GC-QMS Application: Differential analysis of coffee aroma compounds using HS GC-QMS and msFineAnalysis iQ

  • Summary

MSTips No. 363

Overview

The msFineAnalysis iQ is an automated qualitative analysis software for gas chromatograph quadrupole mass spectrometer JMS-Q1500GC / JMS-Q1600GC that performs integrated analysis combining library database (DB) search results using EI (Electron Ionization) mass spectra and molecular weight information using soft ionization methods. In addition, the software provides automatic peak detection by deconvolution, differential analysis of two samples, and qualitative analysis by retention index (RI). Using this software, a more accurate qualitative analysis can be achieved in a shorter time.
Coffee aroma contains a very large number of components. Therefore, a large number of peaks are observed in TIC chromatogram, and it takes a long time to identify the components of each peak and to analyze differences between samples. In this report, we present the results of differential and integrated analyses performed on coffee aroma components using msFineAnalysis iQ.

Methods

A headspace sampler MS-62071STRAP and a GC-QMS JMS-Q1600GC UltraQuad™ SQ-Zeta were used for the measurements. Data were acquired using the EI method and the low ionization energy EI method as a soft ionization (SI) method for the components collected using the trap mode. Samples were 2 mL of coffee extracted from commercially available instant drip-type packets (A: fresh coffee immediately after opening, B: oxidized coffee for 5 days after opening) and measured by the EI (n = 5) and SI (n = 1) methods for components extracted into the headspace by heating. Comparison of two samples (differential analysis between A and B) was attempted using the measurement data obtained under the measurement conditions shown in Table 1. Please refer to MSTips No.348 for the function of differential analysis.

JMS-Q1600GC UltraQuad™ SQ-Zeta w/ MS-62071STRAP

Table 1 Measurement Condition

GC HS MS
Column InerCap WAX
(GL Sciences Inc.)
60 m × 0.32 mm id, 0.5 μm 
film thickness
Sample temp. 60°C Interface temp. 250°C
Oven temp. 40°C (3 min) → 10°C / min
→ 250°C (10 min)
Heating time 15 min Ion source temp. 250°C
Carrier gas 1.5 mL / min
(Constant Flow)
Sampling mode Trap Acquisition mode Scan (m/z 29-400)
Injection temp. 250°C Number of sampling 3 Ionization EI (70 eV, 50 μA)
SI (15 eV, 30 μA)
Injection mode Split 30:1 Trap tube AQUATRAP1
(GL Sciences Inc.)

Results

Figure 1 shows the results of the differential analysis (volcano plots). The difference in the number of components and the detected amount (peak area value) between Sample A and Sample B was visualized and easily confirmed. The characteristic components of Sample A were 64 peaks (A Only 49 peaks, A > B 15 peaks), the common components of Sample A and Sample B were 23 peaks (A = B), and the characteristic components of Sample B were 4 peaks.
Next, the results of the integrated analysis of the characteristic components and the mass spectra (ID: 010, 042, 075) are shown as an example.

Figure 1

Figure 1 Volcano plot of variance component analysis result between fresh coffee (A) and oxidized coffee (B)

Table 2 shows the names of compounds with a similarity of 900 or more that were estimated as characteristic aroma components of Sample A by the integrated analysis. Estimated compounds were aldehydes, furans, esters, ketones, pyrroles, and pyridines. As an example, Figure 2 shows the mass spectra of "Furan, 2-methyl-" (ID: 010), "Pyridine" (ID: 042), and "2-Furanmethanol, acetate" (ID: 075) acquired by the EI and SI (low ionization energy EI) methods. Integrated qualitative analysis was able to complement the search results not only by the molecular ions in the SI method, but also by ΔRI (tolerance = |50|).

Table 2 Integrated qualitative analysis result of characteristic aroma components in fresh coffee (A)

Table 2
Figure 2

Figure 2 An example of the mass spectra detected from fresh coffee (A)

Table 3 shows the names of all compounds estimated as characteristic aroma components of Sample B by the integrated qualitative analysis. The components detected in Sample A decreased and disappeared, while ethanol was detected as a characteristic component of Sample B.

Table 3 Integrated qualitative analysis result of characteristic aroma components in oxidized coffee (B)

Figure 2

Table 4 shows the names of compounds with a similarity of 850 or more that were estimated as common components of Sample A and Sample B by the integrated qualitative analysis. Acetic acid, 2-Furanmethanol, and pyrazines were estimated as characteristic compounds.

Table 4 Integrated qualitative analysis result of characteristic aroma components in both coffee of A and B

Table 4

Summary

In this report, we presented the results of integrated qualitative analysis and differential analysis using msFineAnalysis iQ for coffee aroma components acquired by HS GC-QMS. It has been shown that this method can be used to quickly identify multiple components with different contents. Integrated qualitative analysis with msFineAnalysis iQ will improve the accuracy of qualitative analysis, reduce work time and increase work efficiency.

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