Novel phenotypes of feeding and social behaviour and their relationship with individual rabbit growth and feed efficiency.

Due to the lack of a recording system for individual consumption of group-housed rabbits, published studies about feeding behaviour are based on information recorded at the group- and not at the individual level and periods covering only a few days or, in some cases, only part of a day. Such information could be used to inform rabbit management systems but cannot be used for genetic selection. We aimed to generate and use information from a novel automated feeder for group-housed rabbits to identify new phenotypes for individual animals that could be incorporated into breeding programs to improve feed efficiency and social behaviour under different feeding regimens. At 39 d of age, rabbits from 15 batches were placed in cages and fed ad libitum to become used to the electronic feeder. From 42 to 58-59 d, one group of 1 086 rabbits was fed ad libitum (AL), while another group of 1 134 rabbits was fed on a restricted feeding schedule (R) by limiting the feeding time to the period between 1800 and 0600 h of the following day. We implemented a reliable multivariate method to remove anomalous feeding behaviour records. We then defined novel traits for feeding behaviour that apply to both types of feeding regimes, and for social behaviour that indicates an animal's rank within the cage hierarchy. We based these traits on feeder records and a biologically sound definition of a meal. Finally, we estimated the phenotypic correlations of those traits with growth and feed efficiency traits. Our findings demonstrate that variables about resource distribution among cage mates and an animal's priority for feed access were found to be good indicators of an animal's dominant or subordinate status within the cage. Based on results obtained in R animals (results were similar in AL animals), the most efficient animals were those that ate less frequently (phenotypic correlation with feed conversion ratio, rho = 0.6), and consumed smaller amounts per meal (rho = 0.7), spent less time at the feeder (rho = 0.4), and appeared to be subordinate, as they did not have priority access to the feeder (rho = -0.3), and had the smallest share of resources (range of rho = 0.2-0.6). We conclude that quantifying feeding and social behaviour traits can enhance the understanding of the mechanisms through which individuals exert their effects on the performance of their cage mates.

Novel epidemiological model of gastrointestinal nematode infection to assess grazing cattle resilience by integrating host growth, parasite, grass and environmental dynamics.

Gastrointestinal nematode (GIN) infections are ubiquitous and often cause morbidity and reduced performance in livestock. Emerging anthelmintic resistance and increasing change in climate patterns require evaluation of alternatives to traditional treatment and management practices. Mathematical models of parasite transmission between hosts and the environment have contributed towards the design of appropriate control strategies in ruminants, but have yet to account for relationships between climate, infection pressure, immunity, resources, and growth. Here, we develop a new epidemiological model of GIN transmission in a herd of grazing cattle, including host tolerance (body weight and feed intake), parasite burden and acquisition of immunity, together with weather-dependent development of parasite free-living stages, and the influence of grass availability on parasite transmission. Dynamic host, parasite and environmental factors drive a variable rate of transmission. Using literature sources, the model was parametrised for Ostertagia ostertagi, the prevailing pathogenic GIN in grazing cattle populations in temperate climates. Model outputs were validated on published empirical studies from first season grazing cattle in northern Europe. These results show satisfactory qualitative and quantitative performance of the model; they also indicate the model may approximate the dynamics of grazing systems under co-infection by O. ostertagi and Cooperia oncophora, a second GIN species common in cattle. In addition, model behaviour was explored under illustrative anthelmintic treatment strategies, considering impacts on parasitological and performance variables. The model has potential for extension to explore altered infection dynamics as a result of management and climate change, and to optimise treatment strategies accordingly. As the first known mechanistic model to combine parasitic and free-living stages of GIN with host feed-intake and growth, it is well suited to predict complex system responses under non-stationary conditions. We discuss the implications, limitations and extensions of the model, and its potential to assist in the development of sustainable parasite control strategies.

Consequences of timing of organic enrichment provision on pig performance, health and stress resilience after weaning and regrouping.

