Science Mapping of Meta-Analysis in Agricultural Science

Weiting Ding · Jialu Li · Yeru Wu · Hailong He

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scientometrics and bibliometrics research Meta-analysis and systematic reviews Psychology Research and Bibliometrics

Abstract

As a powerful statistical method, meta-analysis has been applied increasingly in agricultural science with remarkable progress. However, meta-analysis research reports in the agricultural discipline still need to be systematically combed. Scientometrics is often used to quantitatively analyze research on certain themes. In this study, the literature from a 30-year period (1992–2021) was retrieved based on the Web of Science database, and a quantitative analysis was performed using the VOSviewer and CiteSpace visual analysis software packages. The objective of this study was to investigate the current application of meta-analysis in agricultural sciences, the latest research hotspots, and trends, and to identify influential authors, research institutions, countries, articles, and journal sources. Over the past 30 years, the volume of the meta-analysis literature in agriculture has increased rapidly. We identified the top three authors (Sauvant D, Kebreab E, and Huhtanen P), the top three contributing organizations (Chinese Academy of Sciences, National Institute for Agricultural Research, and Northwest A&F University), and top three productive countries (the USA, China, and France). Keyword cluster analysis shows that the meta-analysis research in agricultural sciences falls into four categories: climate change, crop yield, soil, and animal husbandry. Jeffrey (2011) is the most influential and cited research paper, with the highest utilization rate for the Journal of Dairy Science. This paper objectively evaluates the development of meta-analysis in the agricultural sciences using bibliometrics analysis, grasps the development frontier of agricultural research, and provides insights into the future of related research in the agricultural sciences.

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References

2002Quantifying heterogeneity in a meta‐analysis 2009Software survey: VOSviewer, a computer program for bibliometric mapping 2021PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews 2013Power failure: why small sample size undermines the reliability of neuroscience 2021The PRISMA 2020 statement: An updated guideline for reporting systematic reviews 1999THE META-ANALYSIS OF RESPONSE RATIOS IN EXPERIMENTAL ECOLOGY 2011Science mapping software tools: Review, analysis, and cooperative study among tools 2004Searching for intellectual turning points: Progressive knowledge domain visualization

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