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

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.