Earlier this June, CAST-member Bob Pirok (Van ‘t Hoff Institute for Molecular Sciences) and Johan Westerhuis (Swammerdam Institute for Life Sciences) published their vision on current challenges in data analysis in one-dimensional (1D) and two-dimensional (2D) chromatography .
In their article, the authors discuss the caveats of common data-analysis strategies that are typically employed in processing data obtained from 1D and 2D chromatography. The authors discuss the importance of data pre-processing and the associated challenges. Highlighting one of the conclusions of an earlier review , the authors again emphasized that no current studies provide an objective numerical comparison of background correction metrics.
Figure 1. Comparison of commonly applied methods to assess the area of a peak. Reprinted from  with permission.
Pirok and Westerhuis furthermore explained the difficulties with common curve resolution methods such as matched filtering (a.k.a. curve-fitting) and derivated-based approaches.
While multi-dimensional separations increase the likelihood of resolution, the authors noted that this by no means eases the job of obtaining information of these datasets. The authors also discussed some key opportunities currently in the works by scientists around the globe. You can read the article freely here.
Figure 2. The availability of an additional dimension of data through the detector (in these case DAD) certainly helps to distinguish the peaks, but does not aid in easing extracting the information of the data.
 Challenges in Obtaining Relevant Information from One- and Two-Dimensional LC Experiments
B.W.J. Pirok & J.A. Westerhuis, LC-GC North America, 6(38), 2020, 8-14 [LINK]
 Recent applications of chemometrics in one- and two-dimensional chromatography
T.S. Bos, W.C. Knol, S.R.A. Molenaar, L.E. Niezen, P.J. Schoenmakers, G.W. Somsen, B.W.J. Pirok, J. Sep. Sci. 43(9-10), 2020, 1678-1727, DOI: 10.1002/jssc.202000011