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Poster De Conférence Année : 2016

Comparison of two headspace extraction techniques to determine volatile profiles generated by lactic acid bacteria in a cheese model by GC-MS

Résumé

Development of volatile compounds contributing to cheese flavour primarily depends on the metabolic activity of bacterial cultures used during manufacture. Gas chromatography coupled to mass spectrometry (GC-MS) preceded by volatiles extraction is widely used for volatile analysis. The volatile profiles of ten strains of Lactobacillus casei/paracasei generated using a cheese model were assessed by GC-MS using two extraction methods, headspace solid-phase microextraction (HS-SPME) with DVB/CAR/PDMS fibre and HeadSpace-Trap (HS-Trap) with Tenax® adsorbent. Chromatographic data was processed using XCMS package of R software. Numbers of total fragments detected were 1788 for HSSPME and 2073 for HS-Trap method. After annotation, 70 and 64 compounds considered as flavour contributors were successfully identified in HS-SPME and HS-Trap profiles respectively, with 40 compounds in common. HS-SPME extracted numerous alcohols, esters and acids, while HS-Trap showed higher selectivity towards short aldehydes and ketones, pyrazine derivatives and specific sulfur-containing compounds. Comparison of common volatiles revealed high correlation in extraction of long-chain ketones and alcohols, but poorcorrelation for aldehydes, sulfur compounds and acids. Principal Component Analysis highlighted similar differences between individual samples using both extraction techniques. Although two extraction techniques identified distinct compounds in the samples, they equally represented differences within the sample set.
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Dates et versions

hal-01355659 , version 1 (23-08-2016)

Identifiants

  • HAL Id : hal-01355659 , version 1
  • PRODINRA : 368442

Citer

Anne Thierry, Ewelina Stefanovic, Marie-Bernadette Maillard, Gerald Fitzgerald, Olivia Mcauliffe, et al.. Comparison of two headspace extraction techniques to determine volatile profiles generated by lactic acid bacteria in a cheese model by GC-MS. IDF Cheese Science & Technology Symposium, Apr 2016, Dublin, Ireland. , 2016. ⟨hal-01355659⟩
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