Emerging Techniques: GCMS Food Safety and Food Quality Applications

In a recent overview, Yolanda Picó highlighted the role of mass spectrometry (MS) for the food industry. As with her section on section on LCMS, the author created a comprehensive table comprising the most notable food safety and quality applications of gas chromatography-mass spectrometry (GC-MS). She also reviewed the technology with a focus on food safety and food quality analyses.¹

According to Picó, GC offers faster, more efficient separation when compared with LC. Unfortunately, GC requires volatile, semivolatile, or thermally stable analytes- or labor-intensive chemical derivatization techniques for separation. Picó indicates that GC’s major strength is its high resolution separation and notes its broad usage by the food industry for analyzing target compounds, metabolomics (targeted and untargeted), and volatile compound profiling.

Researchers generally rely on GC-MS for food safety and quality issues that require robust separation power- 1) single compounds or small groups that need to be separated from matrix compounds and 2) analysis of complex mixtures. Examples of single compound applications of GC-MS include monitoring for the formation of ethyl carbamate in foods and beverages that require fermentation and detecting unwanted and/or toxic compounds like furan, acrylamide, and BPA (bisphenol A) in food products. The major complex mixture application is the detection and quantification of pollutants in foods, including residues of various pesticides which comprise the most common GC-mediated food safety issue. The others include polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), polybrominated compounds, phthalates, chloropropanols, and mono aromatic hydrocarbons like benzene, toluene, ethylbenzene, and xylene.

Picó indicates that the current focus for GC innovation is two-fold- mass analyzers and separation techniques. She notes that the quadrupole mass spectrometer is the most widely used with other technology (3diT, QqQ, TOF, Orbitrap) available when research goals require specific features. She highlights the use of tandem MS (MS/MS) for the detection of unwanted compounds such as brominated flame retardants, PCBs, BPA, ethyl carbamate, chloropropanols, acrylamide, and pesticides. She notes several benefits specific to GC-TOF-MS: high peak capacity, enhanced retention time repeatability, and easily accessed compound libraries (eliminating the need for standards). When it comes to analysis times, which can be long with GC techniques, researchers can select smaller diameter columns for more efficient separation.

Two-dimensional GC (GC x GC) uses two serially connected columns for sequential analysis. Picó’s examples of this include:

An oil-absorbing matrix solid-phase dispersion extraction with comprehensive GC x GC-TOF-MS screening 68 pesticide residues in nut and seed matrices.²
GC x GC-qMS for comparative analysis of the volatile fraction of roasted hazelnuts.³

Combining GC with less conventional techniques like:

Inductively coupled plasma (ICP) MS for the quantification of ultra-trace levels of organometallic compounds. One team applied this technique to simultaneously screen a variety of food items for parts-per-billion levels of monomethylmercury and monoethylmercury.⁴
GC combustion isotope ratio MS for sourcing food, including determining the geographic origin of food adulterants.⁵

When it comes to metabolomics studies, GC-MS boasts high equipment stability and user-friendly data analysis tools, rendering it a frequent choice for screening low molecular weight metabolites, particularly when coupled with TOF or q-MS for untargeted analysis of hydrophilic metabolites.

GC-TOF-MS to identify 48 total metabolites (43 primary metabolites and five phenolic acids) in three varieties of millet.⁶

GC-TOF-MS coupled with quantitative descriptive analysis (QDA) from sensory panelists to evaluate the relationships between ingredients, brewing processes, and sensory attributes of soy sauce.⁷
GC-QqQ-MS using SRM to analyze trimethylsilyl derivatives of 110 metabolites, allowing researchers to use both untargeted and widely targeted metabolomics in the same sample preparation.⁸

Additionally, a novel pseudo-targeted method RTL-GC-MS/SIM may be particularly useful for screening differential components when profiling metabolites due to its higher sensitivity, enhanced linearity and data quality, and the fact it does not require peak alignment among varied samples.

When used to analyze tobacco samples from three planting regions, RTL-GC-MS/SIM detected 167 differential components compared with 151 and 131 from extracted ion current (EIC) and TIC, respectively.⁹

GC-Orbitrap is an emerging approach that couples GC with high-resolution/accurate-mass (HR/AM) Orbitrap mass spectrometry, demonstrating particular promise for compound identification, quantification, and discovery. It combines advanced quadrupole technology, high resolving power, and Extractabrite ion source for superior performance when compared with other technology.

