Cargando…

Evaluation of an Active LF Tracking System and Data Processing Methods for Livestock Precision Farming in the Poultry Sector

Tracking technologies offer a way to monitor movement of many individuals over long time periods with minimal disturbances and could become a helpful tool for a variety of uses in animal agriculture, including health monitoring or selection of breeding traits that benefit welfare within intensive ca...

Descripción completa

Detalles Bibliográficos
Autores principales: Montalcini, Camille Marie, Voelkl, Bernhard, Gómez, Yamenah, Gantner, Michael, Toscano, Michael J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780220/
https://www.ncbi.nlm.nih.gov/pubmed/35062620
http://dx.doi.org/10.3390/s22020659
_version_ 1784637783664492544
author Montalcini, Camille Marie
Voelkl, Bernhard
Gómez, Yamenah
Gantner, Michael
Toscano, Michael J.
author_facet Montalcini, Camille Marie
Voelkl, Bernhard
Gómez, Yamenah
Gantner, Michael
Toscano, Michael J.
author_sort Montalcini, Camille Marie
collection PubMed
description Tracking technologies offer a way to monitor movement of many individuals over long time periods with minimal disturbances and could become a helpful tool for a variety of uses in animal agriculture, including health monitoring or selection of breeding traits that benefit welfare within intensive cage-free poultry farming. Herein, we present an active, low-frequency tracking system that distinguishes between five predefined zones within a commercial aviary. We aimed to evaluate both the processed and unprocessed datasets against a “ground truth” based on video observations. The two data processing methods aimed to filter false registrations, one with a simple deterministic approach and one with a tree-based classifier. We found the unprocessed data accurately determined birds’ presence/absence in each zone with an accuracy of 99% but overestimated the number of transitions taken by birds per zone, explaining only 23% of the actual variation. However, the two processed datasets were found to be suitable to monitor the number of transitions per individual, accounting for 91% and 99% of the actual variation, respectively. To further evaluate the tracking system, we estimated the error rate of registrations (by applying the classifier) in relation to three factors, which suggested a higher number of false registrations towards specific areas, periods with reduced humidity, and periods with reduced temperature. We concluded that the presented tracking system is well suited for commercial aviaries to measure individuals’ transitions and individuals’ presence/absence in predefined zones. Nonetheless, under these settings, data processing remains a necessary step in obtaining reliable data. For future work, we recommend the use of automatic calibration to improve the system’s performance and to envision finer movements.
format Online
Article
Text
id pubmed-8780220
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-87802202022-01-22 Evaluation of an Active LF Tracking System and Data Processing Methods for Livestock Precision Farming in the Poultry Sector Montalcini, Camille Marie Voelkl, Bernhard Gómez, Yamenah Gantner, Michael Toscano, Michael J. Sensors (Basel) Article Tracking technologies offer a way to monitor movement of many individuals over long time periods with minimal disturbances and could become a helpful tool for a variety of uses in animal agriculture, including health monitoring or selection of breeding traits that benefit welfare within intensive cage-free poultry farming. Herein, we present an active, low-frequency tracking system that distinguishes between five predefined zones within a commercial aviary. We aimed to evaluate both the processed and unprocessed datasets against a “ground truth” based on video observations. The two data processing methods aimed to filter false registrations, one with a simple deterministic approach and one with a tree-based classifier. We found the unprocessed data accurately determined birds’ presence/absence in each zone with an accuracy of 99% but overestimated the number of transitions taken by birds per zone, explaining only 23% of the actual variation. However, the two processed datasets were found to be suitable to monitor the number of transitions per individual, accounting for 91% and 99% of the actual variation, respectively. To further evaluate the tracking system, we estimated the error rate of registrations (by applying the classifier) in relation to three factors, which suggested a higher number of false registrations towards specific areas, periods with reduced humidity, and periods with reduced temperature. We concluded that the presented tracking system is well suited for commercial aviaries to measure individuals’ transitions and individuals’ presence/absence in predefined zones. Nonetheless, under these settings, data processing remains a necessary step in obtaining reliable data. For future work, we recommend the use of automatic calibration to improve the system’s performance and to envision finer movements. MDPI 2022-01-15 /pmc/articles/PMC8780220/ /pubmed/35062620 http://dx.doi.org/10.3390/s22020659 Text en © 2022 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
Montalcini, Camille Marie
Voelkl, Bernhard
Gómez, Yamenah
Gantner, Michael
Toscano, Michael J.
Evaluation of an Active LF Tracking System and Data Processing Methods for Livestock Precision Farming in the Poultry Sector
title Evaluation of an Active LF Tracking System and Data Processing Methods for Livestock Precision Farming in the Poultry Sector
title_full Evaluation of an Active LF Tracking System and Data Processing Methods for Livestock Precision Farming in the Poultry Sector
title_fullStr Evaluation of an Active LF Tracking System and Data Processing Methods for Livestock Precision Farming in the Poultry Sector
title_full_unstemmed Evaluation of an Active LF Tracking System and Data Processing Methods for Livestock Precision Farming in the Poultry Sector
title_short Evaluation of an Active LF Tracking System and Data Processing Methods for Livestock Precision Farming in the Poultry Sector
title_sort evaluation of an active lf tracking system and data processing methods for livestock precision farming in the poultry sector
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780220/
https://www.ncbi.nlm.nih.gov/pubmed/35062620
http://dx.doi.org/10.3390/s22020659
work_keys_str_mv AT montalcinicamillemarie evaluationofanactivelftrackingsystemanddataprocessingmethodsforlivestockprecisionfarminginthepoultrysector
AT voelklbernhard evaluationofanactivelftrackingsystemanddataprocessingmethodsforlivestockprecisionfarminginthepoultrysector
AT gomezyamenah evaluationofanactivelftrackingsystemanddataprocessingmethodsforlivestockprecisionfarminginthepoultrysector
AT gantnermichael evaluationofanactivelftrackingsystemanddataprocessingmethodsforlivestockprecisionfarminginthepoultrysector
AT toscanomichaelj evaluationofanactivelftrackingsystemanddataprocessingmethodsforlivestockprecisionfarminginthepoultrysector