PAH Analysis in Salmon with Enhanced Matrix Removal
Applications | | Agilent TechnologiesInstrumentation
Polycyclic aromatic hydrocarbons (PAHs) are persistent environmental pollutants with mutagenic and carcinogenic properties. Their ability to accumulate in aquatic species and to coextract with lipids during sample preparation challenges accurate quantitation. A robust and selective cleanup strategy is therefore essential for monitoring PAH levels in high‐fat food matrices like salmon.
The study aims to evaluate a streamlined sample preparation workflow using Agilent Bond Elut Enhanced Matrix Removal—Lipid (EMR‐Lipid) for the analysis of 15 PAHs in salmon. Key objectives include assessing accuracy, precision, and recovery across multiple spiking levels and comparing performance to conventional cleanup methods.
Samples of homogenized salmon (5 g) were spiked with PAH standards and isotopically labeled internal standards, then extracted with 10 mL acetonitrile. After centrifugation, the supernatant underwent dispersive solid phase extraction (dSPE) with EMR‐Lipid to selectively remove lipids. A subsequent salt polishing step with NaCl/MgSO4 induced phase separation. The cleaned extract was directly analyzed by gas chromatography–mass spectrometry (GC–MS) in selected ion monitoring (SIM) mode, using matrix‐matched calibration curves (1–1000 ng/g) and internal standard correction for quantitation.
Baseline separation of all 15 PAHs was achieved, enabling clear resolution of key isomeric pairs. Accuracy ranged from 84 % to 115 % and precision (RSD) from 0.5 % to 4.4 % across spiking levels of 25, 100, and 500 ng/g. Absolute recoveries without internal standards varied from 62 % to 98 %, decreasing slightly for higher‐molecular‐weight PAHs, but were effectively corrected using isotopically labeled surrogates. The optimized workflow, omitting extra water addition, maintained sufficient lipid removal and PAH solubility, simplifying the protocol compared to traditional approaches.
The EMR‐Lipid dSPE approach offers a rapid, robust, and reproducible method for quantifying trace PAHs in fatty food matrices. By minimizing coextracted lipids and leveraging isotopic internal standards, this workflow achieves excellent accuracy and precision, facilitating routine analysis in food safety and environmental research.
GC/MSD, Sample Preparation, GC/SQ, Consumables
IndustriesFood & Agriculture
ManufacturerAgilent Technologies
Summary
Importance of the Topic
Polycyclic aromatic hydrocarbons (PAHs) are persistent environmental pollutants with mutagenic and carcinogenic properties. Their ability to accumulate in aquatic species and to coextract with lipids during sample preparation challenges accurate quantitation. A robust and selective cleanup strategy is therefore essential for monitoring PAH levels in high‐fat food matrices like salmon.
Objectives and Study Overview
The study aims to evaluate a streamlined sample preparation workflow using Agilent Bond Elut Enhanced Matrix Removal—Lipid (EMR‐Lipid) for the analysis of 15 PAHs in salmon. Key objectives include assessing accuracy, precision, and recovery across multiple spiking levels and comparing performance to conventional cleanup methods.
Methodology
Samples of homogenized salmon (5 g) were spiked with PAH standards and isotopically labeled internal standards, then extracted with 10 mL acetonitrile. After centrifugation, the supernatant underwent dispersive solid phase extraction (dSPE) with EMR‐Lipid to selectively remove lipids. A subsequent salt polishing step with NaCl/MgSO4 induced phase separation. The cleaned extract was directly analyzed by gas chromatography–mass spectrometry (GC–MS) in selected ion monitoring (SIM) mode, using matrix‐matched calibration curves (1–1000 ng/g) and internal standard correction for quantitation.
Instrumentation Used
- Gas chromatograph: Agilent 7890B with multimode inlet (MMI), splitless injection at 320 °C
- Mass spectrometer: Agilent 5977 MSD in SIM mode with a transfer line at 340 °C
- Autosampler: Agilent 7693 with 10 µL syringe
- Column: Agilent J&W DB‐5ms UI, 20 m × 0.18 mm × 0.18 µm, with capillary backflush
- Consumables: Bond Elut EMR‐Lipid sorbent, Bond Elut Final Polish salts, vials, ferrules, pipettes
Main Results and Discussion
Baseline separation of all 15 PAHs was achieved, enabling clear resolution of key isomeric pairs. Accuracy ranged from 84 % to 115 % and precision (RSD) from 0.5 % to 4.4 % across spiking levels of 25, 100, and 500 ng/g. Absolute recoveries without internal standards varied from 62 % to 98 %, decreasing slightly for higher‐molecular‐weight PAHs, but were effectively corrected using isotopically labeled surrogates. The optimized workflow, omitting extra water addition, maintained sufficient lipid removal and PAH solubility, simplifying the protocol compared to traditional approaches.
Benefits and Practical Applications
- Efficient lipid cleanup improves instrument performance and reduces matrix interferences.
- Comparable ease to QuEChERS workflows with enhanced selectivity for lipids.
- High accuracy and precision support reliable monitoring of PAH contamination in seafood.
- Scalable and adaptable for routine quality control in food testing laboratories.
Future Trends and Potential Applications
- Extension of EMR‐Lipid cleanup to other high‐fat matrices and complex environmental samples.
- Integration with automated or online SPE systems for higher throughput.
- Adaptation of the protocol for liquid chromatography–mass spectrometry to expand analyte scope.
- Development of multi‐residue methods combining PAHs with other organic contaminants.
Conclusion
The EMR‐Lipid dSPE approach offers a rapid, robust, and reproducible method for quantifying trace PAHs in fatty food matrices. By minimizing coextracted lipids and leveraging isotopic internal standards, this workflow achieves excellent accuracy and precision, facilitating routine analysis in food safety and environmental research.
References
- EPA Compendium Method T0‐13A, US EPA, Cincinnati, OH, 1999.
- Guo Y., Wu K., Xu X., J. Environ. Health 2011, 73, 22–25.
- Beyer J. et al., Environ. Toxicol. Pharmacol. 2010, 30, 224–244.
- Essumang D.K. et al., J. Food Compos. Anal. 2012, 27, 128–138.
- Takigami H. et al., Chemosphere 2009, 76, 270–277.
- Ali N. et al., Chemosphere 2012, 88, 1276–1282.
- Stapleton H.M. et al., Anal. Bioanal. Chem. 2007, 387, 2365–2379.
- Sverko E. et al., Environ. Sci. Technol. 2008, 42, 361–366.
- Saito K. et al., Chemosphere 2004, 57, 373–381.
- Anastassiades M. et al., J. AOAC Int. 2003, 86, 412–431.
- Lehotay S.J. et al., J. AOAC Int. 2005, 88, 615–629.
- Forsberg N.D. et al., J. Agric. Food Chem. 2011, 59, 8108–8116.
- Smith D., Lynam K., Agilent Application Note 5990-6668EN, 2012.
- Sapozhnikova Y., Lehotay S.J., Anal. Chim. Acta 2013, 758, 80–92.
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