Characterizing Important Oils with GC-MS


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 %
1 Diacetone 228.7 C6H12O2 936 839.8 838 123-42-2 1.102
2 sabinene 346.2 C10H16 947 976.5 974 3387-41-5 woody 0.326
3 β-pinene 350.3 C10H16 939 981 979 127-91-3 Herbs- 0.656
4th 3-octanol 362.7 C8H18O 944 994.6 994 589-98-0 earthy 0.835
5 α-terpinene 385.7 C10H16 902 1019.7 1017 99-86-5 woody 0.38
6th p-cymen 392.9 C10H14 925 1027.6 1025 99-87-6 terpenic 0.494
7th Limes 397.0 C10H16 938 1032.1 1030 138-86-3 Citrus fruits 1,978
8th Eucalyptol 400.1 C10H18O 924 1035.4 1032 470-82-6 Herbs- 5,836
9 γ-terpinene 424.6 C10H16 909 1062.1 1060 99-85-4 terpenic 0.81
10 (Z) cabins
432.6 C10H18O 895 1070.7 1070 15537-55-0 balm 2,248
11 Linalool 459.9 C10H18O 883 1100.4 1099 78-70-6 Flower- 0.538
12th Cis-menthone 513.4 C10H18O 946 1160.4 1164 491-07-6 Mentholic 16,828
13th Menthofuran 521.7 C10H14O 893 1169.6 1165 494-90-6 musty 3.12
14th (±) -menthol 522.4 C10H20O 781 1170.4 1169 1490-04-6 Mentholic 2,842
fifteen l-menthone 523.1 C10H18O 857 1171.3 14073-97-3 minty 3,258
16 Levomenthol 530.6 C10H20O 923 1179.7 1175 2216-51-5 Mentholic 29,868
17th (-) – Terpinen-4-ol 534.8 C10H18O 883 1184.3 1185 20126-76-5 3.113
18th Neoisomenthol 539.9 C10H20O 939 1190 1188 491-02-1 Mentholic 2,075
19th (1S, 2R, 5R) – (+) –
543.9 C10H20O 886 1194.5 23283-97-8 musty 0.503
20th α-terpineol 545.4 C10H18O 911 1196.2 1189 98-55-5 terpenic 0.848
21 pulegon 588.7 C10H16O 916 1247.4 1237 89-82-7 minty 2,196
22nd p-menth-1-en-3-one 601.4 C10H16O 902 1262.4 1253 89-81-6 Herbs- 0.944
23 Neomenthylacetate 616.4 C12H22O2 909 1280.3 1274 2230-87-7 0.661
24 Menthyl acetate 632.1 C12H22O2 937 1298.8 1295 89-48-5 Mentholic 9.468
25th Isomenthyl acetate 645.8 C12H22O2 935 1315.7 1305 20777-45-1 0.599
26th (-) – β-Bourbons 712.4 C15H24 922 1398 1384 5208-59-3 Herbs- 0.716
27 Caryophylls 740.6 C15H24 953 1434.9 1419 87-44-5 spicy 4,379
28 Germacrene D 787.0 C15H24 922 1496 1481 23986-74-5 woody 2,316
29 2-cyclogermacran 798.7 C15H24 899 1512 1495 24703-35-3 green 0.632
30th β-Himachalen 801.9 C15H24 928 1516.6 1500 1461-03-6 0.432

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.

Deconvolution provides information on analytes that co-elute chromatographically.

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.

Characterization of essential oils with GC-MS

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.