Quantitative Headspace Measurement of Volatiles in Dairy Products using Vacuum Assisted Sorbent Extraction (VASE) and GCMS Analysis Application
The headspace of common dairy products, including cheese and milk, was analyzed utilizing a new sample preparation technique called Vacuum Assisted Sorbent Extraction (VASE). VASE improves the recovery of heavier and more polar volatile compounds in nearly any matrix by GCMS. After introducing a sample into a 20-40mL vial, a cartridge containing 70mg of Tenax is placed into the headspace of the vial using a vacuum tight interface that allows the vial headspace to be evacuated to less than 0.01atm, or at least until the pressure needed to boil an aqueous mixture at 25°C is reached. This results in faster diffusion from the sample/ headspace boundary layer to the adsorbent, enhancing the rate of sample extraction. In particular, heavy volatile compounds with low vapor pressures that have little to no response by classical SPME are extracted 10-50x more efficiently. Unlike Dynamic Headspace, which uses an inert gas to sweep the volatiles of a sample through the adsorbent bed to concentrate and trap analytes, VASE is performed statically. VASE allows the sample and headspace to come to an equilibrium in a closed system, causing analytes to diffuse onto and collect at the very front of the adsorbent bed.
Consequently, VASE achieves a much better recovery of heavier compounds while reducing the common carryover issues affecting other adsorbent techniques that use flow to push compounds far up into a trap. Once placed under vacuum, the analyst determines the length of extraction time, ranging from minutes to hours, until equilibrium between the sample and headspace is reached to produce complete, reproducible extractions.
Dairy products generally have low levels of headspace volatiles. In this study, VASE proceeded for 4-24 hours, with many Sorbent Pens extracting samples simultaneously to simulate conditions of a production laboratory. The increase in sample extraction duration combined with a large phase to sample ratio allows more accurate determination of headspace composition, with reduced matrix affects. Data is presented showing milk and cheese analysis, with recovery of compounds well into the semi-volatiles range.
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- Last Updated February 15, 2023