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dc.contributor.authorCapozzi V
dc.contributor.authorYener S
dc.contributor.authorKhomenko I
dc.contributor.authorFarneti B
dc.contributor.authorCappellin L
dc.contributor.authorGasperi F
dc.contributor.authorScampicchio M
dc.contributor.authorBiasioli F
dc.description.abstractProton Transfer Reaction (PTR), combined with a Time-of-Flight (ToF) Mass Spectrometer (MS) is an analytical approach based on chemical ionization that belongs to the Direct-Injection Mass Spectrometric (DIMS) technologies. These techniques allow the rapid determination of volatile organic compounds (VOCs), assuring high sensitivity and accuracy. In general, PTR-MS requires neither sample preparation nor sample destruction, allowing real time and non-invasive analysis of samples. PTR-MS are exploited in many fields, from environmental and atmospheric chemistry to medical and biological sciences. More recently, we developed a methodology based on coupling PTR-ToF-MS with an automated sampler and tailored data analysis tools, to increase the degree of automation and, consequently, to enhance the potential of the technique. This approach allowed us to monitor bioprocesses (e.g. enzymatic oxidation, alcoholic fermentation), to screen large sample sets (e.g. different origins, entire germoplasms) and to analyze several experimental modes (e.g. different concentrations of a given ingredient, different intensities of a specific technological parameter) in terms of VOC content. Here, we report the experimental protocols exemplifying different possible applications of our methodology: i.e. the detection of VOCs released during lactic acid fermentation of yogurt (on-line bioprocess monitoring), the monitoring of VOCs associated with different apple cultivars (large-scale screening), and the in vivo study of retronasal VOC release during coffee drinking (nosespace analysis).en_US
dc.titlePTR-ToF-MS Coupled with an Automated Sampling System and Tailored Data Analysis for Food Studies: Bioprocess Monitoring, Screening and Nose-space Analysisen_US
dc.journal.titleJournal of Visualized Experiments

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