Flower scents are commonly used in the fragrance industry. Additionally, smell profiles can 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 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. This information can be used to understand unique differences that may be useful in understanding aroma and consumer preference.
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Dynamic Headspace (DHS) for the Screening of Fragrance Compounds in Flowers by GC/Q-TOF Using Chemometrics