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Repeatability of traits for characterizing feed intake patterns in dairy goats: a basis for phenotyping in the precision farming context
- S. Giger-Reverdin, C. Duvaux-Ponter, D. Sauvant, N. C. Friggens
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In ruminants, feeding behaviour variables are parameters involved in feed efficiency that show variation among individuals. This study aimed to evaluate during the first two production cycles in ruminants the repeatability of feed intake pattern, which is an important aspect of feeding behaviour. Thirty-five dairy goats from Alpine or Saanen breeds were housed in individual pens at four periods (end of first gestation, middle of first and second lactations and middle of second gestation which is also the end of first lactation) and fed a total mixed ration (TMR) ad libitum. Individual cumulative dry matter intake (DMI) was automatically measured every 2 min during the last 4 days of each period. Feed intake pattern was characterized by several measures related to the quantity of feed eaten or to the rate of intake during the 15 h following the afternoon feed delivery. Two main methods were used: modelling cumulative DMI evolution by an exponential model or by a segmentation-clustering method. The goat ability to sort against dietary fibre was also evaluated. There was a very good repeatability of the aggregate measures between days within a period for a given goat estimated by the day effect within breed and goat, tested on the residual variance (P > 0.95). The correlations between periods were the highest between the second and either the third or fourth periods. With increasing age, goats sorted more against the fibrous part of the TMR and increased their initial rate of intake. Alpine goats ate more slowly than Saanen goats but ate during a longer duration. Principal component analysis (PCA) was performed on all the aggregate measures of feed intake patterns. The factor score plots generated by the PCA highlighted the opposition between the different measures of feed intake patterns and the sorting behaviour. The projection of the animals on the scoring plots showed a breed effect and that there was a continuum for the feed intake pattern of goats. In conclusion, this study showed that the feed intake pattern was highly repeatable for an animal in a given period and between periods. This means that phenotyping goats in a younger age might be of interest, either to select them on feeding behaviour and choose preferentially the slow eaters or to adapt the quantity offered and restrict feed delivery to the fast eaters in order to increase feed efficiency and welfare by limiting the occurrence of acidosis, for example.
Towards the quantitative characterisation of piglets’ robustness to weaning: a modelling approach
- M. Revilla, N. C. Friggens, L. P. Broudiscou, G. Lemonnier, F. Blanc, L. Ravon, M. J. Mercat, Y. Billon, C. Rogel-Gaillard, N. Le Floch, J. Estellé, R. Muñoz-Tamayo
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Weaning is a critical transition phase in swine production in which piglets must cope with different stressors that may affect their health. During this period, the prophylactic use of antibiotics is still frequent to limit piglet morbidity, which raises both economic and public health concerns such as the appearance of antimicrobial-resistant microbes. With the interest of developing tools for assisting health and management decisions around weaning, it is key to provide robustness indexes that inform on the animals’ capacity to endure the challenges associated with weaning. This work aimed at developing a modelling approach for facilitating the quantification of piglet resilience to weaning. A total of 325 Large White pigs weaned at 28 days of age were monitored and further housed and fed conventionally during the post-weaning period without antibiotic administration. Body weight and diarrhoea scores were recorded before and after weaning, and blood was sampled at weaning and 1 week later for collecting haematological data. A dynamic model was constructed based on the Gompertz–Makeham law to describe live weight trajectories during the first 75 days after weaning, following the rationale that the animal response is partitioned in two time windows (a perturbation and a recovery window). Model calibration was performed for each animal. Our results show that the transition time between the two time windows, as well as the weight trajectories are characteristic for each individual. The model captured the weight dynamics of animals at different degrees of perturbation, with an average coefficient of determination of 0.99, and a concordance correlation coefficient of 0.99. The utility of the model is that it provides biologically meaningful parameters that inform on the amplitude and length of perturbation, and the rate of animal recovery. Our rationale is that the dynamics of weight inform on the capability of the animal to cope with the weaning disturbance. Indeed, there were significant correlations between model parameters and individual diarrhoea scores and haematological traits. Overall, the parameters of our model can be useful for constructing weaning robustness indexes by using exclusively the growth curves. We foresee that this modelling approach will provide a step forward in the quantitative characterisation of robustness.
