SPE-HPLC-DAD Dosage of Seven Neonicotinoids in Green Coffee
Abstract
:1. Introduction
2. Results
2.1. Extraction and Cleanup Procedure
2.2. Selectivity and Carryover Evaluation
2.3. Linearity
2.4. Matrix Effect
2.5. Trueness
2.6. Precision
2.7. Limits of Detection (LOD) and Quantification (LOQ)
2.8. Accuracy
2.9. Uncertainty
3. Discussion
4. Materials and Methods
4.1. Solvents and Reagents
4.2. Analytical Standards
4.3. Samples
4.4. Sample Extraction and Cleanup with Strata-X PRO Cartridge
4.5. HPLC (High-Performance Liquid Chromatography) Parameters
4.6. Method Validation
4.6.1. Experimental Designs
4.6.2. Calibration Standards
4.6.3. Validation Standards
4.7. Statistical Analysis
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Samoggia, A.; Fantini, A. Revealing the Governance Dynamics of the Coffee Chain in Colombia: A State-of-the-Art Review. Sustainability 2023, 15, 13646. [Google Scholar] [CrossRef]
- Hall, R.D.; Trevisan, F.; De Vos, C.H. Coffee berry and green bean chemistry—Opportunities for improving cup quality and crop circularity. Food Res. Int. 2022, 151, 110825. [Google Scholar] [CrossRef] [PubMed]
- Gorji, Z.; Varkaneh, H.K.; Talaei, S.; Nazary-Vannani, A.; Clark, C.C.; Fatahi, S.; Rahmani, J.; Salamat, S.; Zhang, Y. The effect of green-coffee extract supplementation on obesity: A systematic review and dose-response meta-analysis of randomized controlled trials. Phytomedicine 2019, 63, 153018. [Google Scholar] [CrossRef]
- Wawrzyniak, N.; Skrypnik, K.; Suliburska, J. Dietary supplements in therapy to support weight reduction in obese patients. Acta Sci. Pol. Technol. Aliment. 2022, 21, 67–80. [Google Scholar] [CrossRef] [PubMed]
- Kanchanasurakit, S.; Saokaew, S.; Phisalprapa, P.; Duangjai, A. Chlorogenic acid in green bean coffee on body weight: A systematic review and meta-analysis of randomized controlled trials. Syst. Rev. 2023, 12, 163. [Google Scholar] [CrossRef] [PubMed]
- de Queiroz, V.T.; Azevedo, M.M.; da Silva Quadros, I.P.; Costa, A.V.; do Amaral, A.A.; dos Santos, G.M.A.D.A.; Juvanhol, R.S.; de Almeida Telles, L.A.; dos Santos, A.R. Environmental risk assessment for sustainable pesticide use in coffee production. J. Contam. Hydrol. 2018, 219, 18–27. [Google Scholar] [CrossRef]
- Harelimana, A.; Rukazambuga, D.; Hance, T. Pests and diseases regulation in coffee agroecosystems by management systems and resistance in changing climate conditions: A review. J. Plant Dis. Prot. 2022, 129, 1041–1052. [Google Scholar] [CrossRef]
- Dantas, J.; Motta, I.O.; Vidal, L.A.; Nascimento, E.F.M.B.; Bilio, J.; Pupe, J.M.; Veiga, A.; Carvalho, C.; Lopes, R.B.; Rocha, T.L.; et al. A Comprehensive Review of the Coffee Leaf Miner Leucoptera coffeella (Lepidoptera: Lyonetiidae)—A Major Pest for the Coffee Crop in Brazil and Others Neotropical Countries. Insects 2021, 12, 1130. [Google Scholar] [CrossRef]
- Miranda, R.A.; Silva, B.S.; de Moura, E.G.; Lisboa, P.C. Pesticides as endocrine disruptors: Programming for obesity and diabetes. Endocrine 2023, 79, 437–447. [Google Scholar] [CrossRef]
- Seccia, S.; Fattore, M.; Grumetto, L.; Albrizio, S. Bisphenols and alkylphenols in food: From farm to table. Curr. Anal. Chem. 2018, 14, 325–343. [Google Scholar] [CrossRef]
- Han, W.; Tian, Y.; Shen, X. Human exposure to neonicotinoid insecticides and the evaluation of their potential toxicity: An overview. Chemosphere 2018, 192, 59–65. [Google Scholar] [CrossRef] [PubMed]
- EU Pesticides Database. Available online: https://food.ec.europa.eu/plants/pesticides/eu-pesticides-database_en (accessed on 18 July 2023).
