Cargando…

Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations

Free range systems can improve the welfare of laying hens. However, the access to environmental resources can be partially limited by social interactions, feeding of hens, and productivity, can be not stable and damaging behaviors, or negative events, can be observed more frequently than in conventi...

Descripción completa

Detalles Bibliográficos
Autores principales: Zaninelli, Mauro, Redaelli, Veronica, Luzi, Fabio, Mitchell, Malcolm, Bontempo, Valentino, Cattaneo, Donata, Dell’Orto, Vittorio, Savoini, Giovanni
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5796280/
https://www.ncbi.nlm.nih.gov/pubmed/29303981
http://dx.doi.org/10.3390/s18010132
_version_ 1783297475012984832
author Zaninelli, Mauro
Redaelli, Veronica
Luzi, Fabio
Mitchell, Malcolm
Bontempo, Valentino
Cattaneo, Donata
Dell’Orto, Vittorio
Savoini, Giovanni
author_facet Zaninelli, Mauro
Redaelli, Veronica
Luzi, Fabio
Mitchell, Malcolm
Bontempo, Valentino
Cattaneo, Donata
Dell’Orto, Vittorio
Savoini, Giovanni
author_sort Zaninelli, Mauro
collection PubMed
description Free range systems can improve the welfare of laying hens. However, the access to environmental resources can be partially limited by social interactions, feeding of hens, and productivity, can be not stable and damaging behaviors, or negative events, can be observed more frequently than in conventional housing systems. In order to reach a real improvement of the hens’ welfare the study of their laying performances and behaviors is necessary. With this purpose, many systems have been developed. However, most of them do not detect a multiple occupation of the nest negatively affecting the accuracy of data collected. To overcome this issue, a new “nest-usage-sensor” was developed and tested. It was based on the evaluation of thermografic images, as acquired by a thermo-camera, and the performing of patter recognitions on images acquired from the nest interior. The sensor was setup with a “Multiple Nest Occupation Threshold” of 796 colored pixels and a template of triangular shape and sizes of 43 × 33 pixels (high per base). It was tested through an experimental nesting system where 10 hens were reared for a month. Results showed that the evaluation of thermografic images could increase the detection performance of a multiple occupation of the nest and to apply an image pattern recognition technique could allow for counting the number of hens in the nest in case of a multiple occupation. As a consequence, the accuracy of data collected in studies on laying performances and behaviors of hens, reared in a free-range housing system, could result to be improved.
format Online
Article
Text
id pubmed-5796280
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-57962802018-02-13 Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations Zaninelli, Mauro Redaelli, Veronica Luzi, Fabio Mitchell, Malcolm Bontempo, Valentino Cattaneo, Donata Dell’Orto, Vittorio Savoini, Giovanni Sensors (Basel) Article Free range systems can improve the welfare of laying hens. However, the access to environmental resources can be partially limited by social interactions, feeding of hens, and productivity, can be not stable and damaging behaviors, or negative events, can be observed more frequently than in conventional housing systems. In order to reach a real improvement of the hens’ welfare the study of their laying performances and behaviors is necessary. With this purpose, many systems have been developed. However, most of them do not detect a multiple occupation of the nest negatively affecting the accuracy of data collected. To overcome this issue, a new “nest-usage-sensor” was developed and tested. It was based on the evaluation of thermografic images, as acquired by a thermo-camera, and the performing of patter recognitions on images acquired from the nest interior. The sensor was setup with a “Multiple Nest Occupation Threshold” of 796 colored pixels and a template of triangular shape and sizes of 43 × 33 pixels (high per base). It was tested through an experimental nesting system where 10 hens were reared for a month. Results showed that the evaluation of thermografic images could increase the detection performance of a multiple occupation of the nest and to apply an image pattern recognition technique could allow for counting the number of hens in the nest in case of a multiple occupation. As a consequence, the accuracy of data collected in studies on laying performances and behaviors of hens, reared in a free-range housing system, could result to be improved. MDPI 2018-01-05 /pmc/articles/PMC5796280/ /pubmed/29303981 http://dx.doi.org/10.3390/s18010132 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Zaninelli, Mauro
Redaelli, Veronica
Luzi, Fabio
Mitchell, Malcolm
Bontempo, Valentino
Cattaneo, Donata
Dell’Orto, Vittorio
Savoini, Giovanni
Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations
title Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations
title_full Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations
title_fullStr Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations
title_full_unstemmed Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations
title_short Development of a Machine Vision Method for the Monitoring of Laying Hens and Detection of Multiple Nest Occupations
title_sort development of a machine vision method for the monitoring of laying hens and detection of multiple nest occupations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5796280/
https://www.ncbi.nlm.nih.gov/pubmed/29303981
http://dx.doi.org/10.3390/s18010132
work_keys_str_mv AT zaninellimauro developmentofamachinevisionmethodforthemonitoringoflayinghensanddetectionofmultiplenestoccupations
AT redaelliveronica developmentofamachinevisionmethodforthemonitoringoflayinghensanddetectionofmultiplenestoccupations
AT luzifabio developmentofamachinevisionmethodforthemonitoringoflayinghensanddetectionofmultiplenestoccupations
AT mitchellmalcolm developmentofamachinevisionmethodforthemonitoringoflayinghensanddetectionofmultiplenestoccupations
AT bontempovalentino developmentofamachinevisionmethodforthemonitoringoflayinghensanddetectionofmultiplenestoccupations
AT cattaneodonata developmentofamachinevisionmethodforthemonitoringoflayinghensanddetectionofmultiplenestoccupations
AT dellortovittorio developmentofamachinevisionmethodforthemonitoringoflayinghensanddetectionofmultiplenestoccupations
AT savoinigiovanni developmentofamachinevisionmethodforthemonitoringoflayinghensanddetectionofmultiplenestoccupations