{"title":"Is artificial intelligence revolutionising agricultural sciences yet? An AI-based bibliometric analysis","authors":"Marcin Kozak","doi":"10.1111/aab.70010","DOIUrl":null,"url":null,"abstract":"<p>Artificial intelligence (AI) has been increasingly influencing both the general public and scientific research, yet its adoption in agricultural sciences remains unclear. While recent reviews suggest that AI has already permeated agricultural research, no systematic study has examined this phenomenon. This study employs a bibliometric analysis to assess AI-related publication trends using metadata from 14 agricultural and applied biology journals, along with a reference methodological journal (<i>Computers and Electronics in Agriculture</i>), covering the period from 2010 to 2023. The findings reveal a significant rise in AI-related studies in methodological quantitative research for agricultural sciences, with over 60% of recent articles in <i>Computers and Electronics in Agriculture</i> incorporating AI. This trend, however, has not yet extended to applied agricultural research, where AI-related publications remain a small fraction of the total output. These results indicate that while AI is transforming methodological studies related to data science for agriculture, its broader adoption in applied agricultural research is still in its early stages.</p>","PeriodicalId":7977,"journal":{"name":"Annals of Applied Biology","volume":"187 1","pages":"121-136"},"PeriodicalIF":1.8000,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Applied Biology","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/aab.70010","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AGRICULTURE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) has been increasingly influencing both the general public and scientific research, yet its adoption in agricultural sciences remains unclear. While recent reviews suggest that AI has already permeated agricultural research, no systematic study has examined this phenomenon. This study employs a bibliometric analysis to assess AI-related publication trends using metadata from 14 agricultural and applied biology journals, along with a reference methodological journal (Computers and Electronics in Agriculture), covering the period from 2010 to 2023. The findings reveal a significant rise in AI-related studies in methodological quantitative research for agricultural sciences, with over 60% of recent articles in Computers and Electronics in Agriculture incorporating AI. This trend, however, has not yet extended to applied agricultural research, where AI-related publications remain a small fraction of the total output. These results indicate that while AI is transforming methodological studies related to data science for agriculture, its broader adoption in applied agricultural research is still in its early stages.
期刊介绍:
Annals of Applied Biology is an international journal sponsored by the Association of Applied Biologists. The journal publishes original research papers on all aspects of applied research on crop production, crop protection and the cropping ecosystem. The journal is published both online and in six printed issues per year.
Annals papers must contribute substantially to the advancement of knowledge and may, among others, encompass the scientific disciplines of:
Agronomy
Agrometeorology
Agrienvironmental sciences
Applied genomics
Applied metabolomics
Applied proteomics
Biodiversity
Biological control
Climate change
Crop ecology
Entomology
Genetic manipulation
Molecular biology
Mycology
Nematology
Pests
Plant pathology
Plant breeding & genetics
Plant physiology
Post harvest biology
Soil science
Statistics
Virology
Weed biology
Annals also welcomes reviews of interest in these subject areas. Reviews should be critical surveys of the field and offer new insights. All papers are subject to peer review. Papers must usually contribute substantially to the advancement of knowledge in applied biology but short papers discussing techniques or substantiated results, and reviews of current knowledge of interest to applied biologists will be considered for publication. Papers or reviews must not be offered to any other journal for prior or simultaneous publication and normally average seven printed pages.