Multi-objective optimization of beef roasting.

S.M. GOÑI; V. O. SALVADORI

Procedia Food Science

Elsevier

Año: 2011 vol. 1 p. 747 - 752

2211-601X

In this work a beef roasting model is used to analyze the behaviour of two significant parameters during roasting: process times and weight losses, as a function of oven temperature. The cooking model considers conductive heat transfer inside the sample and take into account both evaporative and dripping losses. The evaporative losses are considered at the surface of the meat. The dripping losses are predicted through the internal moisture content variation, which is modelled as a function of water demand. Such water demand is the difference between actual water content and the water holding capacity of beef. For model simulation six 3D irregular geometrics models of semitendinosus muscle were used. In all cases constant oven temperature was considered, with operative limits of 150 and 230ºC. A restriction to the optimization problem was imposed: the coldest point must reach a minimum temperature of 72ºC. The model prediction indicates that an increase in oven temperature leads to a decrease in cooking time and an increase in weight loss. In average, rates of variation with oven temperature are -0.3 min/ºC for cooking time, and 0.21%/ºC for weight loss, which are similar to published experimental results. Because of the mentioned behaviour, a compromise situation is encountered, since no operative condition lead to a minimization of both objectives.semitendinosus muscle were used. In all cases constant oven temperature was considered, with operative limits of 150 and 230ºC. A restriction to the optimization problem was imposed: the coldest point must reach a minimum temperature of 72ºC. The model prediction indicates that an increase in oven temperature leads to a decrease in cooking time and an increase in weight loss. In average, rates of variation with oven temperature are -0.3 min/ºC for cooking time, and 0.21%/ºC for weight loss, which are similar to published experimental results. Because of the mentioned behaviour, a compromise situation is encountered, since no operative condition lead to a minimization of both objectives.