Different ways to model biological relationships between fertility and pH of the semen in rabbits

This work aimed to study the relationship between pH of the semen and fertility (Fert, defined as the success or failure of conception), which is of special interest because pH of the semen can be considered a global marker of the expression of some seminal quality traits. Different methods used to model the relationship between Fert and pH are presented here: 1) ignoring genetic and environmental correlations and including pH either as a covariate or as a cross-classified effect on fertility, 2) a bivariate mixed model, and 3) recursive bivariate mixed models. A total of 653 pH records and 6,365 Fert records after AI were used. Crossbreed does from 2 maternal lines were artificially inseminated with buck semen from a paternal line in a commercial environment. A negative, and almost linear, effect of pH on Fert was detected. The posterior median of pH and Fert heritabilities, and the highest posterior density interval at 95% (in parentheses) were approximately 0.18 (0.05, 0.29) and approximately 0.10 (0.02, 0.20) across all the models, respectively. Genetic correlations between traits were negative, but the highest posterior density interval at 95% included zero [i.e., -0.31 (-0.91, 0.33) in the bivariate mixed model and -0.17 (-0.99, 0.48) and -0.44 (-0.99, 0.10) in the recursive bivariate mixed models including pH as a covariate or as a cross-classified effect, respectively]. All models predicted Fert data reasonably well (i.e., 76 and 62% correct predictions for success and failure, respectively). No differences in the prediction of the EBV for male fertility were encountered between models, showing a good concordance in the animals ranked by their EBV (the correlation between EBV in all models was close to 1). Thus, no differences in results were obtained considering, or not considering, genetic and environmental correlations between pH and Fert and assuming, or not assuming, recursiveness between each trait. This is because the magnitude of the effect of pH on Fert was not large enough; therefore, the same results were obtained even though the models were of different complexity.     

Genetic parameters of fertility in two lines of rabbits with different reproductive potential

A Bayesian analysis with a threshold model was performed for fertility defined as a binary trait (1 = successful mating, 0 = unsuccessful mating) in two populations of rabbits of different reproductive potential and different genetic origin: Line P selected for litter size and Line C selected for growth rate. There were 20,793 records of natural mating (86.2% successful) in Line C between 1983 and 2003, and 17,548 records (80.5% successful) in Line P, between 1992 and 2003. Data related to 5,388 and 3,848 females and 1,021 and 685 males in Lines C and P, respectively. The pedigree included 6,409 and 4,533 individuals in Lines C and P, respectively. The binary response was modeled under a probit approach. The model for the latent variable included male and female additive genetic effects, male and female permanent environmental effects, and the year-season and physiological status of the female (nulliparous, multiparous lactating, or multiparous nonlactating) as systematic effects. Means (standard deviation in parentheses) of the estimated marginal posterior distribution (EMPD) of male heritability were 0.013 (0.006) and 0.010 (0.008) in Lines C and P, respectively, and those of EMPD of female heritability were 0.056 (0.013) and 0.062 (0.018) in Lines C and P, respectively. Means of the EMPD of the proportion of the phenotypic variance due to environmental male and female effects were, respectively, 0.031 (0.007) and 0.128 (0.018) in Line C and 0.053 (0.010) and 0.231 (0.024) in Line P. Means (standard deviations in parentheses) of the EMPD of genetic correlation between male and female fertility were 0.733 (0.197) in Line C and 0.434 (0.381) in Line P. The posterior distribution of genetic correlations presents a huge dispersion, and the estimates should be taken with caution because of the almost negligible estimate of the male genetic component. Results indicate that little genetic variation exists for female fertility, and practically none for male fertility. It would, therefore, be possible to improve reproductive performance by including female fertility in a breeding program, but response to selection would be very small.     

