Artículo

Bibliometric analysis of publications discussing the use of the artificial intelligence technique agent-based models in sustainable agriculture

Resumen

The purpose of this article consists of analyzing publications discussing the use of agent-based artificial intelligence models in sustainable agriculture research. The analysis involved bibliometric indicators and the Rstudio software with Bibliometrix library. The methodology is descriptive with a quantitative approach. Scientific databases SCOPUS and Web of Science were consulted and the PRISMA methodology was used during the selection process. This led to finding 86 publications that met the inclusion criteria. Amongst the results, United States was listed as the country with the highest production of scientific material, although France had a higher impact. Additionally, the bibliographical resources that help promote scientific development are open source. It was concluded that the agent-based model has been adopted to simulate different scenarios, which help decision-makers to formulate public policies in favor of sustainable agriculture. This optimizes the use of natural resources and reduces negative consequences for the environment, while also delivering value for the stakeholders of the agricultural system.
Wu, Ruishan (59528115400); Mai, Zhensheng (57295116000); Song, Xiaoyan (59527466400); Zhao, Wenzhong (55725970700)
Hotspots and research trends of gut microbiome in polycystic ovary syndrome: a bibliometric analysis (2012–2023)
2024
10.3389/fmicb.2024.1524521
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85215979774&doi=10.3389%2ffmicb.2024.1524521&partnerID=40&md5=b0ddca5683a81046a48e01743b209408
NHC Key Laboratory of Male Reproduction and Genetics, Guangdong Provincial Reproductive Science Institute, Guangdong Provincial Fertility Hospital, Guangzhou, China; Department of Obstetrics and Gynecology, First People’s Hospital of Foshan, Foshan, China
All Open Access; Gold Open Access
Scopus
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