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Animals
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Biotechnology in Animals' Management, Health and Welfare 2019
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Biotechnology in Animals' Management, Health and Welfare 2019

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Animal System and Management".

Deadline for manuscript submissions: closed (31 January 2020) | Viewed by 13206

Special Issue Editors

Prof. Dr. Paolo Baragli

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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
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Antonio Lanatà

E-Mail Website
Guest Editor
Department of Information Engineering, University of Florence, Via santa Marta, 3 - 50139 Firenze, Italy
Interests: human animal interaction; autonomic nervous system response; emotional interaction; heart rate ariability; physiological and behavioral integration; wearable system for physiological monitoring; physiological inspired models

Special Issue Information

Dear Colleagues,

Synergy between the fields of engineering, medicine, and biology has led to the rapid development of extremely sophisticated and complex monitoring systems, with highly efficient algorithms for signals analysis. These new technological tools are becoming strongly useful in different fields of human clinical practice, with evident advantages in terms of comfort (non-invasiveness), efficiency, and ease of use. The main aim is to improve the monitoring of physiological and behavioral parameters in order to accurately assess the emotional and health state of subjects.

Moreover, in this age of strong global competition, 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 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 real-time monitoring of subjects through non- or minimally invasive systems is extremely useful in other 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, and veterinary medicine, are invited to contribute to this Special Issue that aims to bring together the 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 systems;

3) Animal welfare and health as indicator of sustainable production;

4) Innovative personalized systems for ecological monitoring;

5) Dedicated models and data processing algorithms;

6) Novel sensor and system design.

Dr. Paolo Baragli
Dr. Antonio Lanatà
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.

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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15 pages, 4586 KiB  
Article
Automated Collection and Analysis of Infrared Thermograms for Measuring Eye and Cheek Temperatures in Calves
by Gemma Lowe, Brendan McCane, Mhairi Sutherland, Joe Waas, Allan Schaefer, Neil Cox and Mairi Stewart
Animals 2020, 10(2), 292; https://doi.org/10.3390/ani10020292 - 12 Feb 2020
Cited by 25 | Viewed by 3908
Abstract
As the reliance upon automated systems in the livestock industry increases, technologies need to be developed which can be incorporated into these systems to monitor animal health and welfare. Infrared thermography (IRT) is one such technology that has been used for monitoring animal [...] Read more.
As the reliance upon automated systems in the livestock industry increases, technologies need to be developed which can be incorporated into these systems to monitor animal health and welfare. Infrared thermography (IRT) is one such technology that has been used for monitoring animal health and welfare and, through automation, has the potential to be integrated into automated systems on-farm. This study reports on an automated system for collecting thermal infrared images of calves and on the development and validation of an algorithm capable of automatically detecting and analysing the eye and cheek regions from those images. Thermal infrared images were collected using an infrared camera integrated into an automated calf feeder. Images were analysed automatically using an algorithm developed to determine the maximum eye and cheek (3 × 3-pixel and 9 × 9-pixel areas) temperatures in a given image. Additionally, the algorithm determined the maximum temperature of the entire image (image maximum temperature). In order to validate the algorithm, a subset of 350 images analysed using the algorithm were also analysed manually. Images analysed using the algorithm were highly correlated with manually analysed images for maximum image (R2 = 1.00), eye (R2 = 0.99), cheek 3 × 3-pixel (R2 = 0.85) and cheek 9 × 9-pixel (R2 = 0.90) temperatures. These findings demonstrate the algorithm to be a suitable method of analysing the eye and cheek regions from thermal infrared images. Validated as a suitable method for automatically detecting and analysing the eye and cheek regions from thermal infrared images, the integration of IRT into automated on-farm systems has the potential to be implemented as an automated method of monitoring calf health and welfare. Full article
(This article belongs to the Special Issue Biotechnology in Animals' Management, Health and Welfare 2019)
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11 pages, 1430 KiB  
Article
The Use of an Activity Monitoring System for the Early Detection of Health Disorders in Young Bulls
by Mohammed Anouar Belaid, Maria Rodriguez-Prado, Eric Chevaux and Sergio Calsamiglia
Animals 2019, 9(11), 924; https://doi.org/10.3390/ani9110924 - 5 Nov 2019
Cited by 12 | Viewed by 2945
Abstract
Bulls (n = 770, average age = 127 days, SD = 53 days of age) were fitted with an activity monitoring device for three months to study if behavior could be used for early detection of diseases. The device measured the number of [...] Read more.
Bulls (n = 770, average age = 127 days, SD = 53 days of age) were fitted with an activity monitoring device for three months to study if behavior could be used for early detection of diseases. The device measured the number of steps, lying time, lying bouts, and frequency and time of attendance at the feed bunk. All healthy bulls (n = 699) throughout the trial were used to describe the normal behavior. A match-pair test was used to assign healthy bulls for the comparison vs. sick bulls. The model was developed with 70% of the data, and the remaining 30% was used for the validation. Healthy bulls did 2422 ± 128 steps/day, had 28 ± 1 lying bouts/day, spent 889 ± 12 min/day lying, and attended the feed bunk 8 ± 0.2 times/d for a total of 95 ± 8 min/day. From the total of bulls enrolled in the study, 71 (9.2%) were diagnosed sick. Their activities changed at least 10 days before the clinical signs of disease. Bulls at risk of becoming sick were predicted 9 days before clinical signs with a sensitivity and specificity of 79% and 81%, respectively. The validation of the model resulted in a sensitivity, specificity, and accuracy of 92%, 42%, and 82 %, respectively, and a 50% false positive and 12.5% false negative rates. Results suggest that activity-monitoring systems may be useful in the early identification of sick bulls. However, the high false positive rate may require further refinement. Full article
(This article belongs to the Special Issue Biotechnology in Animals' Management, Health and Welfare 2019)
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8 pages, 817 KiB  
Article
Infrared Thermography—A Non-Invasive Method of Measuring Respiration Rate in Calves
by Gemma Lowe, Mhairi Sutherland, Joe Waas, Allan Schaefer, Neil Cox and Mairi Stewart
Animals 2019, 9(8), 535; https://doi.org/10.3390/ani9080535 - 7 Aug 2019
Cited by 58 | Viewed by 5813
Abstract
Respiration rate (RR) is a common measure of cattle health and welfare. Traditionally, measuring RR involves counting flank movements as the animal inhales and exhales with each breath. This method is often considered difficult, labour-intensive and impractical. We validated the use of infrared [...] Read more.
Respiration rate (RR) is a common measure of cattle health and welfare. Traditionally, measuring RR involves counting flank movements as the animal inhales and exhales with each breath. This method is often considered difficult, labour-intensive and impractical. We validated the use of infrared thermography (IRT) as an alternative method of non-invasively measuring RR in young calves. RR was simultaneously recorded in two ways: (1) by observing flank movements from video recordings; and (2) by observing thermal fluctuations around the nostrils during inhalations and exhalations from infrared recordings. For each method, the time taken to complete five consecutive breaths (a breath being a complete inhalation/exhalation cycle) was recorded and used to calculate RR (breaths/min). From a group of five calves, a total of 12 video recordings and 12 infrared recordings were collected. For each procedure, 47 sets of five consecutive breaths were assessed. The RRs measured from video recordings of flank movements and thermal fluctuations around the nostrils from infrared recordings were highly correlated (R2 = 0.93). Validated as a suitable method for recording RR, future research can now focus on the development of algorithms to automate the use of IRT to support its integration into existing automated systems to remotely monitor calf health and welfare. Full article
(This article belongs to the Special Issue Biotechnology in Animals' Management, Health and Welfare 2019)
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