Application and Commercialization of Flow Cytometrically Sex-Sorted Semen

The current technology to sort X and Y chromosome bearing sperm population requires individual identification and selection of spermatozoa in a modified high-speed flow cytometer. For farm animal species, the technology is capable of producing sexed sperm at greater than 90% purity. However, only in the bovine, the technology has reached a developmental level that allows its commercial application. Meanwhile, the demand for female calves has grown rapidly, which encourages the demand for sex-sorted semen from high genetic value bulls. The success of the technology will depend mainly on the fertilizing capacity of the sorted spermatozoa, as this is the most affecting and economically relevant factor. To date, fertility is still variable and is quite dependant on post-sort processing. New processing techniques are under investigation and will likely be able to improve the fertility rates after AI with sex-sorted semen. It is of great importance to select the right bulls and to test the sorted samples on a routine basis. In addition to the demand for sex-sorted semen by the cattle industry, there is also a significant demand expressed by pig farmers. However, it is still unknown if the use of sex-sorted semen through commercial pig AI will be economically feasible. For the pig, the combination of in vitro fertilization with sexed semen and non-surgical embryo transfer is an alternative that merits further scientific attention. Recent developments in ovine AI and ET will make it very likely that commercial sheep industry will adopt the sexing technology in their breeding concepts.     

Comparative efficiency of novel laparoscopic and routine vaginal inseminations with cryopreserved semen in rabbits

Laparoscopic artificial insemination technique (LAI) is described to overcome reduced fertility problems in sheep artificial insemination (AI) programmes with frozen semen. Later on, this technology was modified for endangered non-domestic cats to deposit low quality or reduced number of sperm cells hardly obtained by electro-ejaculation into the oviduct. This technique by passes the complex structure of cervix and efficiently transfers the sperm cells to the point of fertilization. In recent years, rabbits are becoming popular transgenic animal models producing various therapeutic and commercial products, as well as being experimental animals for disease models. The worldwide transportation of frozen semen and re-establishment of transgenic lines using AI technology has become a common practice. Therefore, this study was designed to describe a laparoscopic intrauterine insemination technique, which might assist in conceiving the animals with limited number of sperm cells. The female rabbits were laparoscopically (n = 22) or vaginally (n = 13) inseminated with frozen–thawed semen samples containing approximately 10 × 10⁶ motile sperm. The laparoscopic insemination technique provided higher pregnancy rate (45.5%) than vaginal insemination technique (7.7%) (p < .05). In conclusion, the described laparoscopic AI might be a new alternative technique, thus enabling limited or low-quality frozen sperm samples to establish pregnancy in rabbits.     

Autoregressive model for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle

Reproductive efficiency is major determinant of the dairy herd profitability. Thus, reproductive traits have been widely used as selection objectives in the current dairy cattle breeding programs. We aimed to evaluate strategies to model days open (DO), calving interval (CI) and daughter pregnancy rate (DPR) in Brazilian Holstein cattle. These reproductive traits were analysed by the autoregressive (AR) model and compared with classical repeatability (REP) model using 127,280, 173,092 and 127,280 phenotypic records, respectively. The first three calving orders of cows from 1,469 Holstein herds were used here. The AR model reported lower values for Akaike Information Criteria and Mean Square Errors, as well as larger model probabilities, for all evaluated traits. Similarly, larger additive genetic and lower residual variances were estimated from AR model. Heritability and repeatability estimates were similar for both models. Heritabilities for DO, CI and DPR were 0.04, 0.07 and 0.04; and 0.05, 0.06 and 0.04 for AR and REP models, respectively. Individual EBV reliabilities estimated from AR for DO, CI and DPR were, in average, 0.29, 0.30 and 0.29 units higher than those obtained from REP model. Rank correlation between EBVs obtained from AR and REP models considering the top 10 bulls ranged from 0.72 to 0.76; and increased from 0.98 to 0.99 for the top 100 bulls. The percentage of coincidence between selected bulls from both methods increased over the number of bulls included in the top groups. Overall, the results of model-fitting criteria, genetic parameters estimates and EBV predictions were favourable to the AR model, indicating that it may be applied for genetic evaluation of longitudinal reproductive traits in Brazilian Holstein cattle.     

