The information below has been supplied by dairy marketers and other industry organizations. It has not been edited, verified or endorsed by Hoard’s Dairyman. A University of Illinois research study by
Ferreira et al. (2018)* evaluated four commercial on-farm culture methods used to identify clinical mastitis-associated pathogens. Results showed AccuMast® had the highest overall accuracy, plus AccuMast was the only on-farm system capable of detecting
Staphylococcus aureus. Other culture plates involved in the study included Minnesota Easy System Tri-Plate, Mastitis SSGN Quad Plate and Mastitis SSGNC Quad Plate. The results were presented at the American Dairy Science Association’s 2017 annual meeting.
AccuMast, from FERA Animal Health, utilizes color to identify multiple mastitis pathogens. It diagnoses all of the treatable mastitis pathogens in only 16 hours, making selective therapy possible, significantly reducing the overall cost of mastitis and improving cure rates, cow health and profitability.
“While mastitis diagnosis is critical for targeted therapy, this study was the first to compare these on-farm culture systems for accuracy in identifying specific pathogens,” says Rodrigo Bicalho, chief executive officer of FERA Animal Health. “AccuMast had the highest sensitivity, positive predictive value, negative predictive value and overall accuracy. Plus it was the only test with almost perfect agreement as measured by Cohen-K value.”
The study used 299 milk samples from two commercial dairy herds. The four on-farm systems, along with two reference laboratories, cultured the samples. See Table 1 for the results.
FERA Animal Health is dedicated to improving the lives of dairy cattle and farmers by producing easy-to-use products that improve animal health through accurate diagnostics and disease prevention.
For more information, call
(585) 465-2218, visit
www.FeraAnimalHealth.com or email
feraanimalhealth@gmail.com.
*Evaluation of four on-farm culture plates to identify pathogens associated with mastitis in dairy cows. J. C. Ferreira, M. S. Gomes, E. C. R. Bonsaglia, I. F. Canisso, E. F. Garrett, J. S. Stewart, Z. Zhou, F. S. Lima
