FUZZY FOOD ENGINEERING

A classical quantitative (analytical and/or statistical) analysis is not appropriate for some ill defined and/or very complex food engineering problems. Therefore, a new form of analysis using fuzzy mathematics has been applied. The fuzzy model can utilize data which are to a certain level inconsistent. To minimize an information loss of valuable knowledge, conventional pre-processing (usually statistical analysis) of this knowledge is eliminated Primary knowledge (e.g. experimental results) is used directly. Conventional experimental and other records used in food engineering are not suitable for an efficient uncertainty reasoning. A revitalization of these valuable records is a retrospective application of knowledge engineering algorithms. The final goal of the revitalization is to insert additional information items (eg. expert guess) to increase the reasoning power. One revitalization technique (fractal analysis) is presented. Two realistic case studies (meat chilling and malt modification) are given in full detail.