Most pigs in slatted systems are provided with enrichment meeting only minimum legal requirements. We aimed to explore the effects of a novel enrichment treatment consisting of daily provided fodder beet and jute bags for pigs in slatted systems, and investigate the timing of enrichment provision on performance, health and stress resilience. We used 280 weaners allocated into standard (S, meeting only legal requirements consisting of a plastic toy and softwood) or enriched (E) treatment (n = 14 groups/treatment). At regrouping during the grower to finisher transition, pigs were either kept in the same treatment (EE, SS) or switched from enriched to standard (ES) and vice versa (SE); each treatment was replicated on five groups. Pigs were weighted at the start and end of weaner, and finisher stage, and feed intake was recorded. Occurrence of scouring, respiratory problems, locomotor disorders, tail, ear, and body lesions were recorded twice a week. Ten males per treatment were sampled for saliva on days 1, 2 and 4, either postweaning or after the housing switch. Saliva samples were analysed for cortisol, alpha-amylase, haptoglobin (Hp), and adenosine deaminase. Additionally, these pigs were sampled for hair at the start and end of weaner, and end of finisher stage to analyse for hair cortisol and cortisone. We found that E weaners consumed less feed (P = 0.04), had better FCR (feed conversion ratio, P = 0.03) and less ear lesions for two weeks postweaning (P = 0.04), and tended to have lower occurrence of scouring (P = 0.07) and higher salivary cortisol concentrations (P = 0.09) than S weaners. Effects of enrichment treatment during weaner stage on performance were carried through to finisher stage, with EE and ES pigs having better FCR (P = 0.0009) and higher BW (P = 0.0001) compared to SS and SE pigs. E treatment during finisher stage decreased feed intake (P = 0.04) and tended to decrease Hp levels (P = 0.07). There was a significant interaction between enrichment treatments during weaner and finisher stages on finisher body lesions: EE finishers had less lesions than SS, ES, and SE finishers (P = 0.04). There were no other significant differences caused either by enrichment treatment during weaner/finisher stage or their interaction. We conclude that the novel enrichment applied at weaner stage had positive effects on ear lesions and performance, which were carried through to finisher stage. Body lesions were affected by its application during both stages, with finishers receiving the enrichment treatment throughout (EE) having reduced body lesions than the rest of the finishers.

Farm characteristics affecting antibiotic consumption in pig farms in England.

BACKGROUND: Pig production has been highlighted as one of the highest users of antibiotics amongst livestock, with several studies suggesting a variety of approaches to antibiotic reduction. We aimed to investigate links between antibiotic use (defined as total amount of critically (CIA) and non-critically important antibiotics, and as mg per kg of pig on farm), production stages present on farm (Breeder-Finisher, Nursery-Finisher, and Finisher), and pig farm characteristics using farm data collected through national recording systems in Great Britain for 2017 & 2018. Providing enrichment within pig pens may reduce the need for antibiotics by enhancing both pig welfare and resilience to infection; this was one of the hypotheses addressed by this paper. RESULTS: The amount of antibiotic used, expressed as mg/kg, reduced between 2017 and 2018 for Breeder-Finisher farms, but not for Nursery-Finisher or Finisher farms. Breeder-Finisher farms were more likely to use CIA compared with other production stages. Larger farms were more likely to use CIA, but farm size had no effect on mg/kg of antibiotic used. As the proportion of pens containing straw increased, the total use of antibiotics decreased for Breeder-Finisher, but not for Nursery-Finisher or Finisher farms. As the proportion of pens containing straw increased, the probability of using CIAs also decreased. Farms with a higher proportion of finisher pens with an outdoor space had a lower use of non-critical antibiotics and lower probability of use of CIA. Farms with a higher proportion of pens with automatically controlled natural ventilation (ACNV) had lower total use of antibiotics, although ACNV had no effect on the probability of using CIA. CONCLUSIONS: We quantified the influence of farm characteristics on the consumption of antibiotics in pig farms in England. Our findings support the hypothesis that farm characteristics have an influence on antibiotic use within a system and suggest that this reflects the balance of effects on both animal resilience and disease challenge. Consistent with our hypothesis, provision of straw was associated with reduced antibiotic use. We also demonstrate the value of using secondary databases, although further structural improvements are required to facilitate effective database combination and ensure maximum information benefits can be realised.

