Importance of the Topic
The detailed analysis of fragrance components in aroma oils is critical for quality control in consumer goods, cosmetics, and food industries. By characterizing volatile compounds, manufacturers can ensure product consistency, optimize sensory profiles, and detect contaminants that affect safety and odor quality.
Objectives and Study Overview
This study demonstrates the application of GC/MS Off-Flavor Analyzer with the GCMS-TQ8040 NX system to analyze non-odorous fragrance oils. Four commercial aroma oils—Jasmine, Lavender, Rose, and Citrus—were examined to compare the performance of scan, SIM, and MRM modes, and to evaluate the integration of sensory database information.
Instrumentation Used
- Autosampler: AOC-20s Plus
- Auto injector: AOC-20i Plus (1 μl split 1:5)
- GC/MS: GCMS-TQ8040 NX
- Column: InertCap 5MS/Sil (30 m × 0.32 mm I.D., 0.5 μm)
- Carrier gas: Helium at 44.5 kPa (pressure control)
- Temperature program: 50 °C (5 min), 10 °C/min to 250 °C (10 min)
- Interface temp: 250 °C; Ion source temp: 200 °C
- Detection modes: Scan (m/z 45–500, 0.1 min), SIM/MRM (0.3 min)
Methodology and Instrumentation
Samples were diluted to 0.1 % in ethanol and directly injected. The GC/MS Off-Flavor Analyzer software automated the creation of scan, SIM, and MRM methods. A database containing retention times and sensory descriptors guided component identification and provided odor quality attributes for detected compounds.
Main Results and Discussion
- Quantitative profiling in MRM mode revealed major components for each oil, correlating with sensory notes: floral and sweet for Jasmine and Rose, minty and camphoraceous for Lavender, and citrusy for Citrus.
- TIC chromatograms obtained by simultaneous scan-MRM runs allowed library matching of unexpected peaks such as benzyl acetate in Jasmine.
- MRM analysis demonstrated superior selectivity over SIM, enabling accurate identification of n-decanal and n-dodecanal even when SIM failed due to ion ratio mismatches.
- In samples spiked with mineral oil, MRM maintained correct identification of α-terpineol, whereas SIM signals were distorted by the contaminant.
Benefits and Practical Applications of the Method
The combined use of GC/MS Off-Flavor Analyzer and GCMS-TQ8040 NX offers:
- Rapid method setup and simultaneous scan/SIM/MRM analysis for comprehensive profiling.
- Database-driven sensory evaluation for objective odor assessment.
- Reliable identification and approximate quantification of trace and contaminant compounds.
Future Trends and Potential Applications
Integration with artificial intelligence for predictive odor modeling, expansion of sensory databases, and coupling with advanced sampling techniques (e.g., SPME, headspace) will further streamline fragrance quality control. Real-time monitoring and multivariate data analysis may enable in-line process control in manufacturing environments.
Conclusion
The GC/MS Off-Flavor Analyzer paired with GCMS-TQ8040 NX provides a powerful platform for detailed fragrance analysis, combining automated method creation, database-driven identification, and robust MRM selectivity. This approach enhances the reliability of aroma oil profiling, even in the presence of complex background matrices or contaminants.
Reference
Shimbo E., Nagao Y. Analysis of Fragrance Components in Aroma Oils Using GC/MS Off-Flavor Analyzer. Shimadzu Application News, First Edition: Jun. 2021.
Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.
User Benefits
Application
News
GC-MS
GCMS-TQ™8040 NX
Analysis of Fragrance Components in Aroma Oils
Using GC/MS Off-Flavor Analyzer
E. Shimbo, Y. Nagao
Using GC/MS Off-Flavor Analyzer, components analysis can be easily performed even on non-odorous fragrances.
The fragrance of samples can be easily evaluated by the sensory information registered in the database of GC/MS Off-Flavor
Analyzer.
By using GC-MS/MS, more reliable identifications are possible even for samples containing contaminants.
GC/MS Off-Flavor Analyzer
Although GC/MS is widely used for odor analyses, it requires a
great deal of effort to determine the analysis conditions and to
perform post-analysis. GC/MS Off-Flavor Analyzer is a system
that allows the efficient analysis of the odor-causing substances.
Fig. 1 shows the analysis flow of the GC/MS Off-Flavor Analyzer.
The system is compatible with three types of liquid-phase
columns. It can also be used for analysis with pretreatment
techniques, such as MonoTrap, solid-phase microextraction, and
headspace sampling, and supports analyses using a sniffer.
