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Bull semen production centres (SPC) generally present satisfactory quality control for sperm processing, but non-standardized hygiene procedures. This study describes a Hazard Analysis and Critical Control Points (HACCP) system developed for bull SPC and subsequently implemented in a commercial SPC. After the identification of hazards at each step of semen processing and the determination of their risk and severity, monitoring and corrective procedures were designed to assess the system's efficiency. The HACCP system identified six microbiological hazards, 10 physical hazards, four chemical hazards and three critical control points. After the establishment of Good Processing Practices, Standard Operating Procedures and Standard Sanitizing Operating Procedures, the system was validated through an audit, to identify eventual failures and to define measures to correct them.

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The objective of the present study was to evaluate the accuracy and bias of direct and blended genomic predictions using different methods and cross-validation techniques for growth traits (weight and weight gains) and visual scores (conformation, precocity, muscling, and size) obtained at weaning and at yearling in Hereford and Braford breeds. Phenotypic data contained 126,290 animals belonging to the Delta G Connection genetic improvement program, and a set of 3,545 animals genotyped with the 50K chip and 131 sires with the 777K. After quality control, 41,045 markers remained for all animals. An animal model was used to estimate (co)variance components and to predict breeding values, which were later used to calculate the deregressed estimated breeding values (DEBV). Animals with genotype and phenotype for the traits studied were divided into 4 or 5 groups by random and k-means clustering cross-validation strategies. The values of accuracy of the direct genomic values (DGV) were moderate to high magnitude for at weaning and at yearling traits, ranging from 0.19 to 0.45 for the k-means and 0.23 to 0.78 for random clustering among all traits. The greatest gain in relation to the pedigree BLUP (PBLUP) was 9.5% with the BayesB method with both the k-means and the random clustering. Blended genomic value accuracies ranged from 0.19 to 0.56 for k-means and from 0.21 to 0.82 for random clustering. The analyses using the historical pedigree and phenotypes contributed additional information to calculate the GEBV, and in general, the largest gains were for the single-step (ssGBLUP) method in bivariate analyses with a mean increase of 43.00% among all traits measured at weaning and of 46.27% for those evaluated at yearling. The accuracy values for the marker effects estimation methods were lower for k-means clustering, indicating that the training set relationship to the selection candidates is a major factor affecting accuracy of genomic predictions. The gains in accuracy obtained with genomic blending methods, mainly ssGBLUP in bivariate analyses, indicate that genomic predictions should be used as a tool to improve genetic gains in relation to the traditional PBLUP selection.

Heterospermic AI is commonly used in swine despite preventing precise evaluation of individual boar fertility. The present study compared the contribution of four boars (A, B, C and D) for reproductive performance and for paternity using homospermic and heterospermic (AB, AC, AD, BC, BD and CD) AI (n=204 for homospermic AI; n=307 for heterospermic AI). Blood samples from the four boars, from all sows inseminated with heterospermic doses and from the umbilical cords of their piglets, as well as tissue smears from mummified fetuses, were genotyped using single nucleotide polymorphisms (SNPs). Differences among boars were detected for the in vitro oocyte penetration rate and for the number of spermatozoa per oocyte (P<0.05), but not for sperm motility, mitochondrial functionality and integrity of the membrane, acrosome and DNA (P>0.05). Homospermic and heterospermic AI resulted in similar (P>0.05) farrowing rates (90.5% and 89.9%, respectively) and total litter size (12.4±0.4 and 12.7±0.7, respectively). Farrowing rate was lower for Boar B than for Boar C (P<0.05), but no other differences in reproductive performance among boars were observed with homospermic AI. The SNPs determined the paternity of 94.2% of the piglets sired by heterospermic AI. In the AC pool, paternity contribution per boar was similar (P>0.05), but differences between boars occurred in all other pools (P<0.05). Boar D achieved the greatest paternity contribution in all pools and parity categories (nearly 60%), whereas Boar B sired the fewest piglets (at most 40%). Reproductive performance was similar with homospermic and heterospermic AI, but differences in performance among boars undetected with homospermic AI were only evident after genotyping the piglets sired through heterospermic AI.

Many microorganisms from various sources may be present in ejaculates of bulls. This study identified and isolated bacteria from bull sperm samples in a commercial stud and evaluated their resistance to antibiotics. The number of colony‐forming units was determined in semen samples collected at distinct steps during freezing and thawing. The minimum inhibitory concentration and the minimum bactericidal concentration were determined for four antibiotics commonly used in commercial studs. A total of 135 microorganisms from 25 genera were isolated. After a sensitivity test, all evaluated microorganisms (n = 55) were resistant to penicillin and most of them were resistant to tylosin and lincomycin (n = 54). Resistance to all tested antibiotics was observed in 22% of all isolates, whereas only 3.9% of the isolates were inhibited by the tested antibiotics at the concentrations recommended by the international legislation. As the isolated microorganisms presented high resistance to frequently used antibiotics, sensitivity tests should be periodically conducted in commercial bull semen studs to prevent the use of contaminated semen in artificial insemination.

The paraoxonases types 1, 2 and 3 (PON1, PON2 and PON3, respectively) are enzymes that degrade lipid peroxides, preventing oxidative damages relevant for male reproductive function. This study determined the expression of those three paraoxonases in reproductive tissues of bulls and evaluated correlations among the activity of PON1 in the serum and seminal plasma with breeding soundness parameters in bulls. The expression of PON1, PON2 and PON3 was characterised by RT-PCR in samples of testicular parenchyma, vesicular glands and epididymis collected from three slaughtered bulls. All three paraoxonases were expressed in the testicular parenchyma, PON2 and PON3 were both expressed in the epididymis head and PON3 was also expressed in the epididymis tail. The PON1 activity was determined in samples of serum and seminal plasma from 110 bulls submitted to breeding soundness evaluation. There was a strong correlation (r = .90) between the activity of the PON1 in both serum and seminal plasma (p < .0001). The PON1 activity in the seminal plasma was positively correlated with ejaculate's colour, sperm mass activity (p = .04), motility, vigour and viability (all p < .01). Thus, PON1 may be a potential marker for sperm motility and viability in bulls.

Bull Semen Collection and Processing Centers (SCPC) have satisfactory control of sperm quality, but commonly lack standardized quality control of hygiene procedures. This study assessed the impact of implementing a Hazard Analysis and Critical Control Points (HACCP) system in a bull SCPC, comparing microbial counts on various steps of semen processing, semen quality and costs across two periods (before and after the HACCP implementation). After surveying all routine activities of the SCPC, control points were identified, preventive measures were designed and corrective actions were employed, whenever necessary. Six months after HACCP implementation, the system was audited and production data covering two similar periods of two consecutive years were compared. Counts of colony forming units in samples collected from artificial vaginas, flexible tubes from the straw filling machine and from fresh and frozen semen after HACCP implementation were lower than during the previous period (P < 0.05). Improved post-thawing sperm motility, membrane integrity and acrosome integrity (P < 0.0001) and reduced rejection of semen batches and frozen doses were observed after HACCP implementation (P < 0.01), resulting in reduced opportunity costs. Thus, the implementation of a HACCP system in a bull SCPC allowed low-cost production of high-quality semen doses with reduced microbial contamination.