Classic publications in food security research: A bibliometric analysis

Yuh-Shan Ho, Francis Lwesya
{"title":"Classic publications in food security research: A bibliometric analysis","authors":"Yuh-Shan Ho, Francis Lwesya","doi":"10.1002/wfp2.12066","DOIUrl":null,"url":null,"abstract":"The article presents classic publications in the field of food security from 1993 to 2022 using bibliometric methods. Data come from the Science Citation Index Expanded (SCI‐EXPANDED) of the Web of Science database. The results show that the years 2010 and 2011 stand out as the most prolific, with a total of three classic articles receiving the highest citations. The articles show that agricultural intensification does not necessarily lead to increased yields but rather contributes to environmental degradation through deforestation, biodiversity loss, and ultimately climate change. The articles highlight the adoption of ecologically friendly methods, natural solution, and technology‐based and sustainable agricultural practices to reduce the impact of climate change and address food insecurity. However, linking agricultural intensification to biodiversity conservation and hunger and the effectiveness of different adaptation models in the increasing variability of extreme events remain complex issues that require further research in the future. Similarly, machine learning research can be used to address food insecurity, especially in crop or plant, and forestry tree breeding, precision agriculture, and so forth.","PeriodicalId":500600,"journal":{"name":"World Food Policy","volume":"57 3","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Food Policy","FirstCategoryId":"0","ListUrlMain":"https://doi.org/10.1002/wfp2.12066","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The article presents classic publications in the field of food security from 1993 to 2022 using bibliometric methods. Data come from the Science Citation Index Expanded (SCI‐EXPANDED) of the Web of Science database. The results show that the years 2010 and 2011 stand out as the most prolific, with a total of three classic articles receiving the highest citations. The articles show that agricultural intensification does not necessarily lead to increased yields but rather contributes to environmental degradation through deforestation, biodiversity loss, and ultimately climate change. The articles highlight the adoption of ecologically friendly methods, natural solution, and technology‐based and sustainable agricultural practices to reduce the impact of climate change and address food insecurity. However, linking agricultural intensification to biodiversity conservation and hunger and the effectiveness of different adaptation models in the increasing variability of extreme events remain complex issues that require further research in the future. Similarly, machine learning research can be used to address food insecurity, especially in crop or plant, and forestry tree breeding, precision agriculture, and so forth.
粮食安全研究方面的经典出版物:文献计量分析
文章采用文献计量学方法介绍了 1993 年至 2022 年粮食安全领域的经典出版物。数据来自科学网数据库的科学引文索引扩展版(SCI-EXPANDED)。结果显示,2010 年和 2011 年的文章最多,共有三篇经典文章的引用率最高。这些文章表明,农业集约化并不一定会带来增产,反而会因森林砍伐、生物多样性丧失以及最终的气候变化而导致环境退化。这些文章强调采用生态友好型方法、自然解决方案以及以技术为基础的可持续农业实践,以减少气候变化的影响并解决粮食不安全问题。然而,将农业集约化与生物多样性保护和饥饿联系起来,以及不同的适应模式在极端事件日益多变的情况下的有效性,仍然是需要在未来进一步研究的复杂问题。同样,机器学习研究也可用于解决粮食不安全问题,特别是在作物或植物、林木育种、精准农业等方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信