Average mass scan of the total ion chromatogram versus percentage chemical composition in multivariate statistical comparison of complex volatile mixtures

Abstract

A análise de misturas voláteis complexas usando cromatografia gasosa-espectrometria de massa (CG-EM) é um processo demorado. Este processo envolve a separação e identificação de componentes baseados em seus tempos de retenção e padrões de fragmentação, seguido da determinação de suas porcentagens relativas a partir da integração das áreas dos picos. No presente trabalho mostramos que análise estatística multi-variada das abundâncias relativas dos valores m/z obtidos a partir das varreduras médias de massa (VMM) da mistura complexa é um método mais rápido e potencialmente mais confiável de avaliação destas misturas. Foram preparadas 15 misturas modelo complexas contendo quantidades variadas de 10 constituintes diferentes. O perfil VMM e a composição química de cada mistura foram comparados uns aos outros utilizando análise de cluster hierárquica aglomerante e análise de componentes principais. Os resultados obtidos indicam fortemente que análise estatística multi-variada dos perfis VMM é uma ferramenta promissora, eficiente e confiável para analisar misturas voláteis complexas, em particular óleos essenciais. The analysis of complex volatile mixtures by gas chromatography-mass spectrometry (GC-MS) is a time-consuming process. It involves separation and identification of the components based on their retention times and fragmentation patterns, followed by determination of their relative percentages from integration of their peak areas. Herein we show that multivariate statistical analysis of the relative abundances of the m/z values obtained from the average mass scans (AMS) of the complex mixture is a faster and potentially more reliable method of assessing these mixtures. To achieve this, 15 model complex mixtures, were prepared comprising varying amounts of 10 different constituents. The AMS profile and chemical composition of each mixture were compared to one another using agglomerative hierarchical cluster analysis and principal component analysis. The results obtained strongly suggest that multivariate statistical analysis of AMS profiles is a promising, time saving and reliable tool for analyzing complex volatile mixtures, in particular essential oils.

The Most Frequently Encountered Volatile Contaminants of Essential Oils and Plant Extracts Introduced During the Isolation Procedure: Fast and Easy Profiling

“…To assess this, the AMS profiles of the samples (A–G) analysed were acquired (as described in Materials and Methods) and considered in terms of the corresponding percentage composition. As expected, and as noticed previously (Radulović et al , ), the fragmentation patterns visible in the AMSs of the samples analysed matched those of the corresponding major compounds or class of compounds. Characteristic m/z values (and their relative abundances) of the AMS profiles of samples A–G are given in Table .…”

“…However, either approach could be considered as rather time consuming, while an additional shortcoming of the former is the significant loss of low boiling solvent (such as diethyl ether is) upon distillation. It has been shown recently by our research group that a multivariate statistical analysis (MSA) of complex volatile mixtures, based on their average mass scans of the total ion chromatograms (AMS), could be considered as a time‐saving tool for comparison of such mixtures (Radulović et al , ). The results obtained were, in general, the same as those acquired by running the MSA using percentage composition (peak areas) of the mixtures used traditionally (Radulović et al , ).…”

“…It has been shown recently by our research group that a multivariate statistical analysis (MSA) of complex volatile mixtures, based on their average mass scans of the total ion chromatograms (AMS), could be considered as a time‐saving tool for comparison of such mixtures (Radulović et al , ). The results obtained were, in general, the same as those acquired by running the MSA using percentage composition (peak areas) of the mixtures used traditionally (Radulović et al , ). This has prompted us to test the possible applicability of the AMS approach to screening and tracking contaminants in both organic solvents and EO/PE mixtures.…”

“…After t R2 (30.94–54.80 min) no ions corresponding to the last peak apex of the given GC chromatogram were detected and the interval between t R2 and 64.00 min was not taken into account to lessen the effect of column bleed peaks. The relative abundances of the AMS m/z peaks, which account for both the relative abundances of ions in individual mass spectra as well as the relative percentages of the corresponding mixture components (Radulović et al ., ), are given in percentages, with 100% assigned to the most abundant peak in every AMS, and the percentages of all other peaks given as relative to the AMS base peak. The m/z values that corresponded to column bleed peaks ( m/z 281 and 207), carbon dioxide ( m/z 44) and argon ( m/z 40, contaminant from the carrier gas) were excluded.…”

α‐Linalool – a marker compound of forged/synthetic sweet basil (Ocimum basilicum L.) essential oils

“…The high level of mutual chemical resemblance of samples A–D is observable from their almost identical AMS (average mass scan of the total ion chromatogram) profiles (see ‘Supporting information’). Mass/charge ratios (relative abundances) of the AMSs were found to be useful for direct and fast comparison of essential oils (as variables for multivariate statistical analysis of volatile complex mixtures such as essential oils) …”