Introduction
Traditional medicinal plants or natural products are considered the best source for a new chemical entity (NEC) or lead molecule. (Katiyar, Gupta, Kanjilal, & Katiyar, 2012) It is estimated that about 80% of those living in developing countries rely on traditional plant products for their healthcare needs.2 This is so because medicinal plants have the upper hand over conventional therapeutic molecules in terms of their comparable efficacy (with conventional molecules), safety, and low cost.3 Plants from the genus Plumeria represent one such traditionally used medicinal plant known for its ornamental excellence and fragrance.4, 5, 6, 7, 8 Since research, at present, is primarily concerned with the development of newer therapeutics (thanks to COVID-19), the role of traditional medicinal plants in the search for novel lead molecules is in full swing.9, 10 Additionally, research nowadays is mostly interdisciplinary, which attracts countless challenges when scrutinizing its thematic composition. This demands detailed analysis, which, in turn, highlights the role of bibliometrics in visualizing the research gap in a pre-decided scientific domain.11, 12
Having said this, it is interesting to note that researchers are increasingly using bibliographic data (from one or more databases) for future study designs.13 However, one also needs to be aware of the limitations of such data sets, as seen when trying to narrow down a definition and delimitate a topic. Thus, it is crucial to establish a correlation between various published documents using bibliographic information in a particular database.
Review Methodology
Documents considered in this retrospective study were retrieved from the Web of Science database on 6th June 2021. The keyword ‘Plumeria’ was used for searching the database. The authors initially intended to conduct a boolean (with AND) search with ‘Plumeria’, ‘stem cell’, and ‘cancer’. However, such a search returned no results, so the authors settled for the keyword Plumeria. Furthermore, all documents published between the time frame 1999-2021 were considered for evaluation. In all, 223 documents emerged as a result of the above-searched keyword. Manuscripts that were incorporated for analysis included articles (n=176), reviews (n=9), proceedings (n=12), meeting abstracts (n=11), editorials (n=7), news items (n=7), book chapters (n=1), book review (n=1) and early access (n=1). Next, data of all 255 documents were downloaded in ‘.txt’ format. The bibliometric analysis was carried out using the software VOSviewer.
Additionally, methods used for the analysis of collected documents include:
Co-occurrence or keyword analysis
Initially, the data was fed into the software for keyword analysis, and ‘co-occurrence’ was chosen as the ‘type of analysis’. Besides, ‘all keywords’ was selected as a ‘unit of analysis’. Subsequently, the minimum ‘number of co-occurrence of a keyword’ was set to 2. In doing so, 197/1,202 keywords met the threshold. Then, based on the exclusion criteria, keywords were verified. This resulted in the selection of 76/197 keywords. The exclusion criteria for keywords included repeated/incomplete words, words with no sense with context to the present study, words beyond the scope of analysis of this review (i.e., names of plant species other than genus Plumeria), and words that had a first/a greater occurrence or link strength.
Other miscellaneous analyses
These were aimed to get more information regarding citations and funding agencies of published manuscripts. The above analysis was done using the ‘Analyze Results’ and the ‘Create Citation Report’ options in the top right corner of a particular search result page in the Web of Science database. After clicking on ‘Analyze Results’, the appropriate option (i.e., funding agencies) was selected for further analysis.
Results and Discussion
Co-occurrence analysis and the keyword map
Keyword co-occurrence analysis was conducted using VOSviewer, as shown in Figure 1.
Of the 76 keywords included in the study, 74 were connected. Words that stood as outliers were tobamovirus and polyphenol. This suggested that they had no relation to the genus Plumeria. Moreover, all interconnected terms were distributed across 9 clusters such as cluster 1 (13 items), cluster 2 (11 items), cluster 3 (11 items), cluster 4 (10 items), cluster 5 (8 items), cluster 6 (7 items), cluster 7 (6 items), cluster 8 (5 items), cluster 9 (3 items). Further, analysis of these clusters helped us identify the various species of Plumeria that had been researched. These included Plumeria rubra (cluster 8), Plumeria obtuse (cluster 4), Plumeria acutifolia (cluster 4), Plumeria pudica (cluster 1), Plumeria acuminata (cluster 5), Plumeria alba (cluster 3), Plumeria bicolor (cluster 6). A detailed analysis of these clusters is shown in Figure 2.
Figure 2
Detailed co-occurrence analysis (A) Plumeria obtusa; (B) Plumeria rubra; (C) Plumeria acutifolia; (D) Plumeria pudica; (E) Plumeria acuminata; (F) Plumeria alba; (G) Plumeria bicolor
Results showed that researchers primarily worked on identifying the phytoconstituents of various plant species. Consequently, the biological activity obtained from these plant extracts/their phytoconstituents was explored, as evidenced by the data obtained from figure and as documented in Table 1 .
Table 1
Overview of research done on various plant species
Other miscellaneous analysis
Citation analysis
Detailed citation analysis is depicted in Figure 3. The h-index was 21, whereas the average citation per item was 9.29. Moreover, articles were cited around 1,826 times (88%, excluding self-citation) from 1999-2021. This also shows that authors self-cited their articles only by a very marginal amount of 12%. Also, citation rates peaked at around 2020, which could be due to researchers trying to find new lead molecules for the treatment of COVID-19 or its associated comorbidities (i.e., cancer and diabetes).14, 15
Analysis of funding agencies involved
Top 3 funding agencies which financed Plumeria research included the Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq) (7.623%), the Fundação Cearense de Apoio ao Desenvolvimento Científico e Tecnológico (FUNCAP) (4.036%) and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) (3.139%). Figure 4 shows the document count of the top 25 funding agencies across the globe.
Conclusion
Analysis of the role of funding sources and the critical research gaps are the most vital areas in research for a research scholar. Results revealed that although much work had been done in the phytochemical screening of various species of Plumeria, there still remains a research gap as far as biological activity and the development of viable pharmaceutical formulations were concerned. One such possible gap is that the nephroprotective (and hepatoprotective) activity of genus Plumeria, which has not been explored despite the fact that this genus has been proven to be quite useful in treating diabetes (diabetic nephropathy is a common problem in diabetes). Therefore, scholars can work in this direction and many such gaps, as mentioned by N/A in Table 1. Consequently, this would help fulfill the grey areas of research in this thematic arena (as evident by the h-index and funding agencies involved in financing the study) and further impact our current knowledge of medicinal plants to develop better therapeutics for the future.
Article DOI