Isolating the cow-specific part of residual energy intake in lactating dairy cows using random regressions
- A. Fischer, N. C. Friggens, D. P. Berry, P. Faverdin
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The ability to properly assess and accurately phenotype true differences in feed efficiency among dairy cows is key to the development of breeding programs for improving feed efficiency. The variability among individuals in feed efficiency is commonly characterised by the residual intake approach. Residual feed intake is represented by the residuals of a linear regression of intake on the corresponding quantities of the biological functions that consume (or release) energy. However, the residuals include both, model fitting and measurement errors as well as any variability in cow efficiency. The objective of this study was to isolate the individual animal variability in feed efficiency from the residual component. Two separate models were fitted, in one the standard residual energy intake (REI) was calculated as the residual of a multiple linear regression of lactation average net energy intake (NEI) on lactation average milk energy output, average metabolic BW, as well as lactation loss and gain of body condition score. In the other, a linear mixed model was used to simultaneously fit fixed linear regressions and random cow levels on the biological traits and intercept using fortnight repeated measures for the variables. This method split the predicted NEI in two parts: one quantifying the population mean intercept and coefficients, and one quantifying cow-specific deviations in the intercept and coefficients. The cow-specific part of predicted NEI was assumed to isolate true differences in feed efficiency among cows. NEI and associated energy expenditure phenotypes were available for the first 17 fortnights of lactation from 119 Holstein cows; all fed a constant energy-rich diet. Mixed models fitting cow-specific intercept and coefficients to different combinations of the aforementioned energy expenditure traits, calculated on a fortnightly basis, were compared. The variance of REI estimated with the lactation average model represented only 8% of the variance of measured NEI. Among all compared mixed models, the variance of the cow-specific part of predicted NEI represented between 53% and 59% of the variance of REI estimated from the lactation average model or between 4% and 5% of the variance of measured NEI. The remaining 41% to 47% of the variance of REI estimated with the lactation average model may therefore reflect model fitting errors or measurement errors. In conclusion, the use of a mixed model framework with cow-specific random regressions seems to be a promising method to isolate the cow-specific component of REI in dairy cows.
Modeling homeorhetic trajectories of milk component yields, body composition and dry-matter intake in dairy cows: Influence of parity, milk production potential and breed
- J. B. Daniel, N. C. Friggens, H. van Laar, K. L. Ingvartsen, D. Sauvant
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The control of nutrient partitioning is complex and affected by many factors, among them physiological state and production potential. Therefore, the current model aims to provide for dairy cows a dynamic framework to predict a consistent set of reference performance patterns (milk component yields, body composition change, dry-matter intake) sensitive to physiological status across a range of milk production potentials (within and between breeds). Flows and partition of net energy toward maintenance, growth, gestation, body reserves and milk components are described in the model. The structure of the model is characterized by two sub-models, a regulating sub-model of homeorhetic control which sets dynamic partitioning rules along the lactation, and an operating sub-model that translates this into animal performance. The regulating sub-model describes lactation as the result of three driving forces: (1) use of previously acquired resources through mobilization, (2) acquisition of new resources with a priority of partition towards milk and (3) subsequent use of resources towards body reserves gain. The dynamics of these three driving forces were adjusted separately for fat (milk and body), protein (milk and body) and lactose (milk). Milk yield is predicted from lactose and protein yields with an empirical equation developed from literature data. The model predicts desired dry-matter intake as an outcome of net energy requirements for a given dietary net energy content. The parameters controlling milk component yields and body composition changes were calibrated using two data sets in which the diet was the same for all animals. Weekly data from Holstein dairy cows was used to calibrate the model within-breed across milk production potentials. A second data set was used to evaluate the model and to calibrate it for breed differences (Holstein, Danish Red and Jersey) on the mobilization/reconstitution of body composition and on the yield of individual milk components. These calibrations showed that the model framework was able to adequately simulate milk yield, milk component yields, body composition changes and dry-matter intake throughout lactation for primiparous and multiparous cows differing in their production level.
Impact of hygiene of housing conditions on performance and health of two pig genetic lines divergent for residual feed intake
- A. Chatelet, F. Gondret, E. Merlot, H. Gilbert, N. C. Friggens, N. Le Floc’h
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Pigs selected for high performance may be more at risk of developing diseases. This study aimed to assess the health and performance of two pig lines divergently selected for residual feed intake (RFI) (low RFI (LRFI) v. high RFI (HRFI)) and housed in two contrasted hygiene conditions (poor v. good) using a 2×2 factorial design (n=40/group). The challenge period (Period 1), started on week zero (W0) when 12-week-old pigs were transferred to good or poor housing conditions. At week 6 (W6), half of the pigs in each group were slaughtered. During a recovery period (Period 2) from W6 to W13 to W14, the remaining pigs (n=20/group) were transferred in good hygiene conditions before being slaughtered. Blood was collected every three (Period 1) or 2 weeks (Period 2) to assess blood indicators of immune and inflammatory responses. Pulmonary lesions at slaughter and performance traits were evaluated. At W6, pneumonia prevalence was greater for pigs housed in poor than in good conditions (51% v. 8%, respectively, P<0.001). Irrespective of hygiene conditions, lung lesion scores were lower for LRFI pigs than for HRFI pigs (P=0.03). At W3, LRFI in poor conditions had the highest number of blood granulocytes (hygiene×line, P=0.03) and at W6, HRFI pigs in poor conditions had the greatest plasma haptoglobin concentrations (hygiene×line, P=0.02). During Period 1, growth rate and growth-to-feed ratio were less affected by poor hygiene in LRFI pigs than in HRFI pigs (hygiene×line, P=0.001 and P=0.02, respectively). Low residual feed intake pigs in poor conditions ate more than the other groups (hygiene×line, P=0.002). Irrespective of the line, fasting plasma glucose concentrations were higher in poor conditions, whereas fasting free fatty acids concentrations were lower than in good conditions. At the end of Period 2, pneumonia prevalence was similar for both housing conditions (39% v. 38%, respectively). During Period 2, plasma protein concentrations were greater for pigs previously housed in poor than in good conditions during Period 1. Immune traits, gain-to-feed ratio, BW gain and feed consumption did not differ during Period 2. Nevertheless, at W12, BW of HRFI previously housed in poor conditions was 13.4 kg lower than BW of HRFI pigs (P<0.001) previously housed in good conditions. In conclusion, health of the most feed efficient LRFI pigs was less impaired by poor hygiene conditions. This line was able to preserve its health, growth performance and its feed ingestion to a greater extent than the less efficient HRFI line.
