On-line monitoring of continuous beer fermentation process using automatic membrane inlet mass spectrometric system.

A fully automatic membrane inlet mass spectrometric (MIMS) on-line instrumentation for the analysis of aroma compounds in continuous beer fermentation processes was constructed and tested. The instrumentation includes automatic filtration of the sample stream, flushing of all tubing between samples and pH control. The calibration standards can be measured periodically. The instrumentation has also an extra sample line that can be used for off-line sample collection or it can be connected to another on-line method. Detection limits for ethanol, acetic acid and eight organic beer aroma compounds were from mugl(-1) to low mgl(-1) levels and the standard deviations were less than 3.4%. The method has a good repeatability and linearity in the measurement range. Response times are shorter than or equal to 3min for all compounds except for ethyl caproate, which has a response time of 8min. In beer aroma compound analysis a good agreement between MIMS and static headspace gas chromatographic (HSGC) measurements was found. The effects of different matrix compounds commonly present in the fermentation media on the MIMS response to acetaldehyde, ethyl acetate and ethanol were studied. Addition of yeast did not have any effect on the MIMS response of ethanol or ethyl acetate. Sugars, glucose and xylose, increased the MIMS response of all studied analytes only slightly, whereas salts, ammonium chloride, ammonium nitrate and sodium chloride, increased the MIMS response of all three studied compounds prominently. The system was used for on-line monitoring of continuous beer fermentation with immobilised yeast. The results show that with MIMS it is possible to monitor the changes in the continuous process as well as delays in the two-phase process.

A new maximum likelihood approach with asymmetric residual distribution for multicomponent mass spectra analysis.

This paper proposes a new maximum likelihood approach for the deconvolution of identity and quantity of individual compounds based on the multicomponent mass spectra measured by mass spectrometry (MS). Mixture analysis of multicomponent mass spectra is, typically, based on a linear multicomponent mass spectrum model, where the compounds of the measured spectra to be solved are explicitly stated and assumed to be known. In many cases, however, the measured spectrum may contain unknown compounds that are not explicitly stated in the model and a commonly used least square (LS) solution fails. Moreover, a standard improvement over the LS method in these cases, namely the M-estimation (ME) approach, also suffers from this same problem. Our method overcomes the limitations of the LS and ME methods by modeling the effect of the unknown compound(s) to the residual of the linear model. The experimental results presented show that this new approach can separate more robustly the complex multicomponent mass spectra into their individual constituents compared to the LS and ME methods.

Computing positional isotopomer distributions from tandem mass spectrometric data.

The isotopomer distributions of metabolites are invaluable pieces of information in the computation of the flux distribution in a metabolic network. We describe the use of tandem mass spectrometry with the daughter ion scanning technique in the discovery of positional isotopomer distributions (PID). This technique increases the possibilities of mass spectrometry since given the same fragment ions, it uncovers more information than the full scanning mode. The mathematics of the new technique is slightly more complicated than the techniques needed by full scanning mode methods. Our experiments, however, show that in practice the inadequacy of the fragmentation of amino acids in the tandem mass spectrometer does not allow uncovering the PID exactly even if the daughter ion scanning is used. The computational techniques have been implemented in a MATLAB application called PIDC (Positional Isotopomer Distribution Calculator).