Length of metacarpal and metatarsal bones in five Iranian sheep breeds and their associations with ungula measurements.

BACKGROUND: This study aimed to measure the length of metacarpal and metatarsal bones in five Iranian sheep breeds and to correlate the length of the bones with ungula measurements. Thoracic and pelvic limbs of 2-year-old, previously untrimmed, pastured Afshari, Moghani, Kurdi, Makoui, and Lori-Bakhtiari ewes, (n = 20 ewes per breed) were collected after slaughter. The following lengths were recorded in the metacarpal and metatarsal bones: from the margo proximalis lateralis to the lateral (L1) and medial (D1) cartilago physialis; from the margo proximalis lateralis to the margo abaxialis of the lateral (L2) and medial (D2) caput; from the cartilago physialis lateralis to the margo abaxialis of the lateral caput (X1); from the cartilago physialis medialis to the margo distalis of the caput ridge (X2) and from the margo axialis of cartilago physialis to the margo axialis of the lateral caput (X3). Additionally, measurements of the ungula including pars dorsalis length, pars mobilis lateralis and medialis height, pars dorsalis height to the ground and to the solea cornea, thickness of the solea in the pars dorsalis, pars mobilis lateralis and medialis, solea cornea length and angulus dorsalis were recorded in the medial and lateral digits of the thoracic and pelvic limbs. Data on length of the metatarsal and metacarpal bones were analysed using mixed model equations while Pearson correlations were calculated between metacarpal and metatarsal bones and ungula measurements. RESULTS: Lori- Bakhtiari and Moghani ewes had greater L1, L2, and D1 and D2 while X1, X2 and X3 was greater in Kurdi ewes (P < 0.05). Measurements such as L1, L2, D1 and D2 were greater in the metatarsal than in metacarpal bones (P < 0.05) and the opposite was observed for X1, X2 and X3 (P < 0.05). No asymmetry was observed between the lateral and medial measurements (P > 0.05). Low to moderate correlations were observed between bone and ungula measurements (P < 0.05). CONCLUSION: Under the conditions of this study, differences in metacarpal and metatarsal bone measurements were observed between breeds but no asymmetry was observed between lateral and medial bones. Results indicate an association between metacarpal and metatarsal bones ungula measurements. This could provide baseline information for the development and/or improvement of current ungula health protocols in the studied sheep breeds.

Prevalence of welfare outcomes in the weaner and finisher stages of the production cycle on 31 Irish pig farms.

BACKGROUND: Knowledge on the most prevalent welfare problems for pigs in different production stages is required to improve herd management plans. Thirty-one farrow-to-finish pig farms were visited between July and November 2015 to assess the welfare of pigs using the multicriteria approach of the Welfare Quality® protocol. On each farm, 6 pens were selected using proportionate stratified sampling in the first weaner (S1, 4 to 8 wks), second weaner (S2, 8 to 13 wks) and finisher stage (S3, 13 to 23 wks), excluding hospital pens. Each pen was observed for 10 min and the number of pigs affected by different welfare outcomes was recorded. The percentage of pigs affected was calculated and ranked to identify the most prevalent outcomes within each production stage. Differences between production stages were analysed using generalised linear mixed models for binomial data with pen within stage and farm as a random effect. RESULTS: Tail and ear lesions showed the highest prevalence; however, large variation was observed between farms. In S1 the most prevalent welfare outcomes (presented as median prevalence) were poor body condition (4.4%), lethargic pigs (1.5%), scouring (20.3% of pens) and huddling (3.7%). In S2 and S3 outcomes related to injurious behaviour (tail lesions: 5.9% [S2] and 10.5% [S3], ear lesions: 9.1% [S2] and 3.3% [S3], and flank lesions: 0.4% [S2] and 1.3% [S3]), lameness (0.8% [S2] and 1.1% [S3]), bursitis (3.9% [S2] and 7.5% [S3]) and hernias (1.6% [S2] and 1.8% [S3]) were more prevalent. CONCLUSIONS: A large variation was observed for the recorded welfare outcomes corresponding to the different challenges pigs experience during the different stages of production on commercial pig farms. The prevalence of pigs affected by lesions caused by injurious behavior is a cause for concern and requires a collaborative approach to identify appropriate intervention strategies. This information could be used to further investigate appropriate benchmark values for different welfare outcomes that would assist the pig industry to develop appropriate health and welfare management plans to minimise welfare problems. At herd level such plans should include information on aspects of intervention, treatment, and the management of hospital pens as well as euthanasia.

