Digitizing Fresh Food Supply Chains to Reduce Loss and Waste

Carlos Esquerre Fernandez, Anastasia Ktenioudaki, Emily Crofton, Cristina Botinestean, Jean Pierre Emond, Ultan McCarthy

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Food loss and waste is an ever increasing challenge facing humankind from both a corporate and social perspective. A key driver of this challenge is the requirement to continue to offer and in some cases increase the range of products offered to the consumer both in and out of the local season. Coupled with this is also a requirement to increase, or at the very least maintain supply networks that are flexible, adaptive, responsive and fully transparent, comply with local and international policy and maintain tight margins. A solution requires the implementation of policies, procedures and frameworks to promote standardization, collective effort and shared value and burden across global food supply chain. To address these challenges, a digital remaining shelf life predictor tool was designed using an array state of the art Convolution Neural Networking (CNNs) and machine learning techniques architected within an array of low cost industry affordable technology. This digital tool is designed to (1) determine quality of and (2) predict remaining shelf-life (RSL) of fresh produce across the supply chain. Provisioning this information will empower all stakeholders regardless of their positioning in the supply chain, to adopt a First Expired First Out (FEFO) biologic-based supply chain, facilitating a product-based decision framework yielding more agile, responsive and efficient supply chains. Preliminary results indicate an overall accuracy of prediction of 99.9 % from a theoretical industry standard (best case scenario) of 84 %.

Original languageEnglish
Title of host publication2023 IEEE Conference on AgriFood Electronics, CAFE 2023 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages94-98
Number of pages5
ISBN (Electronic)9798350327113
DOIs
Publication statusPublished - 25 Sep 2023
Event1st IEEE Conference on AgriFood Electronics, CAFE 2023 - Torino, Italy
Duration: 25 Sep 202327 Sep 2023

Publication series

Name2023 IEEE Conference on AgriFood Electronics (CAFE)

Conference

Conference1st IEEE Conference on AgriFood Electronics, CAFE 2023
Country/TerritoryItaly
CityTorino
Period25/09/202327/09/2023

Keywords

  • Circular Bioeconomy
  • Digital food supply chains
  • Digital Shelf life
  • Food Waste

Fingerprint

Dive into the research topics of 'Digitizing Fresh Food Supply Chains to Reduce Loss and Waste'. Together they form a unique fingerprint.

Cite this