Alternative hormone-free reproduction management of a dairy sheep flock disrupts the farm's annual feeding system calendar and its associated strategies.

Hormone-free (HF) reproduction in dairy sheep is a way to meet current societal demands, but it requires being prepared for collateral impacts on related system components. The efficiency of HF practices (e.g., using the male effect for estrus induction and synchronization) is uncertain compared with hormonal treatment (HT). For example, these practices can lead to higher variability in the flock physiological stage patterns throughout the year, which has direct consequences for feeding regimens. The objective of this work was to simulate the impacts of HF reproduction management, including artificial insemination (AI), on the temporal distribution of productive performance and nutritional requirements of a conventional dairy sheep flock. Using the REPROsheep2.0 model, 6 scenarios were compared over one typical production season for the same flock (n = 597 Lacaune ewes) intensively reared in the Roquefort region of France. These scenarios depicted reproduction with HT and AI in mid-May (Early); HT and AI in July (Summer Late); HT and AI in November (Autumn Late); and their HF versions (HF-Early; HF-Summer Late, and HF-Autumn Late, respectively). In all HF scenarios, a reduction in the number of ewes lambing and consequently in the annual milk production of the farm was observed (-1 to -7%). This affected annual performance with a subsequent decrease of total annual nutritional requirements (-2 to -6%). The HF scenarios resulted in a staggering of lambing events with a 7- to 14-d shift in the appearance of milk production peaks and related nutritional requirements compared with the HT scenarios. Transitioning from conventional to HF reproduction management, while preserving AI, would increase farm workload, lengthen milking period operations, and necessitate a readjustment of feeding management strategies with regard to available feed resources. Depending on the production season, the observed delay in the distribution of nutritional requirements could be either an attractive or an unfavorable outcome for farmers. The delay may be concordant, for example, with the recently observed impacts of climate change on seasonal forage availability in Mediterranean regions (less spring herbage production and warmer temperatures) that are affecting farmers' decision-making about the most efficient use of forage and feed resources.

Measuring liveweight changes in lactating dairy ewes with an automated walk-over-weighing system.

Monitoring liveweight (LW) is an important part of sound management practices at the individual and flock level (e.g., controlling for nutritional status based on body condition, reproduction, and health-related issues), but it is time consuming and stressful. To our knowledge, no literature has reported on the evaluation of automated weighing systems in dairy sheep as an alternative to conventional static scales. The objective of this research was to evaluate the practical feasibility of using an automated walk-over-weighing (WoW) prototype to measure daily LW changes in dairy ewes without human intervention. We used adult Lacaune dairy ewes in 2 complementary trials conducted indoors. Trial 1 aimed at evaluating the repeatability, precision, and accuracy of LW measures recorded using WoW scales compared with a static scale (the gold standard). Forty-two adult ewes (LW ± standard deviation = 71.3 ± 10.4 kg) were randomly drafted from the main flock and used in a 1-day session. The trial included 3 passages. In each passage, ewes were weighed first on a static scale; once a static position was achieved and LW recorded, they continued the circuit and immediately traversed the WoW scale for an automated LW record. Trial 2 aimed to demonstrate the feasibility of using the WoW device under real-world conditions in a dairy sheep-farming system. The WoW scale was installed in the exit race of the milking parlor and evaluated over 7 wk with adult ewes in mid lactation (n = 93; LW 78.5 ± 8.1 kg). Once the ewes were acclimated to the WoW system, 1 group of ewes (n = 48) continued to receive the same feeding regimen (controls), and the other group (n = 45) underwent a nutritional challenge [challenged; 2 wk of undernutrition and then back to control regimen (refeeding) for 1 wk]. We evaluated the ability of the WoW to detect small changes in LW. We collected LW data (2 weighings per ewe per day) from the WoW after each of the 2 milking sessions (morning and evening). We also obtained LW values by weighing the ewes using a static scale once a week. The automated WoW system showed substantial agreement with the gold standard when assessed using Lin's concordance correlation coefficient and Bland and Altman's method, largely due to high repeatability. The WoW system was adequate for detecting small daily variations in LW during undernutrition and refeeding periods. Misbehaviors resulted in spurious WoW values in trial 2, requiring us to use filtration methods to exclude outlier weights and allow meaningful assessment of small LW changes. The WoW system evaluated here is an alternative to the static scales conventionally used on dairy sheep farms. If sound filtration of raw data is applied, WoW could contribute to the close (daily) monitoring of individual LW without operator intervention (i.e., voluntary weighing) and taking animal welfare into account (i.e., no stress related to the weighing session on static scales).

Somatic cell count-based selection reduces susceptibility to energy shortage during early lactation in a sheep model.

