, registration
services, clinical services, herd health, transport, cooling and pay on behalf of the members and deduct
from their dues.
The Cooperatives or Groups could also arrange for affordable credit for its members from financiers
working from the membership strength and get appropriate products for them with better terms.
The Development Partners can work with the Cooperative Societies or Dairy Groups to build capacities in
areas of corporate governance, adherence to cooperatives culture, good business practices, transparency
and accountability.
They can also provide seed funding for putting systems in place to facilitate other business operations
The Partners can also offer assistance in boosting cold chain infrastructure and assist in areas to foster
adherence to quality and market access.
The County Government to promote private public partnership by creating enabling environment through
business friendly policies and laws.
16 | P a g e
The County Government should provide infrastructure such as roads, electricity and disease control
mechanisms.
Also promote formation of cooperative societies provide cold chain, provide initial semen, liquid nitrogen
and personnel daily subsistence allowance to start off the massive dairy improvement program.
The Technicians need to work as a team and solicit for contractual arrangement with the Cooperatives or
Dairy Groups to offer their services to the farmers through a central system. In the initial stages they need
to recognize that all other allied activities promoting AI or dairy enterprises is growing demand for their
services and hence growth of their businesses. So they must be prepared to go the extra mile to promote
these efforts even if it means charging low but sustainable fees at the beginning of this venture.
5.0 CONCLUSION
The FTAI system is applicable in upgrading of local cattle for dairy production. However, the animals need
to be in good nutritional status for optimum pregnancy rates to be achieved.
6.0 RECOMMENDATIONS


The criteria for recruitment of candidate animals for FTAI should be strictly adhered to,
especially as relates to the nutritional status of animals. Recruited animals should at least
approaching a body condition score of 2.5 and on a rising plane of nutrition.
Inseminated animals should be checked for pregnancy as early as possible (6 to 8 weeks) after
the insemination for reproductive intervention in non-pregnant animals to reduce days open.
7.0 REFERENCES
1. Colazo, M.G. and Mapletoft, R.J. (2014). A review of current timed-AI (TAI) programs for beef and
dairy cattle. Can. Vet. J., 55: 772-780.
2. de La Sota, R.L., Risco, C.A., Moriera, F., Burke, J.M. and Thatcher, W.W. (1998). Evaluation of
timed insemination during summer-heat stress in lactating dairy cattle. Theriogenology, 49: 761770.
3. Pursley, J.R., Wiltbank, M.C., Stevenson, J.S., Ottobre, J.S., Garverick, H.A. and Anderson, L.L.
(1997). Pregnancy rates per artificial insemination for cows and heifers inseminated at a
synchronized ovulation or synchronized estrus. J. Dairy Sci., 80: 295-300.
17 | P a g e
8.0 APPENDICES
8.1 APPENDIX 1: LIST OF VETERINARIANS RE-TOOLED IN BOVINE EARLY PREGNANCY
DIAGNOSIS IN HOMA BAY, MIGORI, AND SIAYA COUNTIES
Name
Dr. Ruth Origa
Dr. Eric Were
Dr. Ibrahim Moses Muchule
Dr. Erick Orimbo
Dr. Mark Otieno
Dr. Argwings Milan
Dr. Owade
Dr. Steve Odhiambo
Dr. Wambongo
18 | P a g e
Sex
Female
Male
Male
Male
Male
Male
Male
Male
Male
County
Migori
Migori
Migori
Migori
Siaya
Siaya
Siaya
Busia
Busia
8.2 APPENDIX 2: TABLE OF ANIMALS EXAMINED AT DIFFERENT SITES IN DIFFERENT
COUNTIES
County Sub-County
Crush Site
Homa
Bay
Koyoo
Kasipul
No.
No.
expected for examine
examinatio
d
n
4
0
0
%
Tur
n
Out
11
4
2
50
36.4
Kwoyo
6
4
3
75
66.7
Mathenge
26
17
2
11.8
65.4
21
2
9.5
Soko Adongo
16
11
2
18.2
68.8
Karabok
35
16
4
25
45.7
Nyahera
53
41
4
9.8
77.4
118
19
16.1
24
12
50
Total
Karoko
Oriang
50
7
7
100
14.0
Nyaluru
50
30
7
23.3
60.0
14
6
42.9
Kaduke
Kokwanyo
Kakelo
31
16
3
18.8
51.6
Nyangiela
14
10
4
40
71.4
Anjech
67
42
7
16.7
62.7
7
1
14.2
3
1
33.3
Total
153
48
31.4
County Total
271
67
24.7
Kolundo Alela
Othoro
Migori
%
pregnan
t
Kasimba
Sino
Kabondo
Kasipul
No.
pregnan
t
Awendo
19 | P a g e
19
15.8
Malunga
47
21
4
19
44.7
Kuja
63
26
15
57.7
41.3
Manyatta
53
31
4
12.9
58.5
Kuria West
29.5
10
5
1
20
50.0
Kerario farm
11
10
6
60
90.9
Naora
43
12
5
41.7
27.9
Kombe
27
23
13
56.5
85.2
Ikerege
37
16
7
43.8
43.2
Lichota
51
39
15
38.5
76.5
105
47
44.8
Matagaro
37
10
1
10
27.0
KangesoNyandon’g
34
19
5
26.3
55.9
Chamgiwadu
52
27
10
37
51.9
8
2
25
Total
64
18
28.1
County Total
247
88
35.6
Not identified
Siaya
23
IFAD/Townshi
p
Total
Rongo
78
Alego Usonga
Kamagoye
14
8
4
50
57.1
Ndere
39
30
4
13.3
76.9
Nyalgunga
24
14
2
14.3
58.3
52
10
19.2
5
2
40
Total
Gem
Nango
Omindo
21
10
0
0
47.6
Kodero
26
16
6
37.5
61.5
18
6
33.3
49
14
28.6
Kosoro
Total
Ugenya/Ugunj
a
20 | P a g e
Awendo
22
19
5
26.3
86.4
Jera
15
14
5
35.7
93.3
Murumba
29
16
2
12.5
55.2
Uria Magoya
38
18
5
27.8
47.3
Grand
Total
Total
67
17
25.3
County Total
168
41
24.4
Grand Total
686
196
28.6
21 | P a g e

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