Search

Abstract: The aim of this study is to update the values concerning nutritional components for sheep and goat dairy products. The bibliography examines first the main biochemical constituents of sheep and goat milk products but also the more specific components with potential nutritional impact and lastly it gathers information on the relationship between cheese and milk compositions and the impact of technologies. Since the composition of French small ruminant cheeses is not well established, with composition tables being old and lacking information, recent studies have been conducted in France to investigate the nutritional characteristics of sheep and goat milks and cheeses on a large scale. Goat milk cheese sampling was representative of French production, taking into account the variability linked to geographic origin, dairy or on-farm transformation and type of cheeses. Fresh lactic cheeses made with raw (6 samples) or pasteurised (6) milk, ripened lactic cheeses made with raw (11) or pasteurised (6) milk, spreads (4), soft ripened cheeses (6 “Chèvre Boite or “Brique” type cheeses) and 4 bulk raw milks were sampled twice in a summer–autumn period. These 86 samples were analysed for their nutritional value. The impact of the technological process was assessed with, for example, its effect on mineral and vitamin B content. With respect to sheep, 5 representative samples of milk were collected, just before cheese making, in the 3 main French traditional areas of dairy sheep production. The sampling was carried out 4 times in the year. The objective was to explore the variability of the nutritional characteristics of the original milk. The cheeses made with these milks were analysed after ripening with a double objective: to specify their nutritional content and to assess the relationship between milk and cheese content. Some preliminary results are given concerning fatty acids. [Copyright &y& Elsevier]

Abstract: In four flocks, 215 dairy ewes were monthly sampled, throughout lactation, in order to study the relationship between subclinical intramammary infections (IMI) and milk individual SCC (iSCC). A decision rule proposes to consider an udder as healthy (specificity=75%) if every iSCC are lower than 0.500×106 cells/ml and infected (sensitivity=82%) if at least two iSCC are higher than 1 or 1.2million cells/ml. At a flock level (annual geometric mean of bulk SCC), this rule allows the estimation of the prevalence of subclinical IMI: an annual bulk SCC of 0.650×106 cells/ml corresponds to a prevalence of 15%. These results are discussed. [Copyright &y& Elsevier]

Presents a study that estimated genetic parameters for milk somatic cell scores and relationships with production traits in French Lacaune dairy sheep. Method of the study; Results and discussion; Conclusion.

A total of 416,670 lactations for 189,101 ewes from 3,603 sires and distributed across 1,978 herd-year groups were used to estimate genetic and environmental parameters of standardized milk yield (SMYT), fertility in ewe lambs (PR1), and fertility in adult ewes (PRA). Parameters were estimated with a multiple-trait sire linear model. Heritabilities for SMYT, PR1, and PRA were 0.27 (0.009), 0.04 (0.004), and 0.05 (0.004), respectively. These results were in accordance with the literature. The genetic correlation between PR1 and PRA was 0.55, indicating that fertility is not the same trait in ewe lambs and adult ewes. The genetic correlation between milk yield and lamb fertility was not significantly different from zero. The genetic correlation between milk yield and fertility in adult ewe (-0.23) was in the range of antagonistic correlations reported in dairy cattle. Consequently, these results show that selection for milk yield can induce an indirect decrease in fertility. Nevertheless, no phenotypic decrease in fertility in artificial insemination matings has been observed in this population. This is the first time that correlation between milk yield and fertility is reported in sheep and further investigations are needed to confirm this result. [ABSTRACT FROM AUTHOR]

The outcome of an insemination depends on male and female fertility. Nevertheless, few studies have incorporated genetic evaluation of these 2 traits jointly. The aim of this work was to compare genetic parameter estimates of male and female fertility defined as success or failure to artificial insemination (AI), using 8 different models. The first 2 models were simple repeatability models studying fertility of one sex and ignoring any information of the other. Models 3 and 4 took into account the information of the other sex by the inclusion of its random permanent environmental effect, whereas models 5 and 6 included fixed effects of the other sex. Models 7 and 8 were joint genetic evaluation models of male and female fertility ignoring or considering genetic correlation. Data were composed of 147,018 AI of the Manech Tête Rousse breed recorded from 2000 to 2004 corresponding to 79,352 ewes and 963 rams. The pedigree file included 120,989 individuals. Variance component estimates from the different models were quite similar; heritabilities varied from 0.050 to 0.053 for female fertility and were near 0.003 for male fertility. Correlations among estimated breeding values in the same sex using different models were higher than 0.99. The genetic correlation between male and female fertility was not significantly different from 0. These results show that for French dairy sheep with extensive use of AI, estimation of breeding values for male and female fertility might be implemented with quite simple models. [ABSTRACT FROM AUTHOR]

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., (Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.)

Artificial inseminations (n = 678 168) recorded during 5 years in five French artificial insemination (AI) centres (2 'Lacaune', 1 'Manech tête rousse', 1 'Manech tête noire' and 1 'Basco béarnaise') were analysed to determine environmental and genetic factors affecting the insemination results. Analyses within centre-breed were performed using a linear model, which jointly estimates male and female fertility. This model combined four categories of data: the environmental effects related to the female, those related to the male, the non-sex-specific effects and finally the pedigree data of these males and females. After selection, the environmental female effects considered were age, synchronisation (0/1) on the previous year, total number of synchronisations during the female reproductive life, time interval between previous lambing and insemination, already dry or still lactating (0/1) when inseminated, and milk quantity produced during the previous year expressed as quartiles intra herd * year. The environmental male effects were motility and concentration of the semen. The non-sex-specific effects were the inseminator, the interaction herd * year nested within the inseminator, considered as random effects and the interaction year * season considered as a fixed effect. The main variation factors of AI success were relative to non-sex-specific effects and to female effects. Heritability estimates varied from 0.001 to 0.005 for male fertility and from 0.040 to 0.078 for female fertility. Repeatability estimates varied from 0.007 to 0.015 for male fertility and from 0.104 to 0.136 for female fertility. These parameters indicate that genetic improvement of AI results through a classical polygenic selection would be difficult. Moreover, in spite of the large quantity of variation factors fitted by the joint model, a very large residual variance remained unexplained.

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.

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.

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.

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.