A Binary Logistic Regression Model as a Tool to Predict Craft Beer Susceptibility to Microbial Spoilage

A Binary Logistic Regression Model as a Tool to Predict Craft Beer Susceptibility to Microbial Spoilage

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...

Full description

Bibliographic Details
Main Authors: Magaly Rodríguez-Saavedra, Karla Pérez-Revelo, Antonio Valero, M. Victoria Moreno-Arribas, Dolores González de Llano
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:Foods
Subjects:
spoilage microorganisms
susceptibility prediction
antimicrobial hurdles
beer intrinsic factors
growth/no growth
model development
Online Access:https://www.mdpi.com/2304-8158/10/8/1926

Internet

https://www.mdpi.com/2304-8158/10/8/1926

Similar Items