Detecting sow vulva size change around estrus using machine vision technology
Accurate estrus detection of sows is critical to achieving a high farrowing rate and maintaining good reproductive performance. The conventional method of estrus detection uses a back pressure test by breeding technicians, which is time-consuming and labor-intensive. This study aimed to develop an a...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-02-01
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| Series: | Smart Agricultural Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375522000557 |
| _version_ | 1818118375540260864 |
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| author | Ziteng Xu Riley Sullivan Jianfeng Zhou Corinne Bromfield Teng Teeh Lim Timothy J. Safranski Zheng Yan |
| author_facet | Ziteng Xu Riley Sullivan Jianfeng Zhou Corinne Bromfield Teng Teeh Lim Timothy J. Safranski Zheng Yan |
| author_sort | Ziteng Xu |
| collection | DOAJ |
| description | Accurate estrus detection of sows is critical to achieving a high farrowing rate and maintaining good reproductive performance. The conventional method of estrus detection uses a back pressure test by breeding technicians, which is time-consuming and labor-intensive. This study aimed to develop an automated estrus detection method by monitoring the change in vulva swelling around the estrus using a LiDAR camera. A total of seven multiparous individually housed sows and a gilt were monitored once per day for 19 consecutive days, starting from 2 days before they stopped receiving Matrix®. A three-dimensional (3D) point cloud of the vulva region was manually acquired using the LiDAR camera at 0.7 - 1.0 m from the back of the sows. The accuracy of the LiDAR camera was examined in a laboratory before imaging sows. Results showed that the measurement error in depth was 3.4 ± 3.0 mm (mean ± SD). Collected point cloud data of sows were processed using a customized algorithm to create 3D models of the vulva region by separating them from the sow's body. Five 2D and 3D features were extracted from the 3D models to describe vulva size. Linear regression analysis showed that the calculated volume (CV = width × length × height) could represent the vulva volume (R2 = 0.92). Results also showed that the vulva volume was a reliable estrous indicator. Swelling duration and intensity showed large variation among different sows. This study also indicates that sows with larger vulva volume had a smaller percentage of increase around estrus. The results suggest that the LiDAR camera has the potential as a non-invasive tool to help identify the sow's estrus. |
| first_indexed | 2024-12-11T04:53:18Z |
| format | Article |
| id | doaj.art-27143c4740ba46dab45be326c4fcad98 |
| institution | Directory Open Access Journal |
| issn | 2772-3755 |
| language | English |
| last_indexed | 2024-12-11T04:53:18Z |
| publishDate | 2023-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj.art-27143c4740ba46dab45be326c4fcad982022-12-22T01:20:20ZengElsevierSmart Agricultural Technology2772-37552023-02-013100090Detecting sow vulva size change around estrus using machine vision technologyZiteng Xu0Riley Sullivan1Jianfeng Zhou2Corinne Bromfield3Teng Teeh Lim4Timothy J. Safranski5Zheng Yan6Department of Biomedical, Biological and Chemical Engineering, University of Missouri,211 Agricultural Engineering Buildi, Columbia, MO 65211, United StatesDivision of Animal Sciences, University of Missouri, Columbia, MO 65211, United StatesDepartment of Biomedical, Biological and Chemical Engineering, University of Missouri,211 Agricultural Engineering Buildi, Columbia, MO 65211, United States; Division of Plant Science and Technology, University of Missouri, Columbia, MO 65211, United States; Corresponding author at: Department of Biomedical, Biological and Chemical Engineering, University of Missouri, 211 Agricultural Engineering Buildi, Columbia, MO 65211, United States.Division of Animal Sciences, University of Missouri, Columbia, MO 65211, United StatesDepartment of Biomedical, Biological and Chemical Engineering, University of Missouri,211 Agricultural Engineering Buildi, Columbia, MO 65211, United States; Division of Plant Science and Technology, University of Missouri, Columbia, MO 65211, United StatesDivision of Animal Sciences, University of Missouri, Columbia, MO 65211, United StatesDepartment of Biomedical, Biological and Chemical Engineering, University of Missouri,211 Agricultural Engineering Buildi, Columbia, MO 65211, United StatesAccurate estrus detection of sows is critical to achieving a high farrowing rate and maintaining good reproductive performance. The conventional method of estrus detection uses a back pressure test by breeding technicians, which is time-consuming and labor-intensive. This study aimed to develop an automated estrus detection method by monitoring the change in vulva swelling around the estrus using a LiDAR camera. A total of seven multiparous individually housed sows and a gilt were monitored once per day for 19 consecutive days, starting from 2 days before they stopped receiving Matrix®. A three-dimensional (3D) point cloud of the vulva region was manually acquired using the LiDAR camera at 0.7 - 1.0 m from the back of the sows. The accuracy of the LiDAR camera was examined in a laboratory before imaging sows. Results showed that the measurement error in depth was 3.4 ± 3.0 mm (mean ± SD). Collected point cloud data of sows were processed using a customized algorithm to create 3D models of the vulva region by separating them from the sow's body. Five 2D and 3D features were extracted from the 3D models to describe vulva size. Linear regression analysis showed that the calculated volume (CV = width × length × height) could represent the vulva volume (R2 = 0.92). Results also showed that the vulva volume was a reliable estrous indicator. Swelling duration and intensity showed large variation among different sows. This study also indicates that sows with larger vulva volume had a smaller percentage of increase around estrus. The results suggest that the LiDAR camera has the potential as a non-invasive tool to help identify the sow's estrus.http://www.sciencedirect.com/science/article/pii/S2772375522000557Swine reproductionEstrus detection3D cameraDigital agriculture |
| spellingShingle | Ziteng Xu Riley Sullivan Jianfeng Zhou Corinne Bromfield Teng Teeh Lim Timothy J. Safranski Zheng Yan Detecting sow vulva size change around estrus using machine vision technology Smart Agricultural Technology Swine reproduction Estrus detection 3D camera Digital agriculture |
| title | Detecting sow vulva size change around estrus using machine vision technology |
| title_full | Detecting sow vulva size change around estrus using machine vision technology |
| title_fullStr | Detecting sow vulva size change around estrus using machine vision technology |
| title_full_unstemmed | Detecting sow vulva size change around estrus using machine vision technology |
| title_short | Detecting sow vulva size change around estrus using machine vision technology |
| title_sort | detecting sow vulva size change around estrus using machine vision technology |
| topic | Swine reproduction Estrus detection 3D camera Digital agriculture |
| url | http://www.sciencedirect.com/science/article/pii/S2772375522000557 |
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