Literature DB >> 7047600

Electrical conductivity of milk for detection of mastitis.

R S Fernando, R B Rindsig, S L Spahr.   

Abstract

The potential value of electrical conductivity of milk as a screening test for subclinical mastitis was evaluated. Conductivity of foremilk and of postmilking strippings from 368 quarters of 92 cows was measured. Infection status of quarters was determined by bacteriological analysis of strict foremilk samples. Infections were classified as by primary or secondary pathogens, depending on the importance of the isolated organism as a mastitis pathogen. Somatic cells were counted on foremilk samples. Milk conductivity increased with infection. Conductivity of postmilking strippings was higher than that of foremilk in samples from quarters infected by primary pathogens. By thresholds which correctly classified at least 90% of normal quarters, accuracy of identifying primary pathogen infections by absolute conductivity was 62.8 and 96.2% with foremilk and postmilking strippings. Differential conductivity and combination of absolute and differential methods also were evaluated with the latter being the most effective. Number of quarters with elevated conductivity of postmilking strippings tended to be higher when somatic cell count was greater than 500,000/ml in both normal and infected groups. Conductivity of milk seems to hold promise as an indicator of subclinical mastitis.

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Year:  1982        PMID: 7047600     DOI: 10.3168/jds.S0022-0302(82)82245-5

Source DB:  PubMed          Journal:  J Dairy Sci        ISSN: 0022-0302            Impact factor:   4.034


  3 in total

1.  Potential of differential somatic cell counts as indicators of mastitis in quarter milk samples from dairy cows.

Authors:  U Emanuelson; P Wever
Journal:  Acta Vet Scand       Date:  1989       Impact factor: 1.695

2.  Milk prostaglandins and electrical conductivity in bovine mastitis.

Authors:  F Atroshi; J Parantainen; R Kangasniemi; T Osterman
Journal:  Vet Res Commun       Date:  1987       Impact factor: 2.459

3.  Using Sensor Data to Detect Lameness and Mastitis Treatment Events in Dairy Cows: A Comparison of Classification Models.

Authors:  Christian Post; Christian Rietz; Wolfgang Büscher; Ute Müller
Journal:  Sensors (Basel)       Date:  2020-07-10       Impact factor: 3.576

  3 in total

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