- Pizzutti, I.R.; de Kok, A.; Dickow Cardoso, C.; Reichert, B.; de Kroon, M.; Wind, W.; Weber Righi, L.; Caiel da Silva, R. A multi-residue method for pesticides analysis in green coffee beans using gas chromatography-negative chemical ionization mass spectrometry in selective ion monitoring mode. J. Chromatogr. A 2012, 1251, 16–26. [Google Scholar] [CrossRef] [PubMed]
- Harmoko, H.; Kartasasmita, R.E.; Tresnawati, A. QuEChERS method for the determination of pesticide residues in indonesian green coffee beans using liquid chromatography tandem mass spectrometry. J. Math. Fund. Sci. 2015, 47, 296. [Google Scholar] [CrossRef]
- Bresin, B.; Piol, M.; Fabbro, D.; Mancini, M.A.; Casetta, B.; Del Bianco, C. Analysis of organo-chlorine pesticides residue in raw coffee with a modified “quick easy cheap effective rugged and safe” extraction/clean up procedure for reducing the impact of caffeine on the gas chromatography-mass spectrometry measurement. J. Chromatogr. A 2015, 1376, 167–171. [Google Scholar] [CrossRef]
- De Oliveira, L.A.B.; Pacheco, H.P.; Scherer, R. Flutriafol and Pyraclostrobin Residues in Brazilian Green Coffees. Food Chem. 2016, 190, 60–63. [Google Scholar] [CrossRef]
- Nardin, T.; Barnaba, C.; Abballe, F.; Trenti, G.; Malacarne, M.; Larcher, R. Fast analysis of quaternary ammonium pesticides in food and beverages using cation-exchange chromatography coupled with isotope-dilution high-resolution mass spectrometry. J. Sep. Sci. 2017, 40, 3928–3937. [Google Scholar] [CrossRef]
- Reichert, B.; de Kok, A.; Pizzutti, I.R.; Scholten, J.; Cardoso, C.D.; Spanjer, M. Simultaneous determination of 117 pesticides and 30 mycotoxins in raw coffee, without cleanup, by LC-ESI-MS/MS analysis. Anal. Chim. Acta 2018, 1004, 40–50. [Google Scholar] [CrossRef]
- Asadi, M.; Sereshti, H. Magnetic amino-functionalized hollow silica-titania microsphere as an efficient sorbent for extraction of pesticides in green and roasted coffee beans. J. Sep. Sci. 2020, 43, 2115–2124. [Google Scholar] [CrossRef]
- Gamal, A.; Soliman, M.; Al-Anany, M.S.; Eissa, F. Optimization and Validation of High Throughput Methods for the Determination of 132 Organic Contaminants in Green and Roasted Coffee Using GC-QqQ-MS/MS and LC-QqQ-MS/MS. Food Chem. 2024, 449, 139223. [Google Scholar] [CrossRef]
- Paiva, A.C.P.; de Assis, E.C.; d’Antonino, L.; de Queiroz, M.E.L.R.; da Silva, A.A. Alternative Method for Glyphosate Determination in Unroasted Green Coffee Beans by Liquid Chromatography Tandem Mass Spectrometry (LC-MS/MS). J. Agric. Food Chem. 2024, 72, 26098. [Google Scholar] [CrossRef]
- Wang, D.; Wu, X.; Mao, J.; Wang, Z.; Xie, Y.; Wu, X. A modified QuEChERS method for the generic and rapid determination of pesticides and mycotoxins in raw coffee beans by liquid chromatography. J. Food Compost. Anal. 2025, 137, 106928. [Google Scholar] [CrossRef]
