Application of the Support Vector Machine to Predict Subclinical Mastitis in Dairy Cattle

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dc.contributor.authorMammadova, Nazira
dc.contributor.authorKeskin, Ismail
dc.date.accessioned2020-03-26T18:41:08Z
dc.date.available2020-03-26T18:41:08Z
dc.date.issued2013
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThis study presented a potentially useful alternative approach to ascertain the presence of subclinical and clinical mastitis in dairy cows using support vector machine (SVM) techniques. The proposed method detected mastitis in a cross-sectional representative sample of Holstein dairy cattle milked using an automatic milking system. The study used such suspected indicators of mastitis as lactation rank, milk yield, electrical conductivity, average milking duration, and control season as input data. The output variable was somatic cell counts obtained from milk samples collected monthly throughout the 15 months of the control period. Cattle were judged to be healthy or infected based on those somatic cell counts. This study undertook a detailed scrutiny of the SVM methodology, constructing and examining a model which showed 89% sensitivity, 92% specificity, and 50% error in mastitis detection.en_US
dc.description.sponsorshipScientific Research Project Office of Selcuk University, TurkeySelcuk University [10201056]en_US
dc.description.sponsorshipThis research was supported as a doctoral thesis by a grant from The Scientific Research Project Office of Selcuk University, Turkey (Project no. 10201056). The authors wish to thank the staff of KARYEM AS, Konya, TURKEY.en_US
dc.identifier.doi10.1155/2013/603897en_US
dc.identifier.issn1537-744Xen_US
dc.identifier.pmid24574862en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://dx.doi.org/10.1155/2013/603897
dc.identifier.urihttps://hdl.handle.net/20.500.12395/29235
dc.identifier.wosWOS:000329691300001en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherHINDAWI LTDen_US
dc.relation.ispartofSCIENTIFIC WORLD JOURNALen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleApplication of the Support Vector Machine to Predict Subclinical Mastitis in Dairy Cattleen_US
dc.typeArticleen_US

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