Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-26T04:59:06.631Z Has data issue: false hasContentIssue false
  • English
  • Français

Economic consequences of mastitis and withdrawal of milk with high somatic cell count in Swedish dairy herds

Published online by Cambridge University Press:  21 May 2010

C. Nielsen ,
S. Østergaard ,
U. Emanuelson ,
H. Andersson ,
B. Berglund  and
E. Strandberg
C. Nielsen*
Affiliation:
Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, PO Box 7023, SE-750 07 Uppsala, Sweden
S. Østergaard
Affiliation:
Faculty of Agricultural Sciences, University of Aarhus, Research Centre Foulum, PO Box 50, DK-8830 Tjele, Denmark
U. Emanuelson
Affiliation:
Department of Clinical Sciences, Swedish University of Agricultural Sciences, PO Box 7054, SE-750 07 Uppsala, Sweden
H. Andersson
Affiliation:
Department of Economics, Swedish University of Agricultural Sciences, PO Box 7013, SE-750 07 Uppsala, Sweden
B. Berglund
Affiliation:
Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, PO Box 7023, SE-750 07 Uppsala, Sweden
E. Strandberg
Affiliation:
Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, PO Box 7023, SE-750 07 Uppsala, Sweden
*
†E-mail: [email protected]
Get access

Abstract

The main aim was to assess the impact of mastitis on technical and economic results of a dairy herd under current Swedish farming conditions. The second aim was to investigate the effects obtained by withdrawing milk with high somatic cell count (SCC). A dynamic and stochastic simulation model, SimHerd, was used to study the effects of mastitis in a herd with 150 cows. Results given the initial incidence of mastitis (32 and 33 clinical and subclinical cases per 100 cow-years, respectively) were studied, together with the consequences of reducing or increasing the incidence of mastitis by 50%, modelling no clinical mastitis (CM) while keeping the incidence of subclinical mastitis (SCM) constant and vice versa. Six different strategies to withdraw milk with high SCC were compared. The decision to withdraw milk was based on herd-level information in three scenarios: withdrawal was initiated when the predicted bulk tank SCC exceeded 220 000, 200 000 or 180 000 cells/ml, and on cow-level information in three scenarios: withdrawal was initiated when the predicted SCC in an individual cow’s milk exceeded 1 000 000, 750 000 or 500 000 cells/ml. The accuracy with which SCC was measured and predicted was assumed to affect the profitability of withdrawing milk with high SCC and this was investigated by applying high, low or no uncertainty to true SCC. The yearly avoidable cost of mastitis was estimated at €8235, assuming that the initial incidence of mastitis could be reduced by 50%. This cost corresponded to 5% of the herd net return given the initial incidence of mastitis. Expressed per cow-year, the avoidable cost of mastitis was €55. The costs per case of CM and SCM were estimated at €278 and €60, respectively. Withdrawing milk with high SCC was never profitable because this generated a substantial amount of milk withdrawal that was not offset by a sufficient increase in the average price per delivered kg milk. It had the most negative impact on net return when high incidence of mastitis was simulated. Withdrawing milk with high SCC based on low-uncertainty information reduced the amount of withdrawn milk and thus resulted in less negative effect on net return. It was concluded that the current milk-pricing system makes it more profitable for farmers to sell a larger amount of milk with higher SCC than to withdraw milk with high SCC to obtain payment premiums, at least in herds with mastitis incidences within the simulated ranges.

Keywords

dairy herdmastitiswithdrawing milkin-line SCC sensoreconomic performance
Type
Full Paper
Information
animal , Volume 4 , Issue 10 , October 2010 , pp. 1758 - 1770
Copyright
Copyright © The Animal Consortium 2010