Shifting sows: longitudinal changes in the periparturient faecal microbiota of primiparous and multiparous sows.

Knowledge of periparturient longitudinal changes in sow microbiota composition is necessary to fully understand her role in the development of the piglet microbiota, but also to improve gut health and performance of the sow in lactation. Primiparous sows face the challenge of partitioning nutrients to support maternal growth in addition to supporting foetal growth and the demands of lactation. Additional metabolic stress present during the periparturient period may induce changes in the microbiota profile between primiparous and multiparous sows. Using 16S rRNA gene sequencing, the study aimed to characterise the longitudinal changes in the periparturient microbiota and identify differences within the sow microbiota profile associated with parity. Faecal samples from primiparous (n = 13) and multiparous (n = 16) sows were collected at four different time points (day -6, -1, 3 and 8) in relation to farrowing (day 0). Microbiota richness was lowest on day 3 and -1 of the periparturient period (P < 0.05). Microbiota community composition, assessed by weighted and unweighted UniFrac distances, demonstrated longitudinal changes, with day 3 samples clustering away from all other sampling time points (P < 0.05). The relative abundance of several genera segregated gestation from lactation samples including Roseburia, Prevotella 1, Prevotella 2, Christensenellaceae R-7 group, Ruminococcaceae UCG-002 and Ruminococcaceae UCG-010 (P < 0.01). Furthermore, day 3 was characterised by a significant increase in the relative abundance of Escherichia/Shigella, Fusobacterium and Bacteroides, and a decrease in Alloprevotella, Prevotellaceae UCG-003 and Ruminococcus 1 (P < 0.001). Primiparous sows had overall lower periparturient microbiota diversity (P < 0.01) and there was a significant interaction between parity and sampling time point, with primiparous sows having lower microbiota richness on day -6 (P < 0.001). There was a significant interaction between sow parity and sampling time point on microbiota composition on day -6 and -1 (unweighted UniFrac distances;  ≤ 0.01) and day 8 (weighted and unweighted UniFrac distances; P < 0.05). Whilst no significant interactions between sow parity and sampling day were observed for genera relative abundances, multiparous sows had a significantly higher relative abundance of Bacteroidetes dgA-11 gut group and Prevotellaceae UCG-004 (P < 0.01). This study demonstrates that the sow microbiota undergoes longitudinal changes, which are collectively related to periparturient changes in the sow environment, diet and physiological changes to support foetal growth, delivery and the onset of lactation, but also sow parity.

Short communication: Identifying key parameters for modelling the impacts of livestock health conditions on greenhouse gas emissions.

Improved animal health can reduce greenhouse gas (GHG) emissions intensity in livestock systems while increasing productivity. Integrated modelling of disease impacts on farm-scale emissions is important in identifying effective health strategies to reduce emissions. However, it requires that modellers understand the pathways linking animal health to emissions and how these might be incorporated into models. A key barrier to meeting this need has been the lack of a framework to facilitate effective exchange of knowledge and data between animal health experts and emissions modellers. Here, these two communities engaged in workshops, online exchanges and a survey to i) identify a comprehensive list of disease-related model parameters and ii) test its application to evaluating models. Fifty-six parameters were identified and proved effective in assessing the potential of farm-scale models to characterise livestock disease impacts on GHG emissions. Easy wins for the emissions models surveyed include characterising disease impacts related to feeding.

A reassessment of the vitamin D requirements of modern broiler genotypes.

