On the road to automation: a comparative review on chemometric strategies for GC-MS data analysis

Agnieszka Smolinska; Samuele Pellacani; Michal Skawinski; Caterina Durante

doi:10.1016/j.trac.2025.118286

On the road to automation: a comparative review on chemometric strategies for GC-MS data analysis

Agnieszka Smolinska, Samuele Pellacani, Michal Skawinski, Caterina Durante^*

^*Corresponding author for this work

Research output: Contribution to journal › (Systematic) Review article › peer-review

Abstract

It is widely proved in the literature the pivotal role of GC-MS technique in obtaining information across diverse research contexts. Given the great importance of GC-MS analysis and the undeniable role of chemometric techniques in signal processing, this review provides perspectives on the latest automatic procedures for performing peak detection, resolution, baseline, and time-shift correction. Herein, insights into the principles behind the most common chemometric methods in scientific literature, PARAFAC2 (PARAllel FACtor analysis 2) and MCR-ALS (Multivariate Curve Resolution - Alternating Least Squares), are provided, along with their respective strengths and limitations. In particular, regarding PARAFAC2, the PARADISe (PARAFAC2-based Deconvolution and Identification System) has been further described, while for MCR-ALS, the latest automated procedures have been explored. The aim of this review is to shed light on the evolving field of automatic GC-MS data analysis and to facilitate the advancement of this field.

Original language	English
Article number	118286
Number of pages	16
Journal	Trac-Trends in Analytical Chemistry
Volume	190
DOIs	https://doi.org/10.1016/j.trac.2025.118286
Publication status	Published - 1 Sept 2025

Keywords

MCR-ALS
PARADISe
GC-MS
Chemometrics
Resolution
Compounds extraction
Automatic data pre-processing
MULTIVARIATE CURVE RESOLUTION
MASS-SPECTROMETRY DATA
GAS-CHROMATOGRAPHY
LEAST-SQUARES
COMPREHENSIVE ANALYSIS
COMPUTATIONAL TOOL
IDENTIFICATION
L.
DECONVOLUTION

Access to Document

10.1016/j.trac.2025.118286Licence: CC BY

Cite this

@article{036bf692361547639b7f9b4be8d24ff5,

title = "On the road to automation: a comparative review on chemometric strategies for GC-MS data analysis",

abstract = "It is widely proved in the literature the pivotal role of GC-MS technique in obtaining information across diverse research contexts. Given the great importance of GC-MS analysis and the undeniable role of chemometric techniques in signal processing, this review provides perspectives on the latest automatic procedures for performing peak detection, resolution, baseline, and time-shift correction. Herein, insights into the principles behind the most common chemometric methods in scientific literature, PARAFAC2 (PARAllel FACtor analysis 2) and MCR-ALS (Multivariate Curve Resolution - Alternating Least Squares), are provided, along with their respective strengths and limitations. In particular, regarding PARAFAC2, the PARADISe (PARAFAC2-based Deconvolution and Identification System) has been further described, while for MCR-ALS, the latest automated procedures have been explored. The aim of this review is to shed light on the evolving field of automatic GC-MS data analysis and to facilitate the advancement of this field.",

keywords = "MCR-ALS, PARADISe, GC-MS, Chemometrics, Resolution, Compounds extraction, Automatic data pre-processing, MULTIVARIATE CURVE RESOLUTION, MASS-SPECTROMETRY DATA, GAS-CHROMATOGRAPHY, LEAST-SQUARES, COMPREHENSIVE ANALYSIS, COMPUTATIONAL TOOL, IDENTIFICATION, L., DECONVOLUTION",

author = "Agnieszka Smolinska and Samuele Pellacani and Michal Skawinski and Caterina Durante",

year = "2025",

month = sep,

day = "1",

doi = "10.1016/j.trac.2025.118286",

language = "English",

volume = "190",

journal = "Trac-Trends in Analytical Chemistry",

issn = "0165-9936",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - On the road to automation

T2 - a comparative review on chemometric strategies for GC-MS data analysis

AU - Smolinska, Agnieszka

AU - Pellacani, Samuele

AU - Skawinski, Michal

AU - Durante, Caterina

PY - 2025/9/1

Y1 - 2025/9/1

N2 - It is widely proved in the literature the pivotal role of GC-MS technique in obtaining information across diverse research contexts. Given the great importance of GC-MS analysis and the undeniable role of chemometric techniques in signal processing, this review provides perspectives on the latest automatic procedures for performing peak detection, resolution, baseline, and time-shift correction. Herein, insights into the principles behind the most common chemometric methods in scientific literature, PARAFAC2 (PARAllel FACtor analysis 2) and MCR-ALS (Multivariate Curve Resolution - Alternating Least Squares), are provided, along with their respective strengths and limitations. In particular, regarding PARAFAC2, the PARADISe (PARAFAC2-based Deconvolution and Identification System) has been further described, while for MCR-ALS, the latest automated procedures have been explored. The aim of this review is to shed light on the evolving field of automatic GC-MS data analysis and to facilitate the advancement of this field.

AB - It is widely proved in the literature the pivotal role of GC-MS technique in obtaining information across diverse research contexts. Given the great importance of GC-MS analysis and the undeniable role of chemometric techniques in signal processing, this review provides perspectives on the latest automatic procedures for performing peak detection, resolution, baseline, and time-shift correction. Herein, insights into the principles behind the most common chemometric methods in scientific literature, PARAFAC2 (PARAllel FACtor analysis 2) and MCR-ALS (Multivariate Curve Resolution - Alternating Least Squares), are provided, along with their respective strengths and limitations. In particular, regarding PARAFAC2, the PARADISe (PARAFAC2-based Deconvolution and Identification System) has been further described, while for MCR-ALS, the latest automated procedures have been explored. The aim of this review is to shed light on the evolving field of automatic GC-MS data analysis and to facilitate the advancement of this field.

KW - MCR-ALS

KW - PARADISe

KW - GC-MS

KW - Chemometrics

KW - Resolution

KW - Compounds extraction

KW - Automatic data pre-processing

KW - MULTIVARIATE CURVE RESOLUTION

KW - MASS-SPECTROMETRY DATA

KW - GAS-CHROMATOGRAPHY

KW - LEAST-SQUARES

KW - COMPREHENSIVE ANALYSIS

KW - COMPUTATIONAL TOOL

KW - IDENTIFICATION

KW - L.

KW - DECONVOLUTION

U2 - 10.1016/j.trac.2025.118286

DO - 10.1016/j.trac.2025.118286

M3 - (Systematic) Review article

SN - 0165-9936

VL - 190

JO - Trac-Trends in Analytical Chemistry

JF - Trac-Trends in Analytical Chemistry

M1 - 118286

ER -

On the road to automation: a comparative review on chemometric strategies for GC-MS data analysis

Abstract

Keywords

Access to Document

Fingerprint

Cite this