Review: Deciphering animal robustness. A synthesis to facilitate its use in livestock breeding and management
- N. C. Friggens, F. Blanc, D. P. Berry, L. Puillet
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As the environments in which livestock are reared become more variable, animal robustness becomes an increasingly valuable attribute. Consequently, there is increasing focus on managing and breeding for it. However, robustness is a difficult phenotype to properly characterise because it is a complex trait composed of multiple components, including dynamic elements such as the rates of response to, and recovery from, environmental perturbations. In this review, the following definition of robustness is used: the ability, in the face of environmental constraints, to carry on doing the various things that the animal needs to do to favour its future ability to reproduce. The different elements of this definition are discussed to provide a clearer understanding of the components of robustness. The implications for quantifying robustness are that there is no single measure of robustness but rather that it is the combination of multiple and interacting component mechanisms whose relative value is context dependent. This context encompasses both the prevailing environment and the prevailing selection pressure. One key issue for measuring robustness is to be clear on the use to which the robustness measurements will employed. If the purpose is to identify biomarkers that may be useful for molecular phenotyping or genotyping, the measurements should focus on the physiological mechanisms underlying robustness. However, if the purpose of measuring robustness is to quantify the extent to which animals can adapt to limiting conditions then the measurements should focus on the life functions, the trade-offs between them and the animal’s capacity to increase resource acquisition. The time-related aspect of robustness also has important implications. Single time-point measurements are of limited value because they do not permit measurement of responses to (and recovery from) environmental perturbations. The exception being single measurements of the accumulated consequence of a good (or bad) adaptive capacity, such as productive longevity and lifetime efficiency. In contrast, repeated measurements over time have a high potential for quantification of the animal’s ability to cope with environmental challenges. Thus, we should be able to quantify differences in adaptive capacity from the data that are increasingly becoming available with the deployment of automated monitoring technology on farm. The challenge for future management and breeding will be how to combine various proxy measures to obtain reliable estimates of robustness components in large populations. A key aspect for achieving this is to define phenotypes from consideration of their biological properties and not just from available measures.
Association between body energy content in the dry period and post-calving production disease status in dairy cattle
- G. L. Smith, N. C. Friggens, C. J. Ashworth, M. G. G. Chagunda
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The transition from gestation to lactation is marked by significant physiological changes for the individual cow such that disease incidence is highest in early lactation. Around the time of calving, cows rely on mobilisation of body energy reserves to fill the energy deficit created by an increase in nutrient demands at a time of restricted feed intake. It is well established that monitoring of body energy reserves in lactation is an important component of herd health management. However, despite their influence on future health and productivity, monitoring of body energy reserves in the dry period is often sparse. Further, there is increasing concern that current dry off management is inappropriate for modern cattle and may influence future disease risk. This study aimed to identify candidate indicators of early lactation production disease from body energy data collected in the dry period and production data recorded at the time of dry off. Retrospective analysis was performed on 482 cow-lactations collected from a long-term Holstein-Friesian genetic and management systems project, the Langhill herd in Scotland. Cow-lactations were assigned to one of four health groups based on health status in the first 30 days of lactation. These four groups were as follows: healthy, reproductive tract disorders (retained placenta and metritis), subclinical mastitis and metabolic disorders (ketosis, hypocalcaemia, hypomagnesaemia and left displaced abomasum). ANOVA, employing a GLM was used to determine effects for the candidate indicator traits. Cows which were diagnosed with a reproductive tract disorder in the first 30 days of lactation experienced a significantly greater loss in body energy content, body condition score and weight in the preceding dry period than healthy cows. The rate of change in body energy content during the first 15 days of the dry period was −18.26 MJ/day for cows which developed reproductive tract disorder compared with +0.63 MJ/day for healthy cows. Cows diagnosed with subclinical mastitis in the first 30 days of lactation had significantly greater milk yield at dry off in the previous lactation than cows that developed a reproductive tract disorder or metabolic disease in addition to a significantly higher yield to body energy content ratio at dry off than healthy cows. Physiological and production traits recorded in the lactation and dry period preceding a disease event differed between cows which developed different diseases post-calving. Differences in these traits allow the development of new disease indicators for use in models for the prediction of disease risk in the transition period.