We hypothesized that performance and bone mineralization of 2 broiler lines will benefit from increasing vitamin D (vitD) supplementation above current commercial levels and by partial substitution of D3 by 25-OH-D3. Male Ross 308 and 708 chicks (n = 576), were offered diets with low (LD; 1,000), medium (MD; 4,000) or high levels of D3 (HD; 7,000 IU/kg), and medium levels of vitD where the majority of D3 was substituted by 25-OH-D3 (25MD; 1,000 D3+3,000 25-OH-D3 IU/kg). Performance was measured at the end of starter (day 10), grower (day 24), and finisher periods (day 38). Three birds per pen were dissected at the end of each period to assess tibia and femur ash percentage (%), ash weight, bone breaking strength (BBS), and serum levels of 25-OH-D3. Remaining birds were gait scored (GS) at day 37 of age. Genotype and diet did not interact for any trait, whilst performance was not affected by diet. Ross 708 had lower body weight (P < 0.005), higher feed conversion ratio over the grower period (P < 0.05), similar levels of 25-OH-D3, but higher GS (P < 0.05) than Ross 308. Serum 25-OH-D3 levels were affected by diet at the end of the starter and grower periods (P < 0.05), being lowest for LD and highest for 25MD. Diet affected GS (P < 0.01), being higher in LD than 25MD. Femur ash % was higher at the end of the starter and grower periods for 25MD than LD and for both HD and 25MD than LD (P < 0.05). Femur and tibia ash weight were higher for 25MD in comparison to LD birds (P < 0.05) at the end of the grower period. Femur and tibia BBS were higher (P < 0.05) for 25MD in comparison to LD at the end of the grower and finisher periods, respectively. Overall, effects of vitD supply were more pronounced for femur than for tibia mineralization. Results do not suggest supplementation of vitD above current maximum levels and support partial substitution by 25-OH-D3.

A systematic literature mapping and meta-analysis of animal-based traits as indicators of production diseases in pigs.

The choice of animal-based traits to identify and deal with production diseases is often a challenge for pig farmers, researchers and other related professionals. This systematic review focused on production diseases, that is, the diseases that arise from management practices, affecting the digestive, locomotory and respiratory system of pigs. The aim was to classify all traits that have been measured and conduct a meta-analysis to quantify the impact of diseases on these traits so that these can be used as indicators for intervention. Data were extracted from 67 peer-reviewed publications selected from 2339 records. Traits were classified as productive (performance and carcass composition), behavioural, biochemical and molecular traits. A meta-analysis based on mixed models was performed on traits assessed more than five times across studies, using the package metafor of the R software. A total of 524 unique traits were recorded 1 to 31 times in a variety of sample material including blood, muscle, articular cartilage, bone or at the level of whole animal. No behavioural traits were recorded from the included experiments. Only 14 traits were measured on more than five occasions across studies. Traits within the biochemical, molecular and productive trait groups were reported most frequently in the published literature and were most affected by production diseases; among these were some cytokines (interleukin (IL) 1-ß, IL6, IL8 and tumour necrosis factor-α), acute phase proteins (haptoglobin) and daily weight gain. Quantification of the influence of factors relating to animal characteristics or husbandry practices was not possible, due to the low frequency of reporting throughout the literature. To conclude, this study has permitted a holistic assessment of traits measured in the published literature to study production diseases occurring in various stages of the production cycle of pigs. It shows the lack of consensus and common measurements of traits to characterise production diseases within the scientific literature. Specific traits, most of them relating to performance characteristics or immunological response of pigs, are proposed for further study as potential tools for the prognosis and study of production diseases.

Review: Precision nutrition of ruminants: approaches, challenges and potential gains.

A plethora of sensors and information technologies with applications to the precision nutrition of herbivores have been developed and continue to be developed. The nutritional processes start outside of the animal body with the available feed (quantity and quality) and continue inside it once the feed is consumed, degraded in the gastrointestinal tract and metabolised by organs and tissues. Finally, some nutrients are wasted via urination, defecation and gaseous emissions through breathing and belching whereas remaining nutrients ensure maintenance and production. Nowadays, several processes can be monitored in real-time using new technologies, but although these provide valuable data 'as is', further gains could be obtained using this information as inputs to nutrition simulation models to predict unmeasurable variables in real-time and to forecast outcomes of interest. Data provided by sensors can create synergies with simulation models and this approach has the potential to expand current applications. In addition, data provided by sensors could be used with advanced analytical techniques such as data fusion, optimisation techniques and machine learning to improve their value for applications in precision animal nutrition. The present paper reviews technologies that can monitor different nutritional processes relevant to animal production, profitability, environmental management and welfare. We discussed the model-data fusion approach in which data provided by sensor technologies can be used as input of nutrition simulation models in near-real time to produce more accurate, certain and timely predictions. We also discuss some examples that have taken this model-data fusion approach to complement the capabilities of both models and sensor data, and provided examples such as predicting feed intake and methane emissions. Challenges with automatising the nutritional management of individual animals include monitoring and predicting of the flow of nutrients including nutrient intake, quantity and composition of body growth and milk production, gestation, maintenance and physical activities at the individual animal level. We concluded that the livestock industries are already seeing benefits from the development of sensor and information technologies, and this benefit is expected to grow exponentially soon with the integration of nutrition simulation models and techniques for big data analysis. However, this approach may need re-evaluating or performing new empirical research in both fields of animal nutrition and simulation modelling to accommodate a new type of data provided by the sensor technologies.

