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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...

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Autores principales: Lei, Kaidong, Zong, Chao, Du, Xiaodong, Teng, Guanghui, Feng, Feiqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
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.
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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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