Enhancing Agri-Food Transparent Sustainability - EATS

增强农业食品的透明可持续性 - EATS

• 批准号: EP/V042270/1
• 负责人: Georgios Leontidis
• 金额: $ 52.05万
• 依托单位: University of Aberdeen
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FV042270%2F1
• 关键词: Enhancing; Agri; Food; Transparent; Sustainability

The UK has a legally binding target of 'net zero' greenhouse gas (GHG) emissions for 2050 (Scotland, 2045) and the Food and Drink sector has a vitally important role to play in helping to achieve this. This must be done while also improving nutrition, protection of ecosystems, reduced risks to soil, water and air quality. Delivery against these ambitious targets will require a range of measures to be adopted across the agri-food supply chain - not just primary producers but also processors, retailers and ultimately consumers. Over the last few decades rapid advances in processes to collect, monitor, disclose, and disseminate information (broadly classified under the concept of 'transparency') have contributed towards the development of entirely new modes of environmental monitoring and governance for supply chains. Unfortunately, existing approaches often suffer from limitations in terms of collection and dissemination of data; over-simplification of supply chains; power dynamics influencing information inclusion/exclusion decisions; and potentially perverse outcomes regarding how the information is used, by whom and to what effect. Given these issues, we need to consider how best to capture information about supply chains in order to document existing sustainability practices in sufficient detail; this is necessary to not only support monitoring and reporting needs of all stakeholders, but also to promote additional pro-environmental behaviours and even re-configuration of the supply chain. Our vision is built around an actionable information ecosystem whose purpose is to deliver transparent sustainability - realised via three pillars that we refer to as: SEE-SHARE-ACT. The first of these encompasses the role of sensors and carbon reporting tools in capturing data about agri-food processes (SEE); the second is a trusted digital platform able to manage sustainability data and report it across supply chain actors(SHARE); the third is the use of data-analytics and machine learning to support decision-making and action (ACT). But what would a trusted infrastructure for transparent sustainability look like, and how would it be framed by (and operate within) its wider environmental, social and economic context? Also - how would such a framework go beyond simply documenting the elements of a supply chain (actors, processes, inputs, outputs) to enable a holistic approach to monitoring, pro-environmental decision-making and action? We have assembled an interdisciplinary team of academics and user organisations spanning the livestock, soft-fruit and brewing sectors to investigate transparent sustainability. Together we will explore the following questions:What datasets, indicators and decision-making processes are relevant to the different actors participating in supply chains to realize sustainable food futures (in the DE)? How do we formulate appropriate vocabularies with which to characterise sustainability practices, their context and rationale, and facilitate data capture and integration? Can we realize a provenance-based sustainability solution for supply chains, operating across a range of technologies and organisational boundaries, that is trusted and able to facilitate pro-environmental decision-making and action? How do we exploit sustainability data assets and ML/AI technologies to inform decision making towards net-zero, resulting in demonstrable changes to practice and behaviour? Answers to these (and the many other questions that will certainly emerge) will lead us to develop prototype solutions that will be evaluated with project partners. Our ambition is to create a means by which farmers and other food and drink supply chain stakeholders can create a more sustainable economy built upon trusted data regarding the lifecycle history of products for enhanced environmental and product safety in (therefore more resilient) food supply chains.

英国制定了具有法律约束力的 2050 年温室气体 (GHG) 净零排放目标（苏格兰，2045），而食品和饮料行业在帮助实现这一目标方面可以发挥至关重要的作用。做到这一点的同时，还必须改善营养、保护生态系统、降低土壤、水和空气质量的风险。要实现这些雄心勃勃的目标，需要在整个农业食品供应链中采取一系列措施——不仅包括初级生产商，还包括加工商、零售商和最终消费者。在过去的几十年里，收集、监测、披露和传播信息（大致归类为“透明度”概念）流程的快速进步促进了供应链环境监测和治理的全新模式的发展。不幸的是，现有的方法常常在数据收集和传播方面受到限制；供应链过度简化；影响信息包含/排除决策的权力动态；以及关于信息如何使用、由谁使用以及达到何种效果的潜在不良结果。鉴于这些问题，我们需要考虑如何最好地捕获有关供应链的信息，以便足够详细地记录现有的可持续发展实践；这不仅是为了支持所有利益攸关方的监测和报告需求，也是为了促进更多的环保行为，甚至是供应链的重新配置。我们的愿景是围绕一个可操作的信息生态系统构建的，其目的是提供透明的可持续性——通过我们称之为“查看-分享-行动”的三大支柱来实现。第一个包括传感器和碳报告工具在捕获农业食品加工数据方面的作用（SEE）；第二个是一个值得信赖的数字平台，能够管理可持续发展数据并跨供应链参与者报告（共享）；第三是利用数据分析和机器学习来支持决策和行动（ACT）。但实现透明可持续发展的可信基础设施会是什么样子？它如何在更广泛的环境、社会和经济背景下构建（并在其中运作）？此外，这样的框架如何超越简单地记录供应链要素（参与者、流程、输入、输出），以实现监测、环保决策和行动的整体方法？我们组建了一支由学者和用户组织组成的跨学科团队，涵盖畜牧业、软果和酿造行业，以研究透明的可持续性。我们将共同探讨以下问题：哪些数据集、指标和决策过程与参与供应链以实现可持续食品未来（在DE）的不同参与者相关？我们如何制定适当的词汇来描述可持续发展实践、其背景和原理，并促进数据捕获和整合？我们能否为供应链实现基于来源的可持续解决方案，跨一系列技术和组织边界运作，值得信赖并能够促进环保决策和行动？我们如何利用可持续发展数据资产和机器学习/人工智能技术来为实现净零排放的决策提供信息，从而对实践和行为产生明显的变化？这些问题（以及肯定会出现的许多其他问题）的答案将引导我们开发原型解决方案，并与项目合作伙伴一起进行评估。我们的目标是创造一种方法，使农民和其他食品和饮料供应链利益相关者能够创建一个更加可持续的经济，该经济建立在有关产品生命周期历史的可信数据的基础上，以增强（因此更具弹性）食品供应链中的环境和产品安全。

项目成果

Model Pruning Enables Localized and Efficient Federated Learning for Yield Forecasting and Data Sharing

• DOI: 10.1016/j.eswa.2023.122847
• 发表时间: 2023-04
• 期刊: Expert Syst. Appl.
• 作者: An-dong Li;Milan Markovic;P. Edwards;G. Leontidis