Once small always small? To what extent morphometric characteristics and post-weaning starter regime affect pig lifetime growth performance.

BACKGROUND: The aim of this study was to determine the effect of piglet morphometric characteristics and starter regime on postnatal growth. Some piglets born light are able to grow faster than others, and identifying which piglets are more at risk to remain light and at which stages of growth is essential. A nutrient enriched starter regime may allow lightweight pigs to improve their post-weaning growth. A total 1487 newly born piglets from 137 litters originating from 8 consecutive farrowing batches were followed from birth (BiW) to weaning (WW, d28) and finishing (d99). At birth morphometric measurements were taken, including body mass index (BMI), ponderal index (PI) and BiW:cranial circumferences (BiW:CC). At weaning pigs were randomly allocated to one of two experimental regimes: either a nutrient enriched regime with a 20% higher essential amino acids (EAA): energy ratio (HIGH) or a standard regime (CTRL). Piglets were retrospectively allocated to 4 different weight classes (C) using percentiles at birth, weaning and finishing, with C1 representing the lightest and C4 the heaviest class. A series of novel statistical models were used to determine which factors were able to predict performance. RESULTS: For BiW C1 piglets, BMI (P = 0.003) and BiW relative to birth litter (P = 0.026) were positively associated with pre-weaning performance, whereas BiW:CC (P = 0.011) and WW (P = 0.001) were positively associated with post-weaning growth. Post-weaning the best predictors of piglets weaned light (WW C1) were PI (P = 0.037), BiW:CC (P < 0.001) and WW (P < 0.001). Starter regime did not influence (P > 0.05) post-weaning performance. CONCLUSION: Our results show that not all light pigs are the same and that their performance is under the influence of body shape rather than BiW. Therefore, pig producers should discriminate between light pigs based on birth characteristics to improve the effectiveness of intervention strategies at the different stages of growth. Irrespective of weight class piglets did not benefit from the EAA enriched regime applied.

Publisher Correction: Artificial selection for improved energy efficiency is reaching its limits in broiler chickens.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

Artificial selection for improved energy efficiency is reaching its limits in broiler chickens.

Modern broiler chickens are a major animal husbandry success story, both in terms of efficient resource utilisation and environmental sustainability. However, continuing artificial selection for both efficiency and rapid growth will be subject to both biological limits and animal welfare concerns. Using a novel analytical energy flow modelling approach, we predict how far such selection can go, given the biological limits of bird energy intake and partitioning of energy. We find that the biological potential for further improvements in efficiency, and hence environmental impact reduction, is minimal relative to past progress already made via artificial selection. An alternative breeding strategy to produce slower-growing birds to meet new welfare standards increases environmental burdens, compared to current birds. This unique analytic approach provides biologically sound guidelines for strategic planning of sustainable broiler production.

The "Real Welfare" scheme: Identification of risk and protective factors for welfare outcomes in commercial pig farms in the UK.

