Sustainability of dairy cattle breeding systems utilising artificial insemination in less developed countries - examples of problems and prospects (original) (raw)
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Executive summary This paper was aimed to review significance of artificial insemination in genetic improvement of dairy cattle in Ethiopia: achievement and challenges including, trends of artificial insemination service in Ethiopia, merit and demerit of AI, major factors that affect the efficiency of AI mating system, breeding objectives, traditional selection practice of farmers, estrus detection and time of insemination, to assess problems and constraints associated with the AI service in Ethiopia, and the gaps that exist in Ethiopia. There is no such a satisfactory cattle’s breeding system and reproduction performance in the country in general and particularly at the farmers’ level. More farmers practiced natural, unplanned and uncontrolled mating system. Communal grazing land is the main source of breeding bull in most part of Ethiopia with exception of few AI service. Therefore, in Ethiopia, there is a need to use breeding objectives in line with vibrant and effective breeding policies for both AI and natural service for sustainable and effective animal breeding practice. Cows and heifers become fail to conceive with various factors including management failures, nutritional status, postpartum reproductive health, semen quality and other miscellaneous factor and hence reduce efficiency of AI service. Mainly heat detection skill by farmers and timing of insemination are the major factors that determine the success and failure of AI programme. Besides, breeding records such as breeding dates, pregnancy rates and days to first service used to monitor fertility are other advantages of breeding practices that should be given attention. Equally, importance, genetic conservation should not be underestimated in improving dairy cattle. In conclusion, animal breeders, policy designers and any development practitioners have to give due attention to transform the existing agrarian breeding practices targeting towards dairy productivity and production with careful consideration of genetic conservation of local cattle breeds. Key words: reproduction performance, breeding records, genetic conservation, Breading Practice, Efficiency of AI, Ethiopia
The study was conducted before the ignition (before October 2020) of the war in Tigray Region, Ethiopia. Artificial insemination (AI) is the first generation biotechnology and is one of the assisted reproductive techniques (ART) that greatly plays for a faster genetic improvement of farm animals. Though AI was implemented in cattle crossbreeding for many decades in Ethiopia, there is quite insignificant national output of crossbred cattle population (1.54 %). The aim of the survey was to assess the efficiency of AI service in cattle production in the Western Zone of Tigray Region, Ethiopia. Twenty (20) Kebeles and 353 small-scale farmers were purposively involved in the household face-to-face survey interview. The data were analyzed using Statistical Package for Social Sciences (SPSS), and summarized by mean, frequency and percentages. The survey indicated that the existing reproductive efficiency of cattle AI service in the Western Zone of Tigray Region, Ethiopia was extremely poor. The mean number of services per conception (NSC) was very high that could be due to mainly inappropriate heat detections. The recommended, acceptable and excellent grade of NSC fall in the range of 1 − 1.7. The overall conception rate at first insemination (CRFI) was also very poor (20.4 %) and thus calving rate (CR) was poor (20.5 %). About one-third (33.4 %) of the respondents indicated that cows and heifers exhibited heat in 0:01 − 6:00 am of the day. About 30.9 % and 28.6 % of the respondents reported that their cows and heifers were inseminated in 9 − 12 hours and 4 − 8 hours after the onset of heat, respectively. The majority (70.8 %) of the respondents did not practice controlled mating and breeding, and the first preference of 50.1 % of the respondents was natural mating. The most common source of bulls for about 34.3 % of the respondents was from neighbors and followed by own bred bulls (30.0 %). Cattle AI feasibility study and identification of AI strategic interventions should be the first focus to improve the existing poor AI efficiency of the study area.