Estimation of additive and non-additive genetic effects for fertility and reproduction traits in North American Holstein cattle using genomic information

Non-additive genetic effects are usually ignored in animal breeding programs due to data structure (e.g., incomplete pedigree), computational limitations and over-parameterization of the models. However, non-additive genetic effects may play an important role in the expression of complex traits in livestock species, such as fertility and reproduction traits. In this study, components of genetic variance for additive and non-additive genetic effects were estimated for a variety of fertility and reproduction traits in Holstein cattle using pedigree and genomic relationship matrices. Four linear models were used: (a) an additive genetic model; (b) a model including both additive and epistatic (additive by additive) genetic effects; (c) a model including both additive and dominance effects; and (d) a full model including additive, epistatic and dominance genetic effects. Nine fertility and reproduction traits were analysed, and models were run separately for heifers (N = 5,825) and cows (N = 6,090). For some traits, a larger proportion of phenotypic variance was explained by non-additive genetic effects compared with additive effects, indicating that epistasis, dominance or a combination thereof is of great importance. Epistatic genetic effects contributed more to the total phenotypic variance than dominance genetic effects. Although these models varied considerably in the partitioning of the components of genetic variance, the models including a non-additive genetic effect did not show a clear advantage over the additive model based on the Akaike information criterion. The partitioning of variance components resulted in a re-ranking of cows based solely on the cows’ additive genetic effects between models, indicating that adjusting for non-additive genetic effects could affect selection decisions made in dairy cattle breeding programs. These results suggest that non-additive genetic effects play an important role in some fertility and reproduction traits in Holstein cattle.     

Genetic parameters for direct and maternal calving ease in Walloon dairy cattle based on linear and threshold models

Calving ease scores from Holstein dairy cattle in the Walloon Region of Belgium were analysed using univariate linear and threshold animal models. Variance components and derived genetic parameters were estimated from a data set including 33 155 calving records. Included in the models were season, herd and sex of calf × age of dam classes × group of calvings interaction as fixed effects, herd × year of calving, maternal permanent environment and animal direct and maternal additive genetic as random effects. Models were fitted with the genetic correlation between direct and maternal additive genetic effects either estimated or constrained to zero. Direct heritability for calving ease was approximately 8% with linear models and approximately 12% with threshold models. Maternal heritabilities were approximately 2 and 4%, respectively. Genetic correlation between direct and maternal additive effects was found to be not significantly different from zero. Models were compared in terms of goodness of fit and predictive ability. Criteria of comparison such as mean squared error, correlation between observed and predicted calving ease scores as well as between estimated breeding values were estimated from 85 118 calving records. The results provided few differences between linear and threshold models even though correlations between estimated breeding values from subsets of data for sires with progeny from linear model were 17 and 23% greater for direct and maternal genetic effects, respectively, than from threshold model. For the purpose of genetic evaluation for calving ease in Walloon Holstein dairy cattle, the linear animal model without covariance between direct and maternal additive effects was found to be the best choice.     

Fertility and viability rates of hydatid cysts in slaughtered animals in the Mazandaran Province,Northern Iran

The aim of this study was to determine the fertility and viability of hydatid cysts in slaughtered sheep and cattle. Cysts were collected from the liver and lungs of 169 sheep and 171 cattle infected with Echinococcus granulosus when slaughtered in industrial abattoir in Sari, Iran, 2007–2008. Fertility was determined by the examination of cyst fluid for the presence of protoscoleces. The viability of the protoscoleces was assessed by staining with 0.1% aqueous eosin solution. The fertility rates of hepatic cyst of sheep and cattle were 47.1% and 1.4%, respectively and the fertility rates of pulmonary cyst of sheep and cattle were 39.4% and 8.1%. In the sheep, the fertility of cysts in the liver was higher than that in lungs, but in the cattle the fertility of cysts in lungs was higher than liver. The viability of protoscoleces of fertile cysts for sheep and cattle were about 76.9% and 82.5%, respectively. Based on the finding in the present study, effort should be made to control transmission of cystic echinococcosis by safe disposal of Echinococcus cysts such that dogs cannot have access to the cysts.     

