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Scientific Articles - PTR-MS Bibliography

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Publications

Found 2 results
Title [ Year(Desc)]
Filters: First Letter Of Title is G and Author is Koot, Alex  [Clear All Filters]
2008
[Araghipour2008] Araghipour, N., J. Colineau, A. Koot, W. Akkermans, J. Manuel Mor Rojas, J. Beauchamp, A. Wisthaler, T. D. Märk, G. Downey, C. Guillou, et al., "Geographical origin classification of olive oils by PTR-MS", Food Chemistry, vol. 108, no. 1: Elsevier, pp. 374–383, 2008.
Link: http://www.sciencedirect.com/science/article/pii/S0308814607010965
Abstract
The volatile compositions of 192 olive oil samples from five different European countries were investigated by PTR-MS sample headspace analysis. The mass spectra of all samples showed many masses with high abundances, indicating the complex VOC composition of olive oil. Three different PLS-DA models were fitted to the data to classify samples into ‘country’, ‘region’ and ‘district’ of origin, respectively. Correct classification rates were assessed by cross-validation. The first fitted model produced an 86% success rate in classifying the samples into their country of origin. The second model, which was fitted to the Italian oils only, also demonstrated satisfactory results, with 74% of samples successfully classified into region of origin. The third model, classifying the Italian samples into district of origin, yielded a success rate of only 52%. This lower success rate might be due to either the small class set, or to genuine similarities between olive oil VOC compositions on this tight scale.
2014
[1611] Granato, D., A. Koot, and S. M. { van Ruth}, "Geographical provenancing of purple grape juices from different farming systems by proton transfer reaction mass spectrometry using supervised statistical techniques.", J Sci Food Agric, Nov, 2014.
Link: http://dx.doi.org/10.1002/jsfa.7001
Abstract
<p>Organic, biodynamic and conventional purple grape juices (PGJ; n = 79) produced in Brazil and Europe were characterized by volatile organic compounds (m/z 20-160) measured by proton transfer reaction mass spectrometry (PTR-MS), and classification models were built using supervised statistical techniques.k-Nearest neighbours and soft independent modelling of class analogy (SIMCA) models discriminated adequately the Brazilian from European PGJ (overall efficiency of 81% and 87%, respectively). Partial least squares discriminant analysis (PLSDA) classified 100% European and 96% Brazilian PGJ. Similarly, when samples were grouped as either conventional or organic/biodynamic, the PLSDA model classified 81% conventional and 83% organic/biodynamic juices. Intraregional PLSDA models (juices produced in the same region&nbsp;-&nbsp;either Europe or Brazil) were developed and were deemed accurate in discriminating Brazilian organic from conventional PGJ (81% efficiency), as well as European conventional from organic/biodynamic PGJ (94% efficiency).PGJ from Brazil and Europe, as well as conventional and organic/biodynamic PGJ, were distinguished with high efficiency, but no statistical model was able to differentiate organic and biodynamic grape juices. These data support the hypothesis that no clear distinction between organic and biodynamic grape juices can be made with respect to volatile organic compounds. &copy; 2014 Society of Chemical Industry.</p>

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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).
Link

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.
Link

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.
Link

 

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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