Characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parity
Precision livestock farming can combine sensors and complex data to provide a simple score of meaningful productivity, pig welfare, and farm sustainability, which are the main drivers of modern pig production. Examples include using infrared thermography to monitor the temperature of sows to detect...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-09-01
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| Series: | Frontiers in Veterinary Science |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fvets.2022.920302/full |
| _version_ | 1811279905652998144 |
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| author | Stephan Rosengart Stephan Rosengart Bussarakam Chuppava Lea-Sophie Trost Hubert Henne Jens Tetens Imke Traulsen Ansgar Deermann Michael Wendt Christian Visscher |
| author_facet | Stephan Rosengart Stephan Rosengart Bussarakam Chuppava Lea-Sophie Trost Hubert Henne Jens Tetens Imke Traulsen Ansgar Deermann Michael Wendt Christian Visscher |
| author_sort | Stephan Rosengart |
| collection | DOAJ |
| description | Precision livestock farming can combine sensors and complex data to provide a simple score of meaningful productivity, pig welfare, and farm sustainability, which are the main drivers of modern pig production. Examples include using infrared thermography to monitor the temperature of sows to detect the early stages of the disease. To take account of these drivers, we assigned 697 hybrid (BHZP db. Viktoria) sows to four parity groups. In addition, by pooling clinical findings from every sow and their piglets, sows were classified into three groups for the annotation: healthy, clinically suspicious, and diseased. Besides, the udder was thermographed, and performance data were documented. Results showed that the piglets of diseased sows with eighth or higher parity had the lowest daily weight gain [healthy; 192 g ± 31.2, clinically suspicious; 191 g ± 31.3, diseased; 148 g ± 50.3 (p < 0.05)] and the highest number of stillborn piglets (healthy; 2.2 ± 2.39, clinically suspicious; 2.0 ± 1.62, diseased; 3.91 ± 4.93). Moreover, all diseased sows showed higher maximal skin temperatures by infrared thermography of the udder (p < 0.05). Thus, thermography coupled with Artificial Intelligence (AI) systems can help identify and orient the diagnosis of symptomatic animals to prompt adequate reaction at the earliest time. |
| first_indexed | 2024-04-13T01:04:16Z |
| format | Article |
| id | doaj.art-5f4f0ef10c3a4a8eaea777133b453fb8 |
| institution | Directory Open Access Journal |
| issn | 2297-1769 |
| language | English |
| last_indexed | 2024-04-13T01:04:16Z |
| publishDate | 2022-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Veterinary Science |
| spelling | doaj.art-5f4f0ef10c3a4a8eaea777133b453fb82022-12-22T03:09:24ZengFrontiers Media S.A.Frontiers in Veterinary Science2297-17692022-09-01910.3389/fvets.2022.920302920302Characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parityStephan Rosengart0Stephan Rosengart1Bussarakam Chuppava2Lea-Sophie Trost3Hubert Henne4Jens Tetens5Imke Traulsen6Ansgar Deermann7Michael Wendt8Christian Visscher9Clinic for Swine and Small Ruminants, Forensic Medicine and Ambulatory Service, University of Veterinary Medicine Hannover, Foundation, Hanover, GermanyInstitute for Animal Nutrition, University of Veterinary Medicine Hannover, Foundation, Hanover, GermanyInstitute for Animal Nutrition, University of Veterinary Medicine Hannover, Foundation, Hanover, GermanyDepartment of Animal Sciences, Livestock Systems, Georg-August-University Göttingen, Göttingen, GermanyBHZP GmbH, Dahlenburg-Ellringen, GermanyDepartment of Animal Sciences, University of Göttingen, Göttingen, GermanyDepartment of Animal Sciences, Livestock Systems, Georg-August-University Göttingen, Göttingen, GermanyEVH Select GmbH, Meppen, GermanyClinic for Swine and Small Ruminants, Forensic Medicine and Ambulatory Service, University of Veterinary Medicine Hannover, Foundation, Hanover, GermanyInstitute for Animal Nutrition, University of Veterinary Medicine Hannover, Foundation, Hanover, GermanyPrecision livestock farming can combine sensors and complex data to provide a simple score of meaningful productivity, pig welfare, and farm sustainability, which are the main drivers of modern pig production. Examples include using infrared thermography to monitor the temperature of sows to detect the early stages of the disease. To take account of these drivers, we assigned 697 hybrid (BHZP db. Viktoria) sows to four parity groups. In addition, by pooling clinical findings from every sow and their piglets, sows were classified into three groups for the annotation: healthy, clinically suspicious, and diseased. Besides, the udder was thermographed, and performance data were documented. Results showed that the piglets of diseased sows with eighth or higher parity had the lowest daily weight gain [healthy; 192 g ± 31.2, clinically suspicious; 191 g ± 31.3, diseased; 148 g ± 50.3 (p < 0.05)] and the highest number of stillborn piglets (healthy; 2.2 ± 2.39, clinically suspicious; 2.0 ± 1.62, diseased; 3.91 ± 4.93). Moreover, all diseased sows showed higher maximal skin temperatures by infrared thermography of the udder (p < 0.05). Thus, thermography coupled with Artificial Intelligence (AI) systems can help identify and orient the diagnosis of symptomatic animals to prompt adequate reaction at the earliest time.https://www.frontiersin.org/articles/10.3389/fvets.2022.920302/fullinfrared imagingpostpartum dysgalactia syndromeprecision farmingsmart farminghealthcarewelfare monitoring |
| spellingShingle | Stephan Rosengart Stephan Rosengart Bussarakam Chuppava Lea-Sophie Trost Hubert Henne Jens Tetens Imke Traulsen Ansgar Deermann Michael Wendt Christian Visscher Characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parity Frontiers in Veterinary Science infrared imaging postpartum dysgalactia syndrome precision farming smart farming healthcare welfare monitoring |
| title | Characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parity |
| title_full | Characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parity |
| title_fullStr | Characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parity |
| title_full_unstemmed | Characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parity |
| title_short | Characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parity |
| title_sort | characteristics of thermal images of the mammary gland and of performance in sows differing in health status and parity |
| topic | infrared imaging postpartum dysgalactia syndrome precision farming smart farming healthcare welfare monitoring |
| url | https://www.frontiersin.org/articles/10.3389/fvets.2022.920302/full |
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