Year: 2025
Type: article
Abstract: HistoryThe application of reproduction-related biotechnologies, such as artificial insemination in goats, cannot proceed on farms where production records are not available.One of the requirements in adopting AI is early diagnosis of pregnancy, which will facilitate estrus synchronization and avoid the risk of abortion.Both laboratory assays and diagnosis are available.However, they require laboratory equipment and a highly skilled technical person.The use of non-invasive pregnancy detection using barium chloride as a test solution is evaluated.The efficiency of determining pregnancy in 36 heads of 1-year-old Philippine Native goats was carried out at different concentrations (1.5, 2.5, 3.5, and 4.5g).The time consumed before the formation of precipitate (sec) and the quality of the precipitate were evaluated.The result shows that regardless of BaCl2 concentration, pregnancy can be detected.The results obtained show that treatments with higher concentration of BaCl2, requires shorter period for precipitate formation is shorter as compared to treatments with lower concentration.The difference between periods consumed among treatments is highly significant (P<0.05)from Week 1 to Week 7 of the study, with Treatment 4 recording the shortest time consumed for the precipitate to occur.In terms of visibility of the precipitate, there was no significant difference between treatment means 7 days after breeding.However, as the pregnancy progresses, the difference between the treatment means (P<0.05) was significant.Treatment 4 developed more visible precipitate as compared to the other treatments, and this observation was noted throughout the study.Therefore, utilizing BaCl2 to detect early-stage pregnancy in goats is an effective, low-cost procedure with the same accuracy as ultrasound diagnosis.According to this study, 4.5g BaCl2 is a better visual indicator for non-invasive pregnancy diagnosis.
Language: English
Subfield: Agronomy and Crop Science
Domain: Life Sciences
SDG: Zero hunger
Open Access status: bronze
Funder: Isabela State University
OpenAlex ID: W4412729006