smart development works, 2013
We conducted a study which, in summary, was to review the status of breeding programmes in the smallholder dairy sub-sector in Zimbabwe and deliver the following outputs: An aide memoire of not more than 5 pages outlining initial findings based on literature review and consultations with a few stakeholders and experts. This is to be delivered within two weeks of the start of the study. Recommend and rank the most promising dairy breeding models in terms of meaningful smallholder participation and private sector appetite to develop the breeding programme. Develop a dairy breeding framework and identify primary/support services and enabling environment precedent to its actualization. Propose a programme design that would address the issues identified in the studies. Consistent with terms of reference, based on initial visits to Marirangwe Milk Collection Centre and key informant interviews, particularly the Dairy Development Program (DDP), we previously submitted the aide memoire (inception report). We then conducted further work at 6 milk collection centres (MCCs): Guruve, Mushagashe-Hamaruomba, Nharira, Rusitu Mayfield, Tsonzo, and Umzingwane. Rusitu-Mayfield and Tsonzo (in Manicaland Province) were selected from among the best MCCs, Nharira (in Mashonaland East Province), and Mushagashe (in Masvingo Province) were selected from the middle performance tier, while Umzingwane (in Matebeleland South Province) and Guruve (in Mashonaland Central Province) were regarded as least-performing MCCs. We conducted household surveys, key informant interviews (KIIs) and focus group discussions (FGDs) at each MCC. For the household survey, a questionnaire was distributed to men and women at each MCC. Overall, the respondents comprised 36% women and 64% men. The youth (under 35 years of age) made up 20% of the respondents. The KIIs were also with key government, private sector, and development agents involved in the smallholder dairy subsector. The household surveys sought data on statistics including membership of MCCs, milk production and sales, cow productivity, cattle breed distribution across the MCCs, extension and financial support services, breeding methods and technologies, current breeding models, and farmer knowledge. The KIIs with senior government representatives explored existing policies on smallholder dairy sub-sector breeding programmes support. Focus group discussions were held at MCCs in order to triangulate the findings from the household surveys and to address other issues of a general nature. Data was analysed using the Statistical Package for Social Sciences (SPSS). The findings were analysed using the breeding pillars (presented in the inception report) analytical framework. Based on our findings and analysis, MCCs have low membership that does not provide adequate critical mass for self sustaining breeding programmes. The average number of milking cows across breeds per MCC (440 cows) is not adequate for a viable breeding programme that is AI-based. A cow herd of at least 1000 will be required for economies of scale to engage AI service providers. Milk production per cow is low and it is still below 10 litres per day even for the purebred dairy cows. This demonstrates substantial scope to improve production largely through improved feeding and reproductive management. Feeding is not adequate in most herds with most farmers neither conserving feeds for feeding during the dry season nor having sufficient access to concentrate feeds. Calving intervals are still too long resulting in about 50% of the cows calving each year. Lactation lengths are still short at 5.3 ± 2.0 months and 8.1 ± 1.9 months for local and purebred cows, respectively. There is a large array of breeds dominated by the local Mashona breed and largely crossbreds of Brahman, Jersey, Red Dane, and Holstein-Friesian. About 90% of the farmers use bulls (natural service) to breed their cows. Unlike in similar dairy schemes in other countries, AI use is low (10% of respondents). xii This is probably a consequence of inadequately developed AI infrastructure, lack of knowledge on AI by the farmers, and the relatively high cost of AI. Other breeding technologies including heat synchronized AI have not been widely used, and results from the few cases when it was used were unsatisfactory. There are virtually no existing or previous well-defined breeding models for smallholder dairy farms, but it is clear that they were largely anchored on bull schemes. Sire cow breeds acquired by smallholder farmers were not chosen by the farmers but depended on availability and what was provided by funding agents. While some cattle acquisition projects partly succeeded, most were criticized for reasons including failure to prescribe the quality of animals distributed, lack of supplied animal records, stringent cattle finance loan repayment conditions, and failure to provide ancillary support services to improve cow survival. Future cattle acquisition programmes should take into account farmer choices and have feasible,realistic repayment conditions. Key breeding technologies including AI, synchronized AI, sexed semen use, and embryo transfer have not been adequately exploited. In most progressive dairy programmes in developing countries, AI has been the engine for improvement of cow productivity while synchronized AI has been a tool for massive introduction of new genetics in cattle reared under communal grazing systems. Sexed semen can also offer cost-effective opportunities to grow the female cattle herd instead of solely relying on imports. When these technologies are supported through appropriate policies and financing including government subsidies, they can be terminally employed on a large scale and create large dairy herds that provide economies of scale for a sustainable smallholder dairy sector. To create a basis for implementing the smallholder sub-sector breeding programme, we have developed