Description of patterns of ear and tail lesions during the grower-finisher period in a commercial pig farm.

BACKGROUND: Ear and tail lesions are prevalent indicators of impaired welfare observed in pig production with different multifactorial causes. Understanding the progression of ear and tail lesions over time is important to implement preventative strategies on commercial pig farms. Therefore, this case study aimed to provide a detailed account of patterns of ear and tail lesions in pigs on a single commercial farm during the grower-finisher period. CASE PRESENTATION: A total of 1,676 12-week old pigs (n = 773 females and n = 903 males, all tail docked) were followed from arrival to the grower facilities until transferred to the finisher stage on a commercial pig farm in Ireland. Pigs were individually weighed and inspected for the severity of fresh ear and tail lesions (score 0-4) on transfer to the first grower (24.9 ± 5.33 kg, 12 weeks of age, n = 1,676 pigs), second grower (33.3 ± 7.04 kg, 14 weeks of age, n = 1,641 pigs), and finisher stage (60.2 ± 7.74 kg, 18 weeks of age, n = 1,626 pigs). Due to the low number of pigs with high scores, ear lesions were classified as no (score 0), mild (score 1), moderate (score 2) and severe (score ≥ 3) and tail lesions were classified as no (score 0), mild (score 1), and moderate-to-severe (score ≥ 2). Ear lesions were more prevalent than tail lesions at each inspection. There were approx. 19% of pigs with ear lesions at all three inspections but no pigs presented with tail lesions at all three inspections. When considering the specific severity categories, we observed 32 different ear lesion score combinations and 15 different tail lesion score combinations across the three inspections. CONCLUSION: The high number of observed patterns of ear and tail lesions suggest large individual variability in lesion progression. Ear lesions were more of an issue than tail lesions and little is known about this health and welfare problem indicating that further research into causes and management strategies is needed.

Identifying challenges to manage body weight variation in pig farms implementing all-in-all-out management practices and their possible implications for animal health: a case study.

BACKGROUND: Managing body weight (BW) variation is a challenge in farrow-to-finish farms implementing all-in/all-out (AIAO) production systems due to the lack of "off-site" facilities to segregate slow growing pigs (SGP). This case study investigated different approaches to managing BW variation in a farrow-to-finish commercial pig farm with a self-declared AIAO management and the possible implications for animal health. CASE PRESENTATION: A total of 1096 pigs (1047 pigs born within 1 week plus 49 pigs born 1 week later) were tracked until slaughter as they moved through the production stages. Piglets were individually tagged at birth and their location on the farm was recorded on a weekly basis. In total, 10.3% of pigs died during lactation. Four main cohorts of pigs were created at weaning and retrospectively identified: cohort 1 = pigs weaned at 21 days (4.5%); cohort 2 = pigs weaned at 28 days (81.0%), which was sub-divided at the end of the first nursery stage into sub-cohort 2a = pigs split at 3 weeks post-weaning (29.7%); sub-cohort 2b = pigs split at 3 weeks post-weaning from cohort 2a and split again 5 weeks post-weaning (35.5%) and sub-cohort 2c = remaining smaller size pigs from cohort 2b (10.9%); cohort 3 = pigs weaned at 35 days (2.7%) and cohort 4 = pigs weaned at 49 days (1.5%) that were later mixed with SPG, delayed pigs from other cohorts and sick/injured pigs that recovered. Four strategies to manage BW variation were identified: i) earlier weaning (cohort 1); ii) delayed weaning of SGP (cohort 3 and 4); iii) re-grading pens by BW (sub-cohorts 2a, 2b and 2c) and, iv) delayed movement of SGP to the next production stage (several pigs from all cohorts). A higher percentage of delayed pigs presented pericarditis, pleurisy and enzootic pneumonia like lesions at slaughter compared with pigs under other strategies. CONCLUSION: A variety of management practices were implemented to minimise BW variation during the production cycle. However, several cohorts of pigs were created disrupting AIAO management. Earlier weaning should only be practiced under specific circumstances where optimal animal health and welfare are guaranteed. Delayed weaning of SGP and delaying pigs to move to the next production stage could negatively affect animal health and should be avoided.

