Literature DB >> 23932373

Analysis of the unsaponifiable fraction of lipids belonging to various milk-types by using comprehensive two-dimensional gas chromatography with dual mass spectrometry/flame ionization detection and with the support of high resolution time-of-flight mass spectrometry for structural elucidation.

Peter Q Tranchida1, Simona Salivo, Ivana Bonaccorsi, Archimede Rotondo, Paola Dugo, Luigi Mondello.   

Abstract

The present investigation is focused on the use of a comprehensive two-dimensional GC (GC×GC) method, with dual mass spectrometry/flame ionization detection (MS/FID), for the qualitative and quantitative analysis of the unsaponifiable fraction of milk lipids (cow butter, buffalo, ewe, and goat milks). The structure of many constituents (particularly sterols) was confirmed by using GC-high resolution time-of-flight MS. The GC×GC column set used consisted of a low-polarity first dimension, and a medium-polarity secondary one, both characterized by a high thermal stability. The use of dual detection enabled the attainment of both mass spectral information and relative % FID data. The complexity of the fingerprint, generated by the unsaponifiable fraction, justified the employment of the two-dimensional GC technology. However, it was two other GC×GC characteristics that contributed most to the attainment of promising results, namely sensitivity enhancement and the formation of group-type patterns. Because many milk lipid constituents were not contained in the MS databases employed, exact mass information proved to be valuable for identification purposes.
Copyright © 2013 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Butter; Comprehensive two-dimensional gas chromatography; High resolution time-of-flight mass spectrometry; Milk lipids; Unsaponifiable fraction

Mesh:

Substances:

Year:  2013        PMID: 23932373     DOI: 10.1016/j.chroma.2013.07.089

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  3 in total

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3.  Identification of milk quality and adulteration by surface-enhanced infrared absorption spectroscopy coupled to artificial neural networks using citrate-capped silver nanoislands.

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Journal:  Mikrochim Acta       Date:  2022-07-29       Impact factor: 6.408

  3 in total

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