The aim of the course is providing the basic techniques for: food quality monitoring and control, food sensing technologies, food healthiness and safety, data analysis, and design of experiments.
In particular, in the first part of the course the main technologies for food sensing, food quality monitoring and food control will be introduced.
For what concerns data analysis the objective is the knowledge of the most important methodologies for exploratory data analysis, data mining, and product quality improvement.
For what concerns the design and the analysis of experiment the student will acquire competences on how to plan experimental campaigns, managing them with scarce resources in such a way as to extract the maximum information from food treatment. Furthermore, the student will learn how to carry out the analysis of the experiments to find the optimal strategy for food product screening and production/treatment optimization.
At the end of the course, the student will be able to: analyze (uni- and multi-variate) industrial/laboratory data to evaluate the quality of food and the respective treatment process; aid product optimization; monitor a product; identify food unhealthy and unsafe conditions; evaluate the available resources, organize and manage an experimental campaign in an industrial/laboratory environment; extract the most meaningful information from the experimentation to optimize the food safety.
In particular, in the first part of the course the main technologies for food sensing, food quality monitoring and food control will be introduced.
For what concerns data analysis the objective is the knowledge of the most important methodologies for exploratory data analysis, data mining, and product quality improvement.
For what concerns the design and the analysis of experiment the student will acquire competences on how to plan experimental campaigns, managing them with scarce resources in such a way as to extract the maximum information from food treatment. Furthermore, the student will learn how to carry out the analysis of the experiments to find the optimal strategy for food product screening and production/treatment optimization.
At the end of the course, the student will be able to: analyze (uni- and multi-variate) industrial/laboratory data to evaluate the quality of food and the respective treatment process; aid product optimization; monitor a product; identify food unhealthy and unsafe conditions; evaluate the available resources, organize and manage an experimental campaign in an industrial/laboratory environment; extract the most meaningful information from the experimentation to optimize the food safety.
- Docente: Facco Pierantonio