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Prediction of potential malt extract and beer filterability using conventional and novel malt assays.
Cornaggia, C., Evans, D. E., Draga, A., Mangan, D. & McCleary, B. V. (2019). Journal of Institute of Brewing, 125(3), 294-309.
Colourimetric assays were used to measure the activities of six key hydrolases endogenous to barley: β‐glucanase, xylanase, cellulase, α-amylase, beta‐amylase and limit dextrinase. The analysed barley malt samples were previously characterised by 27 conventional malt quality descriptors. Correlations between enzymatic activities and brewing parameters such as extract yield, fermentability, viscosity and filterability were investigated. A single extraction protocol for all six hydrolases was optimised and used for multi‐enzyme analysis using fully automatable assay formats. A regression analysis between malt parameters was undertaken to produce a relationship matrix linking enzyme activities and conventional malt quality descriptors. This regression analysis was used to inform a multi‐linear regression approach to create predictive models for extract yield, apparent attenuation limit, viscosity and filterability using the Small‐scale Wort rapId Filtration Test (SWIFT) and two different mashing protocols – Congress and a modified infusion mash at 65oC (MIM 65oC). It was observed that malt enzyme activities displayed significant correlations with the analysed brewing parameters. Both starch hydrolases and cell wall hydrolase activities together with modification parameters (i.e. Kolbach index) were found to be highly correlated with extract yield and apparent attenuation limit. Interestingly, it was observed that xylanase activity in malts was an important predictor for wort viscosity and filterability. It is envisaged that the automatable measurement of enzyme activity could find use in plant breeding progeny selection and for routine assessment of the functional brewing performance of malt batches. This analytical approach would also contribute to brewing process consistency, product quality and reduced processing times.Hide Abstract