Artificial Insemination Service Delivery System in the Ethiopian Dairy Industry: Evaluation of Semen Supply Chain and Quality

dc.contributor.advisorDr. Ashenafi Mengistu, Dr. Diriba Geleti
dc.contributor.authorKassahun, Melesse
dc.date.accessioned2020-11-05T10:41:39Z
dc.date.accessioned2023-11-08T11:33:05Z
dc.date.available2020-11-05T10:41:39Z
dc.date.available2023-11-08T11:33:05Z
dc.date.issued2020-06
dc.description.abstractA study conducted in Amhara, Oromia, Southern Nations Nationalities and Peoples (SNNP) and Tigray regional states of the country to contribute to increased dairy cattle productivity through providing information on the prevailing AI service delivery and input supply system; and major challenges & opportunities in the AI service delivery system. The research was mainly undertaken using a questionnaire survey, key informants’ interview and focus group discussions. Data on-field performance of AI technicians in the study regions received directly from AI technicians using a structured reporting format from October 2016 through December 2018 to evaluate the actual performance of AI technicians. A follow-up calving survey for AI services provided to farmers was conducted in March 2019 to better understand the performance of AI technicians in terms of conception and calving rates. Secondary data on livestock and livestock characteristics from agricultural sample survey reports of the Central Statistical Agency (CSA) were taken from 2004/05 to 2017/18 to analyze the trend of cattle population in the country. A total of 588 sample straws of semen were collected from production, storage, distribution, and end-users (AI technicians) in the four study regions and National Animal Genetic Improvement Institute (NAGII) and analyzed for their motility and morphology using Computer Assisted Semen Analyzer (CASA). With the current growth rate of indigenous (3.7%) and cross breed (15.8%) cattle population of the country will reach to 121.2 million and 5.4 million, respectively in 2029/30. The CSA data demonstrated that the proportion of crossbred and exotic cattle population from the total population in Ethiopia is less than 2 percent with an average percentage of 1.07% for the last thirteen years. There was an increase of only 1 billion liters without change in lactation length (6 months) but with an increase of only 0.138 liters/day/cow over the last thirteen years since 2004/05. The engagement of women in the AI delivery system increased in 2017/18 from 1.8% to 7.2%. About 42% of the total AI technicians considered in this study trained for 45 days while xxii the other 22%, 32%, and 7% trained for a period of three, six and nine months, respectively. AI technicians in the four study regions served as AI technician for an average of 8.17 years. About 88% and 75% of AI technicians in the four regions reported ready access to LN2 and semen, respectively. About 96% and 89% of AI technicians in the studied regions were providing AI service at their respective woreda/kebele and farm gate, respectively. However, about 56% and 31% of farmers in the four regional states participated in this study reported that they got insemination services only at woreda/kebele crushes and at their farm gate. Significant difference (p<0.05) observed among regions in the number of kebeles assigned per AI technician with an average of 8 kebeles, 199 potential farmers who need the service per kebele but 92 farmers (46%) who were getting the service. The thawing temperature reported by AI technicians was significantly different (p<0.05) among regions with average thawing temperature of 35.7OC. Months from August to December were categorized as peak season when AI technicians on average provided 6.7 inseminations per day. January, February, June, and July were categorized as regular season for AI service when AI technicians provided daily average insemination of 3.8. March, April, and May are off-season for AI service when on average only 2.2 inseminations per day were provided. Field level actual performance data also showed significant difference (p<0.05) in the number of inseminations provided per AI technician per month among regions and between male and female AI technicians with an overall average insemination of 39.3. The SPC reported by AI technicians was not significantly different among regions (p>0.05) with mean SPC of 2.13. About 2.6 SPC obtained from a follow-up survey conducted with farmers who received AI service in a specified period. The result of post-thaw total motility, progressive motility, normal and defective morphology of semen samples taken from studied regions showed significant difference (p<0.05). The overall average total and progressive motility percentage of semen samples taken from the four studied regions were 38% and 28%. Similarly, the normal morphology of semen samples taken from these regions was 77%.en_US
dc.identifier.urihttp://etd.aau.edu.et/handle/123456789/23042
dc.language.isoenen_US
dc.subjectArtificial inseminationen_US
dc.subjectCattleen_US
dc.subjectFarmersen_US
dc.subjectRegionsen_US
dc.subjectSemenen_US
dc.subjectTechniciansen_US
dc.titleArtificial Insemination Service Delivery System in the Ethiopian Dairy Industry: Evaluation of Semen Supply Chain and Qualityen_US
dc.typeThesisen_US

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