Analysis of pesticides, veterinary drugs, and environmental contaminants in goat and lamb by the QuEChERSER mega-method

Author(s)

Ninga, Ederina ; Lehotay, Steven J. ; Sapozhnikova, Yelena ; Lightfield, Alan R. ; Strahan, Gary D. ; Monteiro, Sergio H.

• Document type: Journal article
• Source: ANALYTICAL METHODS; v. N/A, p. 10-pg., 2022-06-27.

Abstract

Analysis of chemical residues in foods is a big challenge for developing countries due to lack of financial and professional resources needed to meet international quality standards for trade. However, the implementation of simple multiclass, multi-residue methods in monitoring programs can provide significant benefits to save cost, time, and labor. The aim of this project was to investigate the "quick, easy, cheap, effective, rugged, safe, efficient, and robust" (QuEChERSER) mega-method for the fatty muscle matrices of goat and lamb. To achieve wide analytical scope covering pesticides, environmental contaminants, and veterinary drugs, extracts were analyzed by both ultrahigh-performance liquid and low-pressure gas chromatography (UHPLC and LPGC) coupled with tandem mass spectrometry (MS/MS). The QuEChERSER mega-method was validated in ovine (goat) and caprine (lamb) muscles at four different spiking levels with 10 replicates per level for a total of 330 analytes and metabolites, consisting of 225 pesticides, 89 veterinary drugs, and 16 polychlorinated biphenyls (PCBs). In the case of LPGC-MS/MS (preceded by automated "instrument-top sample preparation"), 92% and 82% of the analytes met the data quality objectives of 70-120% recovery and <20% RSD for goat and lamb, respectively. For UHPLC-MS/MS, 95% and 92% of the analytes met the acceptable validation criteria in goat and lamb, respectively. Thus, the QuEChERSER mega-method has been demonstrated to be a useful streamlined approach to more efficiently replace multiple methods currently used to cover the same analytical scope. (AU)

• FAPESP's process: 16/22370-2 - Automated high throughput sample preparation and analysis of multi-class contaminants in meat
• Grantee: Sérgio Henrique Monteiro
• Support Opportunities: Scholarships abroad - Research