Literature DB >> 16910037

Headspace-solid-phase microextraction fast GC in combination with principal component analysis as a tool to classify different chemotypes of chamomile flower-heads (Matricaria recutita l.).

Patrizia Rubiolo1, Flavio Belliardo, Chiara Cordero, Erica Liberto, Barbara Sgorbini, Carlo Bicchi.   

Abstract

Headspace-solid-phase microextraction gas chromatography-principal component analysis (HS-SPME GC-PCA) is proposed as a complementary or alternative method to essential oil (EO) GC-PCA in order to discriminate between flower-heads of chamomile of different chemotypes. Ninety-two EOs and the headspaces sampled by HS-SPME of the corresponding chamomile flower-heads were examined by conventional GC and fast GC (F-GC) and the results submitted to statistical analysis by PCA. HS-SPME F-GC-PCA showed itself to be a rapid technique by which to distinguish chamomile flower-head chemotypes a produced results in agreement with the accepted EO classification. Using this method, the analysis time was reduced from at least 4.5 h with EO conventional GC to less than 1 h with HS-SPME F-GC. This approach can thus successfully be used as an analytical decision maker in order to reduce the number of time-consuming EO conventional GC analyses by limiting them to those samples that cannot unequivocally be classified. The EO conventional GC and HS-SPME F-GC results of PCA were very uniform, but they did not provide quantitative correlations between the components as determined by the two methods. A different statistical approach and a larger number of samples will be needed in order to correlate components in the headspace sampled by SPME and those in the corresponding EO quantitatively through a function.

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Year:  2006        PMID: 16910037     DOI: 10.1002/pca.919

Source DB:  PubMed          Journal:  Phytochem Anal        ISSN: 0958-0344            Impact factor:   3.373


  1 in total

1.  Mechanical power driven SPME-SERS ultra-fast detection of illegal additives in aquaculture water.

Authors:  Handi Lv; Qi Guan; Ying Wang; Xiaoli Zhang
Journal:  RSC Adv       Date:  2021-04-06       Impact factor: 3.361

  1 in total

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