Milk yield and milk composition responses to change in predicted net energy and metabolizable protein: a meta-analysis
- J. B. Daniel, N. C. Friggens, P. Chapoutot, H. Van Laar, D. Sauvant
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Using a meta-analysis of literature data, this study aimed to quantify the dry matter (DM) intake response to changes in diet composition, and milk responses (yield, milk component yields and milk composition) to changes in dietary net energy for lactation (NEL) and metabolizable protein (MP) in dairy cows. From all studies included in the database, 282 experiments (825 treatments) with experimentally induced changes in either NEL or MP content were kept for this analysis. These treatments covered a wide range of diet characteristics and therefore a large part of the plausible NEL and MP contents and supplies that can be expected in practical situations. The average MP and NEL contents were, respectively (mean±SD), 97±12 g/kg DM and 6.71±0.42 MJ/kg DM. On a daily supply basis, there were high between-experiment correlations for MP and NEL above maintenance. Therefore, supplies of MP and NEL above maintenance were, respectively, centred on MP supply for which MP efficiency into milk protein is 0.67, and NEL above maintenance supply for which the ratio of NEL milk/NEL above maintenance is 1.00 (centred variables were called MP67 and NEL100). The majority of the selected studies used groups of multiparous Holstein-Friesian cows in mid lactation, milked twice a day. Using a mixed model, between- and within-experiment variation was split to estimate DM intake and milk responses. The use of NEL100 and MP67 supplies substantially improved the accuracy of the prediction of milk yield and milk component yields responses with, on average, a 27% lower root mean square error (RMSE) relative to using dietary NEL and MP contents as predictors. For milk composition (g/kg), the average RMSE was only 3% lower on a supply basis compared with a concentration basis. Effects of NEL and MP supplies on milk yield and milk component yields responses were additive. Increasing NEL supply increases energy partitioning towards body reserve, whereas increasing MP supply increases the partition of energy towards milk. On a nitrogen basis, the marginal efficiency decreases with increasing MP supply from 0.34 at MP67=−400 g/day to 0.07 at MP67=300 g/day. This difference in MP67 supply, assuming reference energy level of NEL100=0, equates to a global nitrogen efficiency decrease from 0.82 to 0.58. The equations accurately describe DM intake response to change in dietary contents and milk responses to change in dietary supply and content of NEL and MP across a wide range of dietary compositions.
Effects of the level of early productivity on the lifespan of ewes in contrasting flock environments
- F. Douhard, N. B. Jopson, N. C. Friggens, P. R. Amer
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Selection for high levels of prolificacy has allowed substantial improvements in the production efficiency of New Zealand (NZ) sheep farms, but the consequences on ewe lifetime performance are mostly unknown. In this study, the relationship between the level of prolificacy early in ewes’ productive lives and their probability to survive later (i.e. stayability) was evaluated in two contrasting NZ flock environments. Records were obtained from 6605 ewes from four ram breeder flocks representing either a moderate (n=2) or a highly variable (n=2) nutritional environment. All ewes lambed for the first time at 2 years of age and were mated the following year. The number of lambs born during the first 2 years of productive life (NLB2–3) was used as a measure of early prolificacy. Effects of NLB2–3 on stayability to 4, 5, 6, 7 and 8 years old were analysed using logistic regression. Curvilinear effects (logit-transformed) were detected (P<0.05) until stayability to 6 years and to 8 years old in the highly variable and the moderate environment, respectively. The NLB2–3 that resulted in maximum expected stayability to various ages was 3.9 to 4.2, and 4.5 to 4.7 lambs in the highly variable and in the moderate flock environments, respectively. In addition, ewe stayability was reduced when the proportion of the litter that survived from birth to weaning (i.e. ewe rearing ability) was submaximal during the early productive life. High prolific ewes had a low rearing ability whatever the environment whereas the rearing ability of lowly prolific ewes was apparently more sensitive to the nutritional environment. The poor maternal performance of ewes with low levels of NLB2–3 led to a premature culling by breeders whereas the high early reproductive effort associated with high levels of NLB2–3 seemed to be at the cost of ewes’ survival, even in the moderate flock environment. In conclusion, the flock environment influenced the level of early prolificacy beyond which ewe longevity was reduced. It is suggested that further selection for high and early prolificacy in NZ flocks is likely to impair ewes’ lifetime productivity.
Modelling impacts of performance on the probability of reproducing, and thereby on productive lifespan, allow prediction of lifetime efficiency in dairy cows
- H. N. Phuong, P. Blavy, O. Martin, P. Schmidely, N. C. Friggens
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Reproductive success is a key component of lifetime efficiency – which is the ratio of energy in milk (MJ) to energy intake (MJ) over the lifespan, of cows. At the animal level, breeding and feeding management can substantially impact milk yield, body condition and energy balance of cows, which are known as major contributors to reproductive failure in dairy cattle. This study extended an existing lifetime performance model to incorporate the impacts that performance changes due to changing breeding and feeding strategies have on the probability of reproducing and thereby on the productive lifespan, and thus allow the prediction of a cow’s lifetime efficiency. The model is dynamic and stochastic, with an individual cow being the unit modelled and one day being the unit of time. To evaluate the model, data from a French study including Holstein and Normande cows fed high-concentrate diets and data from a Scottish study including Holstein cows selected for high and average genetic merit for fat plus protein that were fed high- v. low-concentrate diets were used. Generally, the model consistently simulated productive and reproductive performance of various genotypes of cows across feeding systems. In the French data, the model adequately simulated the reproductive performance of Holsteins but significantly under-predicted that of Normande cows. In the Scottish data, conception to first service was comparably simulated, whereas interval traits were slightly under-predicted. Selection for greater milk production impaired the reproductive performance and lifespan but not lifetime efficiency. The definition of lifetime efficiency used in this model did not include associated costs or herd-level effects. Further works should include such economic indicators to allow more accurate simulation of lifetime profitability in different production scenarios.
