P-28
Prediction of the quality of canned beer related to oxygen concentration and
temperature of storage. Beer flavor is never stable and its alterations practically begin from the
moment of processing, so research has been oriented to controlling the emergence
of certain compounds and the speed of many reactions. As the time of storage
passes, a diminution of the bitter flavor occurs which corresponds with an
increase of sweetness coincident with the development of aromas and flavors in
molasses, toasted sugar or caramel. Many factors influence the intensity of such
changes, among them oxygen content, temperature and time of storage; these also
modify certain important characteristics such as carbon dioxide content, pH,
color, turbidity, bitterness, and degree of oxidation, which directly influence
the sensorial quality of the beer. The objective was to predict the physical
chemistry component concentrations and the sensory quality of canned beer during
the temperature and intervals of time of storing. Beer was elaborated with two
concentrations of oxygen (0.02 and 0.20 ppm) in a local industry and 384 samples
of each one were canned, and stored at 5, 28 and 60°C. Initially and at
intervals of seven days during sixteen weeks, the content of carbon dioxide, pH,
color, turbidity, TBA, and bitterness were instrumentally evaluated.
Simultaneously eight trained panelists evaluated grade of oxidation, quality of
bitterness and sensory stability. Data was divided into two blocks; one was used
to find the models of prediction and the other was used for validation of these
models. A multiple linear regression was used to estimate the coefficients of
the model. These models explained 69-85% (p less than 0.01) of the changes of
the sensory characteristics. The general expression was Y equal B(o) plus
summation B(i)X(i) where Y is the component concentrations or sensory
characteristic, B(o) and B(i) constants, and X(i) is the conjunct of oxygen
concentration, temperature and time during the storage. The models of prediction
were validated by an algorithm written in Matlab language. These results suggest
that component concentrations and sensory characteristics of canned beer would
be predicted by oxygen concentration and storage conditions.
Otoniel Corzo has a degree in Chemical Engineering from the Universidad
Industrial de Santander and a master's degree in Food Science from the
Universidad Simón Bolivar. He has taught food engineering at Universidad de
Oriente for 30 years and now he is the advisor of investigations in analysis and
optimization of food processes.
OTONIEL CORZO and Alfredo Marín. Department of Food Technology, Universidad de
Oriente Núcleo de Nueva Esparta. Nueva Esparta, Boca del Río, Venezuela.