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(752c) Glycerol-Based Intelligent Copolymer Film for Real-Time Monitoring of Food Spoilage

Tong, Z. - Presenter, University of Florida
Moses, K., Tuskegee University
Bao, H., University of Florida
Lou, Y., Georgia Institute of Technology
Lan, G., Georgia Institute of Technology
Food is progressively lost and wasted during the food supply chain due to the lack of real-time and responsive food spoilage detection and/or prevention packaging technology. To reduce food lost, it is essential to develop bio-based package materials to reduce the packaging waste and adopt the detection and prevention technologies for food spoilage reduction. In this project, we will use glycerol (biodiesel waste) as starting materials to produce biofilms and/or bioplastics for food packaging. Glycerol monomers were modified to produce pH-sensitive, dendritic barriers in the copolymer system that can accurately respond to various pH environments which can be achieved during food shelf life. Furthermore, the biofilm with pH-sensitivity was developed using mini-emulsion polymerization to sufficiently encapsulate a dye indicator and controllably release the indicator as a means to evaluate spoilage by visual observation. The copolymer films own the improved water barrier property, thermal stability, and strengths with an additional element of visible color indication to display food shelf life in real time. The food spoilage data were collected using the pork meat at both 4ËšC and 20ËšC storage temperatures. It was found that quality of pork meat varied in 4ËšC and 20ËšC storage temperatures with indication of spoilage from mean concentrations of acetic acid upon 24 and 16 hours of storage time, respectively. Analysis by HPLC-UV detection along with bacterial plate counting and pH sensory, bio-based film color changes in comparison, confirmed the shelf life of meat and accuracy of measured and monitored spoilage. Finally, the functionality of the film was paired with image collection and machine learning technologies to enhance the accuracy of the responsive packaging system as a user-friendly detection method for food spoilage. Using our machine learning approach, the current work aims to communicate and/or evaluate food quality for the shelf life of fresh pork using smartphone (hand-held) devices by portraying the relationship between spoilage, pH, bacteria, volatile organic compound(s), and time. The relationship is used to quantify food spoilage based upon visual color patterns produced from the aforementioned pH-sensory films. The approach transforms smartphones into QR readers that can classify food quality with the high accuracy film color variations in real time.