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.)

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.

Lippia origanoides chemotype differentiation based on essential oil GC‐MS and principal component analysis

“…Comparative studies of MWHD and conventional hydrodistillations have showed that the resulting essential oils have very similar chemical composition and that in some cases, the relative content of oxygenated compounds is slightly higher in the MWHD oils 5, 22, 23. The establishment of similarities and differences within groups of complex mixtures such as essential oils is facilitated by multivariate statistical tools such as PCA 5, 24–26. The L. origanoides essential oil composition table in our previous publication 9 included just 22 substances, those with relative amount higher than 0.8%.…”

Chemical Composition and Antimicrobial and Spasmolytic Properties of Poliomintha longiflora and Lippia graveolens Essential Oils**

“…Headspace volatile compounds analysis Volatile compounds of P. longiflora (PL‐batch 1) and L. graveolens (LG‐batch 2) were separated and identified using solid‐phase microextraction (SPME) system (Yousif and others 2000; Rubiolo and others 2006). One centimeter long poly(dimethylsiloxane)‐coated fibers (Table 2 and 3; 100 μm; Supelco Technology, St. Louis, Mo., U.S.A.) were used for this analysis.…”

Quantitative analysis of essential oils: a complex task

“…The most widely used statistical tool for GC profile elaboration is multivariate analysis (MVA), and in particular principal component analysis (PCA), a method that can highlight differences among the samples of a set characterized by a suitable number of components (variables) through the linear combination of those explaining most of the variability. 4,5 In this case, the more samples are analysed, the better is the reliability of the statistical results obtained. Figure 2 reports the PCA discrimination of 92 chamomile (Matricaria recutita L.) EOs by chemotype, using normalized % abundances of seven characterizing sesquiterpenoid components after normalization to a single internal standard (n-tridecane) and standardization of variables.…”