Literature DB >> 22985413

Matrix behavior during sample preparation using metabolomics analysis approach for pesticide residue analysis by GC-MS in agricultural products.

Kuniyo Sugitate1, Machiko Saka, Takeshi Serino, Sadao Nakamura, Akira Toriba, Kazuichi Hayakawa.   

Abstract

The detailed matrices and their behaviors during pesticide residue analyses were clarified using a metabolomics analysis approach. The matrix profile was investigated using two different extraction solvents, acetone and acetonitrile. Acetone extracted the matrix components with a wide range of log P(O/W) values. Components with log P(O/W) values >10, such as sterols and tocopherols, and components with log P(O/W) values <3.2 were more extracted by acetone than by acetonitrile. In contrast, components with log P(O/W) values in the range from 3.2 to 10 were extracted by both acetone and acetonitrile at the same concentration level. The study also examined the difference in the column cleanup efficiency using a solid phase extraction (SPE). Florisil, silica gel, NH(2), PSA, and GCB were selected as representative columns for pesticide residue analysis, and acetone extraction of brown rice was selected in this experiment. Most of the matrix components were removed by either column, whereas monoacylglycerols, which are the components causing the matrix effect, were not removed by any column. Understanding such a detailed matrix behavior helps to develop a better analytical method for pesticide analysis using GC-MS.

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Year:  2012        PMID: 22985413     DOI: 10.1021/jf3029557

Source DB:  PubMed          Journal:  J Agric Food Chem        ISSN: 0021-8561            Impact factor:   5.279


  2 in total

1.  Development and diffusion of practical technologies for pesticide residue analysis.

Authors:  Machiko Saka
Journal:  J Pestic Sci       Date:  2018-11-20       Impact factor: 1.519

2.  Identification and characterization of matrix components in spinach during QuEChERS sample preparation for pesticide residue analysis by LC-ESI-MS/MS, GC-MS and UPLC-DAD.

Authors:  Abul Kasem Mohammad Mydul Islam; Su-Myeong Hong; Hyo-Sub Lee; Byeong-Chul Moon; Danbi Kim; Hyeyoung Kwon
Journal:  J Food Sci Technol       Date:  2018-07-31       Impact factor: 2.701

  2 in total

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