SwiftDetect™: Revolutionizing Salmonella Dublin Detection

The Need: In the dairy industry, combating Salmonella Dublin is crucial due to production losses and its impact on human health. Current detection methods, particularly culture-based techniques, are laborious, time-consuming, and lack sensitivity in environmental samples. As a result, treatment effective surveillance and epidemiological understanding is hindered. There's a clear need for a culture-independent technique to efficiently detect Salmonella Dublin from clinical and environmental samples to enabling prompt identification of affected animals, premises and transmission pathways.

The Technology: Our solution involves the development of a multiplex endpoint polymerase chain reaction (PCR) for the specific detection of Salmonella Dublin. This PCR method utilizes serovar-specific primers selected through rigorous assessments and provides high specificity and sensitivity. By targeting specific gene markers, our PCR technique offers a faster and more accurate means for the detection of Salmonella Dublin compared to traditional culture-based methods.

Commercial Applications:

  • Surveillance and monitoring of Salmonella Dublin prevalence in dairy production environments.
  • Rapid screening of environmental samples from calf production systems, including veal, dairy-beef, and calf dealer facilities.
  • Quality control in food safety management systems to ensure compliance with regulatory standards.
  • Reference lab use.


  • Improved sensitivity and specificity compared to culture-based methods, leading to enhanced detection..Rapid turnaround time, enabling timely interventions to prevent disease outbreaks and production losses.
  • Cost-effectiveness through streamlined sample processing and reduced labor requirements.
  • Facilitation of data-driven decision-making for disease management and control strategies.
  • Enhanced understanding of Salmonella Dublin transmission, contributing to overall disease prevention efforts in both animal and human populations.

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