Risk Factors for Antimicrobial Use on Irish Pig Farms.

The threat to public health posed by antimicrobial resistance in livestock production means that the pig sector is a particular focus for efforts to reduce antimicrobial use (AMU). This study sought to investigate the risk factors for AMU in Irish pig production. Antimicrobial use data were collected from 52 farrow-to-finish farms. The risk factors investigated were farm characteristics and performance, biosecurity practices, prevalence of pluck lesions at slaughter and serological status for four common respiratory pathogens and vaccination and prophylactic AMU practices. Linear regression models were used for quantitative AMU analysis and risk factors for specific AMU practices were investigated using logistic regression. Farms that milled their own feed had lower total AMU (p < 0.001), whereas higher finisher mortality (p = 0.043) and vaccinating for swine influenza (p < 0.001) increased AMU. Farms with higher prevalence of pericarditis (p = 0.037) and lung abscesses (p = 0.046) used more group treatments. Farms with higher prevalence of liver milk spot lesions (p = 0.018) and farms practising prophylactic AMU in piglets (p = 0.03) had higher numbers of individual treatments. Farms practising prophylactic AMU in piglets (p = 0.002) or sows (p = 0.062) had higher use of cephalosporins and fluoroquinolones. This study identified prophylactic use and respiratory disease as the main drivers for AMU in Irish pig production. These findings highlight areas of farm management where interventions may aid in reducing AMU on Irish pig farms.

Quantification, description and international comparison of antimicrobial use on Irish pig farms.

BACKGROUND: There is concern that the use of antimicrobials in livestock production has a role in the emergence and dissemination of antimicrobial resistance in animals and humans. Consequently, there are increasing efforts to reduce antimicrobial use (AMU) in agriculture. As the largest consumer of veterinary antimicrobials in several countries, the pig sector is a particular focus of these efforts. Data on AMU in pig production in Ireland are lacking. This study aimed to quantify AMU on Irish pig farms, to identify the major patterns of use employed and to compare the results obtained to those from other published reports and studies. RESULTS: Antimicrobial use data for 2016 was collected from 67 Irish pig farms which represented c. 35% of national production. The combined sample population consumed 14.5 t of antimicrobial by weight of active ingredient suggesting that the pig sector accounted for approximately 40% of veterinary AMU in Ireland in 2016. At farm level, median AMU measured in milligram per population correction unit (mg/PCU) was 93.9 (range: 1.0-1196.0). When measured in terms of treatment incidence (TI200), median AMU was 15.4 (range: 0.2-169.2). Oral treatments accounted for 97.5% of all AMU by weight of active ingredient and were primarily administered via medicated feed to pigs in the post weaning stages of production. AMU in Irish pig production in 2016 was higher than results obtained from the national reports of Sweden, Denmark, the Netherlands and France but lower than the United Kingdom. CONCLUSIONS: Pig production in Ireland is an important consumer of veterinary antimicrobials. The quantities and patterns of AMU on Irish pig farms are comparable to pig production in other European countries but higher than some countries with more advanced AMU reduction strategies. This AMU is characterised by a high proportion of prophylactic use and is primarily administered to pigs post weaning via medicated feed. Further studies to better understand the reasons for AMU on Irish pig farms and strategies to improve health among weaner pigs will be of benefit in the effort to reduce AMU.

