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The Analytical Scientist / App Notes / 2020 / Enhancing the sensitivity of headspace analysis using large volume preconcentration (LVP) – Trace-level GC–MS analysis of VOCs in foods and beverages

Enhancing the sensitivity of headspace analysis using large volume preconcentration (LVP) – Trace-level GC–MS analysis of VOCs in foods and beverages

05/27/2020

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In this application note, we show an increase in sensitivity for headspace analysis using a sample preparation technique called large volume preconcentration (LVP). This is particularly useful for the analysis of trace-level volatile organic aroma and flavour compounds in food and beverage samples. As an example, an orange juice was analysed by headspace extraction using the Centri® sample extraction and enrichment platform operating in headspace–trap mode. Inclusion of a multi-bed focusing trap within the system flow path enables a preconcentration step after sample introduction, allowing for the extraction of headspace sample volumes greater than the conventional 1 mL. Additionally, the ability to introduce multiple headspace volumes to the trap is demonstrated as an enrichment process prior to GC–MS analysis. This provides an incremental response for each compound and comparative data are supplied for single and multiple extractions.

The ability to detect and identify aroma and flavour VOCs is important for the food and beverage industry for reasons such as product quality, shelf life, off-odours that may lead to customer complaints, competitive product analysis and consumer organoleptic responses. Some of these odouractive components may have very low odour threshold values (OTV) at the ppb or ppt level; therefore, their identification becomes a very important part of the analysis. Sample extraction and identification of the principal components are routinely achieved in food laboratories using established techniques such as static headspace extraction followed by GC–MS analysis. However, for compounds at trace levels, obtaining quality GC–MS data that generate confident library identifications may require an enhancement in the performance of the traditional headspace technique. This is where the headspace–trap LVP technique can be a valuable asset.

In this work, we show the headspace–trap results obtained using 5 mL sample volumes from both single and multiple injections to the focusing trap from a ready-to-drink supermarket orange juice using the Centri multi-mode sample extraction and enrichment platform. This sample volume is well in excess of the 1 mL volume typically used in static headspace analysis, and the focusing trap is an essential component that facilitates the headspace LVP and enrichment process, providing both selective retention and preconcentration of analytes without peak splitting

>> Download the Full Application Note as a PDF

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