a breeding framework and programme design that has five components with the overall goal of increasing income of smallholder dairy farmers through cow productivity improvement. The five components are: Developing breeding programme clusters for efficient delivery of breeding services; setting up breeding infrastructure and cattle supply structures; implementing reproductive performance improvement of existing smallholder farmer herds programme; establishing cattle breeding and multiplication farms to enhance dairy cattle supply; and building or strengthening institutions and developing policies for breeding programme support. In addition, we suggested breeding models that could be applied in the smallholder dairy sub-sector that are developed in the context of available key resources and feasible breeding methods (e.g., synchronized, ordinary AI, or natural breeding). For example, to this end, we propose a model for communal grazed herds in which we recommend synchronized AI using dual purpose and Jersey breeds, and use of the resulting crossbred bulls in future mating programmes. We have addressed a key concern about breed combination in crossbreeding programmes. In this regard, in our view, the limited availability of dairy cattle does not offer much choice to the farmer other than getting what is available. However, sire breed choice would be feasible with AI. For sire breed choice we would recommend dual purpose and the Jersey breeds for farms in relatively dry areas and with low feed resources. Farms with abundant resources, particularly feed and good support services can use virtually the whole breed range including the Holstein Friesian
Artificial insemination : A tool to improve livestock productivity
2018
Artificial insemination (AI) is the manual placement of semen in the reproductive tract of the female by a method other than natural mating which is one of a group of technologies commonly known as “assisted reproduction technologies” (ART), whereby offspring are generated by facilitating the meeting of gametes (spermatozoa and oocytes). AI is by far the most common method of breeding of intensively kept dairy cattle. In developed countries, advances in artificial insemination have already had a major impact on livestock improvement programmes. AI speeds up genetic progress, reduces the risk of disease transmission and expands the number of animals that can be bred from a superior parent. The acceptance of AI technology worldwide provided the impetus for developing other technologies, such as cryopreservation and sexing of sperm, estrous cycle regulation, and embryo harvesting, freezing, culture and transfer, and cloning.
Research Horizon, 2022
The study was conducted in Sayo district with the objective of assessing challenges and opportunities of artificial insemination on dairy cattle, to document potential opportunities of artificial insemination, to identify the challenges of artificial insemination and to assess the perception of farmers on the AI technology in the study area. Three kebeles, three were taken purposively and 20 households from each kebele were randomly selected. The data were collected using semi structured questionnaires, interview and direct observation. The reproductive and productive data were analysed statistical software (SAS version 9.3.1 where as other data were analysed by simple descriptive statistics. The result of this finding shows that the overall mean of daily milk and lactation length of dairy cows in the Sayo distinct were5.83+0.82L and 240+18.43 days respectively whereas the overall mean of age at first calving, calving interval and number of services in the study area were 968.42+269...
Community Breeding Practice and the Challenges in Dairy Cattle Management in North Gondar, Ethiopia
— Dairy product is an important feed supplementation. However, rearing dairy cattle is became a challenge especially at smallholder level due to lack of indigenous dairy cattle breeds. As a result, the country has established cross breeding program since 1990`s. Nevertheless, it is not uniform and does not consider smallholder farmers. Therefore, this research initiated to identify the breeding practice and the main challenges of smallholder farmers in rearing dairy cattle. For this purpose, first systematic field survey was conducted to generate preliminary information and breed judgment. Then two study areas were selected purposively based on milk production potential and dairy breed characteristics. Two focus group discussions per study area were conducted. Then, randomly 200 respondents per study area were selected. Finally, individual interview and field observation were employed to generate the needed data. Even though there is no established breeding scheme, the smallholder farmers practiced breed improvement by either cross breeding or straight breeding. They implemented Cross breeding to improve milk productivity using 50-100% exotic blood sire/semen. Pure exotic semens were preferred for AI (Artificial insemination). The smallholder framers do not select indigenous caw for cross breeding practice. However, they selected indigenous caw/heifer for replacement based on pedigree history, body stature, and udder vein. Regarding mating system, more than 50% of the respondent exercise control-mating system in their herd. Mostly this was done by pertaining the sire and dam together for a single day. In addition to this partiality in preference of sire, less productive individual cattle culled from the herd by castration, sell and slaughtering. The management system, early castration and lack of accurate estrus detection were the major challenges in dairy cattle development. As the result of this survey in the two study areas, indiscriminate cross breeding without consideration of the production system, body size and blood levels were predominant. Therefore, successive training for smallholder farmers on breeding system is highly recommended.