Hostname: page-component-78c5997874-v9fdk Total loading time: 0 Render date: 2024-11-05T14:53:06.344Z Has data issue: false hasContentIssue false
  • English
  • Français

Electrical conductivity of foremilk for detecting subclinical mastitis in cows

Published online by Cambridge University Press:  27 March 2009

J. L. Linzell ,
M. Peaker  and
J. G. Rowell
J. L. Linzell
Affiliation:
Agricultural Research Council Institute of Animal Physiology, Babraham, Cambridge, and
M. Peaker
Affiliation:
Agricultural Research Council Institute of Animal Physiology, Babraham, Cambridge, and
J. G. Rowell
Affiliation:
Agricultural Research Council Institute of Animal Physiology, Babraham, Cambridge, and A.R.C. Statistics Group, Department of Applied Biology, University of Cambridge
Get access Rights & Permissions [Opens in a new window]

Summary

In order to assess the potential value of milk conductivity sensors for the detection of subclinical mastitis, measurements have been made manually on quarter foremilk samples for 10–74 days from 44 cows in two herds. Some measurements were also made of quarter cell counts and yields but the true status of the cows was established by bacteriological examination near the end of each run.

For uninfected cows, conductivities of the four quarters tended to move in parallel from day to day whereas for infected cows there were usually substantial departures from parallelism. A statistic which is a measure of departure from parallelism is the quarter × day interaction mean square (I.M.S.), the magnitude of which was used to discriminate between infected and uninfected cows. Using conductivity data obtained at the time of the bacteriological examination, I.M.S. correctly identified all 19 un-infected cows and 24 out of 25 infected cows, the single misclassified cow being only mildly infected. The procedure was further tested on data obtained from one of the herds a year later. In this case, using the I.M.S. limits established the year before, 14 out of 18 infected cows were correctly identified, the four failures being only mildly infected. With nine uninfected cows, there were three false positives but these cows were all pregnant and had been lactating for 44 weeks. Although special limits may have to be set for cows in late lactation, two of these animals had been infected during the lactation, so that conductivity changes may reflect past damage to the udder.

The same data used to set I.M.S. limits were also examined in simpler ways that required little or no calculation. These were ‘differential conductivity’ (the quarter with the highest conductivity divided by the value for the lowest), ‘absolute conductivity’, ‘mixed conductivity’ (mixed foremilk from all four glands) and ‘out-of-balance conductivity’ (the product of the conductivities of the fore quarters divided by the product of the hind quarters or vice versa). These methods of analysis were all less sensitive than the I.M.S. test for parallelism. Differential conductivity, absolute conductivity and mixed conductivity all detected severe cases but missed more mild cases. Out-of-balance conductivity was much less satisfactory because it missed some severe cases.

Type
Research Article
Information
The Journal of Agricultural Science , Volume 83 , Issue 2 , October 1974 , pp. 309 - 325
Copyright
Copyright © Cambridge University Press 1974

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Davis, J. G. (1947). The rapid abnormality indicator. Dairy Industries 12, 35–41.Google Scholar
Greatrix, G. R., Quayle, J. C. & Coombe, R. A. (1968). The detection of abnormal milk by electrical means. Journal of Dairy Research 35, 213–21.CrossRefGoogle Scholar
Hall, H. S. (1951). Equipment for individual quarter machine milking. Journal of Dairy Research 18, 151–4.CrossRefGoogle Scholar
Linzell, J. L. & Peaker, M. (1971). Early detection of mastitis. Veterinary Record 89, 393–4.CrossRefGoogle ScholarPubMed
Linzell, J. L. & Peaker, M. (1972). Day-to-day variations in milk composition in the goat and cow as a guide to the detection of subclinical mastitis. British Veterinary Journal 128, 284–96.CrossRefGoogle Scholar
Linzell, J. L. & Peaker, M. (1974). Efficacy of the measurement of the electrical conductivity of milk for the detection of subolinical mastitis in cows: detection of infected cows at a single visit. British Veterinary Journal (in Press).Google Scholar
Little, T. W. A., Hebert, C. N. & Forbes, D. (1968). Electrical conductivity and the leucocyte count of bovine milk. Veterinary Record 82, 431–3.Google Scholar
Malcolm, J. F., King, C. W. & Campbell, M. M. (1942). The value of the cell count and electrical conductivity of milk as criteria of bovine mastitis. Proceedings of the Society of Agricultural Bacteriology 1942 (abstracts section), 30–4.Google Scholar
Massie, K. & Chalton, G. (Chalton Electronics Services) (1972, 1973). Mastitis indicator. U.K. Patent applications 22, 791/72 and 44,170/73.Google Scholar
Natzke, R. P., Everett, R. W., Guthrie, R. S., Keown, J. F., Meek, A. M., Merrill, W. G., Roberts, S. J. & Schmidt, G. H. (1972). Mastitis control program: effect on milk production. Journal of Dairy Science 55, 1256–60.CrossRefGoogle ScholarPubMed
Pearson, J. R. L., Wright, C. L. & Greer, D. O. (1970). A study of methods for estimating the cell content of bulk milk. Journal of Dairy Research 37, 467–80.CrossRefGoogle Scholar
Quayle, J. C. & Greatrix, G. R. (U.K. National Research Development Corp.). (1973). Improvements in methods and apparatus for the detection of mastitis in milk animals. British Patent 1 314 32B.Google Scholar
Sedransk, N. & Okamoto, M. (1971). Estimation of the probabilities of misclassification for a linear discriminant function in the univariate normal case. Annals of the Institute of Statistical Mathematics 23, 419–35.CrossRefGoogle Scholar
Taylor, M. M. & Phillips, J. D. (1972). A comparison between the bacterial growth from milk on two different media and the somatic cell count. British Veterinary Journal 128, 242–8.CrossRefGoogle ScholarPubMed
Wheelock, J. V., Rook, J. A. F., Neave, F. K. & Dodd, F. H. (1966). The effect of bacterial infections of the udder on the yield and composition of cow's milk. Journal of Dairy Research 33, 199–215.CrossRefGoogle Scholar
Wolfe, R. R., Sharma, S. C. & Ward, G. E. (1972). A method for electronic detection of bovine mastitis. Transactions of the American Society of Agricultural Engineers 15, 500–3.CrossRefGoogle Scholar