ABSTRACT
Analysis of acquired data is an important step in the process of food quality quantization. Data analysis can help explain the process it concerns. Also, the analysis is beneficial for determining whether the available data is usable to extract the information to fulfill the goals in problem solving. In general, there are two kinds of data analysis. One is the analysis for static relationships, called static analysis. For example, in food quality classification and prediction, the functions between input and output variables are usually static. That is to say, such input and output relationships may not vary with time. The other kind of data analysis, dynamic analysis, seeks dynamic relationships within the process. This second kind is usually needed for food quality process control because in food process modeling and control, the relationships that are mainly dealt with are dynamic. This means that these relationships change with time. In this chapter, these two kinds of data analysis, static and dynamic, will be discussed with practical examples in food engineering.
