Search

Abstract Background Piglet perinatal and pre-weaning mortality is a welfare problem causing economic losses in pig production. In this study, the effects of housing and management interventions on the economic result of sow enterprises representing six European countries (Belgium, Denmark, Finland, Germany, The Netherlands and Spain) were tested. Interventions concerned: (1) installing mechanical ventilation, (2) re-designing of the gestation unit, (3) drying and warming newborn piglets, (4) providing enrichment for gestating sows, including high-fiber dietary supplementation and point-source objects, and (5) music provision and backscratching of sows in the farrowing unit. A bio-economic model was used to determine the effects of interventions on economic outcomes during the nursery phase and to calculate a maximum cost of 1%-point reduction in perinatal and pre-weaning mortality, irrespective of the intervention type. Biological parameters were set according to previous observational and experimental studies. Interventions 1–4 were expected to decrease perinatal mortality, defined as stillbirths and deaths occurring within the first 48 h of postnatal life. Intervention 5 was expected to decrease pre-weaning mortality. Interventions increased fixed (1–3) and variable costs (3–5). We hypothesized that housing and management interventions would have a positive economic effect. Results Piglet mortality can be decreased in various ways. Interventions concerning ventilation and re-designing of the gestation unit (1 and 2) were the most beneficial in countries with low housing costs and high perinatal mortality. Drying and warming newborn piglets (3) resulted in varying economic results, with the highest increase in profits obtained in a country with low labor costs and high litter size. Interventions providing sows with enrichment and human–animal interaction (4 and 5) were effective across varying conditions. Regardless of intervention type, policies aiming at 1%-point reduction in perinatal and pre-weaning mortality could cost from €0.2 to €0.5 (average €0.4) and from €0.4 to €0.5 (average €0.5) per piglet, respectively, depending on productions conditions. Conclusions To decrease piglet mortality, farmers should consider low input interventions, such as those targeting appropriate behavior. Our results suggest that providing enrichment or increasing human–animal interaction pays off and brings positive economic result even when piglet mortality is marginally reduced.

Within the European Union, there is no harmonization of farm animal welfare quality schemes for meat and dairy products. Instead, there are several industry-driven initiatives and voluntary schemes that seek to provide information on animal welfare for attentive consumers. This study had two aims. First, we quantified how selected industry-wide quality schemes cover the welfare of pigs and dairy cattle on farms by comparing the evaluation criteria selected by schemes with the animal-, resource- and management-based measures defined in the Welfare Quality protocol (WQ®). Second, we identified how these quality schemes use the data generated along the value chain (sensors, breeding, production, and health recordings) for animal welfare assessments. A total of 12 quality schemes, paying attention to animal welfare but not necessarily limited to welfare, were selected for the analysis. The schemes originated from eight European countries: Finland, Sweden, Denmark, Ireland, the Netherlands, Germany, Austria, and Spain. Among the studied quality schemes, we have identified 19 standards for certification: nine for dairy and 10 for pig production. Most of the analyzed standards were comprehensive in welfare assessment. In total, 15 out of 19 standards corresponded to WQ® in more than 70%. However, this high correspondence was obtained when allowing for different information sources (environment instead of animal) than defined in WQ®. Compared to WQ®, the investigated schemes were lagging in terms of the number of measures evaluated based on the animals, with only five standards, out of 19, using predominantly animal-based measures. The quality schemes mostly applied resource-based instead of animal-based measures while assessing good health and appropriate behavior. The utilization of data generated along the value chain by the quality schemes remains insignificant as only one quality scheme allowed the direct application of sensor technologies for providing information on animal welfare. Nevertheless, several schemes used data from farm recording systems, mostly on animal health. The quality schemes rely mostly on resource-based indicators taken during inspection visits, which reduce the relevance of the welfare assessment. Our results suggest that the quality schemes could be enhanced in terms of data collection by the broader utilization of data generated along the value chain.

