Search

This article belongs to the Special Issue Microbiological Risk Assessment in Foods., Beer spoilage caused by microorganisms, which is a major concern for brewers, produces undesirable aromas and flavors in the final product and substantial financial losses. To address this problem, brewers need easy-to-apply tools that inform them of beer susceptibility to the microbial spoilage. In this study, a growth/no growth (G/NG) binary logistic regression model to predict this susceptibility was developed. Values of beer physicochemical parameters such as pH, alcohol content (% ABV), bitterness units (IBU), and yeast-fermentable extract (% YFE) obtained from the analysis of twenty commercially available craft beers were used to prepare 22 adjusted beers at different levels of each parameter studied. These preparations were assigned as a first group of samples, while 17 commercially available beers samples as a second group. The results of G/NG from both groups, after artificially inoculating with one wild yeast and different lactic acid bacteria (LAB) previously adapted to grow in a beer-type beverage, were used to design the model. The developed G/NG model correctly classified 276 of 331 analyzed cases and its predictive ability was 100% in external validation. This G/NG model has good sensitivity and goodness of fit (87% and 83.4%, respectively) and provides the potential to predict craft beer susceptibility to microbial spoilage., This study was supported by grants PID2019-108851RB-C21 (Spanish Ministry of Science and Innovation), and ALIBIRD-CM 2020 P2018/BAA-4343 (Comunidad de Madrid).

Traditionally, beer has been recognised as a beverage with high microbiological stability because of the hostile growth environment posed by beer and increasing attention being paid to brewery hygiene. However, the microbiological risk has increased in recent years because of technological advances toward reducing oxygen in beers, besides the increase in novel beer styles production, such as non-pasteurised, flash pasteurised, cold sterilised, mid-strength, and alcoholic-free beer, that are more prone to spoilage bacteria. Moreover, using innovative beer ingredients like fruits and vegetables is an added cause of microbial spoilage. To maintain quality and good brand image, beer spoilage microorganisms are a critical concern for breweries worldwide. Pectinatus and Megasphaera are Gram-negative bacteria mostly found in improper brewing environments, leading to consumer complaints and financial losses. Because of the lack of compiled scientific knowledge on Pectinatus spoilage ability, this review provides a comprehensive overview of the occurrence, survival mechanisms, and the factors affecting beer spoilage Pectinatus species in the brewing process., This study was supported by the grants AGL2015-64522-C2-1-R (Spanish Ministry of Science and Innovation), and ALIBIRD-CM 2020 P2018/BAA-4343 (Comunidad de Madrid). M. R-S thanks the “President of the Republic Fellowship” from the Ministry of Education of the Republic of Peru.

Craft beer is more susceptible to microbial spoilage because it does not have a pasteurization or filtration process, with lactic acid bacteria (LAB) being the most common beer spoilage microorganism. The aim of this study was to isolate LAB in a craft brewery and their characterization from a food safety and microbiological quality perspective, with a special focus on their abilities to produce biogenic amines (BA) and spoil the beer. The results of 60 monitored points inside the craft brewery showed that LAB associated with the craft brewing processes belonged to Lactobacillus, Pediococcus, and Leuconostoc genera, and most of them were detected in the filling area, which can lead to secondary contamination. Two isolates of L. brevis showed the most significant beer spoilage ability because they could grow in more acidic conditions, at a higher hop and alcohol content, and they displayed horA, horC, and hitA genes, which spoiled the vast majority of the tested beers. In addition, the aforementioned L. brevis isolates showed the highest BA production., This study was supported by grants AGL2015-64522-C2-1-R and PID2019-108851RB-C21 (Spanish Ministry of Science and Innovation), and ALIBIRD-CM 2020 P2018/BAA-4343 (Comunidad de Madrid). M. R-S thanks to the “President of the Republic Fellowship” from the Ministry of Education of the Republic of Peru.