The influence of respiratory disease on the energy envelope dynamics of pig cough sounds

Silva, Mitchell; Exadaktylos, Vasileios; Ferrari, Sara; Guarino, Marcella; Aerts, Jean‐Marie; Berckmans, Daniël

doi:10.1016/j.compag.2009.07.002

Cited by 22 publications

(26 citation statements)

References 21 publications

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“…Care should be taken during long-time culture that the cell number is not overestimated due to cells that might grow close to the scaffold while not being part of the final construct. Although, more frequently used in other scientific domains, such as modeling and controlling heart rate responses of athletes (Lefever et al, 2012), energy transfer in buildings (Price et al, 1999), precision life stock farming (Silva et al, 2009), and other environmental and economic phenomena (Haredasht et al, 2011;Young, 1998), the DBM modeling technique is, as far as known by the author, unexplored in the context of bioprocess control for TE bioreactors. Nevertheless this data-based approach holds promise for the TE domain since high quality bioprocess data are often available from the bioreactor system and purely mechanistic models for complicated biological processes are often non-existent or have a significant cost of development (Koutinas et al, 2012).…”

mentioning

confidence: 99%

Model‐based cell number quantification using online single‐oxygen sensor data for tissue engineering perfusion bioreactors

Lambrechts

Papantoniou

Sonnaert

et al. 2014

Biotech & Bioengineering

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Online and non-invasive quantification of critical tissue engineering (TE) construct quality attributes in TE bioreactors is indispensable for the cost-effective up-scaling and automation of cellular construct manufacturing. However, appropriate monitoring techniques for cellular constructs in bioreactors are still lacking. This study presents a generic and robust approach to determine cell number and metabolic activity of cell-based TE constructs in perfusion bioreactors based on single oxygen sensor data in dynamic perfusion conditions. A data-based mechanistic modeling technique was used that is able to correlate the number of cells within the scaffold (R(2) = 0.80) and the metabolic activity of the cells (R(2) = 0.82) to the dynamics of the oxygen response to step changes in the perfusion rate. This generic non-destructive measurement technique is effective for a large range of cells, from as low as 1.0 × 10(5) cells to potentially multiple millions of cells, and can open-up new possibilities for effective bioprocess monitoring.

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mentioning

confidence: 99%

Model‐based cell number quantification using online single‐oxygen sensor data for tissue engineering perfusion bioreactors

Lambrechts

Papantoniou

Sonnaert

et al. 2014

Biotech & Bioengineering

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“…e sampling frequency of the collected acoustic data is 1 kHz. e porcine acoustic signals we selected are scream [16] and cough [17], which are found most commonly in the pigpen. See the data in the Supplementary Material (available here) for the denoising experiments of porcine acoustic signals.…”

Section: Methodsmentioning

confidence: 99%

An Efficient Porcine Acoustic Signal Denoising Technique Based on EEMD‐ICA‐WTD

Zhang

Tian

Banerjee

et al. 2019

Mathematical Problems in Engineering

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Automatic monitoring of group-housed pigs in real time through porcine acoustic signals has played a crucial role in automated farming. In the process of data collection and transmission, acoustic signals are generally interfered with noise. In this paper, an effective porcine acoustic signal denoising technique based on ensemble empirical mode decomposition (EEMD), independent component analysis (ICA), and wavelet threshold denoising (WTD) is proposed. Firstly, the porcine acoustic signal is decomposed into intrinsic mode functions (IMFs) by EEMD. In addition, permutation entropy (PE) is adopted to distinguish noise-dominant IMFs from the IMFs. Secondly, ICA is employed to extract the independent components (ICs) of the noise-dominant IMFs. The correlation coefficients of ICs and the first IMF are calculated to recognize noise ICs. The noise ICs will be removed. Then, WTD is applied to the other ICs. Finally, the porcine acoustic signal is reconstructed by the processed components. Experimental results show that the proposed method can effectively improve the denoising performance of porcine acoustic signal.

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“…Techniques developed in Precision Livestock Farming (use of sensors, sensing systems and real-time modelling, e.g. Silva et al, 2009) may complement or replace manual measures in the Welfare Quality † protocols. Such automation could greatly increase the effectiveness and time efficiency of the existing welfare assessment protocols while simultaneously providing valuable management information.…”

Section: Workloadmentioning

confidence: 99%

The Welfare Quality® project and beyond: Safeguarding farm animal well-being

Blokhuis

Veissier

Miele

et al. 2010

Acta Agriculturae Scandinavica, Section A - Animal Science

168

172

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Welfare Quality † was the largest ever European research project on animal welfare. Here, we briefly describe some major achievements of Welfare Quality † and identify future research priorities, potential strategies and organisational structures to build on the outcomes. Achievements include: definition of principles and criteria of good welfare; development of standardised, primarily animal-based measures for each welfare criterion and their integration in an overall assessment model. Since Welfare Quality † could not answer all the questions we recommend:(1) Continued development and refinement of the assessment systems and extension to new species.(2) The development of automatic measures of welfare to reduce the duration of the assessment while still retaining its holistic nature.(3) Exploration of potential implementation strategies across food chain actors. (4) Establishment of an independent body to manage and update the assessment and information systems, support their implementation and inform and engage stakeholders.

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The influence of respiratory disease on the energy envelope dynamics of pig cough sounds

Cited by 22 publications

References 21 publications

Model‐based cell number quantification using online single‐oxygen sensor data for tissue engineering perfusion bioreactors

Model‐based cell number quantification using online single‐oxygen sensor data for tissue engineering perfusion bioreactors

An Efficient Porcine Acoustic Signal Denoising Technique Based on EEMD‐ICA‐WTD

The Welfare Quality® project and beyond: Safeguarding farm animal well-being

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