Pawan Khera

1.2k total citations
21 papers, 728 citations indexed

About

Pawan Khera is a scholar working on Plant Science, Inorganic Chemistry and Genetics. According to data from OpenAlex, Pawan Khera has authored 21 papers receiving a total of 728 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Plant Science, 8 papers in Inorganic Chemistry and 7 papers in Genetics. Recurrent topics in Pawan Khera's work include Peanut Plant Research Studies (9 papers), Agricultural pest management studies (8 papers) and Coconut Research and Applications (8 papers). Pawan Khera is often cited by papers focused on Peanut Plant Research Studies (9 papers), Agricultural pest management studies (8 papers) and Coconut Research and Applications (8 papers). Pawan Khera collaborates with scholars based in India, United States and China. Pawan Khera's co-authors include Rajeev K. Varshney, Manish K. Pandey, Baozhu Guo, Manda Sriswathi, A. K. Culbreath, Pasupuleti Janila, C. Corley Holbrook, Suping Feng, Lixian Qiao and Manish K. Vishwakarma and has published in prestigious journals such as PLoS ONE, Frontiers in Plant Science and Plant Science.

In The Last Decade

Pawan Khera

21 papers receiving 702 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pawan Khera India 13 669 215 204 106 33 21 728
Surendra S. Manohar India 16 728 1.1× 166 0.8× 272 1.3× 53 0.5× 17 0.5× 37 761
Sunil S. Gangurde India 15 654 1.0× 179 0.8× 163 0.8× 87 0.8× 33 1.0× 58 716
Marilyne Summo France 8 195 0.3× 252 1.2× 37 0.2× 35 0.3× 33 1.0× 12 430
Vinay Sharma India 12 375 0.6× 82 0.4× 33 0.2× 77 0.7× 18 0.5× 38 438
Fabien De Bellis France 11 253 0.4× 81 0.4× 25 0.1× 51 0.5× 25 0.8× 14 374
Ray O. Hammons United States 13 518 0.8× 100 0.5× 193 0.9× 13 0.1× 34 1.0× 71 571
Eileen A. Kabelka United States 17 729 1.1× 128 0.6× 8 0.0× 180 1.7× 48 1.5× 25 821
Rosa Mazzeo Italy 8 293 0.4× 146 0.7× 10 0.0× 75 0.7× 27 0.8× 9 398
Songxiao Cao China 12 361 0.5× 227 1.1× 9 0.0× 28 0.3× 26 0.8× 14 450
Péricles de Albuquerque Melo Filho Brazil 10 450 0.7× 147 0.7× 47 0.2× 8 0.1× 16 0.5× 26 509

Countries citing papers authored by Pawan Khera

Since Specialization
Citations

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

Fields of papers citing papers by Pawan Khera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pawan Khera. 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 Pawan Khera. The network helps show where Pawan Khera may publish in the future.

Co-authorship network of co-authors of Pawan Khera

This figure shows the co-authorship network connecting the top 25 collaborators of Pawan Khera. A scholar is included among the top collaborators of Pawan Khera 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 Pawan Khera. Pawan Khera 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.
Vries, Michiel E. de, J. R. Adams, Pawan Khera, et al.. (2023). Converting Hybrid Potato Breeding Science into Practice. Plants. 12(2). 230–230. 15 indexed citations
2.
Khera, Pawan, Manish K. Pandey, Nalini Mallikarjuna, et al.. (2018). Genetic imprints of domestication for disease resistance, oil quality, and yield component traits in groundnut (Arachis hypogaea L.). Molecular Genetics and Genomics. 294(2). 365–378. 11 indexed citations
3.
Khera, Pawan, Mahamadou Sawadogo, Yaduru Shasidhar, et al.. (2017). SSR markers associated to early leaf spot disease resistance through selective genotyping and single marker analysis in groundnut ( Arachis hypogaea L.). Biotechnology Reports. 15. 132–137. 18 indexed citations
4.
Pandey, Manish K., Hui Wang, Pawan Khera, et al.. (2017). Genetic Dissection of Novel QTLs for Resistance to Leaf Spots and Tomato Spotted Wilt Virus in Peanut (Arachis hypogaea L.). Frontiers in Plant Science. 8. 25–25. 41 indexed citations
5.
6.
Khera, Pawan, et al.. (2015). Ssr-based molecular profiling of selected donors of wide compatibility, elongated uppermost internode, stigma exsertion and submergence tolerance traits and parental lines of commercial rice (o. Sativa l.) Hybrids. Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics). 5(2). 67–91. 2 indexed citations
7.
Wang, Ming Li, Pawan Khera, Manish K. Pandey, et al.. (2015). Genetic Mapping of QTLs Controlling Fatty Acids Provided Insights into the Genetic Control of Fatty Acid Synthesis Pathway in Peanut (Arachis hypogaea L.). PLoS ONE. 10(4). e0119454–e0119454. 70 indexed citations
8.
Janila, Pasupuleti, Manish K. Pandey, Yaduru Shasidhar, et al.. (2015). Molecular breeding for introgression of fatty acid desaturase mutant alleles ( ahFAD2A and ahFAD2B ) enhances oil quality in high and low oil containing peanut genotypes. Plant Science. 242. 203–213. 113 indexed citations
9.
Fountain, Jake C., Pawan Khera, Liming Yang, et al.. (2015). Resistance to Aspergillus flavus in maize and peanut: Molecular biology, breeding, environmental stress, and future perspectives. The Crop Journal. 3(3). 229–237. 59 indexed citations
10.
11.
Wang, Hui, Pawan Khera, Bingyan Huang, et al.. (2015). Analysis of genetic diversity and population structure of peanut cultivars and breeding lines from China, India and the US using simple sequence repeat markers. Journal of Integrative Plant Biology. 58(5). 452–465. 22 indexed citations
12.
Pandey, Manish K., Ming Li Wang, Lixian Qiao, et al.. (2014). Identification of QTLs associated with oil content and mapping FAD2 genes and their relative contribution to oil quality in peanut (Arachis hypogaeaL.). BMC Genetics. 15(1). 133–133. 91 indexed citations
13.
Khera, Pawan, et al.. (2014). Genetic variability in trait-specific rice germplasm groups based on coefficient of parentage, SSR markers and fertility restoration. Plant Genetic Resources. 13(1). 56–67. 1 indexed citations
14.
15.
Khera, Pawan, Manish K. Pandey, & Rajeev K. Varshney. (2013). Pest and diseases: Old and new threats – Modern breeding tools to tailor new crop cultivars. Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics). 24(4). 261–273. 3 indexed citations
16.
Khera, Pawan. (2012). Scope for utilization of native specialty landraces, cultivars and basmati types in rice heterosis breeding. Journal of Plant Breeding and Crop Science. 4(8). 3 indexed citations
17.
Khera, Pawan, et al.. (2012). Occurrence of Trifid Stigma Morphotype in a Maintainer Line of Rice (Oryza sativa L.). 6(4). 252–255. 4 indexed citations
18.
Khera, Pawan, et al.. (2009). Identification and genetic mapping of elongated uppermost internode gene eui with microsatellite markers in rice (Oryza sativa L.). Journal of Plant Breeding and Crop Science. 1(10). 336–342. 3 indexed citations
19.
Viraktamath, B. C., et al.. (2009). Validation of molecular markers linked to fertility restorer gene(s) for WA-CMS lines of rice. Euphytica. 167(2). 217–227. 43 indexed citations
20.
Khera, Pawan, et al.. (2006). Development of STS marker linked to elongated uppermost internode (eui-1) gene in rice (Oryza sativa L.). 1. 113–116. 3 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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