Marker-assisted selection (MAS) is a fundamental approach for enhancing the cotton crop quality. However, the comprehensive bibliometric analysis within this research domain is still lacking. In August 2023, we conducted a scientific, computer-assisted review methodology based on the bibliometric record use of the Scopus dataset. Employing an innovative research methodology has gathered the data to descend prevailing research trends, influential journals, document types, prolific authors, and key countries related to MAS application in cotton research. The bibliometric analysis helped determine the current general research direction and trend of publications about MAS application in cotton research in the most prolific and distinguished journals and document types with years, authors, countries, and keywords. Data extraction, integration, and visualization employed the VOS-viewer, Microsoft Excel, and Map-chart. The presented review referred to 273 research manuscripts published in 72 journals retrieved from the Scopus database, with China and the United States identified as the most productive nations. Authors, including Zhan T, Zhang J, Guo W, Fan DD, and Yuan Y, emerged as influential contributors to MAS studies. The most important fields were agricultural and biological science, biochemistry, genetics, and molecular biology. The latest review research will objectively assess the current state of MAS utilization in cotton research, offering valuable insights for individuals seeking information on MAS techniques in cotton and serving as a reference guide for researchers exploring further studies in this domain.
Bibliometric analysis, marker-assisted selection (MAS), cotton, Scopus database, collaborative network, co-accurate network, subject area
The study provides a comprehensive overview of MAS research in cotton, emphasizing the leadership of China and the USA. Developing countries should strengthen MAS initiatives by collaborating with chief authors and organizations crucial for further advancements in this field.