- Petrarca, M.H.; Godoy, H.T. Gas chromatography–mass spectrometry determination of polycyclic aromatic hydrocarbons in baby food using QuEChERS combined with low-density solvent dispersive liquid–liquid microextraction. Food Chem. 2018, 257, 44–52. [Google Scholar] [CrossRef] [PubMed]
- Kamal El-Deen, A.; Shimizu, K. Modified μ-QuEChERS coupled to diethyl carbonate-based liquid microextraction for PAHs determination in coffee, tea, and water prior to GC–MS analysis: An insight to reducing the impact of caffeine on the GC–MS measurement. J. Chromatogr. B Anal. Technol. Biomed. Life Sci. 2021, 1171, 122555. [Google Scholar] [CrossRef]
- Wang, X.; Lim, L.T.; Fu, Y. Review of analytical methods to detect adulteration in coffee. J. AOAC Int. 2020, 103, 295–305. [Google Scholar] [CrossRef] [PubMed]
- Dai, Z.; Liang, S.; Zhang, C.; Sun, H.; Zhou, L.; Luo, F.; Chen, Z. Detection of 13 pyrethroid pesticides in jasmine (Jasminum sp.) by modified QuEChERS method and gas chromatography-tandem mass spectrometry. J. Food Comp. Anal. 2024, 135, 106592. [Google Scholar] [CrossRef]
- Harmoko, H.; Munawar, H.; Bahri, S.; Andarwulan, N.; Tjahjono, D.H.; Kartasasmita, R.E.; Fernández-Alba, A.R. Application of the QuEChERS method combined with UHPLC-QqQ-MS/MS for the determination of isoprocarb and carbaryl pesticides in Indonesian coffee. Anal. Methods 2024, 16, 4093. [Google Scholar] [CrossRef] [PubMed]
- Schiano, M.E.; Sodano, F.; Cassiano, C.; Magli, E.; Seccia, S.; Rimoli, M.G.; Albrizio, S. Monitoring of seven pesticide residues by LC-MS/MS in extra virgin olive oil samples and risk assessment for consumers. Food Chem. 2024, 442, 138498. [Google Scholar] [CrossRef]
- Feinberg, M. Validation of analytical methods based on accuracy profiles. J. Chromatogr. A 2007, 1158, 174. [Google Scholar] [CrossRef]
- Hubert, P.; Nguyen-Huu, J.J.; Boulanger, B.; Chapuzet, E.; Cohen, N.; Compagnon, P.A.; Dewé, W.; Feinberg, M.; Laurentie, M.; Mercier, N. Harmonization of strategies for the validation of quantitative analytical procedures: A SFSTP proposal: Part IV. Examples of application. J. Pharm. Biomed. Anal. 2008, 48, 760. [Google Scholar] [CrossRef]
- Feinberg, M.; Boulanger, B.; Dew’e, W.; Hubert, P. New advances in method validation and measurement uncertainty aimed at improving the quality of chemical data. Anal. Bioanal. Chem. 2004, 380, 502. [Google Scholar] [CrossRef]
- Esters, V.; Angenot, L.; Brandt, V.; Frederich, M.; Tits, M.; Van Neruma, C.; Wauters, J.N.; Hubert, P. Validation of a high-performance thin-layer chromatography/densitometry method for the quantitative determination of glucosamine in a herbal dietary supplement. J. Chromatogr. A 2006, 156, 1112. [Google Scholar] [CrossRef] [PubMed]
