Flowers scents are commonly used in the fragrance industry. Additionally, smell profiles can also be useful from a botanical perspective to characterise different species and get a better understanding of the plant volatiles and the chemical ecology behind it. The most challenging task for these applications is the extraction of a representative fragrance profile that mimics the flower smell being studied. Dynamic Headspace (DHS) is a powerful headspace technique that can fully extract the entire profile. In this Application Note, a chemometric approach using Principal Component Analysis (PCA) is shown to effectively separate different flower species and to identify unique fragrance compounds.
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Dynamic Headspace for the Screening of Fragrance Compounds in Flowers by GC/Q-TOF using Chemometrics