1
|
Hearn L, Szafnauer R, Cole R, Green B, Mayser JP, Tomar V, Banerjee K, Amin P. Automated, cryogen-free headspace-trap with gas chromatography-mass spectrometry analysis of ethylene oxide and 2-chloroethanol as residual fumigants in foods. J Environ Sci Health B 2024; 59:81-87. [PMID: 38179701 DOI: 10.1080/03601234.2023.2298169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Abstract
Ethylene oxide (EtO), although banned for use, is still being detected in foodstuffs that have been fumigated to eradicate pests during storage and transport. Residual levels over the European Union's (EU) maximum residue limit (MRL) pose severe health concerns. Recent detection of EtO and its by-product 2-chloroethanol (2-CE) at alarming levels have led to product recalls throughout the EU. Here, a simple, automated headspace (HS)-trap method for the simultaneous determination of EtO and its derivative 2-CE by gas chromatography-mass spectrometry (GC-MS) at the required MRL of ≤ 0.05 mg/kg has been implemented. Syringe-based HS combined with backflushed trapping technology provided enrichment of multiple extractions from the same sample vial (known as multi-step enrichment or MSE®) to increase sensitivity for EtO and 2-CE analysis by GC-MS using single-ion-monitoring (SIM) mode. Method detection limits (MDLs) of 0.00059 mg/kg and 0.00219 mg/kg for EtO and 2-CE, respectively, were obtained without the need for manual handling, solvent extraction or derivatization methods. Recoveries were shown to average (n = 5) at 98% and 107% for EtO and 2-CE, respectively, and the reproducibility was <10% for both compounds.
Collapse
Affiliation(s)
| | | | | | - Bob Green
- Sepsolve Analytical, Peterborough, UK
| | | | | | - Kaushik Banerjee
- National Reference Laboratory, ICAR-National Research Centre for Grapes, Pune, India
| | - Priyesh Amin
- Accurate Laboratory, E-17, Madhavpura Market, Ahmedabad, India
| |
Collapse
|
2
|
Cohnstaedt LW, Rochon K, Duehl AJ, Anderson JF, Barrera R, Su NY, Gerry AC, Obenauer PJ, Campbell JF, Lysyk TJ, Allan SA. Arthropod Surveillance Programs: Basic Components, Strategies, and Analysis. Ann Entomol Soc Am 2012; 105:135-149. [PMID: 26543242 PMCID: PMC4630213 DOI: 10.1603/an11127] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2023]
Abstract
Effective entomological surveillance planning stresses a careful consideration of methodology, trapping technologies, and analysis techniques. Herein, the basic principles and technological components of arthropod surveillance plans are described, as promoted in the symposium "Advancements in arthropod monitoring technology, techniques, and analysis" presented at the 58th annual meeting of the Entomological Society of America in San Diego, CA. Interdisciplinary examples of arthropod monitoring for urban, medical, and veterinary applications are reviewed. Arthropod surveillance consists of the three components: 1) sampling method, 2) trap technology, and 3) analysis technique. A sampling method consists of selecting the best device or collection technique for a specific location and sampling at the proper spatial distribution, optimal duration, and frequency to achieve the surveillance objective. Optimized sampling methods are discussed for several mosquito species (Diptera: Culicidae) and ticks (Acari: Ixodidae). The advantages and limitations of novel terrestrial and aerial insect traps, artificial pheromones and kairomones are presented for the capture of red flour beetle (Coleoptera: Tenebrionidae), small hive beetle (Coleoptera: Nitidulidae), bed bugs (Hemiptera: Cimicidae), and Culicoides (Diptera: Ceratopogonidae) respectively. After sampling, extrapolating real world population numbers from trap capture data are possible with the appropriate analysis techniques. Examples of this extrapolation and action thresholds are given for termites (Isoptera: Rhinotermitidae) and red flour beetles.
Collapse
Affiliation(s)
- Lee W. Cohnstaedt
- Center for Grain and Animal Health Research, USDA-ARS, Manhattan, KS
| | - Kateryn Rochon
- Agriculture and Agri-Food Canada, Lethbridge, AB, Canada
| | - Adrian J. Duehl
- Center for Medical, Agricultural, and Veterinary Entomology, USDA-ARS, Gainesville, EL
| | | | - Roberto Barrera
- Dengue Branch, Centers for Disease Control, San Juan, Puerto Rico
| | - Nan-Yao Su
- University of Florida, Ft. Lauderdale, FL
| | | | | | - James F. Campbell
- Center for Grain and Animal Health Research, USDA-ARS, Manhattan, KS
| | - Tim J. Lysyk
- Agriculture and Agri-Food Canada, Lethbridge, AB, Canada
| | - Sandra A. Allan
- Center for Medical, Agricultural, and Veterinary Entomology, USDA-ARS, Gainesville, EL
| |
Collapse
|