Associations between animal and herd management factors, serological response to three respiratory pathogens and pluck lesions in finisher pigs on a farrow-to-finish farm.

BACKGROUND: Serological screening is a common method to monitor antibody response to pathogen exposure, but results could vary due to several factors. This study aimed to quantify animal and management related factors associated with variation in antibody levels in finisher pigs at slaughter, in an Irish farrow-to-finish farm endemically infected with Actinobacillus pleuropneumonia (App), Mycoplasma hyopneumoniae (Mhyo) and swine influenza virus (SIV). A second objective was to estimate differences in antibody levels in pigs presenting pluck lesions. This was an observational study whereby pigs were managed as per routine farm practice. Data on sow parity, number of born alive (NBA) pigs per litter, cross-fostering status, birth and weaning body weight were recorded from 1016 pigs born from one farrowing batch. At slaughter, blood samples were collected for serological analysis and pigs were inspected for presence of enzootic pneumonia (EP)-like lesions, pleurisy, pericarditis and heart condemnations. Pigs were retrospectively classified into three production flows, depending on time spent in each production stage: flow 1 (F1; pigs followed the normal production flow); flow 2 (F2; pigs which were delayed by 1 week from advancing forward); and flow 3 (F3; pigs delayed by > 1 week from advancing forward). A nested case-control design was applied by matching pigs from each flow by sow parity, birth weight and NBA. RESULTS: Pigs born from primiparous sows had higher antibody levels for App than those born to parity ≥5 sows (P < 0.05) and there was no association between any of the pathogens investigated and other early life indicators (P > 0.05). Pigs in F1 had lower antibody levels for App but higher antibody levels for SIV than F2 and F3 pigs (P < 0.05). There was no association between pluck lesions and respiratory pathogens (P > 0.05), except for increased antibody levels for Mhyo when EP-like lesions were present (P = 0.006). CONCLUSION: Results indicate that offspring from primiparous sows develop higher antibody levels for App IV toxin when exposed to this disease and that enforcement of a strict all-in/all-out production system would reduce on-farm disease circulation. A high percentage of pigs were affected with EP-like lesions which were associated with higher antibody levels for Mhyo.

Does the Use of Different Indicators to Benchmark Antimicrobial Use Affect Farm Ranking?

The need to reduce antimicrobial use (AMU) in livestock production has led to the establishment of national AMU data collection systems in several countries. However, there is currently no consensus on which AMU indicator should be used and many of the systems have defined their own indicators. This study sought to explore the effect of using different internationally recognized indicators on AMU data collected from Irish pig farms and to determine if they influenced the ranking of farms in a benchmarking system. AMU data for 2016 was collected from 67 pig farms (c. 35% of Irish pig production). Benchmarks were defined using seven AMU indicators: two based on weight of active ingredient; four based on the defined daily doses (DDD) used by the European Medicines Agency and the national monitoring systems of Denmark and the Netherlands; and one based on the treatment incidence (TI200) used in several published studies. An arbitrary "action zone," characterized by farms above an acceptable level of AMU, was set to the upper quartile (i.e., the top 25% of users, n = 17). Each pair of indicators was compared by calculating the Spearman rank correlation and assessing if farms above the threshold for one indicator were also above it for the comparison indicator. The action zone was broadly conserved across all indicators; even when using weight-based indicators. The lowest correlation between indicators was 0.94. Fifteen farms were above the action threshold for at least 6 of the 7 indicators while 10 farms were above the threshold for all indicators. However, there were important differences noted for individual farms between most pairs of indicators. The biggest discrepancies were seen when comparing the TI200 to the weight-based indicators and the TI200 to the DDDANED (as used by Dutch AMU monitoring system). Indicators using the same numerator were the most similar. All indicators used in this study identified the majority of high users. However, the discrepancies noted highlight the fact that different methods of measuring AMU can affect a benchmarking system. Therefore, careful consideration should be given to the limitations of any indicator chosen for use in an AMU monitoring system.

