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Fabrication of Bio-Based Intelligent...

Moses, Karyn E.,

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Fabrication of Bio-Based Intelligent Copolymer Film with Computational Technology for Real-Time Food Quality Monitoring and Protection /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Fabrication of Bio-Based Intelligent Copolymer Film with Computational Technology for Real-Time Food Quality Monitoring and Protection // Karyn E Moses.
Author:	Moses, Karyn E.,
Description:	1 electronic resource (149 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 83-12, Section: B.
Contained By:	Dissertations Abstracts International83-12B.
Subject:	Food science. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28260078
ISBN:	9798819366530

Fabrication of Bio-Based Intelligent Copolymer Film with Computational Technology for Real-Time Food Quality Monitoring and Protection /
Moses, Karyn E.,

Fabrication of Bio-Based Intelligent Copolymer Film with Computational Technology for Real-Time Food Quality Monitoring and Protection /Karyn E Moses. - 1 electronic resource (149 pages)

Source: Dissertations Abstracts International, Volume: 83-12, Section: B.

Globally, food is wasted and lost due to spoilage during the food supply chain. From farm to fork, the use of packaging in food distribution can improve and/or maintain food products by protection from exposed environments (e.g., temperature control and ventilation) that greatly influence food loss and waste (FLW). Despite packaging advancements, approximately one-third of food has still been lost from food contamination annually due to the lack of real-time, food spoilage detection methods during the supply chain. Also, the composition of the current packaging material is costly, has harmful effects, and is incapable of the spoilage and cross-contamination prevention. To reduce these food losses, food spoilage detection methods using environmental-friendly packaging materials must be researched. In this study, we first review the current state-of-the-art intelligent food packaging systems for food and packaging waste reduction in three aspects 1) material selection, 2) detection approaches, 3) functionality of materials. By understanding the reasons behind FLW (e.g., food spoilage and label confusion), effects to food security and safety can be pinpointed with packaging systems by describing the relationship between the three aspects. Then, we aim to use glycerol as the starting material to fabricate responsive, sensory films to detect and prevent food spoilage as well as communicate real-time food quality information to the users using smartphone imaging and machine learning approaches based on responses of a developed sensory film. The bio-based material was engineered for a film with high pH sensitivity to detect food spoilage by the color change. Meanwhile, it possessed the enhancements of the film's functionality for efficient barrier and thermomechanical properties for packaging adaptability. In addition, the behavior of the film material was captured and modelled into databases (i.e., colormaps) to elucidate food spoilage relationships and thus challenge the naked eye of detection with artificial intelligent approaches. The k-nearest neighbor (kNN) algorithm was coupled with image analysis to classify the food quality on pork loin. The analytical expression presented in this work can be used as a next level tool to monitor food items under various conditions and assist current, effective strategies in packaging systems to reduce FLW and environmental impacts on food.

English

ISBN: 9798819366530Subjects--Topical Terms:

3173303
Food science.
Subjects--Index Terms:

Intelligent food packaging

Fabrication of Bio-Based Intelligent Copolymer Film with Computational Technology for Real-Time Food Quality Monitoring and Protection /
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245 1 0 $a Fabrication of Bio-Based Intelligent Copolymer Film with Computational Technology for Real-Time Food Quality Monitoring and Protection / $c Karyn E Moses.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 1 electronic resource (149 pages)
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500 $a Source: Dissertations Abstracts International, Volume: 83-12, Section: B.
500 $a Advisors: Tong, Zhaohui Committee members: Correll, Melanie; Welt, Bruce; Gao, Bin; Dempere, Luisa A.
502 $b Ph.D. $c University of Florida $d 2021.
520 $a Globally, food is wasted and lost due to spoilage during the food supply chain. From farm to fork, the use of packaging in food distribution can improve and/or maintain food products by protection from exposed environments (e.g., temperature control and ventilation) that greatly influence food loss and waste (FLW). Despite packaging advancements, approximately one-third of food has still been lost from food contamination annually due to the lack of real-time, food spoilage detection methods during the supply chain. Also, the composition of the current packaging material is costly, has harmful effects, and is incapable of the spoilage and cross-contamination prevention. To reduce these food losses, food spoilage detection methods using environmental-friendly packaging materials must be researched. In this study, we first review the current state-of-the-art intelligent food packaging systems for food and packaging waste reduction in three aspects 1) material selection, 2) detection approaches, 3) functionality of materials. By understanding the reasons behind FLW (e.g., food spoilage and label confusion), effects to food security and safety can be pinpointed with packaging systems by describing the relationship between the three aspects. Then, we aim to use glycerol as the starting material to fabricate responsive, sensory films to detect and prevent food spoilage as well as communicate real-time food quality information to the users using smartphone imaging and machine learning approaches based on responses of a developed sensory film. The bio-based material was engineered for a film with high pH sensitivity to detect food spoilage by the color change. Meanwhile, it possessed the enhancements of the film's functionality for efficient barrier and thermomechanical properties for packaging adaptability. In addition, the behavior of the film material was captured and modelled into databases (i.e., colormaps) to elucidate food spoilage relationships and thus challenge the naked eye of detection with artificial intelligent approaches. The k-nearest neighbor (kNN) algorithm was coupled with image analysis to classify the food quality on pork loin. The analytical expression presented in this work can be used as a next level tool to monitor food items under various conditions and assist current, effective strategies in packaging systems to reduce FLW and environmental impacts on food.
546 $a English
590 $a School code: 0070
650 4 $a Food science. $3 3173303
650 4 $a Packaging. $3 585030
650 4 $a Agricultural engineering. $3 3168406
650 4 $a Materials science. $3 543314
650 4 $a Bioengineering. $3 657580
653 $a Intelligent food packaging
653 $a Food spoilage detection
653 $a Label confusion
653 $a Glycerol
653 $a Responsive, sensory films
653 $a Artificial intelligence
653 $a Food quality analysis
690 $a 0539
690 $a 0359
690 $a 0549
690 $a 0202
690 $a 0794
710 2 $a University of Florida. $b Agricultural and Biological Engineering. $e degree granting institution. $3 3826146
720 1 $a Tong, Zhaohui $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 83-12B.
790 $a 0070
791 $a Ph.D.
792 $a 2021
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28260078