S. V. Ramesh

3.1k total citations
101 papers, 2.0k citations indexed

About

S. V. Ramesh is a scholar working on Plant Science, Inorganic Chemistry and Molecular Biology. According to data from OpenAlex, S. V. Ramesh has authored 101 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Plant Science, 40 papers in Inorganic Chemistry and 16 papers in Molecular Biology. Recurrent topics in S. V. Ramesh's work include Coconut Research and Applications (40 papers), Plant Virus Research Studies (26 papers) and Advanced Chemical Sensor Technologies (10 papers). S. V. Ramesh is often cited by papers focused on Coconut Research and Applications (40 papers), Plant Virus Research Studies (26 papers) and Advanced Chemical Sensor Technologies (10 papers). S. V. Ramesh collaborates with scholars based in India, United States and Thailand. S. V. Ramesh's co-authors include R. Pandiselvam, Anjineyulu Kothakota, Shelly Praveen, M. R. Manikantan, K. B. Hebbar, Shameena Beegum, R. Kaavya, N. U. Sruthi, S. Shahir and S. Subhashini and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Food Chemistry.

In The Last Decade

S. V. Ramesh

92 papers receiving 2.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
S. V. Ramesh India 27 988 529 307 281 246 101 2.0k
Ashish Rawson India 25 740 0.7× 1.5k 2.9× 354 1.2× 613 2.2× 562 2.3× 99 2.7k
Jianmei Yu United States 22 660 0.7× 979 1.9× 571 1.9× 147 0.5× 470 1.9× 56 2.5k
Giovanna Ferrentino Italy 27 329 0.3× 928 1.8× 267 0.9× 562 2.0× 212 0.9× 122 2.3k
Randolph M. Beaudry United States 41 3.5k 3.5× 704 1.3× 733 2.4× 144 0.5× 176 0.7× 161 4.5k
Liang Zhao China 28 308 0.3× 717 1.4× 551 1.8× 622 2.2× 254 1.0× 111 2.2k
Jane Mara Block Brazil 28 326 0.3× 764 1.4× 409 1.3× 56 0.2× 633 2.6× 87 1.9k
Zhi‐Hong Zhang China 23 375 0.4× 780 1.5× 296 1.0× 486 1.7× 260 1.1× 44 1.7k
Rajko Vidrih Slovenia 24 804 0.8× 643 1.2× 276 0.9× 86 0.3× 201 0.8× 99 1.8k
Xiaohu Luo China 31 1.0k 1.0× 1.1k 2.0× 480 1.6× 350 1.2× 928 3.8× 96 2.5k
R. Ravi India 25 700 0.7× 966 1.8× 206 0.7× 134 0.5× 683 2.8× 117 1.9k

Countries citing papers authored by S. V. Ramesh

Since Specialization
Citations

This map shows the geographic impact of S. V. Ramesh'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 S. V. Ramesh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. V. Ramesh more than expected).

Fields of papers citing papers by S. V. Ramesh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. V. Ramesh. 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 S. V. Ramesh. The network helps show where S. V. Ramesh may publish in the future.

