Mastitis diagnosis in ten Galician dairy herds (NW Spain) with automatic milking systems

  1. Angel Castro Ramos 1
  2. José Manuel Pereira González 1
  3. Carlos Amiama Ares 1
  4. Javier Bueno Lema 1
  1. 1 Universidade de Santiago de Compostela

    Universidade de Santiago de Compostela

    Santiago de Compostela, España


Spanish journal of agricultural research

ISSN: 1695-971X

Ano de publicación: 2015

Volume: 13

Número: 4

Tipo: Artigo

DOI: 10.5424/SJAR/2015134-7482 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Outras publicacións en: Spanish journal of agricultural research


Citas recibidas

  • Citas en Scopus: 6 (15-09-2023)
  • Citas en Web of Science: 6 (22-09-2023)
  • Citas en Dimensions: 5 (31-03-2023)

JCR (Journal Impact Factor)

  • Ano 2015
  • Factor de impacto da revista: 0.76
  • Factor de impacto sen autocitas: 0.691
  • Article influence score: 0.25
  • Cuartil maior: Q2
  • Área: AGRICULTURE, MULTIDISCIPLINARY Cuartil: Q2 Posición na área: 24/57 (Edición: SCIE)

SCImago Journal Rank

  • Ano 2015
  • Impacto SJR da revista: 0.385
  • Cuartil maior: Q2
  • Área: Agronomy and Crop Science Cuartil: Q2 Posición na área: 153/350

Scopus CiteScore

  • Ano 2015
  • CiteScore da revista: 1.4
  • Área: Agronomy and Crop Science Percentil: 55


(Datos actualizados na data de 31-03-2023)
  • Total de citas: 5
  • Citas recentes: 2
  • Field Citation Ratio (FCR): 0.9


Over the last few years, the adoption of automatic milking systems (AMS) has experienced significant increase. However, hardly any studies have been conducted to investigate the distribution of mastitis pathogens in dairy herds with AMS. Because quick mastitis detection in AMS is very important, the primary objective of this study was to determine operational reliability and sensibility of mastitis detection systems from AMS. Additionally, the frequency of pathogen-specific was determined. For this purpose, 228 cows from ten farms in Galicia (NW Spain) using this system were investigated. The California Mastitis Test (CMT) was considered the gold-standard test for mastitis diagnosis and milk samples were analysed from CMT-positive cows for the bacterial examination. Mean farm prevalence of clinical mastitis was 9% and of 912 milk quarters examined, 23% were positive to the AMS mastitis detection system and 35% were positive to the CMT. The majority of CMT-positive samples had a score of 1 or 2 on a 1 (lowest mastitis severity) to 4 (highest mastitis severity) scale. The average sensitivity and specificity of the AMS mastitis detection system were 58.2% and 94.0% respectively being similar to other previous studies, what could suggest limitations for getting higher values of reliability and sensibility in the current AMSs. The most frequently isolated pathogens were Streptococcus dysgalactiae (8.8%), followed by Streptococcus uberis (8.3%) and Staphylococcus aureus (3.3%). The relatively high prevalence of these pathogens indicates suboptimal cleaning and disinfection of teat dipping cups, brushes and milk liners in dairy farms with AMS in the present study.

