Sample Preparation for the Study of Flavor Compounds in Food

Jeleń, Henryk H.

doi:10.1002/9780813823621.ch15

Cited by 3 publications

(1 citation statement)

References 114 publications

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“…Headspace analysis in combination with gas chromatography mass spectrometry is the most widely used technique for the analysis of volatile compounds in coffee and other foodstuffs [17,19]. Dynamic headspace extraction has been characterized by high sensitivity, and thus, in the analysis of complex matrices like coffee can provide greater flexibility and compound coverage [20].…”

Section: Discussionmentioning

confidence: 99%

Typification of Green Coffee and Selected Spices Based on the Analysis of Volatile Compounds and Supervised Learning

Lazaridis,

Kokkosi,

Mylonaki

et al. 2024

Preprint

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The present study comprises the second part of our previous work that dealt mainly with the phytochemical and physicochemical characterization of green coffee, clove, cinnamon/clove and nutmeg ethanolic extracts of grape origin. In the present study, we focused on producing a discriminating model concerning green coffee, clove, cinnamon, cinnamon and clove, and nutmeg fine powders based on multivariate analysis of variance and supervised learning on data of volatile compounds analysis, carried out with solid phase dynamic extraction in combination with gas chromatography/mass spectrometry. Results showed that 7 volatile compounds namely ethylene, methanol, 3-methylpentane, ethyl acetate, 9-hexadecen-1-ol, toluene, and methyl acetate could differentiate the investigated samples resulting in a 100% classification rate using the cross-validation method of linear discriminant analysis. Results were further confirmed using partial least squares regression analysis. The study contributes to the typification of green coffee, cinnamon, clove, cinnamon and clove and nutmeg, based on selected volatile compounds, and provides further support to the literature by means of possible adulteration given the statistical models developed.

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Section: Discussionmentioning

confidence: 99%

Typification of Green Coffee and Selected Spices Based on the Analysis of Volatile Compounds and Supervised Learning

Lazaridis,

Kokkosi,

Mylonaki

et al. 2024

Preprint

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Tuning a Bisphenol A Lateral Flow Assay Using Multiple Gold Nanosystems

Lin

Huang

Dutta

et al. 2019

Part & Part Syst Charact

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Advanced bisphenol A (BPA) lateral flow assays (LFAs) that use multiple nanosystems are reported. The assays use three nanosystems: gold nanostars, gold nanocubes, and gold nanorods, which are rarely applied in LFAs, compared with general gold nanoparticles that are referred to as gold nanospheres in this paper. These various nanosystems are bound to anti‐BPA antibodies and applied in LFAs to develop advanced BPA LFAs; the developed LFAs show differing BPA detection performance, as well as different visible colors, optical intensities, limits of detection, and application ranges. Advanced BPA LFAs that use multiple gold nano‐object shapes are successfully developed, and the geometry effects of diverse gold nanosystems coupled with anti‐BPA antibodies and the potential applications of regular BPA LFAs are explored.

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