Lameness detection via leg-mounted accelerometers on dairy cows on four commercial farms
- V. M. Thorup, L. Munksgaard, P.-E. Robert, H. W. Erhard, P. T. Thomsen, N. C. Friggens
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Lameness in dairy herds is traditionally detected by visual inspection, which is time-consuming and subjective. Compared with healthy cows, lame cows often spend longer time lying down, walk less and change behaviour around feeding time. Accelerometers measuring cow leg activity may assist farmers in detecting lame cows. On four commercial farms, accelerometer data were derived from hind leg-mounted accelerometers on 348 Holstein cows, 53 of them during two lactations. The cows were milked twice daily and had no access to pasture. During a lactation, locomotion score (LS) was assessed on average 2.4 times (s.d. 1.3). Based on daily lying duration, standing duration, walking duration, total number of steps, step frequency, motion index (MI, i.e. total acceleration) for lying, standing and walking, eight accelerometer means and their corresponding coefficient of variation (CV) were calculated for each week immediately before an LS. A principal component analysis was performed to evaluate the relationship between the variables. The effects of LS and farm on the principal components (PC) and on the variables were analysed in a mixed model. The first four PC accounted for 27%, 18%, 12% and 10% of the total variation, respectively. PC1 corresponded to Activity variability due to heavy loading by five CV variables related to standing and walking. PC2 corresponded to Activity level due to heavy loading by MI walking, MI standing and walking duration. PC3 corresponded to Recumbency due to heavy loading by four variables related to lying. PC4 corresponded mainly to Stepping due to heavy loading by step frequency. Activity variability at LS4 was significantly higher than at the lower LS levels. Activity level was significantly higher at LS1 than at LS2, which was significantly higher than at LS4. Recumbency was unaffected by LS. Stepping at LS1 and LS2 was significantly higher than at LS3 and LS4. Activity level was significantly lower on farm 3 compared with farms 1 and 2. Stepping was significantly lower on farms 1 and 3 compared with farms 2 and 4. MI standing indicated increased restlessness while standing when cows increased from LS3 to LS4. Lying duration was only increased in lame cows. In conclusion, Activity level differed already between LS1 and LS2, thus detecting early signs of lameness, particularly through contributions from walking duration and MI walking. Lameness detection models including walking duration, MI walking and MI standing seem worthy of further investigation.
Different resource allocation strategies result from selection for litter size at weaning in rabbit does
- D. Savietto, C. Cervera, L. Ródenas, E. Martínez-Paredes, M. Baselga, F. J. García-Diego, T. Larsen, N. C. Friggens, J. J. Pascual
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This study examined the effect of long-term selection of a maternal rabbit line, solely for a reproductive criterion, on the ability of female rabbits to deal with constrained environmental conditions. Female rabbits from generations 16 and 36 (n=72 and 79, respectively) of a line founded and selected to increase litter size at weaning were compared simultaneously. Female rabbits were subjected to normal (NC), nutritional (NF) or heat (HC) challenging conditions from 1st to 3rd parturition. Animals in NC and NF were housed at normal room temperatures (18°C to 25°C) and respectively fed with control (11.6 MJ digestible energy (DE)/kg dry matter (DM), 126 g digestible protein (DP)/kg DM, and 168 g of ADF/kg DM) or low-energy fibrous diets (9.1 MJ DE/kg DM, 104 g DP/kg DM and 266 g ADF/kg DM), whereas those housed in HC were subjected to high room temperatures (25°C to 35°C) and the control diet. The litter size was lower for female rabbits housed in both NF and HC environments, but the extent and timing where this reduction took place differed between generations. In challenging conditions (NF and HC), the average reduction in the reproductive performance of female rabbits from generation 16, compared with NC, was −2.26 (P<0.05) and −0.51 kits born alive at 2nd and 3rd parturition, respectively. However, under these challenging conditions, the reproductive performance of female rabbits from generation 36 was less affected at 2nd parturition (−1.25 kits born alive), but showed a greater reduction at the 3rd parturition (−3.53 kits born alive; P<0.05) compared with NC. The results also showed differences between generations in digestible energy intake, milk yield and accretion, and use of body reserves throughout lactation in NC, HC and NF, which together indicate that there were different resource allocation strategies in the animals from the different generations. Selection to increase litter size at weaning led to increased reproductive robustness at the onset of an environmental constraint, but failure to sustain the reproductive liability when the challenge was maintained in the long term. This response could be directly related to the short-term environmental fluctuations (less severe) that frequently occur in the environment where this line has been selected.