- Liao, Y.; Berthion, J.M.; Colet, I.; Merlo, M.; Nougadère, A.; Hu, R. Validation and application of analytical method for glyphosate and glufosinate in foods by liquid chromatography-tandem mass spectrometry. J. Chromatogr. A 2018, 1549, 31–38. [Google Scholar] [CrossRef]
- Ouakhssase, A.; Fatini, N.; Ait Addi, E. Chemometric Approach Based on Accuracy Profile and Data Chronological Distribution as a Tool to Detect Performance Degradation and Improve the Analytical Quality Control for Aflatoxins’ Analysis in Almonds Using UPLC–MS/MS. ACS Omega 2021, 6, 12746–12754. [Google Scholar] [CrossRef]
- Sayon, D.R.S.; Fakih, A.; Mercier, F.; Kondjoyan, N.; Meurillon, M.; Ratel, J.; Engel, E. Targeted quantification and untargeted exploration of furan and derivatives in infant food by headspace extraction-gas chromatography-Q Exactive Orbitrap mass spectrometry. Food Res. Inter. 2024, 191, 114614. [Google Scholar] [CrossRef] [PubMed]
- Seccia, S.; Albrizio, S.; Morelli, E.; Dini, I. Development and Validation of a High-Performance Liquid Chromatography Diode Array Detector Method to Measure Seven Neonicotinoids in Wheat. Foods 2024, 13, 2235. [Google Scholar] [CrossRef]
- ISO. ISO/IEC 17025—Testing and Calibration Laboratories. Available online: https://www.iso.org/ISO-IEC-17025-testing-and-calibration-laboratories.html (accessed on 6 November 2020).
- Montesano, D.; Gennari, O.; Festa, C.; Zollo, F.; Seccia, S.; Albrizio, S. A simple HPLC-DAD method for the analysis of melamine in protein supplements: Validation using the accuracy profiles. J. Chem. 2013, 2013, 239342. [Google Scholar] [CrossRef]
- United States Pharmacopeia (USP). Stage 4 Harmonization General chapter Chromatography. Available online: https://www.usp.org/sites/default/files/usp/document/harmonization/gen-chapter/harmonization-november-2021-m99380.pdf (accessed on 1 December 2022).
- Schiano, M.E.; Sodano, F.; Cassiano, C.; Fiorino, F.; Seccia, S.; Rimoli, M.G.; Albrizio, S. Quantitative Determination of Bisphenol A and Its Congeners in Plant-Based Beverages by Liquid Chromatography Coupled to Tandem Mass Spectrometry. Foods 2022, 11, 3853. [Google Scholar] [CrossRef] [PubMed]
- Seccia, S.; Dini, I. Development and Validation of an HPLC-DAD Method to Determine Alkylphenols in Milk. Beverages 2025, 11, 59. [Google Scholar] [CrossRef]
- Mancusi, A.; Seccia, S.; Izzi, A.; Coppola, D.; Tessieri, M.; Santini, A.; Dini, I. Chemometric Validation of a High-Performance Liquid Chromatography Method to Detect Ochratoxin A in Green Coffee. Beverages 2025, 11, 32. [Google Scholar] [CrossRef]