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

Agriwise 2008. Områdeskalkyler 2008. Retrieved December 15, 2008, from http://www.agriwise.org/Databoken/databok2k8/kalkyler2008/kalkyler.htmGoogle Scholar
Arla Foods 2006. Kvalitetsprogrammet Arlagården (Quality assurance program for milk production). Retrieved September 15, 2006, from http://www.arlafoods.se/upload/V2a-1370-SE%20Arla%20kval.prog.%20mappe%20opdat.08-SE.pdfGoogle Scholar
Bar, D, Tauer, LW, Bennett, G, Gonzalez, RN, Hertl, JA, Schukken, YH, Schulte, HF, Welcome, FL, Gröhn, YT 2008. The cost of generic clinical mastitis in dairy cows as estimated by using dynamic programming. Journal of Dairy Science 91, 2205–2214.CrossRefGoogle ScholarPubMed
Bennedsgaard, TW, Enevoldsen, C, Thamsborg, SM, Vaarst, M 2003. Effect of mastitis treatment and somatic cell counts on milk yield in Danish organic dairy cows. Journal of Dairy Science 86, 3174–3183.CrossRefGoogle ScholarPubMed
De Haas, Y, Barkema, HW, Veerkamp, RF 2002. The effect of pathogen-specific clinical mastitis on the lactation curve for somatic cell count. Journal of Dairy Science 85, 1314–1323.CrossRefGoogle ScholarPubMed
Dekkers, JCM, Van Erp, T, Schukken, YH 1996. Economic benefits of reducing somatic cell count under the milk quality program of Ontario. Journal of Dairy Science 79, 396–401.CrossRefGoogle ScholarPubMed
Faust, MA, Timms, LL 1995. Estimates of variability for somatic-cell count measurements in the Iowa dairy-industry. Journal of Dairy Science 78, 546–551.CrossRefGoogle ScholarPubMed
Hagnestam, C, Emanuelson, U, Berglund, B 2007. Yield losses associated with clinical mastitis occurring in different weeks of lactation. Journal of Dairy Science 90, 2260–2270.CrossRefGoogle ScholarPubMed
Hagnestam-Nielsen, C, Østergaard, S 2009. Economic impact of clinical mastitis in a dairy herd assessed by stochastic simulation using different methods to model yield losses. Animal 3, 315–328.CrossRefGoogle Scholar
Hagnestam-Nielsen, C, Emanuelson, U, Berglund, B, Strandberg, E 2009. Relationship between somatic cell count and milk yield in different stages of lactation. Journal of Dairy Science 92, 3124–3133.CrossRefGoogle ScholarPubMed
Hansson, H 2007. The links between management’s critical success factors and farm level economic performance on dairy farms in Sweden. Acta Agriculturae Scandinavica. Section C, Food Economics 4, 77–88.CrossRefGoogle Scholar
Huijps, K, Lam, TJ, Hogeveen, H 2008. Costs of mastitis: facts and perception. Journal of Dairy Research 75, 113–120.CrossRefGoogle ScholarPubMed
Kossaibati, MA, Esslemont, RJ 1997. The costs of production diseases in dairy herds in England. Veterinary Journal 154, 41–51.CrossRefGoogle ScholarPubMed
Kristensen, E, Østergaard, S, Krogh, MA, Enevoldsen, C 2008. Technical indicators of financial performance in the dairy herd. Journal of Dairy Science 91, 620–631.CrossRefGoogle ScholarPubMed
Laevens, H, Deluyker, H, Schukken, YH, De Meulemeester, L, Vandermeersch, R, De Muecaronlenaere, E, De Kruif, A 1997. Influence of parity and stage of lactation on the somatic cell count in bacteriologically negative dairy cows. Journal of Dairy Science 80, 3219–3226.CrossRefGoogle ScholarPubMed
Lagerkvist, C-J 1999. The user cost of capital in Danish and Swedish agriculture. European Review of Agriculture Economics 26, 79–100.CrossRefGoogle Scholar
Langford, FM, Weary, DM, Fisher, L 2003. Antibiotic resistance in gut bacteria from dairy calves: a dose response to the level of antibiotics fed in milk. Journal of Dairy Science 86, 3963–3966.CrossRefGoogle Scholar
Miller, GY, Bartlett, PC, Lance, SE, Anderson, J, Heider, LE 1993. Costs of clinical mastitis and mastitis prevention in dairy herds. Journal of the American Veterinary Medical Association 202, 1230–1236.CrossRefGoogle ScholarPubMed
Østergaard, S, Chagunda, MGG, Friggens, NC, Bennedsgaard, TW, Klaas, IC 2005. A stochastic model simulating pathogen-specific mastitis control in a dairy herd. Journal of Dairy Science 88, 4243–4257.CrossRefGoogle Scholar
Seegers, H, Fourichon, C, Beaudeau, F 2003. Production effects related to mastitis and mastitis economics in dairy cattle herds. Veterinary Research 34, 475–491.CrossRefGoogle ScholarPubMed
Steeneveld, W, Swinkels, J, Hogeveen, H 2007. Stochastic modelling to assess economic effects of treatment of chronic subclinical mastitis caused by Streptococcus uberis. Journal of Dairy Research 74, 459–467.CrossRefGoogle ScholarPubMed
Svensk Lantbrukstjänst 2008. Prislista (Price list). Retrieved December 15, 2008, from http://www.svensklantbrukstjanst.se/index.php?id=6Google Scholar
Swedish Board of Agriculture 2008. Prisindex och priser inom livsmedelsområdet. Års- och månadsstatistik 2008:12 (Price indices and prices in the food sector – annual and monthly statistics – 2008:12). Retrieved December 15, 2008, from http://www.sjv.se/amnesomraden/statistik/priserochprisindex.4.7502f61001ea08a0c7fff102468.htmlGoogle Scholar
Swedish Dairy Association 2008a. Avräkningspris för mjölk (Output price for milk). Retrieved December 15, 2008, from http://www.svenskmjolk.se/ImageVault/Images/id_463/scope_128/ImageVaultHandler.aspxGoogle Scholar
Swedish Dairy Association 2008b. Husdjursstatistik (Cattle statistics) 2008. Svensk Mjölk, Stockholm, Sweden.Google Scholar
Swedish Meats 2008. Slaktnoteringar (Output price for meat). Retrieved December 15, 2008, from http://www.swedishmeats.se/webit/websidor/visasida.asp?idnr=jhZxBIDOKaTJsMzcCFGLbgGUqxTdFvlfnBqaoyIMKxFDApsxtip]YMtUpIXHGoogle Scholar
Yalcin, C 2000. Cost of mastitis in Scottish dairy herds with low and high subclinical mastitis problems. Turkish Journal of Veterinary and Animal Sciences 24, 465–472.Google Scholar