The detection and prediction of mastitis in dairy cows by particle analysis

  • Iwona Anna Janik

    Student thesis: Doctoral ThesisDoctor of Philosophy

    Abstract

    This study investigated the hypothesis that the particulate content of milk, as monitored with particle counters, is correlated to the health status of lactating dairy cows, in particular the condition mastitis. Twenty Holstein cows were monitored from the very first day of clinical mastitis outbreak until complete recovery from the disease. During the experiment, the changes in particle behaviour in all four quarters and mixture of milk from all of them were measured. For each sample the following parameters were measured: somatic cell count, fat content, lactose and protein concentration, number and size distribution of milk particles, electric conductivity and diameter of milk fat globules. In total over thirty mastitis outbreaks were observed and monitored throughout, including the first phase of this study when over three thousand samples of foremilk were collected and examined.

    An operational protocol and particle monitoring device were designed with the help of a commercial company Facility Monitoring Systems Ltd (FMS), Malvern. A particle counter and Peak Height Analyser (PHA) were used to monitor particulate content of milk and a compound phase contrast microscope was used to identify milk particles by photographic visualisation and to establish their diameter.

    It was observed that the number of particles, milk fat globule diameter and somatic cell counts were stable during periods without udder inflammation. Mastitis caused great changes in these parameters. Both milk particulate size and number were significantly affected by clinical and subclinical form of inflammation (change to the particulate behaviour). It was observed that the changes to the volume median diameter (VMD) of fat globules became evident a few days before clinical signs were present. Results obtained from a particle counter and the PHA were in agreement with data obtained by microscopy. Major changes were recorded in the number of total particles in milk before and during the outbreak of mastitis. Further research showed that changes took place in the pattern of particulate behaviour without visible signs of disease; additional data established that subclinical mastitis can be also identified through the monitoring of particles in milk. In summary monitoring of the behaviour (changes to size and number) of milk fag globules (MFG) can be used as an early indicator of the onset of mastitis.

    In addition data collected during study produced strong evidence supporting the theory of the interdependence of the quarters within the udder. It was found that the coefficient of correlation for size and number of particles for all four quarters within the udder was statistically significant. Particle counts and the VMD values behaviour were similar for the four quarters. This relationship was observed for all monitored animals. Moreover, the same relationship was also observed during both clinical and subclinical outbreaks of mastitis. Somatic cell count was affected only in an infected quarter while particulate content of milk ―responded to disease in all four quarters within the udder (even if only one was infected). These results were the most surprising and unexpected outcome, suggesting that four quarters within the udder work together as one organ not four separate units.

    It was observed that the mean MFG cannot be used as a baseline to test individual animal deviations due to the unique particle profile of each observed animal. In all monitored animals particle counts obtained from PHA was found to be in the range of 1011 to 1013 with an average of 1012 particles per ml. The number of particles recorded in mastitis for one animal was at the healthy level for another. The particle pattern became a finger print for each animal and therefore MFG behaviour cannot be compared between animals.

    Following the first phase of the study the monitoring period was set at 15 to 20 days. This protocol allowed for minimising the influence of any other parameters on particles, which may influence the outcome of an experiment e.g. the number of particles in single samples detected by the particle counter. It was also essential to understand how the age, nutrition and stage of lactation might influence the particles and affect the results. Therefore two animals were chosen to be examined during their lactation. The analysed data did not present enough evidence to establish the relationship between nutrition and milk fat globules size and number. However to better understand this association additional studies should be carried out.

    Further work is required to optimise the monitoring device and build a fully automated system which will allow collecting and analysing data from the whole herd. This study proposed that particle pattern is unique for each animal – like a finger print. More research is needed to better understand the mechanism behind milk fat globules synthesis during inflammation.

    The results obtained during this study provide new evidence with regard to physiological changes within the udder before and during mastitis outbreak and supported the theory of interdependence between quarters within udder. The particle count in milk can be used as an indicator of the health status of the single animal. Combined the PHA and microscope can be used as a new tool to determine and monitor the particle count in milk. The understanding of the particulate behaviour will help to minimise the chance of mastitis outbreak by early detection and also to reduce the chance of the cross-contamination between animals during the milking process. Milk fat globule size and number can be used as an efficient indicator of the onset of mastitis.
    Date of Award2013
    Original languageEnglish
    Awarding Institution
    • Coventry University
    • Royal Agricultural University
    SupervisorChris Gaskell (Supervisor), Hugh Martin (Supervisor) & Stephen A. Chadd (Supervisor)

    Keywords

    • dairy cows
    • monitoring
    • mastitis

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