- Schiano, M.E.; Sodano, F.; Magli, E.; Corvino, A.; Fiorino, F.; Rimoli, M.G.; Seccia, S.; Albrizio, S. Quantitative Determination of BPA, BPB, BPF and BPS Levels in Canned Legumes from Italian Market. Food Chem. 2023, 416, 135642. [Google Scholar] [CrossRef]
- Moez, E.; Noel, D.; Brice, S.; Benjamin, G.; Pascaline, A.; Didier, M. Aptamer assisted ultrafiltration cleanup with high performance liquid chromatography-fluorescence detector for the determination of OTA in green coffee. Food Chem. 2020, 310, 125851. [Google Scholar] [CrossRef] [PubMed]
- Da Silva Souza, N.R.; Navickiene, S. Multiresidue Determination of Carbamate, Organophosphate, Neonicotinoid, and Triazole Pesticides in Roasted Coffee Using Ultrasonic Solvent Extraction and Liquid Chromatography-Tandem Mass Spectrometry. J. AOAC Int. 2019, 102, 33–37. [Google Scholar] [CrossRef] [PubMed]
- González, A.G.; Herrador, M.Á. A Practical guide to analytical method validation, including measurement uncertainty and accuracy profiles. Trends Anal. Chem. 2007, 26, 227–238. [Google Scholar] [CrossRef]
- International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use. ICH Harmonised Tripartite Guideline. In Validation of Analytical Procedures Q2(R2); International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use: Geneva, Switzerland, 2022. [Google Scholar]
- The European Commission. Commission Regulation (EU) 2023/915 of 25 April 2023 on Maximum Levels for Certain Contaminants in Food and Repealing Regulation (EC) No 1881/2006. Off. J. Eur. Union 2023, 19, 103–157. [Google Scholar]
- Ramani, A.; Seth, R.; Gandhi, K.; Sharma, R.; Saji, R. Development and validation of a HPLC-UV method for the quantification of major phospholipids in milk. J. Food Composit. Anal. 2024, 134, 106552. [Google Scholar] [CrossRef]
- Kucharski, D.; Drzewicz, P.; Nałęcz-Jawecki, G.; Mianowicz, K.; Skowronek, A.; Giebułtowicz, J. Development and Application of a Novel QuEChERS Method for Monitoring of Tributyltin and Triphenyltin in Bottom Sediments of the Odra River Estuary, North Westernmost Part of Poland. Molecules 2020, 25, 591. [Google Scholar] [CrossRef]
NEO | Slope | Intercept | R2 | Residual (%) | Matrix Effect | |
---|---|---|---|---|---|---|
DNT | Solvent Matrix | 216.78 218.12 | 0.52 0.48 | 0.9996 0.9991 | ±0.2 ±2.2 | 99.38 |
NTP | Solvent Matrix | 154.44 163.820 | 0.20 0.16 | 0.9997 0.9991 | ±1.7 ±1.9 | 94.27 |
THT | Solvent Matrix | 150.930 159.940 | −0.23 −0.04 | 0.9998 0.9999 | ±3.3 ±5.2 | 94.36 |
CLT | Solvent Matrix | 176.400 188.950 | −0.03 −0.44 | 0.9998 0.9996 | ±2.1 ±3.5 | 93.35 |
IMD | Solvent Matrix | 189.57 197.25 | 0.69 0.83 | 0.9994 0.9993 | ±0.6 ±2.8 | 96.1 |
ACT | Solvent Matrix | 216,78 222.95 | 0.55 0.61 | 0.9995 0.9991 | ±2.7 ±2.9 | 97.23 |