Environmental sensitivity differs between rabbit lines selected for reproductive intensity and longevity
- D. Savietto, C. Cervera, E. Blas, M. Baselga, T. Larsen, N. C. Friggens, J. J. Pascual
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To better understand the mechanisms that allow some animals to sustain their productive effort in harsh environmental conditions, rabbit does from two selection lines (LP and V) were housed in normal (NC), nutritional (NF) or heat (HC) challenging environmental conditions from first to third partum. The LP line (n=85) was founded on reproductive longevity criteria by selecting does from commercial farms that had a minimum of 25 partum with more than 7.5 kits born alive per parity. Line V (n=79) was constituted from four specialised maternal lines into a composite synthetic line and then selected by litter size at weaning for 36 generations. Female rabbits in NC and NF environments were housed at normal room temperature (18°C to 24°C) and fed with control [11.6 MJ digestible energy (DE)/kg dry matter (DM)] or low-energy diets (9.1 MJ DE/kg DM). HC does were housed at high room temperatures (25°C to 35°C) and fed the control diet. Female rabbits in the HC and NF environments ingested 11.5% and 6% less DE than NC does, respectively (P<0.05). These differences between environments occurred in both lines, with the differences being higher for LP than for V does (+6%; P<0.05). Milk yield responses followed those of energy intake also being higher for LP does (+21.3 g/day; P<0.05). The environmental conditions did not affect the perirenal fat thickness (PFT), but a genotype by environment interaction was observed. In NC and HC, the PFT was higher for line V (+0.23 and +0.35 mm, respectively; P<0.05) than for LP does, but this was not the case at NF (−0.01 mm). Moreover, the PFT evolution was different between them. In the NC environment, LP does used the accreted PFT in late lactation (−0.29 mm), whereas V does did not (−0.08 mm). Conversely, in the HC environment, LP does showed a flat PFT evolution in late lactation, whereas V does accumulated PFT. In the NF environment, LP and V does had a similar PFT evolution. There was also a litter size reduction for V does of −2.59 kits total born in HC and −1.78 kits total born in NF environments, whereas this was not observed for LP does. The results for LP does indicate a direct use of DE ingested for reproduction with little PFT change, whereas V does actively use the PFT reserves for reproduction.
Energy balance of individual cows can be estimated in real-time on farm using frequent liveweight measures even in the absence of body condition score
- V. M. Thorup, S. Højsgaard, M. R. Weisbjerg, N. C. Friggens
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Existing methods for estimating individual dairy cow energy balance typically either need information on feed intake, that is, the traditional input–output method, or frequent measurements of BW and body condition score (BCS), that is, the body reserve changes method (EBbody). The EBbody method holds the advantage of not requiring measurements of feed intake, which are difficult to obtain in practice. The present study aimed first to investigate whether the EBbody method can be simplified by basing EBbody on BW measurements alone, that is, removing the need for BCS measurements, and second to adapt the EBbody method for real-time use, thus turning it into a true on-farm tool. Data came from 77 cows (primiparous or multiparous, Danish Holstein, Red or Jersey) that took part in an experiment subjecting them to a planned change in concentrate intake during milking. BW was measured automatically during each milking and real-time smoothed using asymmetric double-exponential weighting and corrected for the weight of milk produced, gutfill and the growing conceptus. BCS assessed visually with 2-week intervals was also smoothed. EBbody was calculated from BW changes only, and in conjunction with BCS changes. A comparison of the increase in empty body weight (EBW) estimated from EBbody with EBW measured over the first 240 days in milk (DIM) for the mature cows showed that EBbody was robust to changes in the BCS coefficients, allowing functions for standard body protein change relative to DIM to be developed for breeds and parities. These standard body protein change functions allow EBbody to be estimated from frequent BW measurements alone, that is, in the absence of BCS measurements. Differences in EBbody levels before and after changes in concentrate intake were calculated to test the real-time functionality of the EBbody method. Results showed that significant EBbody increases could be detected 10 days after a 0.2 kg/day increase in concentrate intake. In conclusion, a real-time method for deriving EBbody from frequent BW measures either alone or in conjunction with BCS measures has been developed. This extends the applicability of the EBbody method, because real-time measures can be used for decision support and early intervention.
