Welcome to Chinese Agricultural Science Bulletin,

Chinese Agricultural Science Bulletin ›› 2022, Vol. 38 ›› Issue (31): 154-164.doi: 10.11924/j.issn.1000-6850.casb2021-1011

Special Issue: 生物技术 现代农业发展与乡村振兴 农业生态

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Agroecology Meta-analysis Based on Bibliometrics: A Review

YANG Ruizhe1(), CHEN Lanlan2, LIU Xuejian1, ZHENG Yiming1, ZHENG Wei1, ZHAI Bingnian1, WANG Zhaohui1, LI Ziyan1()   

  1. 1College of Natural Resources and Environment, Northwest A&F University/ Key Laboratory of Plant Nutrition and the Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs, Yangling, Shaanxi 712100
    2College of Resources and Environmental Sciences, Gansu Agricultural University/ Gansu Provincial Key Laboratory of Arid-land Crop Science, Lanzhou 730070
  • Received:2021-10-25 Revised:2022-06-16 Online:2022-11-05 Published:2022-10-27
  • Contact: LI Ziyan E-mail:ruizhe_98@163.com;liziyan0161@126.com

Abstract:

To understand the development and application of meta-analysis in agroecology research and provide reference for relevant research, 718 valid literature was obtained with ‘meta’ as the keyword, and quantified by CiteSpace visualization software and Web of Science (WOS) literature analysis tool. The results show that the total number of international publications in agro-ecological meta-analysis has increased significantly. University of California, Davis (UC Davis), China Agricultural University, Chinese Academy of Sciences, Chinese Academy of Agricultural Sciences and Wageningen University have high international influence in the field of agro-ecological meta-analysis. The research topics of agroecology meta-analysis are diverse. The assessment of ecological and environmental effects of farmland management measures, land use change, climate change on biodiversity and greenhouse gases, the dynamics of carbon and nitrogen nutrient cycling, and the changes and interaction difference of different ecosystems are the main application fields at the present stage. As an important tool for agro-ecological research, meta-analysis provides a new way to verify hypotheses and develop new theories for large-scale comprehensive research, but it is still difficult to fully meet the needs of practical work by simple meta-analysis. A comprehensive meta-analysis based on big data fusion, machine learning model algorithms and expert knowledge assessment will be the focus of future research.

Key words: agro-ecosystem, meta-analysis, visual analysis, disciplinary development, research hotspot

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