Co-authorship network of co-authors of S. V. Ramesh

This figure shows the co-authorship network connecting the top 25 collaborators of S. V. Ramesh. A scholar is included among the top collaborators of S. V. Ramesh 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 S. V. Ramesh. S. V. Ramesh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Pandiselvam, R., et al.. (2024). Comparative study on infrared radiation and hot air convective drying of coconut: Effect on oil quality features. Thermal Science and Engineering Progress. 55. 102950–102950. 2 indexed citations
2.
Pandiselvam, R., et al.. (2024). Physicochemical properties of coconut inflorescence sap (neera) under double wall open heating system. Journal of Food Measurement & Characterization. 18(10). 8555–8563.
3.
Ramesh, S. V., R. Pandiselvam, Shameena Beegum, et al.. (2024). Valorization of coconut (Cocos nucifera L.) testa as a biocolourant. Frontiers in Sustainable Food Systems. 8.
4.
Beegum, Shameena, et al.. (2024). Perspectives on the cardioprotective, neuroprotective and anti-obesity functions of coconut (Cocos nucifera L.). Food Bioscience. 58. 103756–103756. 7 indexed citations
5.
Pandiselvam, R., et al.. (2024). Infrared‐aided hot‐air drying of coconut: Impact on drying kinetics and quality metrics. Journal of Food Process Engineering. 47(6). 5 indexed citations
6.
7.
Pandiselvam, R., et al.. (2023). Synergetic Effect of Fermented Coconut Inflorescence Sap for the Production of Virgin Coconut Oil. Journal of Food Biochemistry. 2023. 1–12. 1 indexed citations
8.
Dikshit, Harsh Kumar, Gyan P. Mishra, Nand Lal Meena, et al.. (2023). Evaluation of Growth Conditions, Antioxidant Potential, and Sensory Attributes of Six Diverse Microgreens Species. Agriculture. 13(3). 676–676. 32 indexed citations
9.
Chinnusamy, Viswanathan, Van Schepler‐Luu, Satendra K. Mangrauthia, & S. V. Ramesh. (2023). Genome editing in plants: a tool for precision breeding and functional genomics. Journal of Plant Biochemistry and Biotechnology. 32(4). 657–660. 2 indexed citations
10.
Ramesh, S. V., et al.. (2022). Physicochemical characterization and fatty acid profiles of testa oils from various coconut (Cocos nucifera L.) genotypes. Journal of the Science of Food and Agriculture. 103(1). 370–379. 10 indexed citations
11.
Ramesh, S. V., et al.. (2021). Review of Cocos nucifera L. testa-derived phytonutrients with special reference to phenolics and its potential for encapsulation. Journal of Food Science and Technology. 60(1). 1–10. 7 indexed citations
12.
Bhat, Ravi, et al.. (2021). Data of 16S rRNA gene amplicon-based metagenomic signatures of arecanut rhizosphere soils in Yellow Leaf Disease (YLD) endemic region of India. SHILAP Revista de lepidopterología. 38. 107443–107443. 2 indexed citations
13.
Pandiselvam, R., Anjineyulu Kothakota, M. R. Manikantan, et al.. (2021). Emerging non-thermal processing techniques for preservation of tender coconut water. LWT. 149. 111850–111850. 35 indexed citations
14.
Hebbar, K. B., Piruthivi Sukumar, S. V. Ramesh, et al.. (2020). Understanding Physiology and Impacts of High Temperature Stress on the Progamic Phase of Coconut (Cocos nucifera L.). Plants. 9(12). 1651–1651. 14 indexed citations
15.
Ratnaparkhe, Milind B., Giriraj Kumawat, M. Shivakumar, et al.. (2020). Whole Genome Re-sequencing of Soybean Accession EC241780 Providing Genomic Landscape of Candidate Genes Involved in Rust Resistance. Current Genomics. 21(7). 504–511. 5 indexed citations
16.
Ramesh, S. V., R. Pandiselvam, K. B. Hebbar, et al.. (2020). Antiviral Potential of Coconut (Cocos nucifera L.) Oil and COVID-19. Coronaviruses. 2(4). 405–410. 5 indexed citations
17.
Vinutha, T., et al.. (2020). Tomato auxin biosynthesis/signaling is reprogrammed by the geminivirus to enhance its pathogenicity. Planta. 252(4). 51–51. 28 indexed citations
18.
19.
Ramesh, S. V., M. Shivakumar, Rajkumar Ramteke, et al.. (2019). Quantification of a legume begomovirus to evaluate soybean genotypes for resistance to yellow mosaic disease. Journal of Virological Methods. 268. 24–31. 9 indexed citations
20.
Ramesh, S. V., et al.. (2019). Stress-responsive miRNAome of Glycine max (L.) Merrill: molecular insights and way forward. Planta. 249(5). 1267–1284. 23 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.

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