Bibliometric analysis for advancing chrysanthemum research in India

Abstract

Chrysanthemum, a genetically heterogeneous and economically pivotal ornamental species, has garnered substantial scientific attention due to its agronomic, medicinal, and ecological significance. This study employs an AI-driven bibliometric analysis of 421 chrysanthemum-related publications from 2000 to 2023, systematically delineating global research trajectories. Leveraging advanced machine learning algorithms on Scopus-indexed data, we elucidate publication dynamics, prolific authorship networks, institutional research hubs, and emergent thematic frontiers. Our findings underscore China’s predominant scholarly contributions, followed by India and South Korea. Transcriptomics, functional genomics, and abiotic stress physiology emerge as critical research domains, providing deeper insights into the molecular and adaptive mechanisms underpinning chrysanthemum’s phenotypic plasticity. By integrating bibliographic network modeling with evolutionary computation paradigms, this study constructs a multidimensional representation of chrysanthemum research, revealing intricate interdisciplinary synergies. The AI-powered analytical framework fosters data-driven knowledge discovery, accelerating floral biotechnology innovations and advancing precision horticulture strategies.