Inferring mixed-culture growth from total biomass data in a wavelet approach

It is shown that the presence of mixed-culture growth in batch fermentation processes can be very accurately inferred from total biomass data by means of the wavelet analysis for singularity detection. This is accomplished by considering simple phenomenological models for the mixed growth and the more complicated case of mixed growth on a mixture of substrates. The main quantity provided by the wavelet analysis is the Holder exponent of the singularity that we determine for our illustrative examples. The numerical results point to the possibility that Holder exponents can be used to characterize the nature of the mixed-culture growth in batch fermentation processes with potential industrial applications. Moreover, the analysis of the same data affected by the common additive Gaussian noise still lead to the wavelet detection of the singularities although the Holder exponent is no longer a useful parameterComment: 17 pages and 10 (png) figure

High-gain nonlinear observer for simple genetic regulation process

High-gain nonlinear observers occur in the nonlinear automatic control theory and are in standard usage in chemical engineering processes. We apply such a type of analysis in the context of a very simple one-gene regulation circuit. In general, an observer combines an analytical differential-equation-based model with partial measurement of the system in order to estimate the non-measured state variables. We use one of the simplest observers, that of Gauthier et al., which is a copy of the original system plus a correction term which is easy to calculate. For the illustration of this procedure, we employ a biological model, recently adapted from Goodwin's old book by De Jong, in which one plays with the dynamics of the concentrations of the messenger RNA coding for a given protein, the protein itself, and a single metabolite. Using the observer instead of the metabolite, it is possible to rebuild the non-measured concentrations of the mRNA and the proteinComment: 9 pages, one figur

Application of multifractal wavelet analysis to spontaneous fermentation processes

An algorithm is presented here to get more detailed information, of mixed culture type, based exclusively on the biomass concentration data for fermentation processes. The analysis is performed with only the on-line measurements of the redox potential being available. It is a two-step procedure which includes an Artificial Neural Network (ANN) that relates the redox potential to the biomass concentrations in the first step. Next, a multifractal wavelet analysis is performed using the biomass estimates of the process. In this context, our results show that the redox potential is a valuable indicator of microorganism metabolic activity during the spontaneous fermentation. In this paper, the detailed design of the multifractal wavelet analysis is presented, as well as its direct experimental application at the laboratory levelComment: 12 pages, 3 figures, Physica A, to appea

Yeasts associated with the production of distilled alcoholic beverages

Distilled alcoholic beverages are produced firstly by fermenting sugars emanating from cereal starches (in the case of whiskies), sucrose-rich plants (in the case of rums), fructooligosaccharide-rich plants (in the case of tequila) or from fruits (in the case of brandies). Traditionally, such fermentations were conducted in a spontaneous fashion, relying on indigenous microbiota, including wild yeasts. In modern practices, selected strains of Saccharomyces cerevisiae are employed to produce high levels of ethanol together with numerous secondary metabolites (eg. higher alcohols, esters, carbonyls etc.) which greatly influence the final flavour and aroma characteristics of spirits following distillation of the fermented wash. Therefore, distillers, like winemakers, must carefully choose their yeast strain which will be very important in providing the alcohol content and the sensory profiles of spirit beverages. This Chapter discusses yeast and fermentation aspects associated with the production of selected distilled spirits and highlights similarities and differences with the production of wine

Primjena plinske kromatografije u kombinaciji s masenom spektrometrijom za karakterizaciju hlapljivih spojeva tradicionalnih meksičkih pića proizvedenih iz Agave

Ethnic Agave alcoholic beverages such as raicilla, sisal, tequila, mezcal, bacanora, sotol and pulque have been analyzed by gas chromatography and headspace solid-phase microextraction- gas chromatography-mass spectrometry (HS-SPME-GC-MS). There were 105 compounds identified, eleven were classified as major compounds and the others were classified as minor compounds. Seventeen minor compounds could be used as authenticity markers since they were beverage specific. Cluster analysis (CA) showed that Agave alcoholic beverages could be distinguished by multivariate analysis of major compounds; however, the analysis of minor compounds provided a better fingerprinting.Plinskom kromatografijom i mikroekstrakcijom na čvrstoj fazi, u kombinaciji s plinskom kromatografijom i masenom spektrometrijom (HS-SPME-GC-MS), ispitani su uzorci tradicionalnih meksičkih pića proizvedenih iz Agave (raicilla, sisal, tequila, mezcal, bacanora, sotol i pulque). Identificirano je 105 spojeva, od čega 11 glavnih sastojaka. Utvrđeno je da se za markere autentičnosti pojedinih pića može upotrijebiti 17 sporednih sastojaka. Razvrstavanjem uzoraka (engl. cluster analysis – CA) dokazano je da se tradicionalna meksička pića proizvedena iz Agave mogu razlikovati multivarijantnom analizom glavnih sastojaka, a analiza sporednih sastojaka omogućava točnije utvrđivanje porijekla pića