From 2013-2016, animal-based measures were collected as part of the "Real Welfare" protocol adopted by the Red Tractor Pigs Assurance Scheme to assess the welfare in finisher pig herds in the UK. Trained veterinarians from 89 veterinary practices assessed 112,241 pens (hospital pens excluded) from 1928 farms using a multistage sampling protocol, and collected data about pig welfare, management and farm environment. Multivariable analyses were conducted for five main welfare outcomes: lameness, pigs requiring hospitalization, severe tail lesions, severe body marks and enrichment use ratio (number of active pigs interacting with the enrichment/total number of active pigs). Additionally, a multiple correspondence analysis (MCA) was conducted to analyse systematic patterns of variations of environmental characteristics and improve understanding of the connection between welfare outcomes and environment. The prevalence of the four welfare outcomes and the mean enrichment use ratio differed between pen types (P<0.05), with a higher mean prevalence of lame pigs (0.39%) but lower mean prevalence of pigs requiring hospitalization (0.07%), severe tail lesions (0.07%) and severe body marks (0.12%) in outdoor pens. In&outdoor pens had the highest mean prevalence of the measured outcomes (P<0.05). After adjusting for the farm, date and pen type, lameness, pigs requiring hospitalization and severe tail lesions were less prevalent in large pens (P<0.01), pens with substrates (P≤0.05) and pens fed with meal (P≤0.05), while enrichment use ratio was higher with substrates (P<0.001). Moreover, pigs requiring hospitalization and severe body marks were more prevalent in pens with powered ventilation (P<0.05). On the MCA graph, higher prevalences of lameness and pigs requiring hospitalization (>1, 5 and 10%) were located in the same direction as lower enrichment use ratio, liquid feed, trough feeding, floor feeding, restricted feed and in&outdoor pens. Results suggested that higher prevalences were not specifically connected to a particular system, but that all welfare outcomes were connected to several inappropriate features in the environment. This study highlights individual risk factors which can be considered to improve animal welfare, but also indicates the need to consider the environment as a whole because of potential factor combinations and confounds. Understanding of these requires a large scale database, which can be drawn from assessments carried out as part of farm assurance and support evidence-based advice and future formulation of standards for good practice.

Satiety splits drinking behavior into bouts: Organization of drinking in turkeys.

The regulation of the drinking behavior of animals is usually overlooked, and the traits associated with it are not well defined. We used a unique data set of measurements of individual drinking behavior in turkeys 1) to validate the system of data generation, 2) to develop a methodology to allow clustering of drinking events and splitting behavior into bouts, and 3) to develop traits related to drinking behavior and its regulation and investigate how these traits may be affected by bird genotype. Visits to drinkers were generated by an electronic, custom-made equipment that automatically measures the individual drinking behavior of a large number of turkeys from 3 different genetic lines. The overall reliability of the electronic system was estimated from video observations and resulted in a predictability of 98.8% and sensitivity of 98.6%. A novel method based on mixture distribution models allowed clustering of drinking events and splitting behavior into bouts by estimating the shortest interval between visits to the drinker that was considered to be part of a bout (bout criterion). The method predicted that after the end of a given bout the probability of the bird initiating the next bout was low but increased with time since the last bout. As a result, drinking bouts were not randomly distributed but were predicated on the physiological principle of satiety, suggesting that they constitute biologically appropriate units for expressing drinking behavior. The applied method resulted in bout criteria estimates of 665, 672, and 602 s for genetic lines A, B, and C, respectively. On the basis of this methodology, a number of drinking behavior traits, such as bout duration and frequency, and water intake per bout were identified that revealed differences ( < 0.01) in the drinking behavior between the turkey genetic lines. Similarly, time accumulation patterns of drinking behavior traits within a day differed ( < 0.01) within and between genetic lines, suggesting that variation in drinking behavior exists and birds use different behavioral strategies to meet their water intake requirements. Development of drinking behavior over time was similar between the lines, suggesting conservation of this behavioral organization. As well as providing ideas about the regulation of drinking behavior, the developed behavioral traits may be of practical relevance because water utilization, along with feed efficiency, is part of overall biological efficiency.

The 'Real Welfare' scheme: benchmarking welfare outcomes for commercially farmed pigs.

