Exploring accurate mass measurements in pixel-based chemometrics: Advancing coffee classification with GC-HRMS-A proof of concept study.

This paper presents a study that assesses the application of chemometrics for classifying coffee samples in a quality control context. High-resolution and accurate mass measurements were utilized as input for pixel-based orthogonal partial least squares discriminant analysis (OPLS-DA) models. The compositional data were acquired through a fully automated workflow combining headspace solid-phase microextraction and gas chromatography-high-resolution mass spectrometry (GC-HRMS) using an FT-Orbitrap® mass analyzer.

Practical Considerations in Method Development for Gas Chromatography-Based Metabolomic Profiling.

This chapter discusses the fundamentals of gas chromatography (GC) to improve method development for metabolic profiling of complex biological samples. The selection of column geometry and phase ratio impacts analyte mass transfer, which must be carefully optimized for fast analysis. Stationary phase selection is critical to obtain baseline resolution of critical pairs, but such selection must consider important aspects of metabolomic protocols, such as derivatization and dependence of analyte identification on existing databases.

Exploring a public database to evaluate consumer preference and aroma profile of lager beers by comprehensive two-dimensional gas chromatography and partial least squares regression discriminant analysis.

In this paper is reported a proof of concept study to evaluate the usage of a public metadata base about beers to guide chemical interpretation of volatile organic compounds (VOC) profiling. 1,569,641 consumers' evaluations were collected from Untappd® platform and used to define a property of interest according to beer preference. 14 brands of beers from lager family were divided in two groups, first one containing samples with low consumers' ratings and the second with brands that exhibited high evaluations.