Knowledge based system for quality monitoring in industrial meat cooking process

The quality of cooking is usually estimated at the end of the cooking process from chef evaluating aroma, color, tenderness and so on. When the cooking process is an industrial process a predefined quality cooked foodstuff must be furnished. Three are the main factors that influences cooking quality: the preservation, the cooking cycles and internal food temperature. Safety assurance recommends cooking the foods until the minimum internal temperature is greater than a particular imposed value, so that the microbial concentration is drastically reduced. This threshold value is related only to the food safety and not to the quality estimation of the final product, which is still demanded to the opinion of an expert. This paper shows the first step of a novel method for real time quality assessment and control that emulates the chef visual perception. In particular it describes the monitoring part that is done inside the meat, because the internal visual aspect offers a correct parameter of cooking quality. Measuring the meat reflectance at different wavelengths in conjunction with the internal temperature evolution allows the construction of a pattern of features, for example extracted with a fuzzy system, which leads to the definition of a parameter for quality classification in meat cooking process.