Cryotrap/SPME/GC/MS Method for Profiling of Monoterpenes in Cheese and Their Clustering According to Geographic Origin

Authors

  • Gorazd Tompa University of Ljubljana, Biotechnical Faculty, Department of Animal Science, Groblje 3, 1230 Domžale, Slovenia
  • Robert Susič University of Ljubljana, Faculty of Chemistry and Chemical Technology, Aškerčeva 5, 1000 Ljubljana, Slovenia
  • Irena Rogelj University of Ljubljana, Biotechnical Faculty, Department of Animal Science, Groblje 3, 1230 Domžale, Slovenia
  • Matevž Pompe University of Ljubljana, Faculty of Chemistry and Chemical Technology, Aškerčeva 5, 1000 Ljubljana, Slovenia

Keywords:

Cheese, cryotrapping, solid phase microextraction, monoterpenes, clustering

Abstract

A variant of purge/cryotrap/thaw/static headspace Solid Phase Microextraction (SPME) was developed as a means for preconcentrating Volatile Organic Compounds (VOC) in cheese. An originally designed cryotrap partially filled with glass beads was employed that facilitated efficient flow-through of purging gas and trapping of the volatiles. In stoppedflow mode, thawing was allowed, and the same vessel was used for the exposure of the appropriate SPME fiber, effectively achieving double preconcentration. Gas chromatography/mass spectrometry (GC/MS) was subsequently employed to identify components and assess their relative chromatographic peak areas. Monoterpenes were chosen as a model group of substances, and their relative concentration profiles were evaluated as potential markers for the respective geographic origin. The procedure was tested on samples of five traditional Slovenian cheeses featuring Protected Designation of Origin (PDO): Tolminc, Mohant, Nano{ki cheese, together with Bov{ki cheese and Karst Ewe’s cheese. The dataset of the peak areas of nine prominent monoterpenes (α-pinene, camphene, α-phellandrene, β-pinene, 3-carene, 2-carene, limonene, tricyclene, and γ-terpinene) in cheese samples showed clustering that relates the cheeses to the area of production. According to the silhouette metrics, four clusters were identified by partitioning around medoids (PAM) method. The latter packed data for Tolminc and Bov{ki cheese into a single cluster, closely reflecting the vicinity of their geographic origin, but classified correctly the rest of the data into separate clusters for all other cheeses.

 

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Published

06.11.2013

Issue

Section

Analytical chemistry