e-Cow: an animal model that predicts herbage intake, milk yield and live weight change in dairy cows grazing temperate pastures, with and without supplementary feeding
- J. Baudracco, N. Lopez-Villalobos, C. W. Holmes, E. A. Comeron, K. A. Macdonald, T. N. Barry, N. C. Friggens
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This animal simulation model, named e-Cow, represents a single dairy cow at grazing. The model integrates algorithms from three previously published models: a model that predicts herbage dry matter (DM) intake by grazing dairy cows, a mammary gland model that predicts potential milk yield and a body lipid model that predicts genetically driven live weight (LW) and body condition score (BCS). Both nutritional and genetic drives are accounted for in the prediction of energy intake and its partitioning. The main inputs are herbage allowance (HA; kg DM offered/cow per day), metabolisable energy and NDF concentrations in herbage and supplements, supplements offered (kg DM/cow per day), type of pasture (ryegrass or lucerne), days in milk, days pregnant, lactation number, BCS and LW at calving, breed or strain of cow and genetic merit, that is, potential yields of milk, fat and protein. Separate equations are used to predict herbage intake, depending on the cutting heights at which HA is expressed. The e-Cow model is written in Visual Basic programming language within Microsoft Excel®. The model predicts whole-lactation performance of dairy cows on a daily basis, and the main outputs are the daily and annual DM intake, milk yield and changes in BCS and LW. In the e-Cow model, neither herbage DM intake nor milk yield or LW change are needed as inputs; instead, they are predicted by the e-Cow model. The e-Cow model was validated against experimental data for Holstein–Friesian cows with both North American (NA) and New Zealand (NZ) genetics grazing ryegrass-based pastures, with or without supplementary feeding and for three complete lactations, divided into weekly periods. The model was able to predict animal performance with satisfactory accuracy, with concordance correlation coefficients of 0.81, 0.76 and 0.62 for herbage DM intake, milk yield and LW change, respectively. Simulations performed with the model showed that it is sensitive to genotype by feeding environment interactions. The e-Cow model tended to overestimate the milk yield of NA genotype cows at low milk yields, while it underestimated the milk yield of NZ genotype cows at high milk yields. The approach used to define the potential milk yield of the cow and equations used to predict herbage DM intake make the model applicable for predictions in countries with temperate pastures.
Advances in predicting nutrient partitioning in the dairy cow: recognizing the central role of genotype and its expression through time
- N. C. Friggens, L. Brun-Lafleur, P. Faverdin, D. Sauvant, O. Martin
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In recent years, it has become increasingly clear that understanding nutrient partitioning is central to a much broader range of issues than just being able to predict productive outputs. The extent to which nutrients are partitioned to other functions such as health and reproduction is clearly important, as are the efficiency consequences of nutrient partitioning. Further, with increasing environmental variability, there is a greater need to be able to predict the ability of an animal to respond to the nutritional limitations that arise from the environment in which it is placed. How the animal partitions its nutrients when resources are limited, or imbalanced, is a major component of its ability to cope, that is, its robustness. There is mounting evidence that reliance on body reserves is increased and that robustness of dairy cows is reduced by selection for increased milk production. A key element for predicting the partition of nutrients in this wider context is to incorporate the priorities of the animal, that is, an explicit recognition of the role of both the cow's genotype (genetic make-up), and the expression of this genotype through time on nutrient partitioning. Accordingly, there has been a growing recognition of the need to incorporate in nutritional models these innate driving forces that alter nutrient partitioning according to physiological state, the genetically driven trajectories. This paper summarizes some of the work carried out to extend nutritional models to incorporate these trajectories, the genetic effects on them, as well as how these factors affect the homeostatic capacity of the animal. At present, there are models capable of predicting the partition of nutrients throughout lactation for cows of differing milk production potentials. Information concerning genotype and stage of lactation effects on homeostatic capacity has not yet been explicitly included in metabolic models that predict nutrient partition, although recent results suggest that this is achievable. These developments have greatly extended the generality of nutrient partitioning models with respect to the type of animal and its physiological state. However, these models remain very largely focussed on predicting partition between productive outputs and body reserves and, for the most part, remain research models, although substantial progress has been made towards developing models that can be applied in the field. The challenge of linking prediction of nutrient partitioning to its consequences on health, reproduction and longevity, although widely recognized, is only now beginning to be addressed. This is an important perspective for future work on nutrient partitioning.
Nutritional sub-fertility in the dairy cow: towards improved reproductive management through a better biological understanding
- N. C. Friggens, C. Disenhaus, H. V. Petit
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There has been a significant decline in the reproductive performance of dairy cattle in recent decades. Cows, take longer time to return to the oestrus after calving, have poorer conception rates, and show fewer signs of oestrus. Achieving good reproductive performance is an increasing challenge for the dairy producer. In this study we focus on understanding the overall biological phenomena associated with nutritional sub-fertility rather than the underlying multiplicity of physiological interactions (already described in a number of recent studies). These phenomena are important because they represent the natural adaptations of the animal for dealing with variations in the nutritional environment. They can also be used to monitor and modulate reproductive performance on-farm. There is an underlying trade-off between two aspects of reproduction: investment in the viability of the current calf and investment in future offspring. As the investment in, and viability of, the current calf is related to maternal milk production, we can expect that level of milk production per se has effects on subsequent reproductive performance (investment in future offspring). Lactating cows have a lower proportion of viable embryos, which are of poorer quality, than do non-lactating cows. The same applies to high- compared to medium-genetic merit cows. Another important biological property is the adaptive use of body reserves in support of reproduction. Orchestrated endocrine changes in pregnancy and lactation facilitate the deposition of body lipid during pregnancy and mobilisation in early lactation. When the cow fails to accumulate the reserves she needs to safeguard reproduction she delays committing to further reproductive investment. But how does the cow ‘know’ that she is failing in energy terms? We argue that the cow does this by ‘monitoring’ both the body fat mobilisation and body fatness. Excessive body fat mobilisation indicates that current conditions are worse than expected. Body fatness indicates the future ability of the cow to safeguard her reproductive investment is compromised. Both delay further reproductive commitment. The relationship between reproductive performance and; milk production as an index of maternal investment, body fatness as an index of ability to safeguard reproductive investment, and body fat mobilisation as an index of the current nutritional environment – are examined. Nutritional strategies that seek to modulate body mobilisation and the endocrine environment by use of glucogenic and lipogenic diets, and the use of in-line progesterone profiles to monitor reproductive status are then discussed in this biological context.