Furthermore,
the
calibration
curve
information
can
be
registered after the analysis of the sample for correction, which
enables approximate quantifications of detected components.
Fig. 1 Analysis Flow with GC/MS Off-Flavor Analyzer
Introduction
Fragrances are known to have various effects such as promoting
relaxation, masking unpleasant odors, and increasing appetite.
Therefore, the importance of fragrance is emphasized in many
fields, including daily necessities, cosmetics, and foods. While
sensory analyses by professionals are often used to evaluate
fragrances, analyses with gas chromatography enable detailed
components analyses of complex fragrances.
GC/MS Off-Flavor Analyzer is a database of expert information
for odor analyses. It is also known that odor-causing substances
produce
pleasant
smells
as
well,
depending
on
their
concentrations and compositions. In this article, we applied
GC/MS Off-Flavor Analyzer to the analyses of non-odorous
fragrances. Belows are the examples of how we used GCMS-
TQ8040 NX gas chromatograph mass spectrometer to investigate
the characteristics of aroma oil fragrances.
Table 1 Instrument Configuration and Analysis Conditions
Auto sampler
: AOC™-20s Plus
[AOC]
Auto injector
: AOC-20i Plus
Injection volume
: 1 μl
Instrument
: GCMS-TQ8040 NX
[GCMS]
Flow control mode
: Pressure (44.5 kPa)
Column temp. program
: 50 ˚C (5 min)
o 10 ˚C/min o 250 ˚C (10 min)
Injection mode
: Split (1 : 5)
Interface temp.
: 250 ˚C
Carrier gas
: He
Ion source temp.
: 200 ˚C
Purge flow rate
: 3 mL/min
m/z range
: 45-500 amu
Column
: InertCap 5MS/Sil
Event time
: 0.1 min (scan)
(30 m × 0.32 mm I.D., 0.5 μm)
0.3 min (SIM/MRM)
①Column and pretreatment device settings
②Standard sample analyses
④Automated method creation
⑤Target analyses/post analyses
· Standard sample for retention time correction (n-alkanes)
· Sample for instrument performance check
· Sample for calibration curve correction
③Retention time modifications by ARRT
Application
News
Analysis Conditions
Table 1 shows the instrument configuration and analysis
conditions used. Note that GC/MS Off-Flavor Analyzer supports
both SIM and MRM analyses. We performed simultaneous scan-
SIM and scan-MRM analyses using the analysis conditions
registered in GC/MS Off-Flavor Analyzer. Here we adopted a
simple test by directly injecting liquid samples.
The notes in the graphs show the "odor quality" of each
components. As shown in Fig.3, the fragrance characteristics of
detected components can be easily confirmed by the "odor
qualities" registered in the database of GC/MS Off-Flavor
Analyzer. For example, the components detected in Jasmine
had fragrances suggestive of plants. It is also found that
Lavender had many refreshing fragrances such as mint,
camphor, and anise, while Citrus, as its name suggested,
contained a high level of citrus fragrance.
Fig. 2 Ratios of Major Components and Flavor Characteristics of Four Aroma Oils
Vertical axis: ratio based on the value of the largest component in each analysis
Analysis of Aroma Oils
Four commercially available aroma oils (Jasmine, Lavender, Rose,
and Citrus) were diluted to 0.1 % with ethanol and then analyzed.
The graphs in Fig. 2 shows the ratios of major components and
fragrance characteristics obtained by SIM and MRM analyses.
The vertical axes refer the ratios based on the value of the
largest component in each analysis.
These graphs show major 8 components quantified by MRM
analysis, excluding those detected only by SIM analysis.
