• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

数字技术对欧盟可持续粮食生产和消费影响的纵向分析

A Longitudinal Analysis of the Impact of Digital Technologies on Sustainable Food Production and Consumption in the European Union.

作者信息

Bocean Claudiu George

机构信息

Department of Management, Marketing and Business Administration, Faculty of Economics and Business Administration, University of Craiova, 13 AI Cuza Street, 200585 Craiova, Romania.

出版信息

Foods. 2024 Apr 22;13(8):1281. doi: 10.3390/foods13081281.

DOI:10.3390/foods13081281
PMID:38672953
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11049518/
Abstract

In today's landscape, digital technologies hold immense potential in tackling challenges associated with food sustainability. This study aims to contextualize a broader investigation of food sustainability and digitalization within the agricultural sector. Its objective is to explore the influence of digital technologies on sustainable food production and consumption, particularly examining relationships among digital technologies, municipal waste, agricultural output, nitrogen emissions, methane emissions from agriculture, and Goal 12 Responsible Consumption and Production (SDG12). Through the use of Structural Equation Modeling, the empirical investigation scrutinizes the relationships between digital technology use and critical variables linked to food sustainability in a longitudinal analysis. The results highlight the significant impact of extensive digital technology use on municipal waste, sustainable production, and consumption, indirectly influencing greenhouse gas (GHG) emissions. Empirical research findings reveal a negative influence of digital technologies on responsible consumption and production (path coefficient -0.349, values < 0.001), suggesting an impact of digital technologies on diminishing sustainability in consumption and production. The relationship between digital technologies and municipal solid waste is also negative (path coefficient -0.360, values < 0.001), suggesting that the use of digital technologies can contribute to reducing the amount of municipal solid waste. Digitalization has the potential to improve the sustainability of supply chains by reducing resource consumption and greenhouse gas emissions associated with production and distribution operations.

摘要

在当今形势下,数字技术在应对与粮食可持续性相关的挑战方面具有巨大潜力。本研究旨在将对农业部门粮食可持续性和数字化的更广泛调查置于具体情境中。其目的是探讨数字技术对可持续粮食生产和消费的影响,特别是研究数字技术、城市垃圾、农业产出、氮排放、农业甲烷排放以及目标12“负责任的消费和生产”(可持续发展目标12)之间的关系。通过使用结构方程模型,实证研究在纵向分析中审视了数字技术使用与与粮食可持续性相关的关键变量之间的关系。结果突出了广泛使用数字技术对城市垃圾、可持续生产和消费的重大影响,间接影响了温室气体(GHG)排放。实证研究结果显示数字技术对负责任的消费和生产有负面影响(路径系数为 -0.349,p值<0.001),这表明数字技术对消费和生产中可持续性的降低有影响。数字技术与城市固体废物之间的关系也是负面的(路径系数为 -0.360,p值<0.001),这表明数字技术的使用有助于减少城市固体废物的数量。数字化有潜力通过减少与生产和分销运营相关的资源消耗和温室气体排放来提高供应链的可持续性。

相似文献

1
A Longitudinal Analysis of the Impact of Digital Technologies on Sustainable Food Production and Consumption in the European Union.数字技术对欧盟可持续粮食生产和消费影响的纵向分析
Foods. 2024 Apr 22;13(8):1281. doi: 10.3390/foods13081281.
2
Assessment of the greenhouse effect impact of technologies used for energy recovery from municipal waste: a case for England.城市垃圾能源回收技术的温室效应影响评估:以英格兰为例
J Environ Manage. 2009 Jul;90(10):2999-3012. doi: 10.1016/j.jenvman.2009.04.012. Epub 2009 May 30.
3
Advancements in technology and innovation for sustainable agriculture: Understanding and mitigating greenhouse gas emissions from agricultural soils.农业可持续发展的技术进步与创新:了解和减轻农业土壤温室气体排放
J Environ Manage. 2023 Dec 1;347:119147. doi: 10.1016/j.jenvman.2023.119147. Epub 2023 Sep 28.
4
Quantification of landfill gas emissions and energy production potential in Tirupati Municipal solid waste disposal site by LandGEM mathematical model.利用LandGEM数学模型对蒂鲁伯蒂市固体废物处理场的填埋气排放量和能源生产潜力进行量化
MethodsX. 2022 Sep 20;9:101869. doi: 10.1016/j.mex.2022.101869. eCollection 2022.
5
Future agricultural systems and the role of digitalization for achieving sustainability goals. A review.未来农业系统以及数字化在实现可持续发展目标中的作用。综述。
Agron Sustain Dev. 2022;42(4):70. doi: 10.1007/s13593-022-00792-6. Epub 2022 Jul 6.
6
Environmental sustainability assessment using dynamic Autoregressive-Distributed Lag simulations-Nexus between greenhouse gas emissions, biomass energy, food and economic growth.采用动态自回归-分布滞后模拟进行环境可持续性评估-温室气体排放、生物质能、粮食和经济增长之间的关系。
Sci Total Environ. 2019 Jun 10;668:318-332. doi: 10.1016/j.scitotenv.2019.02.432. Epub 2019 Mar 1.
7
The Minderoo-Monaco Commission on Plastics and Human Health.美诺集团-摩纳哥基金会塑料与人体健康委员会
Ann Glob Health. 2023 Mar 21;89(1):23. doi: 10.5334/aogh.4056. eCollection 2023.
8
Transformational Steam Infusion Processing for Resilient and Sustainable Food Manufacturing Businesses.面向具有韧性和可持续性的食品制造企业的变革性蒸汽注入加工
Foods. 2021 Jul 30;10(8):1763. doi: 10.3390/foods10081763.
9
Potential Energy and Environmental Footprint Savings from Reducing Food Loss and Waste in Europe: A Scenario-Based Multiregional Input-Output Analysis.欧洲减少食物损失和浪费所带来的潜在能源与环境足迹节约:基于情景的多区域投入产出分析
Environ Sci Technol. 2023 Oct 31;57(43):16296-16308. doi: 10.1021/acs.est.3c00158. Epub 2023 Oct 20.
10
Trends in greenhouse gas emissions from consumption and production of animal food products - implications for long-term climate targets.动物食品消费和生产导致温室气体排放的趋势-对长期气候目标的影响。
Animal. 2013 Feb;7(2):330-40. doi: 10.1017/S1751731112001498. Epub 2012 Jul 13.

