Prashant G. Kawar

1.2k total citations
37 papers, 806 citations indexed

About

Prashant G. Kawar is a scholar working on Plant Science, Molecular Biology and Biomedical Engineering. According to data from OpenAlex, Prashant G. Kawar has authored 37 papers receiving a total of 806 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Plant Science, 14 papers in Molecular Biology and 7 papers in Biomedical Engineering. Recurrent topics in Prashant G. Kawar's work include Sugarcane Cultivation and Processing (10 papers), Plant Stress Responses and Tolerance (7 papers) and Plant Gene Expression Analysis (6 papers). Prashant G. Kawar is often cited by papers focused on Sugarcane Cultivation and Processing (10 papers), Plant Stress Responses and Tolerance (7 papers) and Plant Gene Expression Analysis (6 papers). Prashant G. Kawar collaborates with scholars based in India, United Kingdom and Australia. Prashant G. Kawar's co-authors include R. M. Devarumath, Angelo Santino, Alisdair R. Fernie, Saleh Alseekh, Lionel Hill, Yang Zhang, Cathie Martin, Eugenio Butelli, Takayuki Tohge and Ghanasyam Rallapalli and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and RSC Advances.

In The Last Decade

Prashant G. Kawar

35 papers receiving 782 citations

Peers

Prashant G. Kawar

BIOCH

Jiangli Shi China

Vidhu A. Sane India

Roberto de Armas Urquiza Cuba

Xiaoyun Ren China

Qiuyan Ban China

Claudio E. Voget Argentina

Mijing Jin China

Shuangshuang Tang China

Xianjun Dai China

Irfan Ali Sabir China

Jiangli Shi China

Prashant G. Kawar

432 ×0.7

462 ×1.1

23 ×0.2

94 ×1.0

47 ×0.7

BIOCH

Citations per year, relative to Prashant G. Kawar Prashant G. Kawar (= 1×) peers Jiangli Shi

Countries citing papers authored by Prashant G. Kawar

Since Specialization

Citations

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

Fields of papers citing papers by Prashant G. Kawar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Prashant G. Kawar. 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 Prashant G. Kawar. The network helps show where Prashant G. Kawar may publish in the future.

Co-authorship network of co-authors of Prashant G. Kawar

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

All Works

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20 of 20 papers shown

Jadhav, Pravin V., Parva Kumar Sharma, M. P. Moharil, et al.. (2025). Comparative transcriptome and co-expression network analysis uncovers the regulatory mechanism of silicon-induced soybean defense against charcoal rot disease. Current Plant Biology. 41. 100442–100442. 2 indexed citations

Kulkarni, Ambarish, Pravin Jadhav, T. P. Ahammed Shabeer, et al.. (2025). Phytochemical insights and antioxidant capabilities of rose cultivars: implications for traditional medicine and modern industry. Discover Agriculture. 3(1). 1 indexed citations

Devarumath, R. M., et al.. (2025). Micropropagation of elite varieties of marigold (Tagetes erecta L.). In Vitro Cellular & Developmental Biology - Plant. 61(6). 1340–1347.

Devarumath, R. M., et al.. (2024). Edible flowers: biotechnological interventions for improving bioactives of food and health significance. Journal of Food Composition and Analysis. 134. 106506–106506. 9 indexed citations

Kulkarni, Ambarish, et al.. (2024). Potential assessment of Chrysanthemum flowers from various cultivars as sources of natural antioxidants and bioactive compounds. Genetic Resources and Crop Evolution. 72(2). 1599–1617. 3 indexed citations

Kawar, Prashant G., et al.. (2024). Strategies for marigold micro-propagation to mitigate physiological disorders. Plant Cell Tissue and Organ Culture (PCTOC). 159(2). 1 indexed citations

Sakthivel, K., et al.. (2024). Characterization of Fusarium falciforme inciting wilt in peace lily (Spathiphyllum wallisii). Scientia Horticulturae. 339. 113834–113834. 1 indexed citations

Nimbalkar, Mansingraj S., et al.. (2024). Pollen morphology and variability among Indian cultivars of Chrysanthemum morifolium and comparative analysis with genera of the Asteraceae family. Genetic Resources and Crop Evolution. 72(2). 2227–2247. 2 indexed citations

Kardile, Hemant B., Suhas Gorakh Karkute, Rahul Mahadev Shelake, et al.. (2023). Hemibiotrophic Phytophthora infestans Modulates the Expression of SWEET Genes in Potato (Solanum tuberosum L.). Plants. 12(19). 3433–3433. 2 indexed citations

10.

Mandlik, Rushil, Shivani Sharma, Gaurav Raturi, et al.. (2023). Genome-wide identification and characterisation of Aquaporin s in Rosa chinensis. The Journal of Horticultural Science and Biotechnology. 99(3). 311–325.

11.

Barbadikar, Kalyani M., et al.. (2023). Improvement of floricultural traits in ornamental crops using genome editing tools. Journal of Plant Biochemistry and Biotechnology. 32(4). 773–790. 2 indexed citations

12.

Shingote, Prashant Raghunath, et al.. (2020). Isolation and functional validation of stress tolerant EaMYB18 gene and its comparative physio-biochemical analysis with transgenic tobacco plants overexpressing SoMYB18 and SsMYB18. 3 Biotech. 10(5). 225–225. 7 indexed citations

13.

Jaiswal, Sarika, Pravin V. Jadhav, Rahul Singh Jasrotia, et al.. (2019). Transcriptomic signature reveals mechanism of flower bud distortion in witches’-broom disease of soybean (Glycine max). BMC Plant Biology. 19(1). 26–26. 19 indexed citations

14.

Zhang, Yang, Eugenio Butelli, Saleh Alseekh, et al.. (2015). Multi-level engineering facilitates the production of phenylpropanoid compounds in tomato. Nature Communications. 6(1). 8635–8635. 300 indexed citations

15.

Devarumath, R. M., et al.. (2012). Genetic profiling of sugarcane genotypes using Inter Simple Sequence Repeat (ISSR) markers. Electronic Journal of Plant Breeding. 3(1). 621–628. 8 indexed citations

16.

Devarumath, R. M., et al.. (2012). Assessment of Genetic Diversity in Sugarcane Germplasm Using ISSR and SSR Markers. Sugar Tech. 14(4). 334–344. 35 indexed citations

17.

Devarumath, R. M., et al.. (2011). Biochemical characterization and identification of differentially expressed candidate genes in salt stressed sugarcane. Plant Science. 184. 1–13. 44 indexed citations

18.

Gajjeraman, Prabu, et al.. (2010). Identification of Water Deficit Stress Upregulated Genes in Sugarcane. Plant Molecular Biology Reporter. 29(2). 291–304. 70 indexed citations

19.

Kawar, Prashant G., et al.. (2009). Use of RAPD markers for assessment of genetic diversity in sugarcane cultivars. Indian Journal of Biotechnology. 8(1). 67–71. 24 indexed citations

20.

Kawar, Prashant G., et al.. (2008). Field performance and RAPD analysis for assessment of genetic variation in sugarcane somaclones. Indian Journal of Genetics and Plant Breeding (The). 68(3). 301–306. 9 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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