Predicting Productive Performance in Grow-Finisher Pigs Using Birth and Weaning Body Weight.

This study aimed to (1) investigate the effect of birth and weaning body weight (BW) on performance indicators of grow-finisher pigs and (2) estimate birth and weaning BW cut-off values in order to identify slow growing pigs (SGP). Pigs (n = 144) were classified as SMALL (0.9 ± 0.13 kg) or BIG (1.4 ± 0.20 kg) at birth and re-classified as SMALL (5.4 ± 1.6 kg) or BIG (6.3 ± 1.91 kg) at weaning. Individual BW was recorded bi-weekly, and feed intake was recorded on a daily basis. Average daily gain (ADG) and feed intake, feed conversion ratio (FCR) and days to target slaughter weight (TSW) were calculated. SMALL-SMALL pigs had lower ADG (p < 0.05) requiring 167.1 days (i.e., 14.2 extra days) to TSW (p < 0.05) compared with BIG pigs at birth and/or weaning. However, FCR was similar between groups (p > 0.05). Pigs weaned at <3.7 kg BW would likely be SGP. Pigs born at ≥1.1 kg BW or weaned at ≥6.4 kg BW are more likely to reach TSW at 22 weeks of age. The results suggest that birth BW might not be the best predictor for subsequent performance, as some small-born pigs were able to catch up with their bigger counterparts. The cut-off values identified could be used to design specific management and nutritional strategies for SGP.

Financial Analysis of Herd Status and Vaccination Practices for Porcine Reproductive and Respiratory Syndrome Virus, Swine Influenza Virus, and Mycoplasma hyopneumoniae in Farrow-to-Finish Pig Farms Using a Bio-Economic Simulation Model.

This study aimed (1) to quantify the effects of positive status and vaccination practices for porcine reproductive and respiratory syndrome virus (PRRSv), swine influenza virus (SIV) and Mycoplasma hyopneumoniae (MHYO) on the profitability of farrow-to-finish pig farms and (2) to examine the financial impact of vaccination status in PRRSv and SIV positive farms. Data from 56 Irish farrow-to-finish pig farms were used for this study. Production effects associated with herd status for the three pathogens were incorporated into the Teagasc Pig Production Model (TPPM), a bio-economic stochastic simulation model for farrow-to-finish pig farms. In the analysis, farms negative (-) for either PRRSv, SIV or MHYO were assumed as baseline when presenting results for farms positive (+) for each pathogen. While all MHYO(+) farms used vaccination against the pathogen, not all PRRSv(+) or SIV(+) farms vaccinated against the disease. For all scenarios, a 728-sow farrow-to-finish farm with weekly farrowing batches was simulated. Financial risk analysis was conducted by Monte Carlo simulation within the TPPM using the Microsoft Excel add-in @Risk. Mortality rates, feedstuff costs and price per kg of meat produced were included as input stochastic variables and annual net profit was set as stochastic output variable. Positive farms sold fewer pigs and produced less kg of meat than negative farms and had increased feed usage during the weaner and finisher stages. Variable costs increased in positive farms due to increased feed costs, more dead animals for disposal and healthcare costs. Annual mean profit was lower by 24% in vaccinated PRRSv(+), 14.6% in unvaccinated PRRSv(+), 36.7% in vaccinating SIV(+), 12.8% in unvaccinated SIV(+), and 41% in MHYO(+) farms. Negative farms were first order stochastically dominant over positive farms, indicating that for a given level of profit, the financial risk is lower by avoiding respiratory pathogens. Similarly, unvaccinated farms were second order stochastically dominant over vaccinating farms suggesting that farms that do not vaccinate are less affected by the disease. Results from this study provide further evidence to encourage farmers to undertake improved disease control measures and/or to implement eradication programs.

