Biotechnology in Animals' Management, Health and Welfare

A special issue of Animals (ISSN 2076-2615).

Deadline for manuscript submissions: closed (31 October 2017) | Viewed by 14024

Special Issue Editors


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Guest Editor
Department of Veterinary Sciences, University of Pisa, 56124 Pisa, Italy
Interests: animal; physiology; behavior; emotion; welfare; animal–human relationship; autonomic nervous system; cognition
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Special Issue Information

Dear Colleagues,

In recent years, the interdisciplinary synergy between engineering, medicine, and biology has led to the development of extremely sophisticated clinical devices, monitoring systems and signals analysis. These new tools are being used in different fields of human clinical practice, with evident advantages in terms of comfort (non-invasiveness), efficiency and ease of use. The main target of these devices is monitoring physiological and behavioral parameters allowing the acquisition of accurate information on both emotional state and health status of subjects.

Moreover, in this age of strong global competition, the sustainable production carried out by farms needs to be strongly improved both in terms of efficiency and animal welfare. In this context, real-time monitoring of physical, physiological and mental health of the animals using both “ready to use” technologies and ad-hoc dedicated systems, directly applicable to every day practice by farmers and technicians, is the most demanding and promising challenge to deal with.

Recent studies highlighted how the Autonomic Nervous System parameters and the behavioral changes (i.e., manifestation of acute and chronic pain or evaluation of fear-induced states) can provide concrete information about the emotional and physical well-being of animals, with the consequent impact on livestock production.

It is worth noting that the real-time monitoring of subjects through non- or minimally invasive systems is extremely useful in others application areas, such as in laboratory animals where the determination of the end-point of a trial is fundamental to the well-being of animals. Similarly, another application of these systems can be found in assisted Activities and Therapy with animals, where behavioral and physiological monitoring systems can help to estimate the efficacy of the intervention itself. In these situations, humans and animals play the actor roles in the interaction process and their emotional response is an essential information to be measured.

Innovative papers from different research areas such as biotechnologies, bioengineering, computer science, animal science, veterinary medicine, are invited to contribute to this Special Issue that aims at bring together latest advances of biotechnologies for the management, health and welfare of animals. Interdisciplinary studies will be taken into account, especially ones regarding (but not limited to): 1) long- and short-term body monitoring at individual and/or group level of animals involved in breeding production, laboratory and Assisted Intervention, 2) data analysis of farm activity and laboratory system (measuring physical and behavioral indicators), 3) measuring animal welfare and health as indicator of sustainable production, 4) personalized system for ecological monitoring, 5) dedicated models and data processing algorithms, and 6) novel sensor and system design.

Dr. Paolo Baragli
Dr. Antonio Lanata
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Animals is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (3 papers)