Echinococcosis/hydatidosis in western Iran

In the present study, 115 stray dogs (56 males and 59 females, mixed breed), 86 golden jackal (Canis aureus, 42 males and 44 females), 60 red foxes (Vulpes vulpes, 33 males and 27 females), and three female wolves (Canis lupus) were examined for Echinococcus granulosus infection, as well as, 32,898 sheep, 10,691 goats, 15,779 cattle and 659 buffaloes for hydatid infection from five provinces in western Iran during 3 years (1997-2000). Meanwhile fertility rates of different types and forms of cysts isolated from infected animals and the viability of protoscolices were also determined. Results indicated that 19.1% of the dogs, 2.3% of the golden jackals and 5% of the red foxes were infected with Echinococcus granulosus. 11.1% of the sheep, 6.3% of the goats, 16.4% of the cattle and 12.4% of the buffaloes were also found to be infected with hydatid cyst. The cysts isolated from liver and lungs of the sheep show higher fertility rate than the cysts of liver and lungs of goats, cattle and buffaloes.     

Threshold-linear analysis of measures of fertility in artificial insemination data and days to calving in beef cattle

Mating and calving records for 47,533 first-calf heifers in Australian Angus herds were used to examine the relationship between days to calving (DC) and two measures of fertility in AI data: 1) calving to first insemination (CFI) and 2) calving success (CS). Calving to first insemination and calving success were defined as binary traits. A threshold-linear Bayesian model was employed for both analyses: 1) DC and CFI and 2) DC and CS. Posterior means (SD) of additive covariance and corresponding genetic correlation between the DC and CFI were -0.62 d (0.19 d) and -0.66 (0.12), respectively. The corresponding point estimates between the DC and CS were -0.70 d (0.14 d) and -0.73 (0.06), respectively. These genetic correlations indicate a strong, negative relationship between DC and both measures of fertility in AI data. Selecting for animals with shorter DC intervals genetically will lead to correlated increases in both CS and CFI. Posterior means (SD) for additive and residual variance and heritability for DC for the DC-CFI analysis were 23.5 d2 (4.1 d2), 363.2 d2 (4.8 d2), and 0.06 (0.01), respectively. The corresponding parameter estimates for the DC-CS analysis were very similar. Posterior means (SD) for additive, herd-year and service sire variance and heritability for CFI were 0.04 (0.01), 0.06 (0.06), 0.14 (0.16), and 0.03 (0.01), respectively. Posterior means (SD) for additive, herd-year, and service sire variance and heritability for CS were 0.04 (0.01), 0.07 (0.07), 0.14 (0.16), and 0.03 (0.01), respectively. The similarity of the parameter estimates for CFI and CS suggest that either trait could be used as a measure of fertility in AI data. However, the definition of CFI allows the identification of animals that not only record a calving event, but calve to their first insemination, and the value of this trait would be even greater in a more complete dataset than that used in this study. The magnitude of the correlations between DC and CS-CFI suggest that it may be possible to use a multitrait approach in the evaluation of AI and natural service data, and to report one genetic value that could be used for selection purposes.     

扩增SRY基因鉴定牛、羊胚胎性别的初步研究

本研究利用本试验室设计的SRY基因3对常规PCR引物扩增牛SRY基因和羊的SRY基因,结果表明:第2对引物扩增出公牛和公羊基因组的DNA 750 bp左右清晰条带,而母牛、母羊基因组DNA无此扩增条带,说明第2对引物可以应用于牛和羊的早期胚胎性别鉴定;     

Neutralizing antibody to bovine rotavirus in various animal species

A total of 288 serum samples were collected from 12 species of animals in various localities of Japan from 1975 to 1977. Neutralizing antibody to bovine rotavirus was found in serum samples from all the species, viz., horses, cattle, sheep, goats, pigs, dogs, rabbits, guinea pigs, rats, mice, chickens and human beings. The incidence of neutralizing antibody in titers of 1 : 2 or higher ranged from 31 to 100%, and high incidences exceeding 70% were obtained in horses, cattle, sheep, pigs, dogs, rabbits and human beings. High titers were most common in horses, cattle, sheep and pigs. These serological results suggest that rotaviruses occur commonly in these species of animals.     