GC-Orbitrap for food food product authentication and pesticide testing offers intuitive data searching as well as enhanced linearity, sensitivity, and selectivity.¹⁰
GC-Orbitrap harnessed to identify and quantify veterinary and pesticide residues as well as natural contaminants allows for easy data acquisition, higher resolving power than other instruments, and the benefits of full scan mode for retrospective analysis.¹¹

As stated, volatile compound profiling is a particular strength of GC-based analysis. Because volatile compounds contribute to food flavor and aroma, the detection of these compounds, including at trace levels, is of great interest to food researchers. Picó indicates that head space isolation combined with SPME (HS-SPME) and/or stir-bar sorptive extraction (HS-SBSE) is the most common option for addressing diverse volatile compounds. The author offers a few representative examples of this:

HS-SPME and GC x GC-TOF-MS to measure 29 analytes useful for the prediction of moisture damage in cocoa beans before molds become visible.¹²
SPME-GC-3DIT-MS for the detection of volatile compounds responsible for kiwifruit aroma differentially impacted by pervaporation process.¹³
HS-SPME and GC x GC-qMS to comprehensively profile roasted hazelnuts from nine geographical regions, allowing researchers to apply measurable parameters to questions of sensory properties and food product origin.³
SBSE with GC-MS to identify 76 volatile compounds in 14 Chinese liquors containing soy sauce aromatics. This enabled the team to compare volatile profiles and differentiate between liquor samples to determine that extended storage time impacts prominent sauce aroma.¹⁴

In sum, the author represents GC-MS as a solid technique within food safety and food quality applications, particularly for metabolomics and analysis of volatiles. Additionally, emerging couplings like GC-Orbitrap may allow researchers to “fill the gap” between traditional -omics tools and complex food applications.

References

1 Picó, Y. (2015) ‘Mass Spectrometry in Food Quality and Safety: An Overview of the Current Status.’ Comprehensive Analytical Chemistry, Vol. 68, http://dx.doi.org/10.1016/B978-0-444-63340-8.00001-7

2 Wang, X. et al. (2012) ‘Screening for pesticide residues in oil seeds using solid-phase dispersion extraction and comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry.’ Journal of Separation Science 35 (13): 1634–1643.

3 Cordero, C. et al. (2010) ‘Profiling food volatiles by comprehensive two-dimensional gas chromatography coupled with mass spectrometry: advanced fingerprinting approaches for comparative analysis of the volatile fraction of roasted hazelnuts (Corylus avellana L.) from different origins.’ Journal of Chromatography A 1217 (37): 5848–5858.

4 Batista, B.L. et al. (2011) ‘Mercury speciation in seafood samples by LC–ICP-MS with a rapid ultrasound-assisted extraction procedure: application to the determination of mercury in Brazilian seafood samples.’ Food Chemistry 126 (4): 2000–2004.

5 Zhang, Y. et al. (2012) ‘Calibration and data processing in gas chromatography combustion isotope ratio mass spectrometry.’ Drug Testing and Analysis 4 (12): 912–922.

6 Kim, J.K. et al. (2013) ‘Metabolic profiling of millet (Panicum miliaceum) using gas chromatography-time-of-flight mass spectrometry (GC-TOFMS) for quality assessment.’ Plant Omics 6 (1): 73–78.

7 Yamamoto, S. et al. (2012) ‘Metabolite profiling of soy sauce using gas chromatography with timeof-flight mass spectrometry and analysis of correlation with quantitative descriptive analysis.’ Journal of Bioscience and Bioengineering 114 (2): 170–175.

8 Tsugawa, H. et al. (2014) ‘Highly sensitive and selective analysis of widely targeted metabolomics using gas chromatography/triple-quadrupole mass spectrometry.’ Journal of Bioscience and Bioengineering 117 (1): 122–128.

9 Li, Y. et al. (2012) ‘A novel approach to transforming a non-targeted metabolic profiling method to a pseudo-targeted method using the retention time locking gas chromatography/mass spectrometry-selected ions monitoring.’ Journal of Chromatography A 1255: 228–236.

10 Hasjlova, J. Interview: Food Safety, Thermo Scientific. http://www.thermoscientific.com/en/product/q-exactive-gc-orbitrap-gc-ms-ms.html

11 Mol, H. Interview: Food Safety, Thermo Scientific. http://www.thermoscientific.com/en/product/q-exactive-gc-orbitrap-gc-ms-ms.html

12 Humston, E.M. et al. (2010) ‘Quantitative assessment of moisture damage for cacao bean quality using two-dimensional gas chromatography combined with time-of-flight mass spectrometry and chemometrics.’ Journal of Chromatography A 1217 (12): 1963–1970.

13 Figoli, A. et al. (2010) ‘Evaluation of pervaporation process of kiwifruit juice by SPME-GC/ion trap mass spectrometry.’ Desalination 250 (3): 1113–1117.

14 Fan, W. et al. (2011) ‘Quantification of volatile compounds in Chinese soy sauce aroma type liquor by stir bar sorptive extraction and gas chromatography-mass spectrometry.’ Journal of the Science of Fod and Agriculture 91 (7): 1187–1198.