A bio-economic simulation study on the association between key performance indicators and pluck lesions in Irish farrow-to-finish pig farms.

BACKGROUND: Pluck lesions are associated with decreased performance in grower-finisher pigs, but their economic impact needs to be further investigated. This study aimed to identify the main pluck lesions and the cut-off value for their prevalence, associated with changes in average daily gain (ADG) during the wean-to-finish period, to simulate their effects on economic performance of farrow-to-finish farms. Pigs (n = 162 ± 51.9 per farm) from 56 farrow-to-finish farms were inspected at slaughter and the prevalence of enzootic pneumonia-like lesions, pleurisy, lung scars, abscesses, pericarditis, and liver milk spots was estimated. For each farm, annual performance indicators were obtained. Regression trees analysis (RTA) was used to identify pluck lesions and to estimate cut-off values for their prevalence associated with changes in ADG. Different scenarios were simulated as per RTA results and economic and risk analyses were performed using the Teagasc Pig Production Model. Risk analysis was performed by Monte Carlo sampling using the Microsoft Excel add-in @Risk with 10,000 iterations. RESULTS: Pleurisy and lung scars were the main lesions associated with changes in ADG. Three scenarios were simulated based on RTA results: a 728 sow farrow-to-finish farm with prevalence of i) pleurisy < 25% and lung scars < 8% (LPLSC; ADG = 760 g); ii) pleurisy < 25% and lung scar ≥8% (LPHSC; ADG = 725 g) and iii) pleurisy ≥25% (HP; ADG = 671 g). The economic analysis showed increased feed and dead animals for disposal costs, and lower sales in the HP and LPHSC scenarios than in the LPLSC scenario; thereby reducing gross margin and net profit. Results from the risk analysis showed lower probability of reaching any given level of profit in the HP scenario compared with the LPHSC and LPLSC scenarios. CONCLUSION: Under the conditions of this study, higher prevalence of pleurisy and lung scars were associated with decreased ADG during the grower-finisher period and with lower economic return in the simulated farms. These results highlight the economic benefits and importance of preventing and/or controlling respiratory disease.

Using the Biocheck.UGent™ scoring tool in Irish farrow-to-finish pig farms: assessing biosecurity and its relation to productive performance.

BACKGROUND: Biosecurity is one of the main factors affecting disease occurrence and antimicrobial use, and it is associated with performance in pig production. However, the importance of specific measures could vary depending on the (national) context. The aim of this study was to describe the biosecurity status in a cohort of Irish pig farms, to investigate which of those biosecurity aspects are more relevant by using the Biocheck.UGent™ scoring system, and to study the impact of such aspects on farm performance. RESULTS: External biosecurity score was high compared to most countries due to the characteristics of the Irish pig sector (i.e. purchasing only semen and breeding gilts on farm). The internal biosecurity score was lower and had greater variability among farms than other EU countries. Using multivariable linear regression, the biosecurity practices explained 8, 23, and 16% of variability in piglet mortality, finisher mortality, and average daily gain, respectively. Three clusters of farms were defined based on their biosecurity scores (0 to 100) using principal components and hierarchical clustering analysis. Scores for clusters 1, 2 and 3 were (mean ± SD) 38 ± 7.6, 61 ± 7.0 and 66 ± 9.8 for internal and 73 ± 5.1, 74 ± 5.3 and 86 ± 4.5 for external biosecurity. Cluster 3 had lower piglet mortality (P = 0.022) and higher average daily gain (P = 0.037) when compared to cluster 2. CONCLUSIONS: Irish farms follow European tendencies with internal biosecurity posing as the biggest liability. Our results suggest that practices related to the environment and region, feed, water and equipment supply, and the management of the different stages, need to be addressed in lower performing farms to improve productive performance. Further studies on the economic impact of these biosecurity practices including complementary data on herd health, gilt rearing, piglet management, vaccination and feeding strategies are needed.

Description, evaluation, and validation of the Teagasc Pig Production Model1.

