Mass sperm motility is associated with fertility in sheep.

The study was to focus on the relationship between wave motion (mass sperm motility, measured by a mass sperm motility score, manually assessed by artificial insemination (AI) center operators) and fertility in male sheep. A dataset of 711,562 artificial inseminations performed in seven breeds by five French AI centers during the 2001-2005 time period was used for the analysis. Factors influencing the outcome of the insemination, which is a binary response observed at lambing of either success (1) or failure (0), were studied using a joint model within each breed and AI center (eight separate analyses). The joint model is a multivariate model where all information related to the female, the male and the insemination process were included to improve the estimation of the factor effects. Results were consistent for all analyses. The male factors affecting AI results were the age of the ram and the mass motility. After correction for the other factors of variation, the lambing rate increased quasi linearly from three to more than ten points with the mass sperm motility score depending on the breed and the AI center. The consistency of the relationship for all breeds indicated that mass sperm motility is predictive of the fertility resulting when sperm are used from a specific ejaculate. Nonetheless, predictability could be improved if an objective measurement of mass sperm motility were available as a substitute for the subjective scoring currently in use in AI centers.

Genetic and environmental effects on semen traits in Lacaune and Manech tête rousse AI rams.

Data from 51,107 and 11,839 ejaculates collected on rams of the "Lacaune" and "Manech tête rousse" breeds, respectively, were analysed to determine environmental and genetic factors affecting semen production traits (ejaculate volume, semen concentration, number of spermatozoa and motility) in young (< or = 1 year) and adult (> or = 2 years) rams. Fixed effects and variance components were estimated using multiple trait animal models within each breed. For all traits, the main environmental effects identified were year, season, number of ejaculations, daily variation, interval from previous to current collection and age. Heritability estimates were moderate for volume, concentration and number of spermatozoa (0.12 to 0.33) and lower for motility (0.02 to 0.14). Genetic correlations between ages differed from 1 for all traits (0.14 to 0.90), indicating that semen characteristics corresponded to different traits in young and adult rams. Genetic and phenotypic correlations among traits within age category were globally similar for the different breeds and categories of animals.

Character process model for semen volume in AI rams: evaluation of correlation structures for long and short-term environmental effects.

The objective of this study was to build a character process model taking into account serial correlations for the analysis of repeated measurements of semen volume in AI rams. For each ram, measurements were repeated within and across years. Therefore, we considered a model including three environmental effects: the long-term environmental effect, which is a random year(*)subject effect, the short-term environmental effect, which is a random within year subject(*)collection effect, and the classical measurement error. We used a four-step approach to build the model. The first step explored graphically the serial correlations. The second step compared four models with different correlation structures for the short-term environmental effect. We selected fixed effects in the third step. In the fourth step, we compared four correlation structures for the long-term environmental effect. The model, which fitted best the data, used a spatial power correlation structure for the short-term environmental effect and a first order autoregressive process for the long-term environmental effect. The heritability estimate was 0.27 (0.04), the within year repeatability decreased from 0.56 to 0.44 and the repeatability across years decreased from 0.43 to 0.37.

Genetic analysis of milking ability in Lacaune dairy ewes.

The milking ability of Lacaune ewes was characterised by derived traits of milk flow patterns, in an INRA experimental farm, from a divergent selection experiment in order to estimate the correlated effects of selection for protein and fat yields. The analysis of selected divergent line effects (involving 34 616 data and 1204 ewes) indicated an indirect improvement of milking traits (+17% for maximum milk flow and -10% for latency time) with a 25% increase in milk yield. Genetic parameters were estimated by multi-trait analysis with an animal model, on 751 primiparous ewes. The heritabilities of the traits expressed on an annual basis were high, especially for maximum flow (0.54) and for latency time (0.55). The heritabilities were intermediate for average flow (0.30), time at maximum flow (0.42) and phase of increasing flow (0.43), and low for the phase of decreasing flow (0.16) and the plateau of high flow (0.07). When considering test-day data, the heritabilities of maximum flow and latency time remained intermediate and stable throughout the lactation. Genetic correlations between milk yield and milking traits were all favourable, but latency time was less milk yield dependent (-0.22) than maximum flow (+0.46). It is concluded that the current dairy ewe selection based on milk solid yield is not antagonistic to milking ability.

Mastitis of dairy small ruminants.

Staphylococci are the main aetiological agents of small ruminants intramammary infections (IMI), the more frequent isolates being S. aureus in clinical cases and coagulase negative species in subclinical IMI. The clinical IMI, whose annual incidence is usually lower than 5%, mainly occur at the beginning of machine milking and during the first third of lactation. These features constitute small ruminant peculiarities compared to dairy cattle. Small ruminant mastitis is generally a chronic and contagious infection: the primary sources are mammary and cutaneous carriages, and spreading mainly occurs during milking. Somatic cell counts (SCC) represent a valuable tool for prevalence assessment and screening, but predictive values are better in ewes than in goats. Prevention is most often based on milking machine management, sanitation and annual control, and milking technique optimisation. Elimination mainly relies on culling animals exhibiting clinical, chronic and recurrent IMI, and on drying-off intramammary antibiotherapy; this treatment allows a good efficacy and may be used selectively by targeting infected udders only. Heritability values for lactation mean SCC scores are between 0.11 and 0.15. Effective inclusion of ewe's mastitis resistance in the breeding goal has recently been implemented in France following experimental and large scale estimations of genetic parameters for SCC scores.