Scoring biosecurity in European conventional broiler production

Limbergen, Tommy Van; Dewulf, Jeroen; Klinkenberg, M.; Ducatelle, R.; Gelaude, Philippe; Méndez, J.; Heinola, Katriina; Papasolomontos, Sotiris; Szeleszczuk, P.; Maes, Dominiek

doi:10.3382/ps/pex296

Cited by 63 publications

(51 citation statements)

References 36 publications

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“…Data from five EU countries with a geographical range from south to the north of Europe were included. The effects attributed per country were included in this study as a fixed factor as has been the case with other studies (Postma et al, 2016a;Van Limbergen et al, 2017). Thus, the variation or the clustering due to country was taken into account.…”

Section: Study Limitations and Remarksmentioning

confidence: 99%

Factors associated with specific health, welfare and reproductive performance indicators in pig herds from five EU countries

Chantziaras

Dewulf

Limbergen

et al. 2018

Preventive Veterinary Medicine

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Production diseases are often of multi-factorial origin in which environment (housing, nutrition and management) health and reproductive challenges show complex interactions. The aim of this study was to identify specific environment-related factors and to discuss their associations with health, welfare and reproductive performance in sows and piglets, in diverse systems using data from 130 farms from five EU countries. Two sets of data were used: a) a questionnaire was developed for sows and piglets covering farm management, interventions and housing and b) farm production data covering various performance parameters. Eight parameters were further selected, four of which were related to sow reproductive performance (litter index, replacement rate, repeat breeding (i.e. failure to breed after one mating), weaning to first mating interval) and the remaining four to litter / piglet health performance (piglets born alive per litter, piglets born dead per litter, preweaning mortality rate and weaned piglets per litter). Univariable and multivariable linear models were employed to identify risk factors. Associations were considered significant if P ≤ 0.007 (a criterion of p≤0.05 corrected for the number of parameters tested). Various risk and protective factors were identified for each tested outcome variable. Country effects were included in all models as a fixed factor. Adjusted R-squared values for the multivariable models varied between 9.6% (preweaning mortality) and 66% (litter index). Litter index (litters/sow/year) was negatively associated with a higher weaning age of the piglets. Housing recently weaned sows to be inseminated in a separate unit from the gestation unit had a positive association with litter index. Repeat breeding was negatively associated with PRRS-free farms, farms that bred (raised) all gilts on the farm and farms that perform farrowing induction of sows. PRRS-free farms were also associated with a higher replacement rate. Farms that bred gilts on the farm and PRRS-free farms were negatively associated with preweaning mortality. Natural ventilation in the gestation unit was associated with fewer piglets born alive and with fewer weaned piglets. Closed type of farms was associated with less piglets born dead. The use of open box housing system for pregnant sows (provision of individual resting areas) was associated with more weaned piglets. In conclusion, several factors related to applying good farm and health management, and optimal housing conditions showed positive association with various sow and piglet performance parameters. Further studies will help to assess causal links for these factors.

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Section: Study Limitations and Remarksmentioning

confidence: 99%

Factors associated with specific health, welfare and reproductive performance indicators in pig herds from five EU countries

Chantziaras

Dewulf

Limbergen

et al. 2018

Preventive Veterinary Medicine

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“…The relatively high number of broiler farms that was included in this investigation increases the representativeness of the study population. The farm characteristics in the seven participating member states were in accordance with previous publications [12,13].…”

Section: Discussionmentioning

confidence: 78%

Risk factors for poor health and performance in European broiler production systems.

Limbergen¹,

Sarrazin

Chantziaras

et al. 2019

Preprint

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Background Conventional broilers are currently one of the most efficient protein converters. Although decades of progress in genetic selection and feed formulation have lead to high standards of efficient broiler production, still a lot of variability is found between farms and between successive flocks. The aim of this study was to investigate risk- and/or protective factors for poor health and performance in conventional broiler-farms in Europe by developing eight multivariable linear mixed models. Three different models were used to investigate mortality (overall, first week, after first week), three models for performance variables (growth, feed conversion, European production index) and two models were related to slaughterhouse data (i.e. dead on arrival and condemnation rate). Results Several factors related to management and housing were significantly associated with health and performance of broilers. The following factors were associated with increased mortality: floor quality, neonatal septicemia, ventilation type and other professional activities of the farmer. The factors associated with performance were chick sex, coccidiosis infections, necrotic enteritis, dysbacteriosis, light intensity adaptations, ventilation type, comparing daily flock results with previous flock results by farmer, daily check of feed and water system and type of feed. For dead on arrival three risk factors were identified i.e. daily growth, type of light adaptation and type of drinkers system. For condemnation rate seven risk factors were found, i.e. type of drinking system, daily growth, feed withdrawal time, type of ventilation, house size, septicemia after seven days and type of feed. Conclusions These results imply that a multifactorial approach is required with adaptations involving both improvements in management, housing, health programs and an increasing level of professionalism of the farmer in order to improve broiler performance and health.

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“…This was to test the effect of each farm characteristic on each welfare indicator and the overall animal welfare value. Variables with a p value of < 0.20 were retained for further analysis in a multivariable model (Van Limbergen et al 2018). The correlations between the farm characteristics were assessed with bivariate Pearson correlation and were considered to be significant with a p value < 0.05.…”

Section: Discussionmentioning

confidence: 99%

The challenge of incorporating animal welfare in a social life cycle assessment model of European chicken production

Tallentire

Edwards

Limbergen

et al. 2018

Int J Life Cycle Assess

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Purpose There is increasing public concern over standards of farm animal welfare, yet the majority of sustainability studies of livestock have thus far focused only on environmental performance and profitability. Where social analysis has been carried out, there has yet to be a consistent methodology developed that incorporates animal welfare into social life cycle assessment (S-LCA). A framework was developed to assess animal welfare, using conventional broiler chicken meat production in Europe as a case in point. Methods Data were collected on stocking density, mortality, and carcass condemnation rate from conventional chicken meat production systems in Europe. The quantitative risk of each welfare indicator was characterised in accordance with the Social Hotspots Database methodology based on best to worst farm performances, i.e. quartiles of the data collected for each indicator. The overall animal welfare impact was assessed using a weighted sum methodology, which accounted for the level of risk animals were exposed to for each indicator and the animal lifespan. From this, a Social Hotspot Index (SHI) could be calculated for the animal welfare impact associated with the functional unit, which was 1 kg of chicken meat production. The animal welfare impact of four European countries was then compared. Results and discussion The countries assessed displayed a range of values for overall animal welfare impact; the country with the best animal welfare had a SHI for animal welfare impact of 0.14, whilst the worst had a SHI for animal welfare impact of 0.72. Farms that kept more birds per building had an increased overall animal welfare impact. Animal welfare, determined by negative welfare indicators, was worse in more recently established farm buildings due to increased flock size. Conclusions A methodology that incorporates animal welfare indicators into S-LCA was developed that is both scalable and related to welfare assessment frameworks. Although only some specific negative welfare indicators were considered here, the methodology could easily accommodate additional negative indicators and even positive welfare indicators as advancements are made in the understanding of animal welfare. Hence, this study provides a springboard for further development of S-LCA, animal welfare assessment and, ultimately, improved animal welfare in livestock systems.

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Scoring biosecurity in European conventional broiler production

Cited by 63 publications

References 36 publications

Factors associated with specific health, welfare and reproductive performance indicators in pig herds from five EU countries

Factors associated with specific health, welfare and reproductive performance indicators in pig herds from five EU countries

Risk factors for poor health and performance in European broiler production systems.

The challenge of incorporating animal welfare in a social life cycle assessment model of European chicken production

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