Dataset Information

Optimal Flow-A Pilot Study Balancing Sheep Movement and Welfare in Abattoirs.

ABSTRACT: Abattoirs are faced with the challenge of moving livestock efficiently through the plant, while also engaging in handling practices that assure good animal welfare. Achieving optimal outcomes for both of these goals can bring them into conflict. An additional source of conflict can arise from the design of the abattoir. These problems are compounded by the dearth of research available to inform how livestock should be handled to achieve all of these goals. We applied the concept of 'Optimal Flow' to describe conditions under which rate of movement is maximised while overt signs of distress in sheep are minimised. Effectively, this represents the point at which trade-offs between speed and welfare converge. The current pilot study examined the behavioural interactions between humans (n = 5), livestock herding dogs (n = 7), and sheep (n = 3235) in a large Australian abattoir to describe the factors associated with an increase or decrease in rate of sheep movement per minute. It revealed that distress behaviours in sheep were associated with dog presence and with a decrease in livestock movement rate. However, we found that as sheep density increased, there was increased livestock movement rate as well as an elevated incidence of distress behaviours. Optimal Flow at this abattoir was achieved by maintaining sheep at lower densities. Our report discusses the possible confounds in this interpretation.

SUBMITTER: Starling MJ

PROVIDER: S-EPMC7912567 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Optimal Flow-A Pilot Study Balancing Sheep Movement and Welfare in Abattoirs.

Starling Melissa J MJ Payne Elyssa E McGreevy Paul P

Animals : an open access journal from MDPI 20210129 2

Abattoirs are faced with the challenge of moving livestock efficiently through the plant, while also engaging in handling practices that assure good animal welfare. Achieving optimal outcomes for both of these goals can bring them into conflict. An additional source of conflict can arise from the design of the abattoir. These problems are compounded by the dearth of research available to inform how livestock should be handled to achieve all of these goals. We applied the concept of 'Optimal Flow ...[more]

PMID: 33572885

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Project description:The aim of this study was to identify the main on-farm welfare issues likely to be encountered in extensive sheep farming systems. Thirty-two commercial sheep farms in Victoria, Australia were involved in this study. Of the 32 farms involved, 30 were visited twice (at mid-pregnancy and weaning), and 2 farms only once (both at weaning). In total, 62 visits were conducted and 6,200 ewes (aged 2-5 years) were examined using six animal-based indicators: body condition score (BCS), fleece condition, skin lesions, tail length, dag score and lameness. In addition, the number of ewes that needed further care (such as sick or injured sheep) was recorded and reported to the farmers. Generalised linear mixed models were conducted to investigate associations between welfare outcomes and visit, ewe breed and location, with all three, and their interactions, as fixed factors. In all instances, farm was set as a random factor to account for specific variation between farms. Overall, the welfare of the ewe flocks, based on the six indicators measured, was considered good. A total of 86.9% of the ewes were in adequate BCS (2.5-3.5), 91% had good fleece condition, 69.2% had no skin lesions, 97.1% had low dag scores, and overall lameness was 4.7%. An important and prevalent risk to welfare identified across farms was short tail length; with 85.7% of ewes having tails docked shorter than the third palpable joint. While the welfare of the flock was good, ewes in need of further care were identified at all farms. There were 185 (3.0%) cases needing further care, and the extent of welfare compromise of these animals was considered significant. Main reasons for further care were moderate/severe lameness or foot-related issues, BCS ≤ 2 and active dermatophilosis or broken wool. To our knowledge, this study constitutes the largest assessment of ewes conducted in Australia, and the findings provide valuable insight into the main welfare issues likely to be encountered in extensive sheep farming enterprises. Future studies should develop practical technologies that can assist in the detection of the welfare issues identified in this study. In addition, the thresholds identified here could be used for future comparison and sheep welfare benchmarking programs to assess farm performance and measure continuous improvements.

Project description:ObjectiveThe objectives of this paper are to 1) construct a new network model compatible with distributed computation, 2) construct the full optimal power flow (OPF) in a distributed fashion so that an effective, non-inferior solution can be found, and 3) develop a scalable algorithm that guarantees the convergence to a local minimum.Existing challengesDue to the nonconvexity of the problem, the search for a solution to OPF problems is not scalable, which makes the OPF highly limited for the system operation of large-scale real-world power grids-"the curse of dimensionality". The recent attempts at distributed computation aim for a scalable and efficient algorithm by reducing the computational cost per iteration in exchange of increased communication costs.MotivationA new network model allows for efficient computation without increasing communication costs. With the network model, recent advancements in distributed computation make it possible to develop an efficient and scalable algorithm suitable for large-scale OPF optimizations.MethodsWe propose a new network model in which all nodes are directly connected to the center node to keep the communication costs manageable. Based on the network model, we suggest a nodal distributed algorithm and direct communication to all nodes through the center node. We demonstrate that the suggested algorithm converges to a local minimum rather than a point, satisfying the first optimality condition.ResultsThe proposed algorithm identifies solutions to OPF problems in various IEEE model systems. The solutions are identical to those using a centrally optimized and heuristic approach. The computation time at each node does not depend on the system size, and Niter does not increase significantly with the system size.ConclusionOur proposed network model is a star network for maintaining the shortest node-to-node distances to allow a linear information exchange. The proposed algorithm guarantees the convergence to a local minimum rather than a maximum or a saddle point, and it maintains computational efficiency for a large-scale OPF, scalable algorithm.

Dataset Information

Optimal Flow-A Pilot Study Balancing Sheep Movement and Welfare in Abattoirs.

Publications

Optimal Flow-A Pilot Study Balancing Sheep Movement and Welfare in Abattoirs.

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