The aim of this application note is to demonstrate the performance of the Thermo Scientific™ TSQ™ 9610 triple quadrupole mass spectrometer coupled to the Thermo Scientific™ TRACE™ 1610 GC equipped with programmable temperature vaporizing injector (PTV) for the determination of trace level pesticide residues in baby food.
This work aimed to develop and validate an analytical method for simultaneous screening and quantification of pesticide residues in potato by using the QuEChERS extraction method in combination with the Thermo Scientific™ Exactive™ GC Orbitrap™ GC-MS system operated in full scan mode. The data acquisition and processing were carried out by using Thermo Scientific™ TraceFinder™ software. The optimized method was validated as per the SANTE/12682/2019 guidelines.
The Thermo Scientific™ TSQ™ 8000 Evo triple quadrupole GC-MS is an excellent tool for the control of MRL levels in food commodities. The enhanced velocity optics (EVO) driving EvoCell collision cell technology provide high SRM transition speeds, precision, and sensitivity for even complex methods involving several pesticides in a short run time. This application is focused on the analysis of 247 compounds in two different herbal juices, Aloe vera and Amla (Indian gooseberry), demonstrating the potential of the method to detect trace level compounds at concentrations as low as 1-2 ng/g.
As agricultural trade grows and food safety concerns mount, stricter pesticide regulations are being enforced around the world. Increased pesticide testing and reductions in maximum permissible residue levels have driven demand for fast, sensitive and cost-effective analytical methods for high-throughput screening of multi-class pesticides in food. Detection of 510 pesticides at low ppb levels was achieved within 12 minutes using the Thermo Scientific Exactive benchtop LC/MS system powered by Orbitrap technology.
Traditionally, LC-MS/MS has been used by the environmental and food industries for the identification and quantitation of these residues. However, this methodology typically requires extensive offline sample preparation, which can be time consuming and expensive. We test the robustness of an LC-MS system for an automated online preconcentration system using a dirty matrix.
