Εμφάνιση απλής εγγραφής

dc.creatorGiannakopoulos A., Vasileiou N.G.C., Gougoulis D.A., Cripps P.J., Ioannidi K.S., Chatzopoulos D.C., Billinis C., Mavrogianni V.S., Petinaki E., Fthenakis G.C.en
dc.date.accessioned2023-01-31T07:41:48Z
dc.date.available2023-01-31T07:41:48Z
dc.date.issued2019
dc.identifier10.1016/j.vetmic.2018.11.021
dc.identifier.issn03781135
dc.identifier.urihttp://hdl.handle.net/11615/72306
dc.description.abstractObjective was to recognise areas potentially of high risk for increased frequency of subclinical mastitis in ewes. Milk samples were collected, for bacteriological and cytological examination, from 2198 clinically healthy ewes in 111 farms in all administrative regions of Greece. Data on farms were located in the field using hand-held Global Positioning System Garmin units. Collected data were analysed by an Ecological Niche Model under the framework of a geographic information system. Two separate analyses were performed: one for subclinical mastitis independently of causal agent (prevalence in population sampled: 0.260) and one for subclinical mastitis caused specifically by slime-producing staphylococci (prevalence in population sampled: 0.153). A model was constructed in which sheep farms were divided into two clusters, according to prevalence of subclinical mastitis: farms in the upper three quartiles of prevalence were used as occurrence points for the Ecological niche modelling procedure (‘infected farms’); farms in the lower quartile of prevalence within each category were (pseudo)negative points. Significant differences in environmental parametres prevailing in locations of farms into the study, were identified for up to 13 parametres between locations of farms according to management system applied in farms. When farms in each management system were considered separately, differences became evident between farms in each management system, as well as between the two infections. The factor with the highest relative contribution in the analyses was the distance from other sheep farms; other factors also of importance in the predictive models were the altitude, the maximum temperature of warmest month and the total precipitation of driest month. Verification of the model revealed that ≥ 0.760 of infected farms’ were located in areas predicted as high risk for prevalence of subclinical mastitis or slime staphylococcal subclinical mastitis. The paper describes for the first time potential association of mastitis with environmental factors and presents predictive models for mastitis in ewes taking into account environmental parametres. © 2018 Elsevier B.V.en
dc.language.isoenen
dc.sourceVeterinary Microbiologyen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85057824943&doi=10.1016%2fj.vetmic.2018.11.021&partnerID=40&md5=e02b99da8dd284ad05606f4275612939
dc.subjectagricultural landen
dc.subjectaltitudeen
dc.subjectArticleen
dc.subjectcontrolled studyen
dc.subjectecological nicheen
dc.subjecteween
dc.subjectfemaleen
dc.subjectgeographic information systemen
dc.subjectglobal positioning systemen
dc.subjectGreeceen
dc.subjectmastitisen
dc.subjectnonhumanen
dc.subjectprecipitationen
dc.subjectprevalenceen
dc.subjectsheep farmingen
dc.subjecttemperatureen
dc.subjectanimalen
dc.subjectecosystemen
dc.subjectgeographic information systemen
dc.subjectisolation and purificationen
dc.subjectmastitisen
dc.subjectmicrobiologyen
dc.subjectsheepen
dc.subjectsheep diseaseen
dc.subjectStaphylococcusen
dc.subjectStaphylococcus infectionen
dc.subjectveterinary medicineen
dc.subjectAnimalsen
dc.subjectEcosystemen
dc.subjectFarmsen
dc.subjectFemaleen
dc.subjectGeographic Information Systemsen
dc.subjectGreeceen
dc.subjectMastitisen
dc.subjectPrevalenceen
dc.subjectSheepen
dc.subjectSheep Diseasesen
dc.subjectStaphylococcal Infectionsen
dc.subjectStaphylococcusen
dc.subjectElsevier B.V.en
dc.titleUse of geographical information system and ecological niche modelling for predicting potential space distribution of subclinical mastitis in ewesen
dc.typejournalArticleen


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