引用本文的文献

1
Impacts of Various Straw Mulching Strategies on Soil Water, Nutrients, Thermal Regimes, and Yield in Wheat-Soybean Rotation Systems.不同秸秆覆盖策略对小麦-大豆轮作系统土壤水分、养分、热状况及产量的影响
Plants (Basel). 2025 Jul 19;14(14):2233. doi: 10.3390/plants14142233.
2
Exploring the Drivers of Food Waste in the EU: A Multidimensional Analysis Using Cluster and Neural Network Models.探索欧盟食物浪费的驱动因素:使用聚类和神经网络模型的多维分析
Foods. 2025 Apr 15;14(8):1358. doi: 10.3390/foods14081358.
3
Critical Issues Faced by Industries Associated with Food Science and Technology: A Delphi Analysis.

本文引用的文献

1
The next protein transition.下一个蛋白质转变。
Trends Food Sci Technol. 2020 Nov;105:515-522. doi: 10.1016/j.tifs.2018.07.008. Epub 2018 Jul 27.
2
Global greenhouse gas emissions from animal-based foods are twice those of plant-based foods.来自动物性食品的全球温室气体排放量是植物性食品的两倍。
Nat Food. 2021 Sep;2(9):724-732. doi: 10.1038/s43016-021-00358-x. Epub 2021 Sep 13.
3
Multiple Facets of Nitrogen: From Atmospheric Gas to Indispensable Agricultural Input.氮的多面性:从大气气体到不可或缺的农业投入
食品科学与技术相关行业面临的关键问题:德尔菲分析
Foods. 2024 Dec 21;13(24):4149. doi: 10.3390/foods13244149.
4
Tackling Food Waste: An Exploratory Case Study on Consumer Behavior in Romania.应对食物浪费:罗马尼亚消费者行为的探索性案例研究
Foods. 2024 Oct 18;13(20):3313. doi: 10.3390/foods13203313.
Life (Basel). 2022 Aug 19;12(8):1272. doi: 10.3390/life12081272.
4
Digitalization to achieve sustainable development goals: Steps towards a Smart Green Planet.数字化实现可持续发展目标:迈向智能绿色星球的步骤。
Sci Total Environ. 2021 Nov 10;794:148539. doi: 10.1016/j.scitotenv.2021.148539. Epub 2021 Jun 19.
5
A systematic literature review on food waste/loss prevention and minimization methods.关于食物浪费/损耗预防和最小化方法的系统文献综述。
J Environ Manage. 2021 May 15;286:112268. doi: 10.1016/j.jenvman.2021.112268. Epub 2021 Mar 5.
6
Digital technology dilemma: on unlocking the soil quality index conundrum.数字技术困境:破解土壤质量指数难题
Bioresour Bioprocess. 2021;8(1):6. doi: 10.1186/s40643-020-00359-x. Epub 2021 Jan 10.
7
Articulating the effect of food systems innovation on the Sustainable Development Goals.阐述食品系统创新对可持续发展目标的影响。
Lancet Planet Health. 2021 Jan;5(1):e50-e62. doi: 10.1016/S2542-5196(20)30277-1. Epub 2020 Dec 9.
8
Supporting food systems transformation: The what, why, who, where and how of mission-oriented agricultural innovation systems.支持粮食系统转型:面向任务的农业创新体系的内容、原因、主体、地点及方式
Agric Syst. 2020 Sep;184:102901. doi: 10.1016/j.agsy.2020.102901. Epub 2020 Aug 5.
9
IoT-Blockchain Enabled Optimized Provenance System for Food Industry 4.0 Using Advanced Deep Learning.物联网-区块链启用的食品工业 4.0 优化溯源系统,采用先进的深度学习技术。
Sensors (Basel). 2020 May 25;20(10):2990. doi: 10.3390/s20102990.
10
The greenhouse gas impacts of converting food production in England and Wales to organic methods.将英格兰和威尔士的粮食生产转换为有机方法对温室气体的影响。
Nat Commun. 2019 Oct 22;10(1):4641. doi: 10.1038/s41467-019-12622-7.