Mastitis is a common disease in dairy cows and is considered to be one of the most intractable diseases in the world. We analyzed Raman spectra of milk samples from cows that have been treated for mastitis and have recovered, and those from cows that have no history of mastitis. The result shows that signal components derived from carotenoids and unsaturated fatty acids can be used as markers to predict mastitis history. Our new method based on simple and direct milk measurements will be a powerful tool to determine the prevalence and severity of mastitis in future field diagnosis applications.
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