U. C. Lavania
- Plant Science top 2%
- Molecular Biology top 10%
- Ecology, Evolution, Behavior and Systematics top 5%
- Genetics
- Food Science top 10%
- Co-authors
- Seshu LavaniaSangeeta SrivastavaYasuhiko MukaiSarita SrivastavaArun Kumar SharmaY. VimalaRitesh BanerjeeAnita Mukherjee
- Topics
- Chromosomal and Genetic Variations (39 papers)Plant tissue culture and regeneration (23 papers)Plant Reproductive Biology (14 papers)
- Partner nations
- IndiaJapanNetherlands
In The Last Decade
U. C. Lavania
66 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 71
- Plant Science 935
- Molecular Biology 731
- Ecology, Evolution, Behavior and Systematics 202
- Genetics 147
- Food Science 90
Countries citing papers authored by U. C. Lavania
This map shows the geographic impact of U. C. Lavania'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 U. C. Lavania with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites U. C. Lavania more than expected).
Fields of papers citing papers by U. C. Lavania
This network shows the impact of papers produced by U. C. Lavania. 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 U. C. Lavania. The network helps show where U. C. Lavania may publish in the future.
Co-authorship network of co-authors of U. C. Lavania
This figure shows the co-authorship network connecting the top 25 collaborators of U. C. Lavania. A scholar is included among the top collaborators of U. C. Lavania 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 U. C. Lavania. U. C. Lavania is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 7 | |
| 3 | 17 | |
| 4 | 90 | |
| 5 | 154 | |
| 6 | 13 | |
| 7 | Sequestration of atmospheric carbon into subsoil horizons through deep-rooted grasses ― vetiver grass model | 21 |
| 8 | 7 | |
| 9 | 20 | |
| 10 | 2 | |
| 11 | Chromosome diversity in population: Defining conservation units and their micro-identification through genomic in situ painting | 8 |
| 12 | 5 | |
| 13 | Vetiver grass technology for environmental protection and sustainable development. | 12 |
| 14 | Genesis of high bivalent pairing in autotetraploids and autotriploids, and reduction in bound arm associations over generations | 5 |
| 15 | 17 | |
| 16 | 26 | |
| 17 | 4 | |
| 18 | 6 | |
| 19 | 9 | |
| 20 | 9 |
About U. C. Lavania
U. C. Lavania is a scholar working on Plant Science, Ecology, Evolution, Behavior and Systematics and Molecular Biology, having authored 68 papers that have together received 1.2k indexed citations. Recurring topics across this work include Chromosomal and Genetic Variations (39 papers), Plant tissue culture and regeneration (23 papers) and Plant Reproductive Biology (14 papers). The work is most often cited by research in Plant Science (935 citations), Molecular Biology (731 citations) and Ecology, Evolution, Behavior and Systematics (202 citations). U. C. Lavania has collaborated with scholars based in India, Japan and Netherlands. Frequent co-authors include Seshu Lavania, Sangeeta Srivastava, Yasuhiko Mukai, Sarita Srivastava, Arun Kumar Sharma, Y. Vimala, Ritesh Banerjee, Anita Mukherjee, Priya Goswami and R.K. Lal. Their work appears in journals such as Scientific Reports, The Plant Journal and Cellular and Molecular Life Sciences.
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.