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Research

13 pages, 373 KiB  
Article
Using Longitudinal Assessment on Extensively Managed Ewes to Quantify Welfare Compromise and Risks
by Carolina Munoz, Angus Campbell, Stuart Barber, Paul Hemsworth and Rebecca Doyle
Animals 2018, 8(1), 8; https://doi.org/10.3390/ani8010008 - 8 Jan 2018
Cited by 21 | Viewed by 4210
Abstract
This study examined variation in the welfare of extensively managed ewes and potential welfare risks. A total of 100 Merino ewes (aged 2–4 years) were individually identified and examined at three key stages: pregnancy, lactation and weaning. Eight animal-based welfare measures were used [...] Read more.
This study examined variation in the welfare of extensively managed ewes and potential welfare risks. A total of 100 Merino ewes (aged 2–4 years) were individually identified and examined at three key stages: pregnancy, lactation and weaning. Eight animal-based welfare measures were used to assess welfare: flight distance, body condition score (BCS), fleece condition, skin lesions, tail length, dag score, lameness and mastitis. Data were analysed by ANOVA and McNemar’s statistics. Overall, the average BCS of the group was in agreement with industry recommendations. However, a number of animals were classified with inadequate condition (either too thin or too fat) across the three observation periods. The presence of heavy dags was greatest at mid-lactation (87%, P < 0.0001), lameness was greatest at weaning (14%, P = 0.01), clinical mastitis was 1% annually, and five ewes were lost from the study. Ewes had better health at mid-pregnancy compared to mid-lactation and weaning. The main welfare issues identified were under and over feeding, ewe mortality, lameness, ecto-parasites (flystrike) and mastitis, all of which have the potential to be reduced with improved management practices. Future welfare assessment programs must consider that significant variation in on-farm welfare will occur in extensively managed systems and this needs to be accounted for when evaluating farms. Full article
(This article belongs to the Special Issue Biotechnology in Animals' Management, Health and Welfare)
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437 KiB  
Article
Animal-Based Measures to Assess the Welfare of Extensively Managed Ewes
by Carolina Munoz, Angus Campbell, Paul Hemsworth and Rebecca Doyle
Animals 2018, 8(1), 2; https://doi.org/10.3390/ani8010002 - 24 Dec 2017
Cited by 34 | Viewed by 4881
Abstract
The reliability and feasibility of 10 animal-based measures of ewe welfare were examined for use in extensive sheep production systems. Measures were: Body condition score (BCS), rumen fill, fleece cleanliness, fleece condition, skin lesions, tail length, dag score, foot-wall integrity, hoof overgrowth and [...] Read more.
The reliability and feasibility of 10 animal-based measures of ewe welfare were examined for use in extensive sheep production systems. Measures were: Body condition score (BCS), rumen fill, fleece cleanliness, fleece condition, skin lesions, tail length, dag score, foot-wall integrity, hoof overgrowth and lameness, and all were examined on 100 Merino ewes (aged 2–4 years) during mid-pregnancy, mid-lactation and weaning by a pool of nine trained observers. The measures of BCS, fleece condition, skin lesions, tail length, dag score and lameness were deemed to be reliable and feasible. All had good observer agreement, as determined by the percentage of agreement, Kendall’s coefficient of concordance (W) and Kappa (k) values. When combined, these nutritional and health measures provide a snapshot of the current welfare status of ewes, as well as evidencing previous or potential welfare issues. Full article
(This article belongs to the Special Issue Biotechnology in Animals' Management, Health and Welfare)
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1962 KiB  
Article
Supporting the Development and Adoption of Automatic Lameness Detection Systems in Dairy Cattle: Effect of System Cost and Performance on Potential Market Shares
by Tim Van De Gucht, Stephanie Van Weyenberg, Annelies Van Nuffel, Ludwig Lauwers, Jürgen Vangeyte and Wouter Saeys
Animals 2017, 7(10), 77; https://doi.org/10.3390/ani7100077 - 8 Oct 2017
Cited by 11 | Viewed by 4164
Abstract
Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system [...] Read more.
Most automatic lameness detection system prototypes have not yet been commercialized, and are hence not yet adopted in practice. Therefore, the objective of this study was to simulate the effect of detection performance (percentage missed lame cows and percentage false alarms) and system cost on the potential market share of three automatic lameness detection systems relative to visual detection: a system attached to the cow, a walkover system, and a camera system. Simulations were done using a utility model derived from survey responses obtained from dairy farmers in Flanders, Belgium. Overall, systems attached to the cow had the largest market potential, but were still not competitive with visual detection. Increasing the detection performance or lowering the system cost led to higher market shares for automatic systems at the expense of visual detection. The willingness to pay for extra performance was €2.57 per % less missed lame cows, €1.65 per % less false alerts, and €12.7 for lame leg indication, respectively. The presented results could be exploited by system designers to determine the effect of adjustments to the technology on a system’s potential adoption rate. Full article
(This article belongs to the Special Issue Biotechnology in Animals' Management, Health and Welfare)
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