Genetic Parameters for Semen Production Traits in Austrian Dual-Purpose Simmental Bulls

Genetic parameters were estimated for semen production traits collected in an Austrian AI centre in the years 2000-2004. In total, 12,746 ejaculates from 301 Austrian dual-purpose Simmental (Fleckvieh) AI bulls were examined considering different effects on ejaculate volume, sperm concentration, percentage of viable spermatozoa in the ejaculate, total spermatozoa per ejaculate and motility. The model for genetic parameter estimation included the fixed effects age of bull, collection interval, number of collections on collection day, bull handler, semen collector, year and month of collection, a random additive genetic component and a permanent environmental effect. Correlations between estimated breeding values for semen traits and male fertility from the routine evaluation were calculated. The fertility trait considered in the routine evaluation is non-return rate 90 for the first insemination. All semen production traits were moderately heritable. Heritabilities for volume, concentration, percentage of viable spermatozoa, total number of spermatozoa and motility were 0.18, 0.14, 0.10, 0.22 and 0.04, respectively. Correlations between breeding values for semen quality traits and routinely estimated breeding values for male fertility were low and ranged from 0.08 to 0.17 indicating that semen production traits are rather poor predictors of male fertility.     

我国部分地区牛羊弓形虫血清流行病学调查

为了解我国牛羊弓形虫病流行情况,应用间接血凝试验（IHA）对河南、山东、山西、内蒙古、云南、贵州6省区151份牛血清、50份奶样、490份羊血清进行了弓形虫病血清流行病学调查。结果显示：151份被检牛血清和50份牛奶样品,弓形虫抗体均为阴性。490份羊血清弓形虫抗体总阳性率5.71％,其中母羊、公羊血清阳性率分别为4.03％和9.79％;山羊、绵羊、杂交羊血清阳性率分别为6.58％、4.81％和5.13％;阳性率最高的为公山羊（13.2％）,最低的为母绵羊（2.96％）。28份阳性羊血清中,75％的抗体滴度为1：64,25％的抗体滴度为1：256。1岁后的羊,随年龄增长,血清阳性率升高。     

Genetic evaluation of calving to first insemination using natural and artificial insemination mating data

Mating and calving records for 51,084 first-parity heifers in Australian Angus herds were used to examine the relationship between probability of calving to first insemination (CFI) in artificial insemination and natural service (NS) mating data. Calving to first insemination was defined as a binary trait for both sources of data. Two Bayesian models were employed: 1) a bivariate threshold model with CFI in AI data regarded as a trait separate from CFI in NS data and 2) a univariate threshold model with CFI regarded as the same trait for both sources of data. Posterior means (SD) of additive variance in the bivariate analysis were similar: 0.049 (0.013) and 0.075 (0.021) for CFI in AI and NS data, respectively, indicating lack of heterogeneity for this parameter. A similar trend was observed for heritability in the bivariate analysis, with posterior means (SD) of 0.025 (0.007) and 0.048 (0.012) for AI and NS data, respectively. The posterior means (SD) of the additive covariance and corresponding genetic correlation between the traits were 0.048 (0.006) and 0.821 (0.138), respectively. Differences were observed between posterior means for herd-year variance: 0.843 vs. 0.280 for AI and NS data, respectively, which may reflect the higher incidence of 100% conception rates within a herd-year class (extreme category problem) in AI data. Parameter estimates under the univariate model were close to the weighted average of the corresponding parameters under the bivariate model. Posterior means (SD) for additive, herd-year, and service sire variance and heritability under the univariate model were 0.063 (0.007), 0.56 (0.029), 0.131 (0.013), and 0.036 (0.007), respectively. These results indicate that, genetically, cows with a higher probability of CFI when mated using AI also have a high probability of CFI when mated via NS. The high correlation between the two traits, along with the lack of heterogeneity for the additive variance, implies that a common additive variance could be used for AI and NS data. A single-trait analysis of CFI with heterogeneous variances for herd-year and service sire could be implemented. The low estimates of heritability indicate that response to selection for probability of calving to first insemination would be expected to be low.     

