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Early detection of mastitis in cows using the system based on 3D motions detectors

cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.author-orcid0000-0003-4233-8803
cris.virtual.author-orcid0000-0002-8244-2763
cris.virtual.author-orcid0000-0003-3038-5805
cris.virtual.author-orcid0000-0001-6297-1580
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid4207065a-66be-4361-8290-3aa02454b4df
cris.virtualsource.author-orcidb06a0b04-dd89-4025-a198-6d97db2079f2
cris.virtualsource.author-orcide55aaaac-9fc9-45aa-a198-fbb59d7d02cd
cris.virtualsource.author-orcid20b7e0c6-f9be-4a0e-b5c7-dd3f22fa47d3
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
dc.abstract.enMastitis is one of the major health problems in dairy herds leading to a reduction in the leading to a reduction in the quality of milk and economic losses. The research aimed to present the system, which uses electronic 3D motion detectors to detect the early symptoms of mastitis. The system would allow more effective prevention of this illness. The experiment was carried out on 118 cows (64 Holstein Friesian and 54 Brown Swiss). The animals were kept in free-stall barn with access to pasture. The occurrence of mastitis cases was noticed in veterinary register. Microbiological culture was taken from milk in order to confirm the development of infection. Data from motion detectors were defined as time spent by animals on feed intake, ruminating, physical activity and rest, and were expanded by adding information about feeding group, breed type and lactation number. During analyses, two approaches were used to process the same dataset: artificial neural networks (ANN) and logistic regression. The obtained ANN and the logistic regression models proved to be satisfactory from the perspective of applied criteria of goodness of fit (area under curve—exceed 0.8). Quality parameters (accuracy, sensitivity and specifity) of logistic regression are relatively high (larger than 0.73), whereas the ranks of significance of the studied variables varied across datasets. These proposed models can be useful for automating the detection of mastitis once integrated into the farm’s IT system.
dc.affiliationWydział Medycyny Weterynaryjnej i Nauk o Zwierzętach
dc.affiliationWydział Inżynierii Środowiska i Inżynierii Mechanicznej
dc.affiliationWydział Rolnictwa, Ogrodnictwa i Bioinżynierii
dc.affiliation.instituteKatedra Genetyki i Podstaw Hodowli Zwierząt​​
dc.affiliation.instituteKatedra Inżynierii Biosystemów
dc.affiliation.instituteKatedra Metod Matematycznych i Statystycznych
dc.contributor.authorGrodkowski, Grzegorz
dc.contributor.authorSzwaczkowski, Tomasz
dc.contributor.authorKoszela, Krzysztof
dc.contributor.authorMueller, Wojciech
dc.contributor.authorTomaszyk, Kamila
dc.contributor.authorBaars, Ton
dc.contributor.authorSakowski, Tomasz
dc.date.access2026-01-28
dc.date.accessioned2026-01-30T11:11:35Z
dc.date.available2026-01-30T11:11:35Z
dc.date.copyright2022-12-08
dc.date.issued2022
dc.description.abstract<jats:title>Abstract</jats:title><jats:p>Mastitis is one of the major health problems in dairy herds leading to a reduction in the leading to a reduction in the quality of milk and economic losses. The research aimed to present the system, which uses electronic 3D motion detectors to detect the early symptoms of mastitis. The system would allow more effective prevention of this illness. The experiment was carried out on 118 cows (64 Holstein Friesian and 54 Brown Swiss). The animals were kept in free-stall barn with access to pasture. The occurrence of mastitis cases was noticed in veterinary register. Microbiological culture was taken from milk in order to confirm the development of infection. Data from motion detectors were defined as time spent by animals on feed intake, ruminating, physical activity and rest, and were expanded by adding information about feeding group, breed type and lactation number. During analyses, two approaches were used to process the same dataset: artificial neural networks (ANN) and logistic regression. The obtained ANN and the logistic regression models proved to be satisfactory from the perspective of applied criteria of goodness of fit (area under curve—exceed 0.8). Quality parameters (accuracy, sensitivity and specifity) of logistic regression are relatively high (larger than 0.73), whereas the ranks of significance of the studied variables varied across datasets. These proposed models can be useful for automating the detection of mastitis once integrated into the farm’s IT system.</jats:p>
dc.description.accesstimeat_publication
dc.description.bibliographyil., bibliogr.
dc.description.financepublication_nocost
dc.description.financecost0,00
dc.description.if4,6
dc.description.points140
dc.description.versionfinal_published
dc.description.volume12
dc.identifier.doi10.1038/s41598-022-25275-2
dc.identifier.issn2045-2322
dc.identifier.urihttps://sciencerep.up.poznan.pl/handle/item/7134
dc.identifier.weblinkhttp://www.nature.com/articles/s41598-022-25275-2#Bib1
dc.languageen
dc.relation.ispartofScientific Reports
dc.relation.pagesart. 21215
dc.rightsCC-BY
dc.sciencecloudnosend
dc.share.typeOPEN_JOURNAL
dc.titleEarly detection of mastitis in cows using the system based on 3D motions detectors
dc.typeJournalArticle
dspace.entity.typePublication
oaire.citation.issue1
oaire.citation.volume12