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Oestrus Analysis of Sows Based on Bionic Boars and Machine Vision Technology
SIMPLE SUMMARY: This study proposes a method and device for the intelligent mobile monitoring of oestrus on a sow farm; this type of monitoring is applied in the field of sow production. A boar model that imitates the sounds, smells, and touch of real boars was built to detect the oestrus in sows af...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8224023/ https://www.ncbi.nlm.nih.gov/pubmed/34063888 http://dx.doi.org/10.3390/ani11061485 |
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author | Lei, Kaidong Zong, Chao Du, Xiaodong Teng, Guanghui Feng, Feiqi |
author_facet | Lei, Kaidong Zong, Chao Du, Xiaodong Teng, Guanghui Feng, Feiqi |
author_sort | Lei, Kaidong |
collection | PubMed |
description | SIMPLE SUMMARY: This study proposes a method and device for the intelligent mobile monitoring of oestrus on a sow farm; this type of monitoring is applied in the field of sow production. A boar model that imitates the sounds, smells, and touch of real boars was built to detect the oestrus in sows after weaning. The models resulted in recognition accuracy rates of 96.12%, 98.25%, and 90.00%. The interaction times and frequencies between the sow and the bionic boar and the static behaviours of both ears during heat were further analysed. The results show that there is a strong correlation between the duration of contact between the oestrus sow and the bionic boar and the static behaviours of both ears. The average contact duration between the sows in oestrus and the bionic boars was 29.7 s/3 min, and the average duration in which the ears of the oestrus sows remained static was 41.3 s/3 min. The interactions between the sow and the bionic boar were used as the basis for judging the sow’s oestrus states. This approach can more accurately obtain the oestrus duration of a sow and provide a scientific reference for the sow’s conception time. ABSTRACT: This study proposes a method and device for the intelligent mobile monitoring of oestrus on a sow farm, applied in the field of sow production. A bionic boar model that imitates the sounds, smells, and touch of real boars was built to detect the oestrus of sows after weaning. Machine vision technology was used to identify the interactive behaviour between empty sows and bionic boars and to establish deep belief network (DBN), sparse autoencoder (SAE), and support vector machine (SVM) models, and the resulting recognition accuracy rates were 96.12%, 98.25%, and 90.00%, respectively. The interaction times and frequencies between the sow and the bionic boar and the static behaviours of both ears during heat were further analysed. The results show that there is a strong correlation between the duration of contact between the oestrus sow and the bionic boar and the static behaviours of both ears. The average contact duration between the sows in oestrus and the bionic boars was 29.7 s/3 min, and the average duration in which the ears of the oestrus sows remained static was 41.3 s/3 min. The interactions between the sow and the bionic boar were used as the basis for judging the sow’s oestrus states. In contrast with the methods of other studies, the proposed innovative design for recyclable bionic boars can be used to check emotions, and machine vision technology can be used to quickly identify oestrus behaviours. This approach can more accurately obtain the oestrus duration of a sow and provide a scientific reference for a sow’s conception time. |
format | Online Article Text |
id | pubmed-8224023 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-82240232021-06-25 Oestrus Analysis of Sows Based on Bionic Boars and Machine Vision Technology Lei, Kaidong Zong, Chao Du, Xiaodong Teng, Guanghui Feng, Feiqi Animals (Basel) Article SIMPLE SUMMARY: This study proposes a method and device for the intelligent mobile monitoring of oestrus on a sow farm; this type of monitoring is applied in the field of sow production. A boar model that imitates the sounds, smells, and touch of real boars was built to detect the oestrus in sows after weaning. The models resulted in recognition accuracy rates of 96.12%, 98.25%, and 90.00%. The interaction times and frequencies between the sow and the bionic boar and the static behaviours of both ears during heat were further analysed. The results show that there is a strong correlation between the duration of contact between the oestrus sow and the bionic boar and the static behaviours of both ears. The average contact duration between the sows in oestrus and the bionic boars was 29.7 s/3 min, and the average duration in which the ears of the oestrus sows remained static was 41.3 s/3 min. The interactions between the sow and the bionic boar were used as the basis for judging the sow’s oestrus states. This approach can more accurately obtain the oestrus duration of a sow and provide a scientific reference for the sow’s conception time. ABSTRACT: This study proposes a method and device for the intelligent mobile monitoring of oestrus on a sow farm, applied in the field of sow production. A bionic boar model that imitates the sounds, smells, and touch of real boars was built to detect the oestrus of sows after weaning. Machine vision technology was used to identify the interactive behaviour between empty sows and bionic boars and to establish deep belief network (DBN), sparse autoencoder (SAE), and support vector machine (SVM) models, and the resulting recognition accuracy rates were 96.12%, 98.25%, and 90.00%, respectively. The interaction times and frequencies between the sow and the bionic boar and the static behaviours of both ears during heat were further analysed. The results show that there is a strong correlation between the duration of contact between the oestrus sow and the bionic boar and the static behaviours of both ears. The average contact duration between the sows in oestrus and the bionic boars was 29.7 s/3 min, and the average duration in which the ears of the oestrus sows remained static was 41.3 s/3 min. The interactions between the sow and the bionic boar were used as the basis for judging the sow’s oestrus states. In contrast with the methods of other studies, the proposed innovative design for recyclable bionic boars can be used to check emotions, and machine vision technology can be used to quickly identify oestrus behaviours. This approach can more accurately obtain the oestrus duration of a sow and provide a scientific reference for a sow’s conception time. MDPI 2021-05-21 /pmc/articles/PMC8224023/ /pubmed/34063888 http://dx.doi.org/10.3390/ani11061485 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Lei, Kaidong Zong, Chao Du, Xiaodong Teng, Guanghui Feng, Feiqi Oestrus Analysis of Sows Based on Bionic Boars and Machine Vision Technology |
title | Oestrus Analysis of Sows Based on Bionic Boars and Machine Vision Technology |
title_full | Oestrus Analysis of Sows Based on Bionic Boars and Machine Vision Technology |
title_fullStr | Oestrus Analysis of Sows Based on Bionic Boars and Machine Vision Technology |
title_full_unstemmed | Oestrus Analysis of Sows Based on Bionic Boars and Machine Vision Technology |
title_short | Oestrus Analysis of Sows Based on Bionic Boars and Machine Vision Technology |
title_sort | oestrus analysis of sows based on bionic boars and machine vision technology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8224023/ https://www.ncbi.nlm.nih.gov/pubmed/34063888 http://dx.doi.org/10.3390/ani11061485 |
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