Genetic correlation between growth and female and male contributions to fertility in rabbit

A Bayesian bivariate Linear-Threshold Animal Model was implemented to determine the genetic correlation between fertility (F), defined as success or failure to conceive, and average daily gain (ADG) in a rabbit line selected for ADG. A total of 27 234 records of F from 7895 females and 1293 males, and 114 135 records of ADG were used for the analysis. The pedigree included 114 485 animals. The model used for ADG included the systematic effects of year-season, parity order and number of kids born alive, the animal additive effect, the maternal and paternal permanent environmental effects, the common litter permanent environmental effect and the residual. The model for the liability of F included the systematic effects of year-season and physiological status of the female, the female and male additive genetic effects, the female and male permanent environmental effects and the residual, which was divided into a permanent environmental effect related to the common litter effect for ADG, and an independent term. The estimated heritabilities were 0.15 for ADG and 0.07 and 0.04 for the female and male contributions to F, respectively. Male and female contributions to F had a positive genetic correlation (0.34). The genetic correlation between ADG and the female component of F was low to moderate and negative (-0.31), whereas it was null for the male contribution to F. Thus, it is expected that only the female contribution to reproductive performance may be impaired by selection for ADG in rabbit lines.     

Fertility and hatchability in RIR and WL breeds as functionally modified by crossing them in alternate sex combinations (Gallus domesticus)

(1) Four breeding groups of Rhode Island Red and White Leghorn domestic fowl (RIR (female) x RIR (male), RIR (female) x WL (male), WL (female) x RIR (male) and WL (female) x WL (male)) were compared for fertility, hatchability, and their post-insemination sustainability, egg weight loss during incubation and uncovered yolk in abdominal cavity of dead in shell in order to understand the problems associated with the RIR breed in these respects. (2) Crossing RIR (female) with WL (male) or in reverse sex combinations did not improve fertility in comparison to pure RIR chickens and all these groups were less fertile than the pure WL. (3) Unlike fertility, hatchability in RIR improved with the change to either sex partner of the WL breed but the WL (female) x RIR (male) combination was similar to the pure WL (97.72 and 97.12%, respectively). In contrast, crossing RIR (female) with WL (male) resulted in an improvement (86.67%) as compared to pure RIR (76.67%) but still lower than the pure WL and WL (female) x RIR (male) cross. (4) Egg weight loss during incubation was more (20.16%) in pure RIR as compared to RIR (female) x WL (male) (17.13%), followed by WL (female) x RIR (male) (10.28%) and pure WL (9.57%). (5) There were more dead-in-shell embryos with yolks outside their abdominal cavity in pure RIR and their crosses as compared to pure WL breeds. (6) Fertility was sustained for longer in WL than other combinations with post-artificial insemination using constant number of spermatozoa. Fertility after a week of insemination tended to decrease more rapidly than hatchability on a fertile egg basis. (7) It is concluded that both sexes are responsible for the poor fertility in RIR but the female is responsible for poor hatchability and this poor performance is mainly due to greater egg weight loss during incubation.     

Intra-uterine Insemination in Farm Animals and Humans

Artificial insemination (AI) is the oldest and currently most common technique in the assisted reproduction of animals and humans. The introduction of AI in farm animals was forced by sanitary reasons and the first large-scale applications with a commercial goal were performed in cattle in the late 1930s of last century. After the Second World War, cryopreservation of semen facilitated distribution and AI was mainly performed for economic reasons, especially in dairy cattle industry. In humans however, AI was initially performed in cases of physiological and psychological sexual dysfunction, but later on also in cases of infertility caused by immunological problems. Currently, the most common indications for intra-uterine insemination (IUI) in humans are unexplained infertility and male subfertility. In these cases, IUI is considered as the treatment of the first choice, before more invasive techniques such as in vitro fertilization (IVF) and intracytoplasmatic sperm injection (ICSI) are used. In contrast with humans, the quantity and quality of semen produced by farm animals is much higher and permits dilution and production of several insemination doses per ejaculate. However, with the introduction of sex-sorted semen in farm animals, the same problem of low-quality semen as in humans has arisen. In cattle, pigs and horses, conventional insemination with low numbers of sex-sorted spermatozoa results in a significant decrease in fertility. To improve the fertility rates with this semen, new insemination techniques have been developed in order to deposit spermatozoa closer to the site of fertilization. In sows and mares the advantage of utero-tubal junction (UTJ) insemination has already been proven; however, in cattle it is still under investigation. In this review, the differences and similarities in the application of AI between animals and humans are discussed and as AI in farm animals is most successful in cattle, the situation in this species is elaborated the most.     