Referencias bibliográficas

  • Barrett DJ, Doherty ML, Healy AM, 2005. A descriptive epidemiological study of mastitis in 12 Irish dairy herds. Irish Vet J 58: 31-35.
  • Cundíns A, Hernádez M, Castro A, Pereira JM, 2010. Parámetros de funcionamiento en 67 instalaciones de ordeño de la zona norte de Lugo y su relación con el estado sanitario de los rebaños. I Jornadas Técnicas sobre Calidad de Leche, Ribadeo (Spain), Oct 22-23, pp: 64-72.
  • Davis A, Reinemann DJ, 2002. Milking performance and udder health of cows milked robotically and conventionally. ASAE An. Int. Meeting. Chicago, ILL, USA, July 28-31, No 02-3112.
  • Dimitar N, Metodija T, 2012. Udder quarter risk factors associated with prevalence bovine clinical mastitis. Mac Vet Rev 35: 55-64.
  • Dohmen W, Neijenhuis F, Hogeveen H, 2010. Relationship between udder health and hygiene on farms with an automatic milking system. J Dairy Sci 93: 4019-4033.
  • Ferguson JD, Azzaro G, Gambina M, Licitra G, 2007. Prevalence of mastitis pathogens in Ragusa, Sicily, from 2000 to 2006. J Dairy Sci 90: 5798-5813.
  • Fouz R, Corrales JR, Fernández G, Yus E, 2004. Manual: Programa de mellora da calidade do leite: control das mamites bovinas. Instituto de Investigación e Análises Alimentarias. Unidad de Epidemiología y Sanidad Animal, Lugo. ISBN: 84-609-2116-6.
  • Fouz R, Yus E, Sanjuán ML, Diéguez FJ, 2010. Statistical evaluation of somatic cell counts in bovine milk at calving, during lactation and at drying-off (by oficial recording). Livest Sci 128: 185-188.
  • Fröhling A, Wienke M, Meierhöfer SR, Schlüter O, 2010. Improved method for mastitis detection and evaluation of disinfectant efficiency during milking process. Food Bioprocess Tech 3: 892-900.
  • Gröhn YT, Wilson DJ, González RN, Hertl JA, Schulte H, Bennett G, Schukken YH, 2004. Effect of pathogen-specific clinical mastitis on milk yield in dairy cows. J Dairy Sci 87: 3358-3374.
  • Hertl JA, Schukken YH, Bar D, Bennett GJ, González RN, Rauch BJ, Welcome FL, Tauer LW, Gröhn YT, 2011. The effect of recurrent episodes of clinical mastitis caused by gram-positive and gram-negative bacteria and other organisms on mortality and culling in Holstein dairy cows. J Dairy Sci 94: 4863-4877.
  • Hogeveen H, Kamphuis C. Steeneveld W, Mollenhors H, 2010. Sensors and clinical mastitis. The quest for the perfect alert. Sensors 10: 7991-8009.
  • Hovinen M, Aisla AM, Pyörälä S, 2005. Visual detection of technical success and effectiveness of teat cleaning in two automatic milking systems. J Dairy Sci 88: 3354-3362.
  • Hovinen M, Pyörälä S, 2011. Invited review: Udder health of dairy cows in automatic milking. J Dairy Sci 94: 547-562.
  • Kamphuis C, Sherlock R, Jago J, Mein G, Hogeveen H, 2008. Automatic detection of clinical mastitis is improved by in-line monitoring of somatic cell count. J Dairy Sci 91: 4560-4570.
  • Kamphuis C, Mollenhorst H, Heesterbeek JAP, Hogeveen H, 2010. Detection of clinical mastitis with sensor data from automatic milking systems is improved by using decision-tree induction. J Dairy Sci 93: 3616-3627.
  • Kamphuis C, Dela Rue B, Mein G, Jago J, 2013. Development of protocols to evaluate in-line mastitis-detection systems. J Dairy Sci 96: 4047-4058.
  • Lam TJGM, Olde Riekerink RGM, Sampimon OC, Smith H, 2009. Mastitis diagnostics and performance monitoring: a practical approach. Irish Vet J 62: 34-39.
  • Makovec JA, Ruegg PL, 2003. Results of milk samples submitted for microbiological examination in Wisconsin from 1994 to 2001. J Dairy Sci 86: 3466-3472.
  • Mollenhorst H, Hogeveen H, 2008. Detection of changes in homogeneity of milk: Internal report. Department of Farm Animal Health, Faculty of Veterinary Medicine, Utrech University, Utrech, The Netherlands.
  • Mollenhorst H, Rijkaart LJ, Hogeveen H, 2012. Mastitis alert preferences of farmers milking with automatic milking systems. J Dairy Sci 95: 2523-2530.
  • Munoz MA, Bennett GJ, Ahlström C, Griffiths HM, Schukken YH, Zadoks RN, 2008. Cleanliness scores as indicator of Klebsiella exposure in dairy cows. J Dairy Sci 91: 3908-3916.
  • Nam HM, Kim JM, Lim SK, Jang KC, Jung SC, 2010. Infectious aetiologies of mastitis on Korean dairy farms during 2008. Res Vet Sci 88: 372-374.
  • National Mastitis Council, 1987. Reasons for negative culture results. [10 October 2014].
  • Olde Riekerink RGM, Barkema HW, Kelton DF, Scholl DT, 2008. Incidence rate of clinical mastitis on Canadian dairy farms. J Dairy Sci 91: 1366-1377.
  • Oliveira L, Hulland C, Ruegg PL, 2013. Characterization of clinical mastitis occurring in cows on 50 large dairy herds in Wisconsin. J Dairy Sci 96: 7538-7549.
  • Pitkälä A, Haveri M, Pyörälä S, Myllys V, Honkanen-Buzalski T, 2004. Bovine mastitis in Finland 2001. Prevalence, distribution of bacteria, and antimicrobial resistance. J Dairy Sci 87: 2433-2441.
  • Polat B, Colak A, Cengiz M, Yanmaz LE, Oral H, Bastan A, Kaya S, Hayirli A, 2010. Sensitivity and specificity of infrared thermography in detection of subclinical mastitis in dairy cows. J Dairy Sci 93: 3525-3532.
  • Rasmussen MD, 2001. Automatic milking. How to define a threshold for dumping mastitic milk? Proc. 2nd Int. Symp. on Mastitis and Milk Quality, AABP & NMC, pp: 401-404.
  • Ruegg, PL, 2003. Investigation of mastitis problems on farms. Vet Clin North Am Food Anim Pract 19: 47-73.
  • Schwarz D, Diesterbeck US, Failing K, König S, Brügemann K, Zschöck M, Wolter W, Czerny CP, 2010. Somatic cell counts and bacteriological status in quarter foremilk samples of cows in Hesse, Germany-A longitudinal study. J Dairy Sci 93: 5716-5728.
  • Steeneveld W, van der Gaag LC, Ouweltjes W, Mollenhorst H, Hogeveen H, 2010a. Discriminating between true-positive and false-positive clinical mastitis alerts from automatic milking system. J Dairy Sci 93: 2559-2568.
  • Steeneveld W, van der Gaag LC, Ouweltjes W, Mollenhorst H, Hogeveen H, 2010b. Simplify the interpretation of alert lists for clinical mastitis in automatic milking systems. Comput Electron Agric 71: 50-56.
  • Sun Z, Samarasinghe S, Jago J, 2010. Detection of mastitis and its stage of progression by automatic milking systems using artificial neural networks. J Dairy Res 77: 168-175.
  • Viguier C, Arora S, Gilmartin N, Welbeck K, O'Kennedy R, 2009. Mastitis detection: current trends and future perspectives. Trends Biotechnol 27: 486-493.