The Teagasc Pig Production Model (TPPM), a stochastic simulation model of a farrow-to-finish pig farm, was developed to investigate effects of changes in production systems on farm profitability. The model simulates, on a weekly basis, the annual production of a farm. Biological [e.g., herd size, number of litters/sow/year, and mortality rates (%)], physical (e.g., infrastructure), and technical (e.g., feeding practices) variables and their associated costs are included as components of the model. These inputs are used to calculate physical (e.g., feed usage and number of pigs slaughtered) and financial (e.g., annual cash flow, profit and loss account, and balance sheet) outputs. The model was validated using the Delphi method and by comparing the TPPM outputs to data recorded on 20 Irish pig farms through the Teagasc e-Profit monitor system and with complete receipts for the year 2016. Results showed that the TPPM closely simulates physical and financial performance of pig farms indicating that the TPPM can be used with confidence to study pig production systems under Irish conditions. Model applicability was demonstrated by investigating the impact of 2 changes in technical performance: 1) building of extra accommodation to increase body weight (BW) at sale by 15 kg (EXTRA ROOM) and 2) a change in feeding practices by providing finisher feed from 28 kg of BW (EARLY FINISHER) compared with over 38 kg of BW. In both scenarios, the same biological parameters were used. Mortality rates, feed ingredients costs, and price per kg of meat produced were included as stochastic variables with the input distributions derived based on historical data simulated using Monte Carlo sampling using the Microsoft Excel add-in @Risk. Annual mean net profit was €198,101 (90% confidence interval [CI]: €119,606-€275,539) for the TPPM base farm, €337,078 (90% CI: €246,320-€426,809) for the EXTRA ROOM, and €225,598 (90% CI: €146,685-€303,590) for the EARLY FINISHER. EXTRA ROOM was associated with higher costs and required higher income to cover the additional costs. The 90% CI of the EARLY FINISHER was similar to the TPPM base farm while the EXTRA ROOM scenario resulted in a wider confidence interval, suggesting that a change in feeding practices could be a better option for farmers looking to improve profit with minimum investment. Thus, the TPPM could be used to facilitate decision making in farrow-to-finish pig farms.

Ear, tail and skin lesions vary according to different production flows in a farrow-to-finish pig farm.

BACKGROUND: Pig performance and risk of disease are associated with production flow. Given the link between health and welfare, it is likely that animal welfare indicators are also associated with production flow. This study investigated the association between production flow and tail, ear and skin lesions on a farm with a purported 'all-in/all-out' policy. This was an observational study whereby pigs were managed according to routine farm practice. A total of 1,016 pigs born within 1 week from the same batch were followed through the production stages and the presence or absence of welfare indicators was recorded at 4, 7, 9, 12, 16 and 24 weeks of age. Three production flows were retrospectively identified: flow 1 = 'normal' pigs that advanced through the production stages together 'on time', flow 2 = pigs delayed from advancing from the 1st to the 2nd nursery stage by 1 week and flow 3 = pigs delayed from advancing through the production stages by > 1 week. A nested case control design was applied by matching pigs by sow parity, number of born alive and birth weight. RESULTS: The presence of ear lesions was 4.5 less likely in pigs in flow 2 and 2.9 times less likely in pigs in flow 3 (P < 0.001) compared to pigs in flow 1. Pigs in flow 3 were 2.2 more likely to have tail and 1.6 times more likely to have ear lesions (P < 0.001) compared to pigs in flow 2. Pigs in flow 2 were less likely to have tail lesions compared with pigs in flow 1 (P < 0.05). Differences between production flows for the risk of skin lesions varied according to age (P < 0.05). CONCLUSION: All production flows were associated with a high risk of lesions which raises concerns for pig welfare. However, risks for ear, tail and skin lesions varied according to each production flow likely due to the specific management practices inherent to each flow. Results from this study could be used to modify existing management practices, thus leading to improvements in animal welfare and possibly performance in intensive pig systems.

