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Background: Artificial insemination (AI) is a reproductive biotechnology that may be influenced by several factors, including the profile of the technicians and the practices used. Assessing technician's profile and their AI practices can be significant in improving AI success rate.
Aim: This study aimed to know the profile and current practices used by AI technicians (AITs), to determine the success rates of AI in water buffaloes in Leyte, Samar, and Biliran from 2011 to 2015, and to evaluate the possible association between the parameters investigated.
Materials and Methods: A total of 50 AITs from Leyte, Samar and Biliran, Philippines, were interviewed using a fixed questionnaire about their profile and employed AI practices, and 20,455 AI-related records of the Philippine Carabao Center (PCC) at Visayas State University (VSU), Baybay City, Leyte, were screened and analyzed. AI success rates were determined by retrospective analysis of the gathered data. Statistical analysis was performed between the technician profile and practices and the AI success rates.
Results: Results revealed that most of the technicians were male, around 31-40 years old, married, college graduates, working under local government units, had other sources of income, and with 1-5 years of continuous AI practice averaging 51-100 inseminations per year. Most of them attended only one basic training seminar, which was conducted more than 3 years ago in PCC in VSU. AI success rates were recorded highest in 2011 and lowest in 2015. Statistical analyses showed that some technician profile parameters (civil status, average AI per year, and the training center) and several practices (checking of soft cervix, rectal palpation, thawing temperature method, straw cutting method, and semen deposition) might have an influence on the success of AI.
Conclusion: This study documents the first report on AIT's profile and their employed AI practices and the AI success rates in Leyte, Samar, and Biliran, Philippines. Selected profile parameters and AI practices may influence AI success rates. AITs should perform more AI services and revisit the employed practices.
