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<p>This study introduces a novel methodology how academic research in plant tissue culture (PTC) frames the themes related to commercial scalability through keyword usage and citation clustering. Drawing on complex systems thinking, commercialization-related keywords (e.g., “large scale,” “market,” “cost-effective”) are treated as thematic attractors within a networked academic discourse. A curated dataset from the Web of Science Core Collection is analyzed using Gephi to map citation-based clusters by crop type, country, and propagation technique. While micropropagation and somatic embryogenesis dominate the network, crops like sugarcane and banana show divergence between research emphasis and global production data. Regional nodes such as India and Brazil illustrate thematic strength, but also raise questions about alignment with industrial realities. Rather than measuring technology transfer, this perspective interprets network structure as a lens on how academia signals application relevance and emerging research priorities.</p>

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Mapping thematic patterns in plant tissue culture research: a citation network perspective

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月9日

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  • Buhara Yücesan

摘要

This study introduces a novel methodology how academic research in plant tissue culture (PTC) frames the themes related to commercial scalability through keyword usage and citation clustering. Drawing on complex systems thinking, commercialization-related keywords (e.g., “large scale,” “market,” “cost-effective”) are treated as thematic attractors within a networked academic discourse. A curated dataset from the Web of Science Core Collection is analyzed using Gephi to map citation-based clusters by crop type, country, and propagation technique. While micropropagation and somatic embryogenesis dominate the network, crops like sugarcane and banana show divergence between research emphasis and global production data. Regional nodes such as India and Brazil illustrate thematic strength, but also raise questions about alignment with industrial realities. Rather than measuring technology transfer, this perspective interprets network structure as a lens on how academia signals application relevance and emerging research priorities.