Comparison of electronic nose and conventional cow-side diagnostic tools for detection of ketosis in early lactation dairy cows

Authors

  • C. S. Schelkopf Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, 66506
  • M. D. Apley Department of Clinical Sciences, College of Veterinary Medicine, Kansas State University, Manhattan, KS 66506
  • B. V. Lubbers Department of Clinical Sciences, College of Veterinary Medicine, Kansas State University, Manhattan, KS 66506

DOI:

https://doi.org/10.21423/aabppro20228667

Abstract

Ketosis is a metabolic disease observed in early lactation, high-producing dairy cows. The disease state is characterized by a negative energy balance with increases in serum, milk and urine ketone bodies (acetoacetate [AcAc], acetone and beta-hy­droxybutyrate [BHB]). Rapid diagnosis of ketosis is imperative for implementing proper treatment protocols and managing economic losses associated with reduced milk production and reproductive performance, increased culling rates and treat­ment costs.

Conventional cow-side diagnostic tools providing rapid results for ketosis detection have improved disease identification; however, these tools still require farm personnel to identify potential ketosis cases prior to their use. The implementation of a hands-off, continuous monitoring system within a produc­tion setting would streamline the diagnostic process leading to real-time health management without the need for a subjective clinical assessment.

Advancements in the non-invasive detection of volatile com­pounds holds potential in the veterinary field for disease diag­nosis. Electronic nose (Enose) technology utilizes volatile com­pounds from patient samples, such as breath, urine or milk to classify disease. Incorporating Enose technology into a contin­uous monitoring system could provide a modernized approach to cattle health management.

The objective of this study was to explore the capabilities of the Enose for ketosis detection in early lactation dairy cattle and compare its performance to diagnostic tools currently used in the dairy industry.

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Published

2023-07-17

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