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dc.contributor.authorTholen, Andreaen_US
dc.date.accessioned2017-04-04T19:49:32Z
dc.date.available2017-04-04T19:49:32Z
dc.date.issued2012-06-14en_US
dc.identifier.otheretd-07192012-115725en_US
dc.identifier.urihttp://hdl.handle.net/10919/76826
dc.description.abstractA study was conducted to examine the correlation between a novel behavior monitoring system and a validated data logger. We concluded that the behavior monitoring system was valid for tracking daily rest time in dairy cows (R=0.96); however the correlation values for rest bouts and rest duration were relatively low, (R=0.64) (R=0.47), respectively. Daily monitoring of animal activity and milk components can be used to detect mastitis prior to clinical onset. Data from 268 cases with clinical mastitis and respective controls (n=268) from Virginia Tech and the University of Florida dairy herds were examined. Variables collected included daily milk yield, electrical conductivity, milk fat, protein, and lactose percent, as well as activity measurements including daily rest time, daily rest duration, daily rest bouts, and daily steps taken. Variables were collected for case and control cows in the 14 d prior to and after clinical diagnosis, for a total 29 d monitoring period. A milk sample was aseptically collected upon detection of clinical signs as observed by milker's at both farms. A statistical method (candisc discriminant analysis) was used to combine all measurements and sensitivity and specificity was calculated. Virginia Tech cows on d -1 (sensitivity=95%, specificity=95%), Virginia Tech and University of Florida cows on d -1 (sensitivity=88%, specificity=90). Overall, daily monitoring of animal activity and milk components can detect mastitis prior to onset of clinical signs of disease. This may allow producers to intervene and make proactive management decisions regarding herd health prior to clinical diagnosis.
dc.language.isoen_USen_US
dc.publisherVirginia Techen_US
dc.rightsI hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Virginia Tech or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report.en_US
dc.subjectanimal activityen_US
dc.subjectmilk componenten_US
dc.subjectmastitisen_US
dc.subjectdetectionen_US
dc.titleThe use of animal activity data and milk components as indicators of clinical mastitisen_US
dc.typeThesisen_US
dc.contributor.departmentDairy Scienceen_US
dc.description.degreeMaster of Scienceen_US
thesis.degree.nameMaster of Scienceen_US
thesis.degree.levelmastersen_US
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen_US
thesis.degree.disciplineDairy Scienceen_US
dc.contributor.committeechairPetersson-Wolfe, Christina Sonjaen_US
dc.contributor.committeememberAkers, Robert Michaelen_US
dc.contributor.committeememberDe Vries, Alberten_US
dc.contributor.committeememberCurrin, John F.en_US
dc.type.dcmitypeTexten_US
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-07192012-115725/en_US
dc.date.sdate2012-07-19en_US
dc.date.rdate2016-10-18
dc.date.adate2012-07-19en_US


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