Gilles Lagriffoul

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.

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.

SIEOL, information system for genetic, technical and economic support for French dairy sheep breeders

In France, the 5,200 sheep dairy farms are mainly located in three traditional sheep milk production areas: Roquefort, in the south of the Massif Central (43% of the farms), the French western Pyrenees (41%), and Corsica (8%). Production is characterised by five local breeds, a traditional management system, and milk processing into PDO cheeses. During the last 20 years, the decrease in the number of dairy farms did not prevent milk production from increasing from 120 million litres in 1985 to 260 million litres in 2006. Both the improvement of the management systems and the efficiency of the selection scheme contributed to this evolution. On the farm, the same technician records milk yields and provides genetic, technical and economic advice to the breeders. To help the technicians, since 2005 an information system called SIEOL has been implemented by the technical organisations. SIEOL manages genetic, technical and technical-economic data by collecting all essential information for collective use (e.g. genetic evaluation for the management of selection) but also for use by the farm technician (e.g. to track down the least productive ewes or to improve breeder’s income). Today, the SIEOL system is used by 48% of all dairy sheep farms of France and for 61% of dairy ewes.