year 13, Issue 1 (5-2026)
CJS 2026, 13(1): 64-79 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Naderi Mahdei K, Ghaffari S, Asadpourian Z. Scientometric Analysis of Sustainable Agriculture Research: From Knowledge Structure to Emerging Trends. CJS 2026; 13 (1) :64-79
URL: http://cjs.mubabol.ac.ir/article-1-417-en.html
URL: http://cjs.mubabol.ac.ir/article-1-417-en.html
Department of Agricultural Extension and Education, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran , zeinab.asadporiuan24@gmail.com
Abstract: (25 Views)
Background and aim: In recent decades, challenges such as climate change and food insecurity have made sustainable agriculture a critical necessity. This study employs a bibliometric approach to examine publication trends, knowledge structures, and emerging topics in sustainable agriculture research, aiming to provide a deeper understanding of the field’s evolutionary trajectory.
Materials and methods: This study employed a scientometric approach to examine research articles on sustainable agriculture. The study population comprised English-language articles in the field of social sciences indexed in the Scopus database from 2000 to 2025. Data collection was performed using a Boolean search strategy that incorporated the keywords “sustainable agriculture” and “agricultural sustainability”, restricted to the titles, abstracts, and keyword fields of the articles. After applying filters including subject area (social sciences), document type (article), language (English), and time period, a total of 3,035 articles were analyzed. To map the knowledge structure, methods such as scientific collaboration networks of countries, keyword co-occurrence analysis, and thematic clustering were used. The H-index and citation counts were calculated to assess the visibility and impact of the research. Statistical and network analyses were performed using R, VOSviewer, and SPSS software.
Findings: The findings revealed an annual growth rate of 10.22% in publications related to sustainable agriculture. Keyword co-occurrence analysis identified six main conceptual clusters, with “sustainability”, “food security”, and “sustainable development” being the most frequent keywords. Analysis of emerging trends indicated a growing research focus on topics such as food security, climate change, adaptation, and the application of machine learning, highlighting the interdisciplinary nature of the field. Correlation analysis showed a significant positive relationship between the number of publications and publication year (r= 0.803), and a significant negative relationship between the number of publications and citation counts
(r= 0.805).
Conclusion: The results suggest that advancing sustainable agriculture requires strengthening interdisciplinary collaborations, developing comprehensive sustainability indicators, and placing greater emphasis on long-term impact assessment. This analysis can serve as an effective guide for policymakers and researchers in setting future research priorities.
Materials and methods: This study employed a scientometric approach to examine research articles on sustainable agriculture. The study population comprised English-language articles in the field of social sciences indexed in the Scopus database from 2000 to 2025. Data collection was performed using a Boolean search strategy that incorporated the keywords “sustainable agriculture” and “agricultural sustainability”, restricted to the titles, abstracts, and keyword fields of the articles. After applying filters including subject area (social sciences), document type (article), language (English), and time period, a total of 3,035 articles were analyzed. To map the knowledge structure, methods such as scientific collaboration networks of countries, keyword co-occurrence analysis, and thematic clustering were used. The H-index and citation counts were calculated to assess the visibility and impact of the research. Statistical and network analyses were performed using R, VOSviewer, and SPSS software.
Findings: The findings revealed an annual growth rate of 10.22% in publications related to sustainable agriculture. Keyword co-occurrence analysis identified six main conceptual clusters, with “sustainability”, “food security”, and “sustainable development” being the most frequent keywords. Analysis of emerging trends indicated a growing research focus on topics such as food security, climate change, adaptation, and the application of machine learning, highlighting the interdisciplinary nature of the field. Correlation analysis showed a significant positive relationship between the number of publications and publication year (r= 0.803), and a significant negative relationship between the number of publications and citation counts
(r= 0.805).
Conclusion: The results suggest that advancing sustainable agriculture requires strengthening interdisciplinary collaborations, developing comprehensive sustainability indicators, and placing greater emphasis on long-term impact assessment. This analysis can serve as an effective guide for policymakers and researchers in setting future research priorities.
Keywords: Sustainable agriculture, Scientometrics, Scopus database, Co-word analysis, Drawing a scientific map
Type of Study: Orginal |
Subject:
Scientometrics
Received: 2025/12/29 | Revised: 2026/05/27 | Accepted: 2026/05/30 | ePublished: 2026/06/9
Received: 2025/12/29 | Revised: 2026/05/27 | Accepted: 2026/05/30 | ePublished: 2026/06/9
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
