Integrative Sustainability Analysis of European Pig Farms: Development of a Multi-Criteria Assessment Tool

Societal interest in all aspects of sustainability has increased. Therefore, pig farmers need to be aware of their strengths and weaknesses in all dimensions of sustainability: economy, environment, social wellbeing, and animal health and welfare. Our aim was to describe and critically discuss the development of a sustainability assessment tool for pig farms and to evaluate its suitability by applying it to 63 European pig farms (13 breeding, 27 breeding-to-finishing, and 23 finishing farms). The multi-criteria assessment tool was developed in several steps (the selection and scaling of indicators and their aggregation and weighting) in order to summarise the indicators into subtheme and theme scores. The indicators contributing the most to the subtheme/theme scores were identified and discussed in order to evaluate the procedure of the development. For example, some indicators, such as Ecological compensation area, Fairness of prices, and Tail docking, for which farms were scored low, were also identified as “real world problems” in other studies. For other sustainability aspects with low performance, the threshold might have been set too ambitiously, e.g., for Number of sows per annual working unit. Furthermore, to analyse the suitability of the tool, we assessed the best and worst median theme scores (good and poor performances) for each dimension, as well as the variability of the performances of the farms within the themes. Some themes were found to be moderate, such as Pig comfort, Biodiversity, or Resilience, whereas others were found to be good, e.g., Water and the Human–animal relationship, as well as several themes of the social wellbeing dimension. Overall, the sustainability tool provides a comprehensive assessment of the sustainability of pig production. Furthermore, this publication contributes to both the theory (development of a robust sustainability tool) and the practice (provision of a tool to assess and benchmark the sustainability on farms). As a next step, a sensitivity analysis should be performed, and the tool should be applied for further development.

Review: Future consequences of climate change for European Union pig production

Climate change is already a reality for livestock production. In contrast to the ruminant species, little is known about the impacts and the vulnerability of pig European Union (EU) sector to climate warming. This review deals with the potential and the already measurable effects of climate change in pig production. Based on evidences published in the literature, climate change may reduce EU pig productivity by indirectly reducing the availability of crops usually used in pig feeding, spreading the vector or pathogen to new locations and increasing the risk of exposure to cereals contaminated with mycotoxins; and directly mainly by inducing heat stress and increasing the animal's susceptibility to various diseases. Provision of realistic projections of possible impacts of future climate changes on EU pig sector is a prerequisite to evaluate its vulnerability and propose effective adaptation strategies. Simulation modelling approach is the most commonly used approach for exploring the effects of medium or long-term climate change/variability in pig production. One of the main challenges for this modelling approach is to account for both direct and indirect possible effects but also to uncertainties in parameter values that substantially increase the uncertainty estimates for model projections. The last part of the paper focus on the main issues that still need to be overcome for developing a decision support tools for simulating the direct and indirect effect of climate change in pig farms.

Computer Vision Applied to Detect Lethargy through Animal Motion Monitoring: A Trial on African Swine Fever in Wild Boar

Early detection of infectious diseases is the most cost-effective strategy in disease surveillance for reducing the risk of outbreaks. Latest deep learning and computer vision improvements are powerful tools that potentially open up a new field of research in epidemiology and disease control. These techniques were used here to develop an algorithm aimed to track and compute animal motion in real time. This algorithm was used in experimental trials in order to assess African swine fever (ASF) infection course in Eurasian wild boar. Overall, the outcomes showed negative correlation between motion reduction and fever caused by ASF infection. In addition, infected animals computed significant lower movements compared to uninfected animals. The obtained results suggest that a motion monitoring system based on artificial vision may be used in indoors to trigger suspicions of fever. It would help farmers and animal health services to detect early clinical signs compatible with infectious diseases. This technology shows a promising non-intrusive, economic and real time solution in the livestock industry with especial interest in ASF, considering the current concern in the world pig industry.

Evaluating environmental impacts of contrasting pig farming systems with life cycle assessment

Environmental impacts of 15 European pig farming systems were evaluated in the European Union Q-PorkChains project using life cycle assessment. One conventional and two non-conventional systems were evaluated from each of the five countries: Denmark, The Netherlands, Spain, France and Germany. The data needed for calculations were obtained from surveys of 5 to 10 farms from each system. The systems studied were categorised into conventional (C), adapted conventional (AC), traditional (T) and organic (O). Compared with C systems, AC systems differed little, with only minor changes to improve meat quality, animal welfare or environmental impacts, depending on the system. The difference was much larger for T systems, using very fat, slow-growing traditional breeds and generally outdoor raising of fattening pigs. Environmental impacts were calculated at the farm gate and expressed per kg of pig live weight and per ha of land used. For C systems, impacts per kg LW for climate change, acidification, eutrophication, energy use and land occupation were 2.3 kg CO2-eq, 44.0 g SO2-eq, 18.5 g PO4-eq, 16.2 MJ and 4.1 m2, respectively. Compared with C, differences in corresponding mean values were +13%, +5%, 0%, +2% and +16% higher for AC; +54%, +79%, +23%, +50% and +156% for T, and +4%, -16%, +29%, +11% and +121% for O. Conversely, when expressed per ha of land use, mean impacts were 10% to 60% lower for T and O systems, depending on the impact category. This was mainly because of higher land occupation per kg of pig produced, owing to feed production and the outdoor raising of sows and/or fattening pigs. The use of straw bedding tended to increase climate change impact per kg LW. The use of traditional local breeds, with reduced productivity and feed efficiency, resulted in higher impacts per kg LW for all impact categories. T systems with extensive outdoor raising of pigs resulted in markedly lower impact per ha of land used. Eutrophication potential per ha was substantially lower for O systems. Conventional systems had lower global impacts (global warming, energy use, land use), expressed per kg LW, whereas differentiated systems had lower local impacts (eutrophication, acidification), expressed per ha of land use.

There is room for selection in a small local pig breed when using optimum contribution selection: a simulation study

Selection progress must be carefully balanced against the conservation of genetic variation in small populations of local breeds. Well-defined breeding programs with specified selection traits are rare in local pig breeds. Given the small population size, the focus is often on the management of genetic diversity. However, in local breeds, optimum contribution selection can be applied to control the rate of inbreeding and to avoid reduced performance in traits with high market value. The aim of this study was to assess the extent to which a breeding program aiming for improved product quality in a small local breed would be feasible. We used stochastic simulations to compare 25 scenarios. The scenarios differed in size of population, selection intensity of boars, type of selection (random selection, truncation selection based on BLUP breeding values, or optimum contribution selection based on BLUP breeding values), and heritability of the selection trait. It was assumed that the local breed is used in an extensive system for a high-meat-quality market. The simulations showed that in the smallest population (300 female reproducers), inbreeding increased by 0.8% when selection was performed at random. With optimum contribution selection, genetic progress can be achieved that is almost as great as that with truncation selection based on BLUP breeding values (0.2 to 0.5 vs. 0.3 to 0.5 genetic SD, P < 0.05), but at a considerably decreased rate of inbreeding (0.7 to 1.2 vs. 2.3 to 5.7%, P < 0.01). This confirmation of the potential utilization of OCS even in small populations is important in the context of sustainable management and the use of animal genetic resources.