Exploring global trends in scientific research on Rubus glaucus Benth.: A comprehensive analysis integrating bibliometrics, LDA, and HJ-Biplot

Journal of Berry Research, Год журнала: 2024, Номер 14(4), С. 287 - 300

Опубликована: Окт. 7, 2024

Background Rubus glaucus Benth, called Andean blackberry, is a species of significant economic and ecological importance. Despite its relevance, scientific research on this plant remains fragmented scattered across disciplines. Objective This study aims to systematically assess the state knowledge R. glaucus, identifying trends, collaborations, thematic evolutions within global community. Methods We employed comprehensive bibliometric analysis integrated with Latent Dirichlet Allocation (LDA) HJ-Biplot methodologies analyze publications from Scopus Web Science databases. Results Our findings reveal substantial increase in interest 1990s, reaching peak early 2010s before recent decline. The highlights contributions United States, Kingdom, Canada, Italy, Colombia, notable international collaborations. Thematic underscored role, nutritional benefits, genetic improvement as focal areas research, pointing out gaps pest management sustainable cultivation practices. Conclusions offers valuable insights into landscape underscoring need for focused efforts underexplored areas. lays groundwork future directions, encouraging interdisciplinary collaboration leverage plant's full potential agricultural innovation.

Язык: Английский

Exploring the Role of Artificial Intelligence in Wastewater Treatment: A Dynamic Analysis of Emerging Research Trends

Resources, Год журнала: 2024, Номер 13(12), С. 171 - 171

Опубликована: Дек. 16, 2024

Wastewater treatment is a critical process for ensuring water quality and public health, particularly in the context of increasing environmental challenges such as pollution scarcity. Artificial intelligence (AI) has emerged transformative technology capable optimizing various wastewater processes, contaminant removal, energy consumption, cost-efficiency. This study presents comprehensive bibliometric analysis AI applications treatment, utilizing data from Scopus Web Science covering 4335 publications 1985 to 2024. Utilizing machine learning techniques neural networks, fuzzy logic, genetic algorithms, reveals key trends role processes. The results show that increasingly been applied solve complex problems like membrane fouling, nutrient biofouling control. Regional contributions highlight strong focus on advanced oxidation microbial sludge optimization. Latent Dirichlet Allocation (LDA) model further identifies emerging topics real-time monitoring AI-driven effluent prediction pivotal areas future research. findings provide valuable insights into current state potential technologies management, offering roadmap researchers exploring integration address sustainability field.

Язык: Английский

Analyzing research trends in glioblastoma metabolism: a bibliometric review

Frontiers in Immunology, Год журнала: 2024, Номер 15

Опубликована: Окт. 18, 2024

A bibliometric and visual analysis of articles related to glioblastoma metabolism was conducted reveal the dynamics scientific development assist researchers in gaining a global perspective when exploring hotspots trends.

Язык: Английский