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Scientific Articles - PTR-MS Bibliography

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Found 3 results
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Filters: Author is Granitto, Pablo  [Clear All Filters]
[Cappellin2013a] Cappellin, L., E. Aprea, P. Granitto, A. Romano, F. Gasperi, and F. Biasioli, "Multiclass methods in the analysis of metabolomic datasets: The example of raspberry cultivar volatile compounds detected by GC-MS and PTR-MS", Food Research International: Elsevier, 2013.
Multiclass sample classification and marker selection are cutting-edge problems in metabolomics. In the present study we address the classification of 14 raspberry cultivars having different levels of gray mold (Botrytis cinerea) susceptibility. We characterized raspberry cultivars by two headspace analysis methods, namely solid-phase microextraction/gas chromatography–mass spectrometry (SPME/GC–MS) and proton transfer reaction-mass spectrometry (PTR-MS). Given the high number of classes, advanced data mining methods are necessary. Random Forest (RF), Penalized Discriminant Analysis (PDA), Discriminant Partial Least Squares (dPLS) and Support Vector Machine (SVM) have been employed for cultivar classification and Random Forest-Recursive Feature Elimination (RF-RFE) has been used to perform feature selection. In particular the most important GC–MS and PTR-MS variables related to gray mold susceptibility of the selected raspberry cultivars have been investigated. Moving from GC–MS profiling to the more rapid and less invasive PTR-MS fingerprinting leads to a cultivar characterization which is still related to the corresponding Botrytis susceptibility level and therefore marker identification is still possible.
[Cappellin2012] Cappellin, L., C. Soukoulis, E. Aprea, P. Granitto, N. Dallabetta, F. Costa, R. Viola, T. D. Märk, F. Gasperi, and F. Biasioli, "PTR-ToF-MS and data mining methods: a new tool for fruit metabolomics", Metabolomics, vol. 8, no. 5: Springer, pp. 761–770, 2012.
Proton Transfer Reaction-Mass Spectrometry (PTR-MS) in its recently developed implementation based on a time-of-flight mass spectrometer (PTR-ToF-MS) has been evaluated as a possible tool for rapid non-destructive investigation of the volatile compounds present in the metabolome of apple cultivars and clones. Clone characterization is a cutting-edge problem in technical management and royalty application, not only for apple, aiming at unveiling real properties which differentiate the mutated individuals. We show that PTR-ToF-MS coupled with multivariate and data mining methods may successfully be employed to obtain accurate varietal and clonal apple fingerprint. In particular, we studied the VOC emission profile of five different clones belonging to three well known apple cultivars, such as ‘Fuji’, ‘Golden Delicious’ and ‘Gala’. In all three cases it was possible to set classification models which can distinguish all cultivars and some of the clones considered in this study. Furthermore, in the case of ‘Gala’ we also identified estragole and hexyl 2-methyl butanoate contributing to such clone characterization. Beside its applied relevance, no data on the volatile profiling of apple clones are available so far, our study indicates the general viability of a metabolomic approach for volatile compounds in fruit based on rapid PTR-ToF-MS fingerprinting.
[DelPulgar2011] Del Pulgar}, Jé. Sánchez {, C. Soukoulis, F. Biasioli, L. Cappellin, C. García, F. Gasperi, P. Granitto, T. D. Maerk, E. Piasentier, and E. Schuhfried, "Rapid characterization of dry cured ham produced following different PDOs by proton transfer reaction time of flight mass spectrometry (PTR-ToF-MS).", Talanta, vol. 85, no. 1: Food Technology, Facultad de Veterinaria, UEx, Campus Universitario s/n, 10003 Cáceres, Spain., pp. 386–393, Jul, 2011.
In the present study, the recently developed proton transfer reaction time of flight mass spectrometry (PTR-ToF-MS) technique was used for the rapid characterization of dry cured hams produced according to 4 of the most important Protected Designations of Origin (PDOs): an Iberian one (Dehesa de Extremadura) and three Italian ones (Prosciutto di San Daniele, Prosciutto di Parma and Prosciutto Toscano). In total, the headspace composition and respective concentration for nine Spanish and 37 Italian dry cured ham samples were analyzed by direct injection without any pre-treatment or pre-concentration. Firstly, we show that the rapid PTR-ToF-MS fingerprinting in conjunction with chemometrics (Principal Components Analysis) indicates a good separation of the dry cured ham samples according to their production process and that it is possible to set up, using data mining methods, classification models with a high success rate in cross validation. Secondly, we exploited the higher mass resolution of the new PTR-ToF-MS, as compared with standard quadrupole based versions, for the identification of the exact sum formula of the mass spectrometric peaks providing analytical information on the observed differences. The work indicates that PTR-ToF-MS can be used as a rapid method for the identification of differences among dry cured hams produced following the indications of different PDOs and that it provides information on some of the major volatile compounds and their link with the implemented manufacturing practices such as rearing system, salting and curing process, manufacturing practices that seem to strongly affect the final volatile organic profile and thus the perceived quality of dry cured ham.

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Selected PTR-MS related Reviews

F. Biasioli, C. Yeretzian, F. Gasperi, T. D. Märk: PTR-MS monitoring of VOCs and BVOCs in food science and technology, Trends in Analytical Chemistry 30 (7) (2011).

J. de Gouw, C. Warneke, T. Karl, G. Eerdekens, C. van der Veen, R. Fall: Measurement of Volatile Organic Compounds in the Earth's Atmosphere using Proton-Transfer-Reaction Mass Spectrometry. Mass Spectrometry Reviews, 26 (2007), 223-257.

W. Lindinger, A. Hansel, A. Jordan: Proton-transfer-reaction mass spectrometry (PTR–MS): on-line monitoring of volatile organic compounds at pptv levels, Chem. Soc. Rev. 27 (1998), 347-375.


Lists with PTR-MS relevant publications of the University of Innsbruck can be found here: Atmospheric and indoor air chemistry, IMR, Environmental Physics and Nano-Bio-Physics


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