The good, the bad and the aged: Predicting sensory quality of anhydrous milk fat by PTR/SRI-Tof-MS analysis and data mining

M. Pedrotti, I. Khomenko, M. Fontana, M. Somenzi, L. Falchero, M. Arveda, L. Cappellin, V. Fogliano, F. Biasioli*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

Abstract

Due to its versatility, anhydrous milk fat (AMF) has become more popular as a food industry ingredient, but its quality control remains a critical challenge. A direct injection mass spectrometry technique was applied to predict sensory quality of AMF. Volatilome analysis through proton transfer reaction mass spectrometry (PTR-MS) was used to classify 39 industrial samples of AMF according to industrial sensory evaluation and to accelerated ageing. A selective reagent ion system was used to evaluate the suitability of PTR-MS alternative ionisation modes for quality control. Supervised multivariate data analysis successfully classified samples and showed that samples exposed to accelerated shelf life at 50 °C presented higher intensities of most volatiles, especially for the ones derived from oxidation like aldehydes and ketones, while samples with an acceptable quality level had lower emissions of volatiles. PTR-MS technique is ideal to support agroindustry sensory quality programs requiring rapid on-line analytical information.

Original languageEnglish
Article number104729
JournalInternational Dairy Journal
Volume109
DOIs
Publication statusPublished - Oct 2020

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