Profile and artificial insemination practices of technicians and the artificial insemination success rates in Leyte, Samar, and Biliran, Philippines (2011-2015)

Uterine tone influences fertility of Merino ewes following laparoscopic artificial insemination

Artificial insemination (AI) plays a critical role in facilitating rapid genetic and production gains within the sheep industry. However, variable rates of AI success remain a concern for the industry and a barrier to adoption. Furthermore, the degree to which female factors influence the success of intrauterine laparoscopic AI rather than natural mating remains unknown. As such, this study investigates the effect of several factors collected during the time of AI, on the success of intrauterine laparoscopic AI. Data was generously donated by artificial breeding companies and stud breeders during routine commercial AI operations. AI data was collected over 3 breeding seasons during commercial AI programs (N = 24 programs) using Merino ewes (N = 24,700). Sire ID (N = 253), time of AI following progesterone removal (approx. 43-59 h post removal), uterine tone and intra-abdominal fat (both scored 1-5) as well as age of the ewe were all recorded at the time of AI. Transcutaneous ultrasound subsequently determined pregnancy rate approximately 55 days post-AI. A multivariate regression analysis was performed and revealed pregnancy success to increase when semen was inseminated into a ewe with a uterine tone score of 4 or 5 (P < 0.001). The remaining factors fell short of significance within the multivariate model. An interclass coefficient variation matrix was also used to determine the proportion of variation contributed to AI success by random factors allocated in the model; site, sire, AI date and breeding season (45.99 %, 29.94 %, 15.15 % and 8.92 %, respectively). These results highlight the influence of uterine tone on ewe fertility following laparoscopic AI, but also that program location and the sire used can further modify this influence on pregnancy rate. These factors must now be considered in combination with semen factors per individual sire used during AI to ascertain the contribution of several factors to the success of laparoscopic AI in Australia.

Adoption of scientifically recommended artificial insemination practices by paravets: a depiction of current scenario of four states in India

The present investigation was done to assess the different practices followed by the AI technicians (paravets) while performing artificial insemination (AI). A total of 160 paravets were selected for the study having equal representation from 4 different states of India (Gujarat, Rajasthan, Telangana, and Odisha). Questionnaire and telephonic survey were used for collecting data. Several practices followed by paravets were assessed under three sub-groups, viz., practices followed prior to, during, and post-artificial insemination. In as many as seven practices, viz., gathering pre-AI information, storage of semen straw, time of performing AI, thawing container, wiping of semen straw, cutting of semen straw, and record keeping, the adoption gap was found to be nil. Maximum adoption gap (30.60%) was seen in "adopting basic sanitary measures," whereas about 13% of adoption gap was found in the case of "monitoring of heat post calving" followed by "checking of heat prior to AI" (8.00%). Hence, along with provision of necessary measures for water bath, apron, and gumboots by State Department of Animal Husbandry (SDAH), the paravets should be made aware about the importance of basic sanitary measures. Crystoscope availability should also be ensured as it is easy to use by paravets and farmers for heat detection.

Information needs of paravets on artificial insemination in India

The present study was conducted to assess the information needs of the paravets on Artificial Insemination (AI) in India. Paravets (160) were selected having equal representation from 4 different parts of India (Gujarat, Rajasthan, Telangana and Odisha). Questionnaire and telephonic survey method was used for data collection. The information needs on AI among paravets was assessed under four sub-groups, viz. information needs on heat detection, AI techniques, post-AI practices and miscellaneous information related to AI. Results revealed that the most needed information was symptoms of heat in buffaloes and pregnancy diagnosis both bearing 1st rank (MWS=7.22), followed by address of semen stations (MWS=6.09) with 2nd rank, rectal palpation (MWS=5.97) ranked 3rd, signs of heat in cattle (MWS=5.91) ranked 4th and use of crystoscope for checking fern pattern (MWS=5.68) with 5th rank. Earlier researchers have established that proper AI technique is essential for improving conception rate. Hence, along with provision of training courses on AI, there is a need to focus on creating efficient information systems platform incorporating knowledge related to AI which can be easily accessed by the paravets. Further, the paravets need to be trained on the use of digital tools for faster information delivery and ease of use. Efforts are also needed for continuous education of the paravets for enhancing the effectiveness of AI. Convergence of various information dissemination efforts of the government and non-government sector, and more number of multipronged information channels are required to fulfil the information needs of the paravets.