Energy intake in late gestation affects blood metabolites in early lactation independently of milk production in dairy cows
- N. I. Nielsen, A. Hameleers, F. J. Young, T. Larsen, N. C. Friggens
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The present experiment examined the effect of offering either a high- (H) or low- (L) energy-density diet in late gestation and early lactation on physiological parameters, body condition score (BCS) and milk production in early lactation. In all, 40 multiparous Holstein cows were randomly allocated to one of four treatments in a 2 × 2 factorial design, where the factors were H- or L-energy density in a total mixed ration (TMR) both pre- and post-calving. Consequently, there were four treatment groups: HH, HL, LL and LH. The pre-calving treatment was initiated 100 days prior to expected calving; the H TMR was fed ad libitum whereas the L TMR was restricted to 10 kg dry matter/day during late lactation, and to approximately 75% of energy requirements from drying off until calving. Both diets were offered ad libitum post-calving. Feeding diet H compared to L pre-calving led to higher BCS at calving (2.68 v. 2.34, P < 0.01). Energy corrected milk yield and energy-intake post-calving were not affected by pre-calving diets. Changes in BCS and blood concentrations of non-esterified fatty acids, beta-hydroxybutyrate and glucose in early lactation showed that cows offered diet H pre-calving generally mobilised more body reserves compared to cows offered diet L pre-calving. An interaction between pre- and post-calving diets showed that cows offered diet H pre-calving had lower body tissue mobilisation when offered diet H post-calving compared to diet L. Cows offered diet L pre-calving, did not mobilise differently whether they were offered diet H or L post-calving. The pre- and post-calving diets had no effect on liver triacylglycerol, whereas liver glycogen was higher in cows on treatment HH compared to the other three treatments. Collectively, these results indicate that overfeeding should be avoided in late gestation and that a high-energy-density diet is desirable in early lactation in order to obtain a more favourable metabolic profile.
Differences in productive robustness in rabbits selected for reproductive longevity or litter size
- P. Theilgaard, M. Baselga, E. Blas, N. C. Friggens, C. Cervera, J. J. Pascual
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The aim of this work was to evaluate the ability of a line selected for reproductive longevity (LP) to confront productive challenges compared to a line selected during 31 generations for litter size at weaning (V). A total of 133 reproductive rabbit does were used (72 and 61 from LP and V lines, respectively). Within each line, three groups with different levels of productive effort were planned: PP9, inseminated at day 4 after the first partum and with nine kits during the second partum, and inseminated after first weaning (30 days) and with nine (PW9) or five kits (PW5) during the second partum. The reproductive performance, body condition (perirrenal fat thickness (PFT)) and lipolytic response were controlled. LP does showed greater mean live weight (LW; +128 g; P < 0.05), PFT (+0.47 mm; P < 0.05) and estimated body energy (EBE; +0.29 MJ/kg; P < 0.01) than V does at second partum. However, LP does that mated at first post partum did not significantly differ in EBE relative to V does at second partum. During the first week of lactation, dry matter (DM) intake was similar for both lines (94 and 95 g DM/kg LW0.75 day for V and LP does, respectively). There was a significant difference in milk yield between both lines during the first week when litter size was nine (60 v. 54 g of milk/kg LW0.75 day for LP and V does, respectively; P < 0.01), but no difference when litter size was five. Consequently, when litter size was nine, LP does showed a lower recovery of PFT (0.6 mm less; P < 0.05) than V does during the first 10 days of lactation. However, when litter size was five, LP does showed a higher LW (+210 g; P < 0.05) than V does at 10 days of lactation and a similar recovery of PFT. During the last 3 weeks of the lactation, LP does showed a higher feed intake (+6 g DM/kg LW0.75 day; P < 0.05) and milk yield (+27 g/day; P < 0.001) than V does when litter size was nine, resulting in no significant differences in LW at 30 days of lactation. However, when litter size was five, both lines showed similar feed intake and milk yield, maintaining their differences in LW at 30 days of lactation (+206 g for LP does; P < 0.05). These results show that the rabbit line selected for reproductive longevity is more robust with respect to coping with productive challenges, than a line selected for reproductive intensity.
Fertility in dairy cows: bridging the gaps
- M. D. Royal, R. F. Smith, N. C. Friggens
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