Abstract
The potential of proton transfer reaction mass spectrometry (PTR-MS) as a tool for classification of milk fats was evaluated in relation to quality and authentication issues. Butters and butter oils were subjected to heat and off-flavouring treatments in order to create sensorially defective samples. The effect of the treatments was evaluated by means of PTR-MS analysis, sensory analysis and classical chemical analysis. Subsequently, partial least square-discriminant analysis models (PLS-DA) were fitted to predict the matrix (butter/butter oil) and the sensory grades of the samples from their PTR-MS data. Using a 10-fold cross-validation scheme, 84% of the samples were successfully classified into butter and butter oil classes. Regarding sensory quality, 89% of the samples were correctly classified. As the milk fats were fairly successfully classified by the combination of PTR-MS and PLS-DA, this combination seems a promising approach with potential applications in quality control and control of regulations.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
