yuanboFaith/QuEChERS-EMR-polyphenols

Method development and validation for analysis of phenolic compounds in fatty complex matrices using enhanced matrix removal (EMR) lipid cleanup and UHPLC-QqQ-MS/MS

See original article published in Food Chemistry.

Abstract

Reliable analysis of phenolic compounds in fatty matrices is a challenging task. In this work, a robust analytical method was developed and validated for 55 phenolic compounds employing QuEChERS (quick, efficient, cheap, easy, rugged and safe) and Enhanced Matrix Removal (EMR)-lipid cleanup in 96-well plates for sample preparation, coupled with ultra-high performance liquid chromatography with triple quadrupole mass spectrometry (UHPLC-QqQ-MS/MS). Seven high-fat matrices of pork brain, belly and liver; horse serum, beef, salmon and avocado were explored for method validation and led to promising stepwise recoveries of extraction, clean-up, drying-reconstitution of most analytes ranging from 75% to 113%, and with an accuracy of 78%∼117%, except for six catechin-analogues. The matrix removal efficiency of EMR was determined using UHPLC-quadruple time of flight (QTOF)-MS, and results indicated that 56%∼77% of co-extractives were removed. This method would be readily extended to wide range of applications demanding high-throughput and sensitive analysis of phenolic compounds in fatty samples.

R Script Reference

This file documents the original R code constructed for various analysis. The code and output can be accessed here. The R code has been developed with reference to R for Data Science (2e), and the official documentation of tidyverse, and DataBrewer.co. See breakdown of modules below:

• Data visualization with ggplot2 (tutorial of the fundamentals; and data viz. gallery).

• Data wrangling with the following packages:
  tidyr: transform (e.g., pivoting) the dataset into tidy structure; dplyr: the basic tools to work with data frames; stringr: work with strings; regular expression: search and match a string pattern; purrr: functional programming (e.g., iterating functions across elements of columns); and tibble: work with data frames in the modern tibble structure.

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