Extracts made from plant materials that capture the taste and scent of the plant are known as essential oils and have many uses.
Mass spectrometry (MS) and gas chromatography (GC) and are excellent tools for essential oil analysis because the semi-volatile and volatile analytes that make up essential oils are easily separated, identified, and quantified.
This can be helpful in obtaining detailed essential oils chemical information for a variety of quality control goals, including process optimization, authentication, and characterization.
When using the Pegasus® BT for GC-MS, it is possible to separate individual chemicals by means of chromatography and also to unfold the data of the entire m / z range with chromatographic coelution.
Many chromatographic co-elutions can be disentangled in less time, which means that more information is obtained by adding a mathematical separation to chromatographic co-elutions. Preliminary identifications are made using GC-MS from both chromatographic retention order information and spectral information.
Spectral verification can be performed by comparing the collected TOFMS data of the entire m / z range with NIST library databases. For additional security, it is possible to link the retention times of the observed peaks to the retention index by using a well-known alkane standard that enables a retention index comparison with the NIST library databases.
This article analyzes and characterizes a mint essential oil and demonstrates the benefits of full m / z range data, deconvolution and retention index determinations.
Illustration 1. TIC chromatogram for mint essential oil. Representative analytes of interest are displayed along with a summary of the sample’s flavor characteristics. Image source: LECO Corporation
A mint essential oil was analyzed by GC-TOFMS after being diluted to 1% in acetone (shown in Table 1). The same retention index (RI) determination methods were also used to collect data for an alkane standard (C6 to C24).
Table 1. GC-TOFMS (Pegasus BT) conditions. Source: LECO Corporation
|Gas chromatograph||Agilent 7890 with LECO L-PAL 3 autosampler|
|injection||1 μL, divided 100: 1|
|inlet||250 ° C|
|Carrier gas||Er @ 1.4 ml / min|
|split||Rxi-5ms, 30 mx 0.25 mm ID x 0.25 μm coating (Restek)|
|Temperature program||40 ° C ramp 10 ° C / min to 280 ° C|
|Transfer line||300 ° C|
|mass spectrometry||LECO Pegasus BT|
|Ion source temperature||250 ° C|
|Mass range||33-500 m / z|
|Activity rate||10 spectra / s|
Results and discussions
Figure 1 shows the representative GC-MS chromatogram for a mint essential oil. Information on the detected peaks in the sample was provided using LECO’s automated data processing software. Table 2 shows the area% quantitation, aroma properties and identifications for the 30 most intense analytes in the sample.
Table 2. Identification information for the top 30 analytes. Source: LECO Corporation
|Surname||RT (s)||formula||Sim||RI||Library RI||CASE||Odor type||Area %|
|17th||(-) – Terpinen-4-ol||534.8||C10H18O||883||1184.3||1185||20126-76-5||3.113|
|19th||(1S, 2R, 5R) – (+) –
|26th||(-) – β-Bourbons||712.4||C15H24||922||1398||1384||5208-59-3||Herbs-||0.716|
Analyte identification determinations were made by searching the observed mass spectral information against the NIST 2017 MS library database with Similarity Ratings (Sim) (see Table 2).
The retention index values were calculated for all detected peaks to give confidence to the identifications. The determinations were made by collecting data for an alkane standard. Table 2 also shows that the library’s RI information in the NIST database was used to verify the observed RI value.
Figure 2. The retention index can help increase the reliability of the identification of analytes with very similar spectral information. Image source: LECO Corporation
Figure 2 shows how the retention index was used to sort out some ambiguous peak identifications. After a preliminary library search, peaks # 23-25 in Table 2 all matched the same library spectrum, isomenthyl acetate.
The upper spectra in Figure 2 show that the observed spectra for each of these three peaks are almost identical, which is mostly an indication of analytes or isomers with very similar chemical structures.
For this example, the retention index provided additional information regarding the expected elution order used to clarify these isomers, with preliminary identifications updated to isomenthyl acetate, menthyl acetate, and neomenthyl acetate.
Figure 3. Deconvolution provides information on analytes that co-elute chromatographically. Image source: LECO Corporation
The software’s data processing tools also had the advantage of deconvolution, which is helpful in chromatographic coelution. Within the data there were some observations of co-elution cases. For example, Figure 3 shows peaks # 13-15 in Table 2.
While it appears that there is a single peak in the TIC view, the graph of XICs specific for each analyte showed that three separate analytes were co-eluting.
Identifications (aided by the retention index) of menthone, menthol and menthofuran were performed by deconvolution, which provided clean spectral information for each coeluting analyte.
The upper right corner of Figure 3 shows the raw spectral information at the TIC tip, which represents the combination of the co-eluting analytes and would be available without deconvolution.
This spectrum is consistent with 6-methyl-cyclodec-5-enol, another analyte with a similarity rating of 727; this indicates that the three coeluting analytes would be obscured without deconvolution.
Menthon, menthol and menthofuran have minty, mentholic and musty odor properties and probably contribute significantly to the overall aroma profile. Therefore, these analytes would have been difficult to detect without deconvolution.
The odor types listed in Table 2 were used to determine the associated aroma properties per analyte with analyte identifications. These aroma properties and the associated peak areas per analyte were then used to compile the overall sample characterization.
Linking an analyte peak area directly to sensory detection requires the sensory threshold for that particular analyte as well as the response factor for that analyte on the instrument.
Without these values, a chemical profile for the aroma characterizations can be provided by the peak areas.
ChromaTOF brand software was used to determine the peak areas by integrating the unfolded TIC peaks (the sum of all spectral peaks in the true spectrum of the unfolded peak integrated over the concentration profile for the chromatographic peak) and the area percentage per analyte is in Table. specified 2.
The pie chart in Figure 1 shows the 30 most important analytes in Table 2, which has compiled the peak area in% by aromatic type. As expected, menthol or mint is the main aroma descriptor for this essential oil.
This work demonstrated the characterization of a mint essential oil through the application of GC-MS. For this sample, the individual analytes and the overall characterization were given based on the aromatic types.
Deconvolution was critical in distinguishing chromatographically coeluting analytes, and retention index information was helpful in clarifying ambiguous analyte identifications.
Essential oil characterization information was provided through this detailed chemical information. GC-MS is a powerful tool for this type of analysis and can provide more information about a sample in less time.
Image source: LECO Corporation
This information has been extracted, checked, and adapted from materials provided by LECO Corporation.
For more information on this resource, please visit LECO Corporation.