Determination of Multiclass, Multiresidue Pesticides in Spring Leaf Mix
Applications | 2022 | Agilent TechnologiesInstrumentation
The monitoring of multiple pesticide residues across diverse chemical classes in fresh leafy produce is critical for food safety, regulatory compliance, and consumer health protection.
Plant-based matrices, especially those high in chlorophyll, pose analytical challenges due to co-extraction of pigments that cause ion suppression, instrument fouling, and reduced sensitivity.
Efficient cleanup strategies that balance pigment removal with recovery of sensitive analytes are essential to ensure accurate, reproducible, and high-throughput analysis in routine food and beverage testing.
This application note describes the development, validation, and comparative evaluation of two rapid passthrough cleanup methods using Agilent Captiva EMR–HCF cartridges following QuEChERS extraction.
The goals were to quantify 138 multiclass pesticides in a high-chlorophyll spring leaf mix by LC–MS/MS, assess cleanup efficiency, analyte recovery, precision, matrix effects, and calibration linearity.
Apollo methods using enhanced matrix removal (EMR) with NH₂ (EMR–HCF1) or PSA (EMR–HCF2) sorbents were benchmarked against traditional dispersive SPE with graphitized carbon black (GCB) and a polymer-based competition dSPE kit.
Extraction and Cleanup Workflow:
Instrumentation:
Pigment Removal:
Recovery, Precision, Matrix Effects:
EMR–HCF passthrough cleanup streamlines workflow by eliminating multiple centrifugation and vortexing steps of dSPE, reducing preparation time by 30–40% for ~30 samples.
The selective Carbon S sorbent formulation prevents loss of planar and labile compounds while effectively removing pigments, acids, lipids, and other matrix components.
These methods can be adopted easily in routine QA/QC, research laboratories, and high-throughput contract testing for leafy vegetables and other high-chlorophyll matrices.
The EMR concept can expand to other challenging matrices (berries, peppers, dry spices) by customizing sorbent blends (PSA, C18, lipid removal) to target interferences.
Integration with automated platforms and online SPE-LC/MS workflows will further increase throughput and reproducibility.
Advances in high-resolution MS and data-independent acquisition may benefit from cleaner extracts, enabling non-targeted screening alongside quantitative residue analysis.
Agilent Captiva EMR–HCF1 and EMR–HCF2 passthrough cleanup methods offer robust, efficient, and user-friendly solutions for multiclass pesticide residue analysis in high-chlorophyll leafy matrices.
They deliver superior pigment removal, enhanced recovery of sensitive analytes, low matrix effects, and strong calibration performance compared to traditional GCB and polymer dSPE kits.
1. González-Curbelo, M. Á.; Montes-Bartolomé, R.; Prats-Montalbán, J. M.; et al. Trends Anal. Chem. 2015, 71, 169–185.
2. Varela-Martínez, D. A.; Fernández-Méndez, C.; et al. In Liquid-Phase Extraction Handbooks in Separation Science; 2020; Ch. 14, pp. 399–437.
3. Zou, A.; Zhao, L.; et al. Agilent Application Note 5994-2370EN, 2020.
4. Lucas, D.; Zhao, L. Agilent Application Note 5991-8694EN, 2017.
5. Zhao, L.; et al. J. Chromatogr. A 2018, 1549, 14–24.
Sample Preparation, Consumables, LC/MS, LC/MS/MS, LC/QQQ
IndustriesFood & Agriculture
ManufacturerAgilent Technologies
Summary
Importance of the Topic
The monitoring of multiple pesticide residues across diverse chemical classes in fresh leafy produce is critical for food safety, regulatory compliance, and consumer health protection.
Plant-based matrices, especially those high in chlorophyll, pose analytical challenges due to co-extraction of pigments that cause ion suppression, instrument fouling, and reduced sensitivity.
Efficient cleanup strategies that balance pigment removal with recovery of sensitive analytes are essential to ensure accurate, reproducible, and high-throughput analysis in routine food and beverage testing.
Study Objectives and Overview
This application note describes the development, validation, and comparative evaluation of two rapid passthrough cleanup methods using Agilent Captiva EMR–HCF cartridges following QuEChERS extraction.
The goals were to quantify 138 multiclass pesticides in a high-chlorophyll spring leaf mix by LC–MS/MS, assess cleanup efficiency, analyte recovery, precision, matrix effects, and calibration linearity.
Apollo methods using enhanced matrix removal (EMR) with NH₂ (EMR–HCF1) or PSA (EMR–HCF2) sorbents were benchmarked against traditional dispersive SPE with graphitized carbon black (GCB) and a polymer-based competition dSPE kit.