Early life indicators predict mortality, illness, reduced welfare and carcass characteristics in finisher pigs.

The objective of this study was to investigate associations between early life indicators, lactation management factors and subsequent mortality, health, welfare and carcass traits of offspring. A total of 1016 pigs from a batch born during one week were used. During lactation, number of liveborn piglets, stillborn and mummies, sow parity, number of times cross-fostered, weaning age, birth and weaning body weight (BW) were collected. Mortality was recorded throughout the offspring production cycle. Prior to slaughter, pigs were scored for lameness (1=non-lame to 3=severely lame). At slaughter, tail lesions were scored (0=no lesion to 4=severe lesion) and cold carcass weight (CCW), lean meat%, presence of pericarditis and heart condemnations were recorded. Additionally, lungs were scored for pleurisy (0=no lesions to 4=severely extended lesions) and enzootic pneumonia (EP) like lesions. There was an increased risk of lameness prior to slaughter for pigs born to first parity sows (P<0.05) compared with pigs born to older sows. Sow parity was a source of variation for cold carcass weight (P<0.05) and lean meat% (P<0.05). Pigs born in litters with more liveborn pigs were at greater risk of death and to be lame prior to slaughter (P<0.05). Pigs that were cross-fostered once were 11.69 times, and those that were cross-fostered ≥2 times were 7.28, times more likely to die compared with pigs that were not cross-fostered (P<0.05). Further, pigs that were cross-fostered once were at greater risk of pericarditis and heart condemnations compared with pigs that were not cross-fostered (P<0.05). Pigs with a birth BW of <0.95kg were at higher mortality risk throughout the production cycle. There was an increased risk of lameness, pleurisy, pericarditis and heart condemnations (P<0.05) for pigs with lower weaning weights. Additionally, heavier pigs at weaning also had higher carcass weights (P<0.05). There was an increased risk of lameness for pigs weaned at a younger age (P<0.05). Males were 2.27 times less likely to receive a score of zero for tail biting compared with female pigs. Results from this study highlight the complex relationship between management, performance and disease in pigs. They confirm that special attention should be given to lighter weight pigs and pigs born to first parity sows and that cross-fostering should be minimised.

Delaying pigs from the normal production flow is associated with health problems and poorer performance.

BACKGROUND: Delaying pigs from advancing through the production stages could have a negative impact on their health and performance. The objective of this study was to investigate the possible implications of delaying pigs from the normal production flow on pig health and performance in a farrow-to-finish commercial farm with a self-declared All-In/All-Out (AIAO) management. RESULTS: Three flows of pigs were defined, flow 1 (i.e. pigs that followed the normal production flow; 8 weeks in the nursery stage, 4 weeks in the growing stage and 8 weeks in the finisher stage), flow 2 (i.e. pigs delayed 1 week from advancing to the next production stage) and flow 3 (i.e. pigs delayed >1 week from advancing to the next production stage). Flow 3 included higher proportions of pigs from first parity sows and of lighter birth weights. When the 3 flows were matched by parity and birth weight, pigs in flow 2 were 3.8 times more likely to be lame prior to slaughter compared with pigs in flow 1. Similarly, pigs in flow 3 were more likely to be lame prior to slaughter, 4.5 times more likely to present pleurisy, 3.3 times more like to present pericarditis and 4.3 times more likely to have their heart condemned at slaughter compared with pigs in flow 1. Additionally, carcasses from pigs in flow 3 were 10 kg lighter compared with carcasses from pigs in flow 1. CONCLUSION: Delayed pigs were more affected by disease and were lighter at slaughter. Besides animal welfare issues, these findings could represent considerable economic loses for pig producers. In practice, delaying pigs from the normal production flow translates into higher feeding costs, increase number of days to slaughter and increased labour requirements reducing production efficiency for the pig operation. In farrow-to-finish farms an 'all-forward' policy (i.e. no pig is left behind from stage to stage and a split marketing approach is applied when sending pigs to slaughter) might be more easily adhered to.