During the transition from late gestation to early lactation ruminants experience a negative energy balance (NEB), which is considered to increase susceptibility to mammary infections. Our previous study in 2 divergent lines of sheep selected for high and low somatic cell score (SCS) suggested an association between the response to NEB and genetic susceptibility to mastitis. Forty-eight early-lactation primiparous dairy ewes from the 2 SCS genetic lines were allocated to 2 homogeneous subgroups-an NEB group, which was energy restricted and received 60% of the energy requirements for 15 d, and a control-fed group-to obtain 4 balanced groups of 12 ewes: high-SCS positive energy balance, low-SCS positive energy balance, high-SCS NEB, and low-SCS NEB. High-SCS ewes showed greater weight loss and increased plasmatic concentrations of ß-hydroxybutyrate and nonesterified fatty acids than low-SCS ewes when confronted with an induced NEB. The aim of this study was to further characterize this interaction by combining transcriptomic and phenotypic data with a generalized partial least squares discriminant analysis using mixOmics package framework. A preliminary analysis using 3 blocks of phenotypes (fatty acids, weight and production, blood metabolites) revealed a high correlation between fat-to-protein ratio, ß-hydroxybutyrate, and nonesterified fatty acids concentrations with milk long-chain fatty acid yields. These phenotypes allowed good discrimination of the energy-restricted high-SCS ewes and confirmed a high level of adipose tissue mobilization in this group. A second analysis, which included RNA-seq data, revealed high correlations between the long-chain fatty acid yields in milk and PDK4, CPT1A, SLC25A20, KLF10, and KLF11 expression, highlighting the relationship between mobilization of body reserves and enhanced fatty acids utilization for energy production in blood cells. Finally, analysis of milk composition measured in 1,025 ewes from the 2 genetic lines over 10 yr confirmed significant higher fat-to-protein ratio in high-SCS ewes in early lactation. Altogether, our results strongly confirmed a genetic link between susceptibility to mastitis and metabolic adaptation to energy shortage. Improving genetic resistance to mastitis using SCS should be accompanied by a favorable effect on the response to metabolic stress, especially in highly stressful early lactation. Moreover, this study suggests that the fat-to-protein ratio could be used as a low-cost tool for monitoring energy balance and ketosis during this critical phase of lactation.

Response to dietary-induced energy restriction in dairy sheep divergently selected for resistance or susceptibility to mastitis.

Dairy ruminants experiencing a severe postpartum negative energy balance (NEB) are considered to be more susceptible to mastitis. Although the genetic variability of mastitis resistance is well established, the biological basis of the link between energy metabolism and resistance is mostly unknown. The aim of this study was to characterize the effect of NEB on metabolism and immune response according to the genetic background for mastitis resistance or susceptibility. Forty-eight ewes from high and low somatic cell score (SCS) genetic lines were allocated to 2 homogeneous subgroups 2 wk after lambing: one group (NEB) received an energy-restricted diet to cover 60% of their energy requirements, and the other group received a control (positive energy balance: PEB) diet. Both diets met the protein requirements. After 10 d on either the NEB or PEB diet, all ewes were injected with a Pam3CSK4/MDP solution in one half-udder to induce an inflammatory response. The ewes were monitored for milk production, somatic cell count (SCC), body weight (BW), body condition score (BCS), and blood metabolites. Differential milk cell counts were determined by flow cytometry. Plasma concentrations of glucose, insulin, nonesterified fatty acids (NEFA), ß-hydroxybutyrate (BHB), and triiodothyronine were determined. Energy restriction resulted in an increased fat:protein ratio in milk and decreased milk yield, BW, and BCS. The NEB ewes had significantly higher NEFA and BHB and lower plasma glucose concentrations than PEB ewes, reflecting a mobilization of body reserves and ketone body synthesis. High-SCS ewes had a higher SCS than low-SCS throughout the experiment, except after the inflammatory challenge, which resulted in similar SCS in all 4 groups. A noteworthy interaction between genetic background and diet was evidenced on metabolic parameters and BW. Indeed, high-SCS ewes subjected to NEB showed greater decrease in BW and increased NEFA and BHB concentrations compared with low-SCS ewes. Thus, NEB in early lactation led to extensive mobilization of body reserves and intense ketone body synthesis in mastitis-susceptible sheep. These results reinforce the hypothesis of a genetic association between mastitis susceptibility and energy metabolism and open the way to further studies on the biological basis for this association.

Opportunities and limits of commercial farm data to study the genetic determinism of feed efficiency throughout lactation in dairy sheep.

The collective economic and environmental interest of the whole dairy sheep sector is to reduce feed costs and the negative impact of milk production on the environment. Thus, this study focused on the characterisation and genetic selection potential of feed efficiency in the Lacaune breed. Estimates for feed efficiency in dairy ewes are limited, mainly due to a lack of individual feed intake measurements in the sheepfold or in the pasture. We estimated the genetic parameters for two approximated (not entirely based on individual data) feed efficiency traits (lactation feed conversion ratio (LFCR) and residual energy intake (REI)) and daily milk yield (DMY) at different stages of lactation and throughout lactation. The accuracy of the efficiency traits was first evaluated on samples from Lacaune dairy ewes that were monitored individually, especially for their feed intake. Then, feed efficiency estimation methods were applied on eight commercial farms corresponding to 4 680 Lacaune dairy ewes over two milk lactations (30 854 records). Animals were collectively (for a large part of feed intake) or individually (for milk performance and dynamics of body fat reserves) monitored at different lactation stages. The heritabilities of LFCR and REI were estimated over lactations at 0.10 ± 0.01 and 0.11 ± 0.01, respectively. High genetic correlations were observed between the two efficiency traits and milk production traits, with a genetic correlation between LFCR and DMY of 0.74 ± 0.04 and between REI and DMY of -0.79 ± 0.04. A strong influence of environmental factors such as farm, year of milk production and lactation stage affected the genetic link between REI and milk production traits. Efficiency values observed in early lactation when animals were bred in the sheepfold were less genetically correlated with values obtained later in lactation when animals were grass-fed. However, individual characterisation of feed efficiency remains difficult due to the collective feeding context in dairy ewe farms.