End products must conform to the characteristics defined in their specifications. These characteristics include sensory properties, which are essential because they condi-tion the choice and the preference of consumers. It is important to take them into account for their control when manufacturing products. Therefore, in food industry, these properties must be controlled these properties close to the manufacturing line by implementing adapted measurement and process control. Although many methods can be applied to process numerical data, from linear regres-sion to more elaborated ones, such as statistical methods (e.g. Bayesian), neural networks, fuzzy logic (theory of fuzzy sets and theory of possibility), few are adapted to deal with symbolic data manipulated by experts and can be implemented in a decision support system used by operators. The fuzzy symbolic approach is a tool which allows solving this problem. This study presents through three examples (sausage crusting, food product browning, meat emulsification process) different possible uses of the fuzzy symbolic approach to control or help the operator to control food processes.