An Overview of the Application of Multivariate Analysis to the Evaluation of Beer Sensory Quality and Shelf-Life Stability

Quantitative analysis of key components in Qingke beer brewing process by multispectral analysis combined with chemometrics

In order to monitor the Qingke beer brewing process in real time, this paper presents an analytical method for predicting the content of key components in the wort during the mashing and boiling stages using multi-spectroscopy combined with chemometrics. The results showed that the Neural Networks (NN) model based on Raman spectroscopy (RPD = 3.9727) and the NN model based on NIR spectroscopy (RPD = 5.1952) had the best prediction performance for the reducing sugar content in the mashing and boiling stages; The partial least Squares (PLS) model based on Raman spectroscopy (RPD = 2.7301) and the NN model based on Raman spectroscopy (RPD = 4.3892) predicted the content of free amino nitrogen best; The PLS model based on UV-Vis spectroscopy (RPD = 4.0412) and the NN model based on Raman spectroscopy (RPD = 4.0540) are most suitable for the quantitative analysis of total phenols. The results can be used as a guide for real-time control of wort quality in industrial production.

Multivariate Analysis of the Influence of Microfiltration and Pasteurisation on the Quality of Beer during Its Shelf Life

Gas chromatography-mass spectrometry (GC-MS), physicochemical and microbiological analyses, sensory descriptive evaluation, and multivariate analyses were applied to evaluate the efficiencies of microfiltration and pasteurization processes during the shelf life of beer. Samples of microfiltered and pasteurised beer were divided into fresh and aged groups. A forced ageing process, which consisted of storing fresh samples at 55° C for 6 days in an incubator and then keeping them under ambient conditions prior to analysis, was applied. Physicochemical analysis showed that both microfiltered and pasteurised samples had a slight variation in apparent extract, pH, and bitterness. The samples that underwent heat treatment had lower colour values compared with those that were microfiltered. Chromatographic peak areas of vicinal diketones increased in both fresh and aged samples. The results of the microbiological analysis revealed spoilage lactic acid bacteria (Lactobacillus) and yeasts (Saccharomyces and non-Saccharomyces) in fresh microfiltered samples. In the GC-MS analysis, furfural, considered by many authors as a heat indicator, was detected only in samples that underwent forced ageing and not in samples that were subjected to thermal pasteurisation. Finally, sensory analysis found differences in the organoleptic properties of fresh microfiltered samples compared with the rest of the samples.

Activated natural zeolites for beer filtration: A pilot scale approach

A clinoptilolite-rich natural zeolite was tested as a substitute for kieselguhr as a filtering material to eliminate ingredients that cause beer haze formation. Two-grain sizes of micronized natural zeolite were thermally activated to 400 °C, to enhance its adsorption performance and remove the impurities adsorbed in the microporous system of zeolites, followed by their physicochemical characterization. The activated zeolites mixed with four commercial filter aids in different ratios were used for beer filtration at the pilot scale. Most of the physicochemical and sensory characteristics of beers filtered with commercial filter aids and with zeolites were similar. Using zeolite in filtering mixtures significantly reduces the number of microorganisms present in the filtered beer, which can eliminate the necessity of beer sterilization after filtration. The results evidenced that activated natural zeolites, which are cheap materials, are promising candidates as filter aids and can replace kieselguhr without producing any degradation of the beer filtration process.