This map shows the geographic impact of D. Uma's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by D. Uma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Uma more than expected).
This network shows the impact of papers produced by D. Uma. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by D. Uma. The network helps show where D. Uma may publish in the future.
Co-authorship network of co-authors of D. Uma
This figure shows the co-authorship network connecting the top 25 collaborators of D. Uma.
A scholar is included among the top collaborators of D. Uma based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with D. Uma. D. Uma is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Manoharan, Renuka Ramalingam, et al.. (2021). Cell Suspension Culture of Mucuna pruriens For Production and Improvement of L-3, 4-Dihydroxy Phenylalanine Concentration. Nigeria Agricultural Journal. 52(2). 120–129.1 indexed citations
9.
Rajamani, K., et al.. (2020). Formulation and evaluation of gymnema soup mix for secondary complications of diabetes. Journal of Pharmacognosy and Phytochemistry. 9(6). 1981–1985.2 indexed citations
10.
Kannan, M., et al.. (2019). Phytochemical screening and nutritional analysis of Nelumbo nucifera (Pink lotus) flower petals and seeds. International Journal of Chemical Studies. 7(3). 3540–3545.2 indexed citations
11.
Kannan, M., et al.. (2019). Phytochemical screening and nutritional analysis of Nelumbo nucifera (Pink lotus) rhizomes to validate its edible value. Journal of Pharmacognosy and Phytochemistry. 8(3). 3612–3616.2 indexed citations
12.
Uma, D., et al.. (2019). Assessment of variability in snap melon (Cucumis melo var. Momordica duth. & full) genotypes. Journal of Pharmacognosy and Phytochemistry. 8(4). 654–657.1 indexed citations
13.
Pandiarajan, T., et al.. (2018). Effect of curing method on the quality of turmeric rhizomes.. 9(6). 1050–1054.
14.
Balakrishnan, S., et al.. (2018). Impact of canopy management on flowering and yield attributes of cocoa (Theobroma cacao L.) under tropical condition of Tamil Nadu. International Journal of Chemical Studies. 6(5). 629–633.
15.
Balakrishnan, S., et al.. (2018). Effect of different pruning levels and growth retardants on growth, yield and quality of cocoa (Theobroma cacao L.). Journal of Pharmacognosy and Phytochemistry. 7(4). 3354–3357.5 indexed citations
16.
Rajamani, K., et al.. (2018). Chemical composition of Vetiver root oil obtained by using GCMS analysis. Journal of Pharmacognosy and Phytochemistry. 7(6). 1709–1713.3 indexed citations
17.
Каннабиран, Кришнан, et al.. (2017). Variability in alkaloid content and phytochemical profile of periwinkle (Catharanthus roseus L.) cv. Local through gamma and ethyl methane sulphonate. Journal of Pharmacognosy and Phytochemistry. 6(5). 2528–2532.1 indexed citations
18.
Vanniarajan, C., et al.. (2010). Development of new vegetable soybean (Glycine max L. Merill) mutants with high protein and less fibre content.. Electronic Journal of Plant Breeding. 1(4). 1060–1065.5 indexed citations
19.
Abirami, S., et al.. (2007). Correlation and path coefficient analysis for morphological and biochemical traits in maize genotypes.. PLANT ARCHIVES. 7(1). 109–113.4 indexed citations
20.
Manivannan, N., et al.. (2007). Correlation and path analysis for oil yield and its components in cultivated sesame (Sesamum indicum L.). Agricultural science digest. 27(1). 62–64.2 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.