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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Microbial and Chemical Food Safety » Research » Publications at this Location » Publication #370433

Research Project: Development, Evaluation, and Validation of Technologies for the Detection and Characterization of Chemical Contaminants in Foods

Location: Microbial and Chemical Food Safety

Title: Assessment of test portion sizes after sample comminution with liquid nitrogen in the high-throughput analysis of pesticide residues in fruits and vegetables

item Lehotay, Steven
item MICHLIG, NICOLAS - Universidad Nacional Del Litoral
item Lightfield, Alan

Submitted to: Journal of Agricultural and Food Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/16/2020
Publication Date: 1/16/2020
Citation: Lehotay, S.J., Michlig, N., Lightfield, A.R. 2020. Assessment of test portion sizes after sample comminution with liquid nitrogen in the high-throughput analysis of pesticide residues in fruits and vegetables. Journal of Agricultural and Food Chemistry. 68:1468-1479.

Interpretive Summary: Just as a chain is only as strong as its weakest link, the overall quality of analysis of pesticide residues in foods depends on the performance of each step in the method. In real-world monitoring, the first step in the method, sample processing of bulk collected samples, is typically the most time-consuming, laborious, and contributes the most error to the quality of the final result. For this reason, analytical method development researchers tend to ignore this preliminary step when evaluating and validating new methods. However, this study overcomes the long-standing challenge to devise a fast, straight-forward, and effective sample processing approach by using liquid nitrogen in a safe, one-step procedure with a typical commercial food chopper. The approach provides such good sample homogenization that 2 g subsamples can be taken for equivalent analysis rather than 10-15 g test portions by traditional means to sample processing. This approach is expected to be used by many laboratories worldwide to improve accuracy of analyses while also increasing sample throughput.

Technical Abstract: In this study, sample processing of bulk commodities using an efficient one-step comminution procedure with liquid nitrogen (LN2) was devised and assessed in the analysis of pesticide residues in fruits and vegetables. The LN2 was added to the fresh samples from a tank by opening a valve, and the standard food chopper was kept in a laboratory hood to reduce safety risks. Test portions of 4 replicates each of 0.25, 0.5, 1, 2, 5, 10, and 15 g were taken from 8 fruits and vegetables (tomato, squash, broccoli, apple, grape, peach, green bean, and cucumber) individually comminuted with LN2. For comparison without comminution, similar test portions of a certified reference material of pesticides in cucumber were also analyzed by the same method. More than 100 pesticides were monitored by both ultrahigh-performance liquid chromatography – tandem mass spectrometry (UHPLC-MS/MS) and instrument-top sample preparation (ITSP) + fast low-pressure gas chromatography (LPGC)-MS/MS. A new version of QuEChERS-based sample preparation was followed in which 5 mL 4/1 (v/v) acetonitrile/water per g sample is used for extraction, 200 µL initial extract is quickly evaporated, reconstituted in water, and ultra-centrifuged for UHPLC-MS/MS analysis. For ITSP+LPGC-MS/MS, another portion of the initial extract undergoes salt-out partitioning with 4/1 (w/w) anh. MgSO4/NaCl and the upper layer extract is transferred to an autosampler vial for automated cleanup and analysis in parallel. Quality control spikes were made during the comminution, extraction, cleanup, and analyses steps to isolate and estimate the individual and overall measurement uncertainties of the approach. Recommended test portion size is 2 g for routine monitoring by this approach, but results demonstrated that subsamples as low as 0.5 g typically gave biases and RSDs <10% for nearly all pesticides, commodities, and methods, which is 3-5% lower than previously evaluated sample processing and analytical methods. This approach can be used to improve data quality, laboratory efficiency, and sample throughput in routine monitoring programs for regulatory, risk assessment, and other purposes.