Sustainable consumption by reducing food waste: A review of the current state and directions for future research

Esther Alvarez de los Mozos, Fazleena Badurdeen, Paul Eric Dossou

Research output: Contribution to journalConference articlepeer-review

20 Scopus citations

Abstract

Almost one third of all food produced in the world currently goes to waste. One of the targets under the 'Responsible consumption and production' sustainable development goal calls for halving the per capita food waste at the consumer level as well as across the supply chain from manufacturing, storage and retail by 2030. While numerous strategies have been recommended and implemented to address this problem, major challenges remain to be overcome. The paper presents an in-depth review of current state-of-art practices in food waste management. The solutions and recommendations presented to reduce food waste at the household, retail, restaurant, manufacturing and supply chain levels are reviewed. Regulations and regional variations in food waste management practices are also examined. The findings are used to identify research gaps and propose a conceptual framework to increase closed-loop material flow for more circular food systems that can reduce food waste. Potential areas for application of engineering and management principles to develop analytical models for food waste reduction are also discussed.

Original languageEnglish
Pages (from-to)1791-1798
Number of pages8
JournalProcedia Manufacturing
Volume51
DOIs
StatePublished - 2020
Event30th International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2021 - Athens, Greece
Duration: Jun 15 2021Jun 18 2021

Bibliographical note

Publisher Copyright:
© 2020 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the scientific committee of the FAIM 2021.

Keywords

  • Circular economy
  • Food waste management

ASJC Scopus subject areas

  • Artificial Intelligence
  • Industrial and Manufacturing Engineering

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