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Data-driven decarbonisation pathways for reducing life cycle GHG emissions from food waste in the hospitality and food service sectors
The Hospitality and Food Service (HaFS) sectors are notoriously known for their contribution to the food waste problem. Hence, there is an urgent need to devise strategies to reduce food waste in the HaFS sectors and to decarbonise their operation to help fight hunger, achieve food security, improve...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9829725/ https://www.ncbi.nlm.nih.gov/pubmed/36624147 http://dx.doi.org/10.1038/s41598-022-27053-6 |
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author | Cheng, I Kit Leong, Kin K. |
author_facet | Cheng, I Kit Leong, Kin K. |
author_sort | Cheng, I Kit |
collection | PubMed |
description | The Hospitality and Food Service (HaFS) sectors are notoriously known for their contribution to the food waste problem. Hence, there is an urgent need to devise strategies to reduce food waste in the HaFS sectors and to decarbonise their operation to help fight hunger, achieve food security, improve nutrition and mitigate climate change. This study proposes three streams to decarbonise the staff cafeteria operation in an integrated resort in Macau. These include upstream optimisation to reduce unserved food waste, midstream education to raise awareness amongst staff about the impact of food choices on the climate and health, and finally downstream recognition to reduce edible plate waste using a state-of-the-art computer vision system. Technology can be an effective medium to facilitate desired behavioural change through nudging, much like how speed cameras can cause people to slow down and help save lives. The holistic and data-driven approach taken revealed great potential for organisations or institutions that offer catering services to reduce their food waste and associated carbon footprint whilst educating individuals about the intricate link between food, climate and well-being. |
format | Online Article Text |
id | pubmed-9829725 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98297252023-01-11 Data-driven decarbonisation pathways for reducing life cycle GHG emissions from food waste in the hospitality and food service sectors Cheng, I Kit Leong, Kin K. Sci Rep Article The Hospitality and Food Service (HaFS) sectors are notoriously known for their contribution to the food waste problem. Hence, there is an urgent need to devise strategies to reduce food waste in the HaFS sectors and to decarbonise their operation to help fight hunger, achieve food security, improve nutrition and mitigate climate change. This study proposes three streams to decarbonise the staff cafeteria operation in an integrated resort in Macau. These include upstream optimisation to reduce unserved food waste, midstream education to raise awareness amongst staff about the impact of food choices on the climate and health, and finally downstream recognition to reduce edible plate waste using a state-of-the-art computer vision system. Technology can be an effective medium to facilitate desired behavioural change through nudging, much like how speed cameras can cause people to slow down and help save lives. The holistic and data-driven approach taken revealed great potential for organisations or institutions that offer catering services to reduce their food waste and associated carbon footprint whilst educating individuals about the intricate link between food, climate and well-being. Nature Publishing Group UK 2023-01-09 /pmc/articles/PMC9829725/ /pubmed/36624147 http://dx.doi.org/10.1038/s41598-022-27053-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Cheng, I Kit Leong, Kin K. Data-driven decarbonisation pathways for reducing life cycle GHG emissions from food waste in the hospitality and food service sectors |
title | Data-driven decarbonisation pathways for reducing life cycle GHG emissions from food waste in the hospitality and food service sectors |
title_full | Data-driven decarbonisation pathways for reducing life cycle GHG emissions from food waste in the hospitality and food service sectors |
title_fullStr | Data-driven decarbonisation pathways for reducing life cycle GHG emissions from food waste in the hospitality and food service sectors |
title_full_unstemmed | Data-driven decarbonisation pathways for reducing life cycle GHG emissions from food waste in the hospitality and food service sectors |
title_short | Data-driven decarbonisation pathways for reducing life cycle GHG emissions from food waste in the hospitality and food service sectors |
title_sort | data-driven decarbonisation pathways for reducing life cycle ghg emissions from food waste in the hospitality and food service sectors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9829725/ https://www.ncbi.nlm.nih.gov/pubmed/36624147 http://dx.doi.org/10.1038/s41598-022-27053-6 |
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