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      Structural characterization of piglet producing farms and their sow removal patterns in Finland

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          Abstract

          Background

          The main objectives of this observational, cross-sectional study were to characterize piglet producing farms in Finland and to investigate how farm profiles are associated with sow culling and mortality.

          The study was conducted on 43 farms during 2014. A questionnaire survey was administered in-person and supplemented with observations in the housing facilities. Annual removal figures and average monthly sow inventories were retrieved from a centralized animal data recording system (National Swine Registry) administered by the Finnish Food Authority. Multiple correspondence analysis and hierarchical clustering were used to explore the complex underlying data-driven patterns.

          Results

          Sow removal varied markedly between farms with an overall average culling percentage of 38.0% (95% CI 34.1–42.0) and a relatively high average mortality percentage 9.7% (95% CI 7.9–11.5). We identified three farm clusters, which differed both in their typologies and removal patterns. Cluster 1 included farms with features indicative of a semi-intensive or intensive kind of farming, such as larger herd and room sizes, higher stocking density and more sows per caretaker. Most of the cluster 1 farms exceeded the investigated cut-off levels for culling and mortality. Cluster 2 farms were estimated to have the best animal welfare among the sample farms based on a combination of environmental indicators (e.g. amount of bedding, rooting and nesting materials, space allowance, pen cleanliness) and the lowest level of sow mortality as an animal-based indicator. Cluster 3 farms followed a strategy of a rather non-intensified system based on the predominance of smaller herd size, lower stocking density and less sows per caretaker, combined breeding and gestation rooms and rare use of farrowing induction. This cluster showed the lowest culling levels within the sample.

          Conclusions

          This study captures the diversity among Finnish sow farms and provides a baseline assessment of their practices and facilities. Our results support the notion that farm typologies are associated with sow culling and mortality. In summary, the control of suboptimal sow removal cannot be based on single improvements only, because of other limitations within the individual farm resources.

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          Most cited references39

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          Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science

          We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Although current agricultural systems models have features that are needed for the Use Cases, we found that all of them have limitations and need to be improved. We identified common limitations across all Use Cases, namely 1) a scarcity of data for developing, evaluating, and applying agricultural system models and 2) inadequate knowledge systems that effectively communicate model results to society. We argue that these limitations are greater obstacles to progress than gaps in conceptual theory or available methods for using system models. New initiatives on open data show promise for addressing the data problem, but there also needs to be a cultural change among agricultural researchers to ensure that data for addressing the range of Use Cases are available for future model improvements and applications. We conclude that multiple platforms and multiple models are needed for model applications for different purposes. The Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.
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            The importance of straw for pig and cattle welfare: A review

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              Invited review: Culling: nomenclature, definitions, and recommendations.

              Replacing cows on a dairy is a major cost of operation. There is a need for the industry to adopt a more standardized approach to reporting the rate at which cows exit from the dairy, and to reporting the reasons why cows are replaced and their destination as they exit the dairy. Herd turnover rate is recommended as the preferred term for characterizing the cows exiting a dairy, in preference to herd replacement rate, culling rate, or percent exiting, all of which have served as synonyms. Herd turnover rate should be calculated as the number of cows that exit in a defined period divided by the animal time at risk for the population being characterized. The terms voluntary and involuntary culling suffer from problems of definition and their use should be discouraged. Destination should be recorded for all cows that exit the dairy and opportunities to record one or more reasons for exiting should be provided by management systems. Comparing reported reasons between dairies requires considerable caution because of differences in case definitions and recording methods. Relying upon culling records to monitor disease has been and will always be an ineffective management strategy. Dairies are encouraged to record and monitor disease events and reproductive performance and use this information as the basis for management efforts aimed at reducing the need to replace cows.
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                Author and article information

                Contributors
                paula.bergman@helsinki.fi
                camilla.munsterhjelm@helsinki.fi
                anna-maija.virtala@helsinki.fi
                olli.peltoniemi@helsinki.fi
                anna.valros@helsinki.fi
                mari.heinonen@helsinki.fi
                Journal
                Porcine Health Manag
                Porcine Health Manag
                Porcine Health Management
                BioMed Central (London )
                2055-5660
                31 May 2019
                31 May 2019
                2019
                : 5
                : 12
                Affiliations
                [1 ]ISNI 0000 0004 0410 2071, GRID grid.7737.4, Faculty of Veterinary Medicine, Department of Production Animal Medicine, , University of Helsinki, ; Paroninkuja 20, 04920, Saarentaus, Helsinki, Finland
                [2 ]Department of Production Animal Medicine, Faculty of Veterinary Medicine, Research Centre for Animal Welfare, P.O. Box 57, 00014 University of Helsinki, Saarentaus, Helsinki, Finland
                [3 ]ISNI 0000 0004 0410 2071, GRID grid.7737.4, Faculty of Veterinary Medicine, Department of Veterinary Biosciences, , University of Helsinki, ; P.O. Box 66, 00014 University of Helsinki, Saarentaus, Helsinki, Finland
                Author information
                http://orcid.org/0000-0002-1646-8797
                Article
                119
                10.1186/s40813-019-0119-8
                6540429
                2f77b9a1-8bf4-4208-8627-7d3e75ca3100
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 29 January 2019
                : 13 May 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100006697, Maa- ja MetsätalousministeriÖ;
                Award ID: 1807/312/2012
                Award Recipient :
                Funded by: Oiva Kuusiston Säätiö (FI)
                Award ID: personal grant
                Funded by: FundRef http://dx.doi.org/10.13039/501100006515, Eläinlääketieteen Tutkimuksen Tukisäätiö;
                Award ID: personal grant
                Funded by: FundRef http://dx.doi.org/10.13039/501100007404, Suomen Eläinlääketieteen Säätiö;
                Award ID: personal grant
                Categories
                Research
                Custom metadata
                © The Author(s) 2019

                sow removal,management,housing,multiple correspondence analysis,hierarchical cluster analysis,epidemiology

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