Impact of Distinct Freezing Curves on the Quality of Ram Sperm after Thawing.

BACKGROUND: Automated equipment with customized freezing curves can be used to cryopreserve ram sperm, but none is considered a standard. OBJECTIVE: This study compared the post-thawing quality of ram sperm frozen using a conventional freezing curve and two controlled-rate curves. MATERIALS AND METHODS: Six ejaculates were collected from four rams (n = 24). In the conventional curve (110 min), sperm was cooled at -0.3 to -0.5°C min-1 until 5°C, stabilized for 60 min and exposed to liquid nitrogen (LN2) vapor for 10 min (-80°C) before submersion. The slow-customized (SC) curve (126.2 min) used a rate of -0.25°C min-1 until 5°C, stabilization for 60 min and a rate of -20°C min-1 until -120°C before immersion in LN2. Rates for the fast-customized (FC) curve (75 min) were: -0.3°C min-1 until 5°C; -3°C min-1 until -10°C; -5°C min-1 until -35°C; and -4°C min-1 until immersion in LN2 (-43°C). RESULTS: Velocity in a straight line and beat-cross frequency were lower for spermatozoa frozen with the FC than with the conventional curve (P < 0.05). The FC curve resulted in more membrane and acrosome damages than the other curves (P < 0.05). Mitochondrial membrane potential was lower with the SC than with the other curves (P < 0.05). CONCLUSION: The conventional curve was more efficient than both tested automated freezing curves. The FC curve may be an alternative to the SC curve due to the shorter processing time.

Expression of paraoxonase types 1, 2 and 3 in reproductive tissues and activity of paraoxonase type 1 in the serum and seminal plasma of bulls.

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.

Contribution of boars to reproductive performance and paternity after homospermic and heterospermic artificial insemination.

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.

Hazard Analysis and Critical Control Points System for a Bull Semen Production Centre.

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.