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.
| Original language | English |
|---|---|
| Pages (from-to) | 307-317 |
| Number of pages | 11 |
| Journal | European Food Research and Technology |
| Volume | 227 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - May 2008 |
| Externally published | Yes |
Keywords
- Butter
- Butter oil
- Headspace analysis
- Matrix
- Sensory analysis
- Volatile compounds
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