TCP | Solvent Matrix | 180.12 185.50 | −0.24 −0.05 | 0.9997 0.9995 | ±1.5 ±1.9 | 97.09 |
Neonicotinoid | Concentration Level (mg/kg) | Relative Bias (%) | Intra- Assay Precision (RSD%) | Interassay Precision (RSD%) | β-Expectation Tolerance Limits (%) | Relative Expanded Uncertainty (%) | Range of Concentration Values (mg/kg) |
---|---|---|---|---|---|---|---|
Acetamiprid | 0.01 | −0.3 | 1.1 | 1.7 | [−3.8;4.2] | 2.3 | 0.0098/0.0102 |
0.10 | −0.8 | 2.4 | 2.0 | [−4.0;3.4] | 3.2 | 0.068/0.103 | |
1.00 | −0.4 | 1.9 | 2.7 | [−4.5;2.4] | 2.6 | 0.97/1.03 | |
Clothianidin | 0.01 | −1.3 | 2.0 | 4.5 | [−4.0;3.7] | 5.8 | 0.0094/0.0106 |
0.10 | −1.4 | 2.7 | 3.9 | [−3.1;3.6] | 4.7 | 0.095/0.105 | |
1.00 | −0.8 | 2.6 | 4.4 | [−5.3;5.1] | 6.1 | 0.94/1.06 | |
Dinotefuran | 0.01 | −2.5 | 2.6 | 5.2 | [−5.0;4.9] | 6.3 | 0.0094/0.0106 |
0.10 | −3.2 | 3.0 | 4.6 | [−5.5;5.1] | 5.5 | 0.094/0.105 | |
1.00 | −2.4 | 4.8 | 5.9 | [−6.9;6.6] | 7.7 | 0.92/1.08 | |
Imidacloprid | 0.01 | 0.8 | 1.7 | 2.5 | [−3.0;3.5] | 3.1 | 0.0097/0.013 |
0.10 | −0.2 | 2.2 | 2.4 | [−6.1;6.7] | 3.3 | 0.097/0.103 | |
1.00 | 0.4 | 1.4 | 2.0 | [−7.4;7.2] | 3.6 | 0.96/1.04 | |
Nitenpyram | 0.01 | −2.3 | 3.3 | 3.3 | [−4.5;4.7] | 7.9 | 0.0092/0.0108 |
0.10 | −2.9 | 3.2 | 3.9 | [−6.1;5.6] | 4.2 | 0.096/0.104 | |
1.00 | −2.7 | 3.9 | 4.1 | [−5.6;5.8] | 6.4 | 0.94/1.06 | |
Thiacloprid | 0.01 | −0.4 | 1.6 | 3.8 | [−7.2;4.4] | 4.8 | 0.0095/0.0105 |
0.10 | 0.1 | 1.8 | 4.4 | [−7.0;4.6] | 5.9 | 0.094/0.106 | |
1.00 | −1.0 | 2.7 | 3.6 | [−8.4;6.0] | 5.4 | 0.94/1.06 | |
Thiamethoxam | 0.01 | −2.2 | 3.1 | 3.1 | [−4.2;4.8] | 5.4 | 0.0095/0.0105 |
0.10 | −1.5 | 4.1 | 4.2 | [−5.0;4.6] | 5.9 | 0.094/0.106 | |
1.00 | −1.8 | 3.3 | 4.0 | [−6.4;7.3] | 6.1 | 0.95/1.05 |
NEO | LOD (mg/kg) | LOQ (mg/kg) | MRL (mg/kg) |
---|---|---|---|
DNT | 0.003 | 0.01 | 0.01 (default MRL) |
NTP | 0.003 | 0.01 | 0.01 (default MRL) |
THT | 0.006 | 0.02 | 0.2 |
CLT | 0.009 | 0.03 | 0.05 |
IMD | 0.003 | 0.01 | 1.0 |
ACT | 0.009 | 0.03 | 0.05 |
TCP | 0.006 | 0.02 | 0.05 |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Seccia, S.; Albrizio, S.; Dini, I. SPE-HPLC-DAD Dosage of Seven Neonicotinoids in Green Coffee. Molecules 2025, 30, 1930. https://doi.org/10.3390/molecules30091930
Seccia S, Albrizio S, Dini I. SPE-HPLC-DAD Dosage of Seven Neonicotinoids in Green Coffee. Molecules. 2025; 30(9):1930. https://doi.org/10.3390/molecules30091930
Chicago/Turabian StyleSeccia, Serenella, Stefania Albrizio, and Irene Dini. 2025. "SPE-HPLC-DAD Dosage of Seven Neonicotinoids in Green Coffee" Molecules 30, no. 9: 1930. https://doi.org/10.3390/molecules30091930
APA StyleSeccia, S., Albrizio, S., & Dini, I. (2025). SPE-HPLC-DAD Dosage of Seven Neonicotinoids in Green Coffee. Molecules, 30(9), 1930. https://doi.org/10.3390/molecules30091930