Separation Science, in collaboration with Agilent, offers a selection of application notes relevant for food analysis using GC or GC/MS. Find out how to achieve reduced carryover and increased reproducibility in your analyses, perfect your method...
Separation Science, in collaboration with Restek, offers an eBook outlining methods to help you achieve faster analysis times and increase sample throughput in your food analyses. Learn about new methods for multiresidue pesticide testing,...
Are you looking for powerful, robust methods to overcome your food analysis challenges? If so, this on-demand e-seminar, brought to you by Separation Science in collaboration with Markes International, offers some solutions.
Professor Erich Leitner from Graz Univeristy of Technology in Austria will share his knowledge of wine profiling and how GC/GCMS as analytical tool can help identify the origin of different wines in this upcoming webinar.
In this article, metabolomic profiles of beer were studied and determined using a triple quadrupole GCMS (GCMS-TQ8040) enabling characteristic compounds (e.g. saccharides) to be identified for some types and brands of beer.
Would you benefit from learning more about the advantages of thin film solid-phase microextraction (TF-SPME) as an extraction technique? If so, this on-demand webinar will provide the answers via a serious of application examples.
Would you like to automate the complex sample preparation process for the determination of 3-MCPD and glycidyl fatty acid esters in edible oils and fats? If so, this on-demand webinar will explain how this can be achieved by using the complete...
Would you like to learn more about different screening methods for metabolomics applications? In this on-demand webinar a benchtop GC Time-of-Flight mass spectrometer was used to evaluate the metabolomic profile of superfood seeds, looking for...
Markes International has produced an application note demonstrating the fully automated sampling and detection of Butylated Hydroxytoluene (BHT) in two foodstuffs using automated headspace–trap GC–MS.
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