Chromatographic fingerprint-based analysis of extracts of green tea, lemon balm and linden: I. Development of global retention models without the use of standards.

We report here the improvement of a procedure to obtain global models, able to describe the retention behaviour of several sample components simultaneously. The reported global models include parameters that account for the general effects of column and solvent on retention and are common for all components, whereas other parameters are specific of each sample component. These models are fitted by alternate regression and offer a prediction performance comparable to individual retention models. The approach is suitable to samples of natural products including a large number of components in extremely diverse concentrations and in the absence of standards. Guidelines are given for the successful development of sample-oriented experimental designs (i.e. adapted to the elution of the components of the natural products), constituted by multi-linear gradients. These designs also facilitate peak tracking. The model proposed by Neue and Kuss to describe the retention was found to yield the best predictions. The approach is applied to the extracts of samples of green tea, lemon balm and linden, yielding excellent predictions of retention for selected components.

Assisted baseline subtraction in complex chromatograms using the BEADS algorithm.

The data processing step of complex signals in high-performance liquid chromatography may constitute a bottleneck to obtain significant information from chromatograms. Data pre-processing should be preferably done with little (or no) user supervision, for a maximal benefit and highest speed. In this work, a tool for the configuration of a state-of-the-art baseline subtraction algorithm, called BEADS (Baseline Estimation And Denoising using Sparsity) is developed and verified. A quality criterion based on the measurement of the autocorrelation level was designed to select the most suitable working parameters to obtain the best baseline. The use of a log transformation of the signal attenuated artifacts associated to a large disparity in signal size between sample constituents. Conventional BEADS makes use of trial-and-error strategies to set up the working parameters, which makes the process slow and inconsistent. This constitutes a major drawback in its successful application. In contrast, the assisted BEADS simplifies the setup, shortens the processing time and makes the baseline subtraction more reliable. The assisted algorithm was tested on several complex chromatograms corresponding to extracts of medicinal herbs analysed with acetonitrile-water gradients, and a mixture of sulphonamides eluted with acetonitrile gradients in the presence of the non-ionic surfactant Brij-35 under micellar conditions.