Is sperm DNA fragmentation a good marker for field AI bull fertility?

This paper aimed at investigating the potential use of sperm DNA fragmentation (SDF) to improve the routine screening of infertility of Holstein bulls. Cryopreserved sperm samples from 201 Holstein bulls provided by an AI center were used in the analyses of SDF at 0 (SDF_0) and 6 (SDF_6) h of incubation at 37°C. A refinement of the sperm chromatin dispersion test implemented in the Sperm-Halomax kit was employed to measure SDF. Records on routinely collected semen traits (volume, concentration, mass and individual motility evaluated in the fresh ejaculate, and individual motility in post-thawed semen straws) were provided by the AI center. Artificial insemination bull fertility was obtained from official field recording as successful or failed insemination. The results show that the average SDF was low (around 3.5%) at 0 and 6 h of incubation. A moderate effect of inbreeding depression was found. Estimated heritability for SDF traits were moderately high (0.41 and 0.29 for SDF_0 and SDF_6, respectively) and estimated repeatability of SDF measures in the same animal were high (0.73 and 0.70 for SDF_0 and SDF_6, respectively). An overall estimated service bull value (ESBV) obtained through statistical modeling that allowed for adjustment of systematic environmental effects not specific to a bull and of the female contribution to fertility, and the estimated genetic values (EGV) were obtained from field-recorded AI information. The ESBV and EGV were also obtained for all semen traits. Moderately large and negative Pearson correlation coefficients were observed between SDF traits and male fertility ranging from (-0.43 to -0.50; P <0.001). Results of stepwise regression analyses showed that SDF_6 had the largest partial r(2) (0.15 to 0.26) among all semen characteristics. Overall, the selected semen traits explained 25% and 31% of the observed variability in bull fertility measured as EGV and ESBV, respectively. When looking at the predictive ability of bull fertility categories, the results of discriminant and logistic regression analyses showed that low-fertility bulls (those in the 10th or lower percentile in the fertility distribution) can be accurately identified by using measures of SDF alone or in combination with sperm motility. Values of SDF around 7% to 10% could be used as indicators of low AI success.     

Poor Prediction Value of Sperm Head Morphometry for Fertility and Litter Size in Rabbit

This study was conducted to investigate the predictive capacity of fertility and litter size of sperm head morphometric measurements when the ejaculates fulfilled the minimum requirements commonly used in artificial insemination (AI). Semen samples from 11 rabbits (77 ejaculates) were evaluated for sperm motility, abnormal spermatozoa and sperm head morphometry using computer automated sperm analysis system. Morphometric dimensions for length, width, area and perimeter were analysed. Only ejaculates with more than 70% of motility rate and <15% of abnormal sperm were used for AI. A total of 1031 individual AI were performed in commercial rabbitries. Our results showed significant differences among animals for all sperm head measurements. The mean values for fertility and litter size obtained were 68.4 ± 0.01% and 9.3 ± 0.1% respectively. To assess the predictive value of morphometric dimensions in fertility, a logistic regression analysis was applied. Moreover, multiple linear regression analyses were used to examine the relationship between litter size and sperm head morphometric parameters. Logistic regression analysis rendered a significant model between fertility and area and perimeter, explaining the 0.65% variation. Multiple linear regression analysis rendered a significant model between litter size and width, area and perimeter that explained the 1.3% variation. By conclusion, the sperm head morphometric parameters assay showed low potential to predict fertility and litter size when the ejaculates fulfilled the minimum requirements commonly used in AI (motility and abnormal spermatozoa) in rabbit.