Short-term responses of meat ewes facing an acute nutritional challenge in early-mid lactation.

Simulating a consequence of a climate change event on feed availability, responses of Mediterranean meat ewes facing an acute undernutritional challenge (CHA; i.e., fed only low nutritional value cereal straw) were evaluated at a sensitive physiological stage (i.e., early suckling). Forty Romane ewes were chosen at early-mid pregnancy (around 2 mo) according to parity (20 primiparous, PRIM; 20 multiparous, MULT); feed efficiency genetic line of their sires (residual feed intake [RFI]; efficient, RFI-, n = 10 per parity; inefficient, RFI+, n = 10 per parity); litter size (i.e., bearing twins, diagnosed by ultrasonography); body weight (BW, kg) and body condition score (BCS) (initial BW and BCS [mean ±â€…SD]: 51.6 ±â€…7.41 kg; 2.5 ±â€…0.20, respectively; representing flock' averages per parity). Effects on dry matter intake (DMI), ewes' BW and BCS, subcutaneous dorsal fat thickness (DFT), energy metabolism (plasma non-esterified fatty acids [NEFA], ß-hydroxybutyrate (ß-OHB), glucose, urea, triiodothyronine [T3]), and lambs' growth (BW and average daily gain [ADG]; g/d) were examined before, during and after CHA. Individuals' profiles of the response-recovery to CHA were described using a piecewise mixed-effects model. The fixed effect of parity and genetic line and the random effect of individual (ewe) were considered. A linear mixed-effects model was fitted to explore the effects on lambs' growth. The 2-d straw-only CHA had significant effects on most of the recorded parameters. Meaningful drops and recoveries were observed on ewes' DMI, BW, and DFT with effect on postchallenge levels. BW, BCS, DFT, or DMI were also affected by parity (MULT > PRIM) but not by genetic line. Plasma NEFA, ß-OHB, glucose, urea, and T3 responded well to CHA with drops in T3, urea, and glucose levels, whereas NEFA and ß-OHB significantly increased after CHA. MULT ewes presented sharper ß-OHB recovery from CHA than PRIM (P ≤ 0.05). With this study, we provide tangible and necessary data for an emerging field of research. Our results give new insights into how such a short and abrupt CHA affects some key zootechnical and physiological parameters, and to what extent the impacts of CHA and the ewes' response-recovery are influenced. It also revealed potential between-individual differences in the adaptive capacities of ewes, which require further exploration.

Disentangling the relative roles of resource acquisition and allocation on animal feed efficiency: insights from a dairy cow model.

BACKGROUND: Feed efficiency of farm animals has greatly improved through genetic selection for production. Today, we are faced with the limits of our ability to predict the effect of selection on feed efficiency, partly because the relative importance of the components of this complex phenotype changes across environments. Thus, we developed a dairy cow model that incorporates the dynamic interplay between life functions and evaluated its behaviour with a global sensitivity analysis on two definitions of feed efficiency. A key model feature is to consider feed efficiency as the result of two processes, acquisition and allocation of resources. Acquisition encapsulates intake and digestion, and allocation encapsulates partitioning rules between physiological functions. The model generates genetically-driven trajectories of energy acquisition and allocation, with four genetic-scaling parameters controlling these processes. Model sensitivity to these parameters was assessed with a complete factorial design. RESULTS: Acquisition and allocation had contrasting effects on feed efficiency (ratio between energy in milk and energy acquired from the environment). When measured over a lactation period, feed efficiency was increased by increasing allocation to lactation. However, at the lifetime level, efficiency was increased by decreasing allocation to growth and increasing lactation acquisition. While there is a strong linear increase in feed efficiency with more allocation to lactation within a lactation cycle, our results suggest that there is an optimal level of allocation to lactation beyond which increasing allocation to lactation negatively affects lifetime feed efficiency. CONCLUSIONS: We developed a model to predict lactation and lifetime feed efficiency and show that breaking-down feed conversion into acquisition and allocation, and introducing genetically-driven trajectories that control these mechanisms, permitted quantification of their relative roles on feed efficiency. The life stage at which feed efficiency is evaluated appears to be a key aspect for selection. In this model, body reserves are also a key component in the prediction of lifetime feed efficiency since they integrate the feedback of acquisition and allocation on survival and reproduction. This modelling approach provided new insights into the processes that underpin lifetime feed efficiency in dairy cows.

Modeling PCB transfer into hen eggs: influence of physiological characteristics of the animal.

Laying hens are likely to be exposed to a wide range of persistent organic pollutants (POPs), including polychlorinated biphenyls (PCBs). To improve the safety of poultry farming systems in terms of POPs, the present research focused on assessing the impact of physiological characteristics of the hen on the transfer of ingested PCBs to eggs. Modeling was used as a research tool to explore the impact of some physiological characteristics on the transfer of PCBs in the laying hen. The mathematical model simulates the dynamics of the size of the lipid compartments in the animal and the frequency of laying, with the PCB concentrations in egg yolk and adipose tissue being model outputs. Simulations were run to assess effects of animal characteristics on the transfer of PCBs to eggs. Laying rate proportionally influenced the PCB level of eggs and adipose tissue at steady state. Body fat diluted absorbed PCBs in the absence of laying and significantly influenced the decontamination rate of tissues during depuration after an exposure period. Application of the present model to actual exposure cases highlights its value in improving the support of risk management in livestock farming.