The good, the bad and the aged: Predicting sensory quality of anhydrous milk fat by PTR/SRI-Tof-MS analysis and data mining. (October 2020)

• Record Type: Journal Article
• Authors: Pedrotti, M.; Khomenko, I.; Fontana, M.; Somenzi, M.; Falchero, L.; Arveda, M.; Cappellin, L.; Fogliano, V.; Biasioli, F.
• Is Part Of: International dairy journal. Volume 109(2020)
• Publication Date: 2020-10
• Subjects: Dairying -- Periodicals; Industrie laitière -- Périodiques; Electronic journals; 338.1762142
• DOI: 10.1016/j.idairyj.2020.104729
• Languages: English
• ISSNs: 0958-6946

Abstract

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.