Quality management system for bull artificial insemination centers: design, execution and impact
Bibliographic record
Abstract
Although more than 12 million doses of bull frozen semen were sold in Brazil in 2012, the production process of the doses sold by the artificial insemination centers registered in the Ministry of Agriculture, Livestock and Supply is not yet standardized. The hypothesis of the present study is that the design and implementation of a hazard analysis and critical control points (HACCP) system in a bull artificial insemination center can identify steps potentially harmful to the viability of semen doses, to decrease their rejection and to improvement their final quality, after the adoption of preventive and process control measures. The implementation of the HACCP system identified hazardous steps for the quality of the produced semen doses, leading to a reduction in their contamination during processing (P<0.05). There was also an increase in progressive motility and plasma membrane and acrosome integrity of spermatozoa (P<0.05) after implementing the HACCP system, which resulted in reduced rejection of semen batches and doses (P<0.05) and decreased production costs. Thus, the execution of the HACCP system standardized the production process of bull frozen semen, with improved sperm quality and reduction in both rejection of doses and costs to the industry. Additionally, during the sandwich doctorate program at the University of Calgary (Canada), the involvement of angiotensin converting enzyme in the capacitation process and in vitro fertilization in cattle was evaluated. After blocking the enzyme s activity by the specific inhibitor captopril, there were similar levels of tyrosine phosphorylation and cleavage and embryonic development until the blastocyst stage in comparison with the control group (P>0.05). Therefore, the present study suggests that the angiotensin converting enzyme is neither required for sperm capacitation nor involved in in vitro fertilization in cattle.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".