Multivariate principal component analysis of beer quality with addition of triticale grain and malt

Expanding the beer assortment by partially replacing barley malt with new types of raw materials based on grain crops is a promising direction for the industry development. A promising grain crop that can partially replace barley malt is triticale. The aim of the work is to study the possibility of using triticale grain and malt for partial replacement of barley malt in beer production and to evaluate the eff ect of this raw material on the physicochemical and organoleptic quality indicators using the principal component analysis (PCA). Barley malt, Spica triticale grain, granulated hops and bottom-fermenting yeast have been used as raw materials. Physicochemical and organoleptic indicators have been determined for grain percent mixtures 90/10, 85/15, 80/20, 75/25 barley malt/triticale grain (or triticale malt). Beer has been produced using decoction and infusion methods. The mass fraction of ethyl alcohol, acidity, color, isohumulone content, diacetyl content, mass fraction of protein and organoleptic indicators were determined for the beer samples. The PCA has been used to assess the main factors aff ecting the quality of beer. It has been shown that with an increase in the proportion of triticale in grain mixtures, the protein content increases, extractivity decreases, and the color and viscosity of the extract increase. Replacing part of the barley malt with triticale grain and malt does not violate the correlation between extractivity and the mass fraction of ethyl alcohol. Adding triticale grain reduces the color index of beer, while adding malt increases it. Total protein increases slightly with an increase in the share of triticale. According to organoleptic indicators, the highest score has been given to the sample with 15% triticale malt. The use of PCA revealed the relationship between the taste characteristics of beer and the data of its physicochemical analysis. The PCA model shows the multivariate nature of the data, when the overall organoleptic assessment consists of the combined contribution of several factors (up to four). According to the physicochemical parameters, the obtained beer samples using triticale grain and malt fully correspond to light beer with an initial wort extract of 11–13% according to GOST 31711-2012. The proposed principal component analysis can be used to optimize fermentation and other food production.

beer, triticale grain, triticale malt, technology optimization, multivariate analysis, principal component analysis