Tail biting is an important animal welfare issue in the pig sector. Studies have identified various risk factors which can lead to biting incidents and proposed mitigation measures. This study focused on the following seven key measures which have been identified to affect the risk of tail biting lesions: improvements in straw provision, housing ventilation, genetics, stocking density, herd health, provision of point-source enrichment objects, and adoption of early warning systems. The aim of this study was to examine whether these selected measures to reduce the risk of tail biting lesions in pig fattening are cost-effective. The problem was analyzed by first summarizing the most prospective interventions, their costs and expected impacts on the prevalence of tail biting lesions, second, by using a stochastic bio-economic model to simulate the financial return per pig space unit and per pig at different levels of prevalence of tail biting lesions, and third by looking at how large a reduction in tail biting lesions would be needed at different levels of initial prevalence of lesions to cover the costs of interventions. Tail biting lesions of a severity which would require an action (medication, hospitalization of the pig or other care, or taking preventive measures) by the pig producer were considered in the model. The results provide guidance on the expected benefits and costs of the studied interventions. According to the results, if the average prevalence of tail biting lesions is at a level of 10%, the costs of this damaging behavior can be as high as €2.3 per slaughtered pig (~1.6% of carcass value). Measures which were considered the least expensive to apply, such as provision of point-source enrichment objects, or provided wider production benefits, such as improvements in ventilation and herd health, became profitable at a lower level of efficacy than measures which were considered the most expensive to apply (e.g., straw provision, increased space allowance, automated early warning systems). Measures which were considered most efficient in reducing the risk of tail biting lesions, such as straw provision, can be cost-effective in preventing tail biting, especially when the risk of tail biting is high. At lower risk levels, the provision of point-source objects and other less costly but relatively effective measures can play an important role. However, selection of measures appropriate to the individual farm problem is essential. For instance, if poor health or barren pens are causing the elevated risk of tail biting lesions, then improving health management or enriching the pens may resolve the tail biting problem cost-effectively.

Several precision livestock farming (PLF) technologies, conceived for optimizing farming processes, are developed to detect the physical and behavioral changes of animals continuously and in real-time. The aim of this review was to explore the capacity of existing PLF technologies to contribute to the assessment of pig welfare. In a web search for commercially available PLF for pigs, 83 technologies were identified. A literature search was conducted, following systematic review guidelines (PRISMA), to identify studies on the validation of sensor technologies for assessing animal-based welfare indicators. Two validation levels were defined: internal (evaluation during system building within the same population that were used for system building) and external (evaluation on a different population than during system building). From 2,463 articles found, 111 were selected, which validated some PLF that could be applied to the assessment of animal-based welfare indicators of pigs (7% classified as external, and 93% as internal validation). From our list of commercially available PLF technologies, only 5% had been externally validated. The more often validated technologies were vision-based solutions (n = 45), followed by load-cells (n = 28; feeders and drinkers, force plates and scales), accelerometers (n = 14) and microphones (n = 14), thermal cameras (n = 10), photoelectric sensors (n = 5), radio-frequency identification (RFID) for tracking (n = 2), infrared thermometers (n = 1), and pyrometer (n = 1). Externally validated technologies were photoelectric sensors (n = 2), thermal cameras (n = 2), microphone (n = 1), load-cells (n = 1), RFID (n = 1), and pyrometer (n = 1). Measured traits included activity and posture-related behavior, feeding and drinking, other behavior, physical condition, and health. In conclusion, existing PLF technologies are potential tools for on-farm animal welfare assessment in pig production. However, validation studies are lacking for an important percentage of market available tools, and in particular research and development need to focus on identifying the feature candidates of the measures (e.g., deviations from diurnal pattern, threshold levels) that are valid signals of either negative or positive animal welfare. An important gap identified are the lack of technologies to assess affective states (both positive and negative states).

In order to base welfare assessment of dairy cattle on real-time measurement, integration of valid and reliable precision livestock farming (PLF) technologies is needed. The aim of this study was to provide a systematic overview of externally validated and commercially available PLF technologies, which could be used for sensor-based welfare assessment in dairy cattle. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic literature review was conducted to identify externally validated sensor technologies. Out of 1,111 publications initially extracted from databases, only 42 studies describing 30 tools (including prototypes) met requirements for external validation. Moreover, through market search, 129 different retailed technologies with application for animal-based welfare assessment were identified. In total, only 18 currently retailed sensors have been externally validated (14%). The highest validation rate was found for systems based on accelerometers (30% of tools available on the market have validation records), while the lower rates were obtained for cameras (10%), load cells (8%), miscellaneous milk sensors (8%), and boluses (7%). Validated traits concerned animal activity, feeding and drinking behavior, physical condition, and health of animals. The majority of tools were validated on adult cows. Non-active behavior (lying and standing) and rumination were the most often validated for the high performance. Regarding active behavior (e.g., walking), lower performance of tools was reported. Also, tools used for physical condition (e.g., body condition scoring) and health evaluation (e.g., mastitis detection) were classified in lower performance group. The precision and accuracy of feeding and drinking assessment varied depending on measured trait and used sensor. Regarding relevance for animal-based welfare assessment, several validated technologies had application for good health (e.g., milk quality sensors) and good feeding (e.g., load cells, accelerometers). Accelerometers-based systems have also practical relevance to assess good housing. However, currently available PLF technologies have low potential to assess appropriate behavior of dairy cows. To increase actors' trust toward the PLF technology and prompt sensor-based welfare assessment, validation studies, especially in commercial herds, are needed. Future research should concentrate on developing and validating PLF technologies dedicated to the assessment of appropriate behavior and tools dedicated to monitoring the health and welfare in calves and heifers.