Animal welfare standards have been incorporated in EU legislation and in farm assurance schemes, based on scientific information and aiming to safeguard the welfare of the species concerned. Recently, emphasis has shifted from resource-based measures of welfare to animal-based measures, which are considered to assess more accurately the welfare status. The data used in this analysis were collected from April 2013 to May 2016 through the 'Real Welfare' scheme in order to assess on-farm pig welfare, as required for those finishing pigs under the UK Red Tractor Assurance scheme. The assessment involved five main measures (percentage of pigs requiring hospitalization, percentage of lame pigs, percentage of pigs with severe tail lesions, percentage of pigs with severe body marks and enrichment use ratio) and optional secondary measures (percentage of pigs with mild tail lesions, percentage of pigs with dirty tails, percentage of pigs with mild body marks, percentage of pigs with dirty bodies), with associated information about the environment and the enrichment in the farms. For the complete database, a sample of pens was assessed from 1928 farm units. Repeated measures were taken in the same farm unit over time, giving 112 240 records at pen level. These concerned a total of 13 480 289 pigs present on the farm during the assessments, with 5 463 348 pigs directly assessed using the 'Real Welfare' protocol. The three most common enrichment types were straw, chain and plastic objects. The main substrate was straw which was present in 67.9% of the farms. Compared with 2013, a significant increase of pens with undocked-tail pigs, substrates and objects was observed over time (P0.3). The results from the first 3 years of the scheme demonstrate a reduction of the prevalence of animal-based measures of welfare problems and highlight the value of this initiative.

Risk factors associated with the different categories of piglet perinatal mortality in French farms.

We aimed to identify mortality patterns and to establish risk factors associated with different categories of piglet perinatal mortality in French farms. At farm level, the analyses were performed on data from 146 farms that experienced perinatal mortality problems. At piglet level, the analyses were performed on data from 155 farms (7761 piglets). All data were collected over a period of 10 years (2004-14) by a consulting company, using a non-probability sampling at farm level and a random sampling at sow level. Six main categories of mortality, determined by standardised necropsy procedure, represented 84.5% of all the perinatal deaths recorded. These six categories were, in order of significance: Death during farrowing, Non- viable, Early sepsis, Mummified, Crushing and Starvation. At farm level, the percentage of deaths due to starvation was positively correlated to the percentage of deaths due to crushing and the percentage of deaths during farrowing (r>0.30, P<0.05) .The percentage of deaths due to crushing was negatively correlated to the percentage of deaths due to early sepsis (r<-0.30, P<0.05) and positively correlated to the deaths due to acute disease (r>0.30, P<0.05). Patterns of perinatal mortality at farm level were identified using a principal component analysis. Based on these, the farms could be classified, using ascending hierarchical classification, into three different clusters, highlighting issues that underlie farm differences. Risk factors were compared at piglet level for the different categories of death. Compared to other categories of death, deaths during farrowing were significantly fewer during the night than during the day. Compared to other categories of death, the likelihood of non-viable piglets tended to be higher in summer than other seasons. A smaller number of deaths in the litter was also identified for the piglets classified as non-viable or mummified. For the six main categories of perinatal mortality, the piglets which died from a specific category tended to have more littermates which died from the same category. Parity and litter size also had more significant effects on certain categories of death compared to others. The study provides novel information on the risk factors associated with specific categories of piglet perinatal mortality. The classification of farms into the 3 different clusters could lead to a more targeted management of perinatal mortality on individual farms.

What is good for small piglets might not be good for big piglets: The consequences of cross-fostering and creep feed provision on performance to slaughter.

