Quantitative whole spectrum analysis with MALDI-TOF MS, Part II: Determining the concentration of milk in mixtures

Abstract

The work summarised in this paper presents the second part of a two-paper series on quantitative whole spectrum analysis with MALDI-TOF MS on skimmed milk. In Part I experiments were carried out to search for optimal sample preparation and instrumental settings in terms of signal-to-noise ratios and repeatability. The results were utilised in the present study when trying to predict concentrations of cow, goat and ewe milk in mixed milk samples. Partial least squares regression was combined with suitable pre- and post-processing of spectra and concentration responses. A plotting method was used where predictions are visualised as a mixture design. The objective was to show that MALDI-TOF MS had potential for being used in quantitative analysis without involving peak comparison or other types of expert guided research. Predictions of a validation data set gave promising results with the best RMSEP values ranging from 5.4% (w/w) to 6.5% (w/w), for the different milk types used, and corresponding R 2 pred values ranging from 94.5% to 96.2%. This indicates that MALDI-TOF is sufficiently accurate and repeatable to be used in practical application for quantitative analysis. Three variable selection strategies based on visual inspections and regression modelling were also evaluated. These were all outperformed, with regard to prediction error, by the use of whole spectra and multivariate regression. The results indicate that multivariate regression on whole spectra can be far more effective than using a few selected variables.