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For those chemical compounds absorbing in the UV-Vis region and not readily applicable to routine mass spectrometry ionisation methods, liquid chromatography coupled to diode array detection is a convenient platform to perform metabolite profiling. Data processing by hand is labour-intensive and error prone. In the present study a strategy based on multivariate curve resolution, and its implementation in an R package called alsace are described. The final result of an analysis is a table containing peak heights or peak areas for all features of the individual injections. The capabilities of the software, providing elements such as splitting the data into separate, possibly overlapping time windows, merging the results of the individual time windows, and parametric time warping to align features, are illustrated using a cassava-derived data set. [ABSTRACT FROM AUTHOR]

Optimal solvent conditions for grape sample preparation were investigated for the purpose of metabolite profiling studies, with the aim of obtaining as many features as possible with the best analytical repeatability. Mixtures of water, methanol and chloroform in different combinations were studied as solvents for the extraction of ground grapes. The experimental design used a two stage study to find the optimum extraction medium. The extracts obtained were further purified using solid phase extraction and analysed using a UPLC full scan TOF MS with both reversed phase and hydrophilic interaction chromatography. The data obtained were processed using data extraction algorithms and advanced statistical software for data mining. The results obtained indicated that a fairly broad optimal area for solvent composition could be identified, containing approximately equal amounts of methanol and chloroform and up to 20% water. Since the water content of the samples was variable, the robustness of the optimal conditions suggests these are appropriate for large scale profiling studies for characterisation of the grape metabolome. [ABSTRACT FROM AUTHOR]