Methodology and Instrumentation
Extraction and Cleanup Workflow:
- Sample: 15 g homogenized spring leaf mix (lettuce, spinach, romaine, chard, arugula, endive).
- Extraction: Agilent Bond Elut QuEChERS AOAC kit with acetonitrile/1% acetic acid, salts packet.
- Cleanup: Passthrough using 3 mL Captiva EMR–HCF1 (Carbon S/NH₂) or EMR–HCF2 (Carbon S/PSA) cartridges.
- Dilution: Fivefold with water to produce 20:80 ACN/water prior to injection.
Instrumentation:
- LC: Agilent 1290 Infinity binary pump, autosampler, column compartment.
- Column: ZORBAX Eclipse Plus C18, 2.1 × 100 mm, 1.8 µm, with UHPLC guard.
- MS/MS: Agilent 6490 Triple Quadrupole with Jet Stream iFunnel electrospray.
- Acquisition: Dynamic MRM in positive/negative modes; 2 µL injection; 0.3 mL/min gradient of ammonium formate/fluoride buffers.
Main Results and Discussion
Pigment Removal:
- EMR–HCF1 and EMR–HCF2 removed >97% of chlorophyll and other pigments (LC-UV at 450 nm), yielding pale yellow extracts.
- GCB dSPE achieved ~95% removal; competition dSPE left noticeable green color and <60% pigment clearance.
Recovery, Precision, Matrix Effects:
- EMR–HCF1 and EMR–HCF2 passed recovery (70–120%) and precision (RSD ≤20%) criteria for >95% of 138 targets at 10 ng/g and 100 ng/g levels.
- Sensitive planar, acidic, and basic pesticides (e.g., thiabendazole, 2,4-D, MCPA) showed significantly improved recoveries compared to GCB dSPE, which lost many labile analytes.
- Matrix effects for EMR–HCF cleanup were largely within 80–120%, outperforming GCB and competition dSPE options.
- Calibration curves (0.5–500 ng/g) exhibited R² > 0.99 for nearly all compounds; limits of quantitation ranged 0.5–10 ng/g depending on analyte sensitivity.
Contributions and Practical Applications
EMR–HCF passthrough cleanup streamlines workflow by eliminating multiple centrifugation and vortexing steps of dSPE, reducing preparation time by 30–40% for ~30 samples.
The selective Carbon S sorbent formulation prevents loss of planar and labile compounds while effectively removing pigments, acids, lipids, and other matrix components.
These methods can be adopted easily in routine QA/QC, research laboratories, and high-throughput contract testing for leafy vegetables and other high-chlorophyll matrices.
Future Trends and Opportunities
The EMR concept can expand to other challenging matrices (berries, peppers, dry spices) by customizing sorbent blends (PSA, C18, lipid removal) to target interferences.
Integration with automated platforms and online SPE-LC/MS workflows will further increase throughput and reproducibility.
Advances in high-resolution MS and data-independent acquisition may benefit from cleaner extracts, enabling non-targeted screening alongside quantitative residue analysis.
Conclusion
Agilent Captiva EMR–HCF1 and EMR–HCF2 passthrough cleanup methods offer robust, efficient, and user-friendly solutions for multiclass pesticide residue analysis in high-chlorophyll leafy matrices.
They deliver superior pigment removal, enhanced recovery of sensitive analytes, low matrix effects, and strong calibration performance compared to traditional GCB and polymer dSPE kits.
Instrumental Setup
- LC System: Agilent 1290 Infinity binary pump, autosampler, column compartment.
- Column: ZORBAX Eclipse Plus C18, 2.1×100 mm, 1.8 µm.
- MS/MS: Agilent 6490 Triple Quadrupole with Jet Stream iFunnel; electrospray ionization; dynamic MRM in positive/negative modes.
References
1. González-Curbelo, M. Á.; Montes-Bartolomé, R.; Prats-Montalbán, J. M.; et al. Trends Anal. Chem. 2015, 71, 169–185.
2. Varela-Martínez, D. A.; Fernández-Méndez, C.; et al. In Liquid-Phase Extraction Handbooks in Separation Science; 2020; Ch. 14, pp. 399–437.
3. Zou, A.; Zhao, L.; et al. Agilent Application Note 5994-2370EN, 2020.
4. Lucas, D.; Zhao, L. Agilent Application Note 5991-8694EN, 2017.
5. Zhao, L.; et al. J. Chromatogr. A 2018, 1549, 14–24.
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