Major odor components
Sensory information
Fig. 3 A Part of Database in GC/MS Off-Flavor Analyzer
0
0.5
1
Sweet,
Flower
Geranium,
Rose
Flower,
Lavender
Honey, Spice,
Rose, Lilac
Jasmine
SIM
MRM
Sweet,
Mint
Flower,
Lavender
Camphor
Mint,
Anise, Oil
Lavender
SIM
MRM
Mint,
Citrus
Geranium,
Rose
Honey,
Clove
Citrus
SIM
MRM
0
0.5
1
Violet,
Wood
Rose
SIM
MRM
Honey, Spice,
Rose, Lilac
Application
News
Using the automated method creation tool of the GC/MS Off-
Flavor Analyzer, users can easily configure SIM and MRM
analysis conditions. Furthermore, scan analysis and SIM or MRM
analysis can be performed at the same time. Fig. 4 shows the TIC
chromatograms of four aroma oil samples obtained by
simultaneous scan-MRM analyses. With a chromatogram from
scan analysis, the peaks can be identified based on a widely-
used mass spectral library search. For example, the distinctive
peak (arrow in Fig. 4) in the chromatogram of Jasmine was
identified as benzyl acetate through the library search. Benzyl
acetate is a major ingredient of essential oils of flowers such as
jasmine, exhibiting a sweet scent. As in this example,
simultaneous scan-SIM/MRM analysis allows us to identify even
the components not registered in the database of GC/MS Off-
Flavor Analyzer.
Accurate Identifications by MRM Analysis
Fragrances are diversified by the combination of many
components. Furthermore, perfumes often contain nature-
derived ingredients such as plants, which contain a lot of
contaminants. These facts make it difficult to analyze the
composition of fragrances. For analysis of such samples, MRM
analysis is more suitable than SIM analysis because of its higher
selectivity. Below shows comparisons between SIM and MRM
analyses.
N-decanal in Jasmine sample (Fig. 5) was not identified in SIM
analysis due to the mismatch of the ion intensity ratio, but was
identified in MRM analysis. In addition, n-dodecanal (Fig. 6) was
identified in SIM analysis because the ion intensity ratio was
within the acceptable range, but not identified in MRM analysis.
In SIM analysis, contaminants can affect the peaks of the target
ions, preventing accurate identification. In the two examples
above, it is assumed that MRM analysis, the two steps of
fragmentation enabled more accurate identification.
Fig. 5 Chromatograms of n-decanal in Jasmine Sample
Jasmine
Citrus
Lavender
Rose
(min)
5.0
10.0
15.0
20.0
25.0
30.0
Fig. 4 TIC Chromatograms Obtained by Scan Analyses of Four Aroma Oil Samples (0.1 %)
(min)
13.2
13.4
13.6
13.8
14.0
0.0
%
100.0
128.00
112.00
57.0
intensi
ty
SIM
112.00>83.00
112.00>55.00
112.00>70.00
(min)
13.2
13.4
13.6
13.8
14.0
0.0
%
100.0
intensi
ty
MRM
82.00
96.00
57.00
(min)
16.4
16.6
16.8
17.0
17.2
0.0
%
100.0
intensi
ty
intensi
ty
110.00>81.00
140.00>70.00
110.00>67.00
(min)
16.4
16.6
16.8
17.0
17.2
0.0
%
100.0
SIM
MRM
Fig. 6 Chromatograms of n-dodecanal in Jasmine Sample
Application
News
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First Edition: Jun. 2021
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Fig. 7 Chromatograms of α-terpineol in Jasmine Sample
Conclusion
Commercially available aroma oils were analyzed with GCMS-
TQ8040 NX gas chromatograph mass spectrometer (Fig. 8).
Using GC/MS Off-Flavor Analyzer, we could easily confirm the
fragrance
characteristics
of
four
different
aroma
oils.
Simultaneous scan and SIM/MRM analysis enabled qualification
of components not registered in the database of GC/MS Off-
Flavor Analyzer.
Furthermore, although compositional analysis of perfumes such
as aroma oils is sometimes difficult due to the nature-derived
contaminants, the use of MRM analysis provided highly reliable
identifications of components. It resulted in more accurate
evaluation of the fragrances even with complex components.
We next analyzed Jasmine sample intentionally contaminated
with a small amount of mineral oil, imitating a nature-derived
sample with contaminants. Fig. 7 shows the chromatograms. In
the SIM analysis, the presence of mineral oil affected the ion
peak of α-terpineol. MRM analysis, however, enabled correct
identification even in the sample spiked with mineral oil.
(min)
13.2
13.4
13.6
13.8
0.0
%
100.0
43.00
59.00
136.00
intensi
ty
43.00
59.00
136.00
(min)
13.2
13.4
13.6
13.8
0.0
%
100.0
intensi
ty
136.00>93.00
121.00>93.00
136.00>121.00
(min)
13.2
13.4
13.6
13.8
0.0
%
100.0
intensi
ty
Sample blank
Spiked with
mineral oil
Spiked with
mineral oil
SIM
MRM
Fig. 8 GCMS-TQ™8040 NX + AOC™-20i+s
