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Automated Mastitis Detection for Dairy Farms

Automated Mastitis Detection for Dairy Farms. Amanda Sterrett & Jeffrey Bewley University of Kentucky Dairy Systems Management. But how we monitor it is different…. What else can we monitor?. Why do these people keep hanging stuff off of me?. Take advantage of simplicity.

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Automated Mastitis Detection for Dairy Farms

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  1. Automated Mastitis Detectionfor Dairy Farms Amanda Sterrett & Jeffrey Bewley University of Kentucky Dairy Systems Management

  2. But how we monitor it is different…

  3. What else can we monitor? Why do these people keep hanging stuff off of me?

  4. Take advantage of simplicity • Because cows are routine-oriented, we can monitor their behavior and examine differences in: • Eating time / DMI • Standing / Lying time • Rumination time • Location within barn

  5. Physiological monitoring • Body temperature • Ear, milk, reticulorumen, udder, vagina • Milk composition • SCC • Fat, lactose, protein, LDH, etc. • Electrical conductivity

  6. Potential Benefits Early Mastitis Detection Early Treatment Improved Prevention Program Improved Treatment Outcome Less Production Loss Less Economic Loss Improved Animal Well-Being

  7. Accuracy and Precision

  8. Sensitivity and Specificity Sensitivity (true positive rate): alert with an observed mastitis case Specificity (true negative rate): no alert with no mastitis

  9. In-Line Monitoring

  10. Electrical Conductivity Ion concentration of milk changes during mastitis Inexpensive and simple equipment Wide range of sensitivity and specificity reported Affected by sample time, milk viscosity, temperature, and sensor calibration Most useful when combined with other data

  11. Automated CMT or WMT • CellSense (New Zealand) • r = 0.76 with FossomaticSCC

  12. Somatic Cell Count • In-line detection of cell count, milk temperature, and electrical conductivity • Uses ATP luminescence as an indicator of the number of somatic cells • Sensor connected to the milk hose below the milking claw • Reagent cassette attached below display

  13. Spectroscopy • Visible, near-infrared, mid-infrared, or radio frequency • Indirect identification through changes in milk composition • AfiLab uses near infrared • Fat, protein, lactose, SCC, and MUN

  14. Cow Sensors http://blog.modernmechanix.com/robot-cow-moos-and-gives-milk/

  15. Temperature Limitations • Not all cases of mastitis result in a temperature response • Best location to collect temperature? • Noise from other physiological impacts

  16. Udder Thermography • Udder temperature closely related to rectal temperature • No early detection in LPS challenge (Hovinen et al., 2008) • Potential use in dry cows Before Infection After Infection Hovinen et al., 2008

  17. Accelerometers • Measures lying time and activity/motion index • Well researched and applied to many areas • Lying is a high priority behavior • May change lying time around mastitis • May decrease activity around mastitis • Lying time decreased by 73 minutes on the day of challenge (P < 0.01, Cyples et al., 2012)

  18. Rumination Behavior • Cows with mastitis may ruminate less • r = 0.93 for automated rumination with live observations in cows (Schirmannet al., 2009)

  19. Animal Position • Real Time Location System • Cows may stay in same spot longer around mastitis

  20. Multi-parameter Sensors • Combination monitors may find a better market than those sensors only targeted at one parameter: • Temperature • Activity • Rumination • Feeding Time • Multivariate analyses

  21. Considerations • Economics • Positive return on investment • Producer satisfaction • What data is useful? • Reading frequency • What do we do with the data? • Culture, monitor, treat, ignore?

  22. Conclusions • Using technologies for mastitis monitoring is newer than using them for estrus detection • Algorithms are not yet perfected • Continued research is needed, particularly in naturally occurring mastitis

  23. Questions? • Amanda Sterrett • 408 WP Garrigus Building • Lexington, KY 40546 • 412-558-2075 • amanda.sterrett@uky.edu • Dr. Jeffrey Bewley • 407 WP Garrigus Building • Lexington, KY 40546 • 859-699-2998 • jbewley@uky.edu

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