Published article now available online “Minimizing False Positives and False Negatives in Pesticide Residue Screening of Grains” with Bruker’s SCION TQ GC-MS

Bruker Chemical & Applied Markets division (CAM), US: Published online at “American Laboratory” a new article authored by Dr. Robert Trengove and colleagues from the Separation Science & Metabolomics Laboratory, Murdoch University (Murdoch, Western Australia) and Bruker’s Chemical and Applied Markets division (Fremont, California). This article examines how gas chromatography-mass spectrometry-based analysis (GC-MS) of pesticide residues in grains often result in enhanced responses (false positive or false negative results), and discusses how the degree of enhancement is dependent on the type of grain under study (e.g. wheat, barley and canola).
In GC-MS analysis problematic grain matrices cause enhancement of results and interference that can lead to false positives, false negatives and significant issues with limits of detection (LODs). The Bruker SCION™ GC-MS triple quadrupole (GC-MS TQ) was utilized in a study of a variety of grains, by scientists at Murdoch University, to understand the problems associated with matrix interference. Standard multiple reaction monitoring assays (MRM) are used routinely, but these should only be used following validation to demonstrate they are free from interference in the matrix system under study. Robert Trengove commented that “There are benefits to evaluating matrix interferences on a compound-by-compound and matrix-by-matrix approach to elucidate causes of false positives, false negatives and compromised LODs.”
One outcome of this study has been the development of a database of reliable MRM transitions on routinely analyzed grain commodities. Alternative MRM transitions are necessary to address issues of false negatives and false positives or the use of Chemical Ionization (CI).

“This study illustrated clearly how the matrices of difference grains can greatly affect GC-MS analysis of some pesticides, and how awareness of these ‘limitations’ can help establish achievable limits of detection for each compound and matrix; and minimize false positives when using matrix specific transitions” concluded Trengove.
To view the publication visit  http://new.americanlaboratory.com/913-Technical-Articles/37177-Pesticide-Residue-Testing-of-Grains-and-Oil-Seeds-Minimizing-False-Positives-and-False-Negatives/
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