Abstract

Due to its high sensitivity and resolving power, gas chromatography-ion mobility spectrometry (GC-IMS) is a powerful technique for the separation and sensitive detection of volatile organic compounds. It is a robust and easy-to-handle technique, which has recently gained attention for non-targeted screening (NTS) approaches. In this article, the general working principles of GC-IMS are presented. Next, the workflow for NTS using GC-IMS is described, including data acquisition, data processing and model building, model interpretation and complementary data analysis. A detailed overview of recent studies for NTS using GC-IMS is included, including several examples which have demonstrated GC-IMS to be an effective technique for various classification and quantification tasks. Lastly, a comparison of targeted and non-targeted strategies using GC-IMS are provided, highlighting the potential of GC-IMS in combination with NTS.

Highlights

  • Quality control and early detection of hazard chemicals, allergens, or biological contaminants are critical to ensure product safety

  • HS-gas chromatography coupled to ion mobility spectroscopy (GC-ion mobility spectrometry (IMS)) in combination with an non-targeted screening (NTS) approach provides an effective tool for classification and quantification tasks not at least due to low maintenance and easy handling of the instruments [9]

  • HS-gas chromatography (GC)-IMS has been applied in the field of process control, for example for the early detection of microbial contaminants or in the field of food safety for the detection of pesticides

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Summary

Introduction

Quality control and early detection of hazard chemicals, allergens, or biological contaminants are critical to ensure product safety. For systematic monitoring of product quality, it is desirable to develop analytical methods capable of discovering unknown or non-targeted compounds from the complex sample matrices. This approach, referred to as NTS, requires comprehensive extraction and analysis of compounds of interest. Subsequent to ionization, the analyte ions enter the drift region, where they are accelerated towards the detector, typically a Faraday plate, and are separated by their drift time (or mobility) in an electrical field at ambient pressure. Process control and quality assurance, such as the control of food freshness or food safety, are topics of interest for NTS using HS-GC-IMS [63,64] techniques

Motivation for Non-Targeted Screening Using HS-GC-IMS
Aim of Reference
Method and Number of Compounds Identified
NTS-Workflow
Data Acquisition
Data Processing and Model Building
Exploratory Data Analysis and Machine Learning Techniques
Model Performance and Validation
Quantification Tasks
Model Interpretation
Comparison of NTS and Targeted Strategies
Conclusions
Findings
Objective
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