Articles
MULTIVARIATE METHODS FOR AROMATIC PLANTS: AN APPLICATION TO MINT ESSENTIAL OILS
Article number
330_18
Pages
159 – 170
Language
Abstract
Essential oil analyses are subject to different interpretations based on both chemotaxonomic and qualitative organoleptic characteristics.
Multivariate statistical methods are widely used to facilitate the partition of chemical races among huge data populations.
The present work shows results on Cluster Analysis as well as Principal Component Analysis performed on essential oils distilled from mint populations.
The identification of the single compounds was performed by GC/MS. Integrated areas of the identified compounds were statistically processed using a Systat statistical package for Macintosh computer.
A clear partition was obtained among plants indicating evident phenotypic, genotypic and geographical differentiations.
Multivariate statistical methods are widely used to facilitate the partition of chemical races among huge data populations.
The present work shows results on Cluster Analysis as well as Principal Component Analysis performed on essential oils distilled from mint populations.
The identification of the single compounds was performed by GC/MS. Integrated areas of the identified compounds were statistically processed using a Systat statistical package for Macintosh computer.
A clear partition was obtained among plants indicating evident phenotypic, genotypic and geographical differentiations.
Authors
M. MAFFEI, V. PERACINO, T. SACCO
Keywords
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