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Elimination of Matrix Interferences in GC‐MS Analysis of Pesticides by Entropy Minimization
Author(s) -
Lu Bo,
Lv Yunbo,
Chua Chun Kiang,
Zhang Hua Jun
Publication year - 2017
Publication title -
journal of the chinese chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.329
H-Index - 45
eISSN - 2192-6549
pISSN - 0009-4536
DOI - 10.1002/jccs.201700075
Subject(s) - chemistry , chromatography , quechers , mass spectrometry , gas chromatography , entropy (arrow of time) , pesticide , preprocessor , complex matrix , matrix (chemical analysis) , pesticide residue , artificial intelligence , computer science , physics , quantum mechanics , agronomy , biology
Gas chromatography‐mass spectrometry ( GC‐MS ) is an important analytical technique for the analysis of organophosphorus pesticides in food products. Because of the complex matrices of food products, multiple preprocessing steps are required prior to performing the GC‐MS analysis. Despite that, it is difficult to totally eliminate the interference of complex matrix background. In this work, we introduce an entropy minimization technique that can eliminate the need for comprehensive preprocessing steps to detect organophosphorus pesticides in a fortified orange juice sample. The pure mass spectra and extracted‐ion chromatograms of the pesticides were extracted and reconstructed. The results achieved higher National Institute of Standard and Technology ( NIST ) match scores in comparison to the conventional background subtraction technique. Taken together, the entropy minimization technique is capable of providing rapid qualitative and quantitative analyses of complex GC‐MS data. This technique is expected to have great potential for natural products and food analysis applications.