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<OL> <LI> Advancing the fundamental science and application of technologies to ensure safety and improve quality of food products <BR> 1a. Utilize innovative methods to characterize food materials <BR> 1b. Develop new and improved processing technologies <BR> 1c. Develop mathematical models to enhance understanding of, and, optimize food processes <LI> Develop pedagogical methodologies for improved learning of food engineering principles <LI> Develop outreach programs to disseminate best practices for enhancing food safety and quality to stakeholders
NON-TECHNICAL SUMMARY: The safety, economics and quality of processed food depend on the ability to tightly control the processing operation. This project focuses on the development of sensors technologies that can be used to measure the progress of the processing steps, control processing steps within prescribed limits, and predict endpoints.
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APPROACH: Food processing safety is enhanced by using sensor technologies to monitor and control processing conditions within prescribed limits. In addition, sensor technologies make it feasible to control the process to maximize yields, minimize losses and produce a consistent final product. The physical and chemical properties of many foods are dynamically changing during thermal, enzymatic, or other food processes. The overall objective of this research is the development of optical sensor technologies for real-time evaluation of food systems during processing for process monitoring and control applications. Sensor systems are also needed in real time applications for process control and endpoint prediction. The development of in-line sensors for monitoring and controlling food processes is needed to optimize product quality, minimize processing waste, minimize energy usage, and improve food safety. Unit operations such as the enzymatic coagulation of milk and the subsequent syneresis process in cheese making are empirically controlled. Sensor systems are needed to extract the coagulation and syneresis kinetics form the process in real time and utilize this information for process control and especially for endpoint prediction. Similar problems with process control occur in culture processes such as that for cottage cheese and yogurt. The development of mathematical models for analysis of food processes would capitalize on the advances of microcomputers for process control. The physical and chemical properties of many foods are dynamically changing during thermal, enzymatic, or other food processes. The development of sensor technologies for measuring the fingerprints of these processes and algorithms for signal analysis of the profiles may lead to estimation of kinetics of other parameters which are correlated to the extent of processing. Chemometric techniques can be used to develop process control strategies.