Major improvements in sow prolificacy have resulted in larger litters but, at the same time, increased the proportion of piglets born light weight. Different management strategies aim to enhance the performance of, and limit light-weight piglet contribution to, BW variation within a batch; however, consequences on heavy-weight littermates are often neglected. This study investigated the effects of different litter compositions, created through cross-fostering, and the provision of creep feed on preweaning behavior and short- and long-term performance of piglets born either light weight (≤1.25 kg) or heavy weight (1.50-2.00 kg). Piglets were cross-fostered at birth to create litters with only similar-sized piglets (light weight or heavy weight; UNIFORM litters) and litters with equal numbers of light-weight and heavy-weight piglets (MIXED litters); half of the litters were offered creep feed and the remaining were not. Piglet behavior during a suckling bout and at the creep feeder was assessed; a green dye was used to discern between consumers and nonconsumers of creep feed. The interaction between litter composition and birth weight (BiW) class influenced piglet BW at weaning ( < 0.001): piglets born light weight were lighter at weaning in MIXED litters than those in UNIFORM litters (6.93 vs. 7.37 kg); however, piglets born heavy weight performed considerably better in MIXED litters (8.93 vs. 7.96 kg). Total litter gain to weaning was not affected ( = 0.565) by litter composition. Teat position affected heavy-weight piglet performance by d 10 ( < 0.001), with heavy-weight piglets in UNIFORM litters being disadvantaged when suckling the middle and posterior teats. Creep feed provision did not affect BW at weaning ( > 0.05) for either BiW class. However, litter composition significantly affected daily creep feed consumption ( = 0.046) and fecal color ( = 0.022), with heavy-weight piglets in UNIFORM litters consuming the highest amount of creep feed and having the greenest feces. In addition, a lower number of heavy-weight piglets in UNIFORM litters were classified as nonconsumers ( = 0.002). The weight advantage heavy-weight and light-weight piglets had at weaning when reared in MIXED and UNIFORM litters, respectively, was sustained throughout the productive period. In conclusion, reducing BW variation within litter (UNIFORM litters) was beneficial for piglets born light weight but not for piglets born heavy weight; the latter were disadvantaged up to slaughter. Although heavy-weight piglets in UNIFORM litters consumed the greatest amount of creep feed, this was not able to overcome their growth disadvantage compared with heavy-weight piglets in MIXED litters.

Are all piglets born lightweight alike? Morphological measurements as predictors of postnatal performance.

Birth weight (BiW) of pigs is a commonly used predictor of postnatal performance; however, it has been suggested that morphological measurements may be more reflective of the intrauterine environment and thus better predictors of postnatal growth. The aim of this study was to determine 1) whether morphological measurements, including ponderal index (PI), body mass index (BMI), and abdominal circumference (AC), could be used as predictors of postnatal performance and 2) if so, would they be better predictors than BiW and 3) would the same predictors apply to pigs of different BiW at different stages of their growth? Morphological measurements, BiW, and BW at d 28 and 70 were available for 731 pigs from experiments conducted over a 2-yr period. A series of linear models was used to determine predictors that affected growth performance from birth to d 28 and from d 28 to 70. For both light (LBiW; ≤1.25 kg) and normal BiW pigs (NBiW; 1.60 to 2.00 kg), BiW was not the best predictor of performance ( > 0.05); different variables for the growth periods considered applied to pigs with different BiW. For LBiW pigs BMI ( < 0.001) and AC ( = 0.0202) were the best predictors for d 1 to 28, and AC ( = 0.0317) and PI ( = 0.0450) were the best predictors from d 28 to 70, with pigs with a larger AC and higher PI/BMI more likely to have higher ADG pre- or postweaning. In contrast, the best predictor variables for NBiW pigs were AC ( = 0.0482) for d 1 to 28 and crown-rump length (CRL; = 0.0138) for d 28 to 70. Focusing on LBiW pigs with low ADG, BMI was the best predictor ( < 0.05) of growth for pre and postweaning, whereas for LBiW pigs with high ADG the best predictors were AC ( = 0.00132) from d 1 to 28 and BiW ( = 0.00601) from d 28 to 70, with increasing BMI, AC, and BiW associated with greater ADG. For NBiW pigs with high preweaning ADG, the best predictor consisted solely of AC ( 0.0210), but no morphological predictor variables were significant for NBiW pigs with low preweaning ADG. For d 28 to 70, the best predictor for NBiW pigs with low ADG was CRL ( = 0.0171), but for high ADG no predictor variables were significant. The present study showed that the morphology of piglets is more important than BiW when predicting the postnatal growth of pigs; however, which measurement is the most important depends on both the BiW and stage of growth. For small-sized pigs, these morphological measures may be considered as a decision-making tool by farmers when trying to identify potential poor performers.