Yaduru Shasidhar

1.1k total citations
16 papers, 674 citations indexed

About

Yaduru Shasidhar is a scholar working on Plant Science, Inorganic Chemistry and Molecular Biology. According to data from OpenAlex, Yaduru Shasidhar has authored 16 papers receiving a total of 674 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Plant Science, 8 papers in Inorganic Chemistry and 4 papers in Molecular Biology. Recurrent topics in Yaduru Shasidhar's work include Peanut Plant Research Studies (16 papers), Agricultural pest management studies (11 papers) and Coconut Research and Applications (8 papers). Yaduru Shasidhar is often cited by papers focused on Peanut Plant Research Studies (16 papers), Agricultural pest management studies (11 papers) and Coconut Research and Applications (8 papers). Yaduru Shasidhar collaborates with scholars based in India, United States and Australia. Yaduru Shasidhar's co-authors include Manish K. Pandey, Rajeev K. Varshney, Manish K. Vishwakarma, Pasupuleti Janila, Surendra S. Manohar, Baozhu Guo, Murali T. Variath, Aamir W. Khan, Sunil S. Gangurde and Vanika Garg and has published in prestigious journals such as PLoS ONE, Frontiers in Plant Science and Plant Science.

In The Last Decade

Yaduru Shasidhar

16 papers receiving 661 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yaduru Shasidhar India 11 639 240 160 97 28 16 674
Manda Sriswathi India 9 620 1.0× 225 0.9× 161 1.0× 74 0.8× 20 0.7× 10 660
Surendra S. Manohar India 16 728 1.1× 272 1.1× 166 1.0× 53 0.5× 26 0.9× 37 761
P. Nagesh India 7 487 0.8× 166 0.7× 92 0.6× 27 0.3× 22 0.8× 15 515
S. K. Bera India 11 415 0.6× 137 0.6× 79 0.5× 41 0.4× 20 0.7× 54 430
Suping Feng China 10 454 0.7× 178 0.7× 216 1.4× 108 1.1× 9 0.3× 14 546
H. L. Nadaf India 11 531 0.8× 216 0.9× 155 1.0× 26 0.3× 6 0.2× 56 565
Yanping Kang China 14 420 0.7× 116 0.5× 206 1.3× 25 0.3× 9 0.3× 40 504
Shijie Wen China 8 317 0.5× 104 0.4× 132 0.8× 31 0.3× 5 0.2× 9 357
Youlin Xia China 7 308 0.5× 138 0.6× 92 0.6× 44 0.5× 6 0.2× 11 337
Jentilal R. Dobaria India 11 339 0.5× 90 0.4× 139 0.9× 11 0.1× 7 0.3× 13 353

Countries citing papers authored by Yaduru Shasidhar

Since Specialization
Citations

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

Fields of papers citing papers by Yaduru Shasidhar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yaduru Shasidhar

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

All Works

16 of 16 papers shown
1.
Gangurde, Sunil S., Ethan Thompson, Yaduru Shasidhar, et al.. (2024). Linkage Mapping and Genome-Wide Association Study Identified Two Peanut Late Leaf Spot Resistance Loci, PLLSR-1 and PLLSR-2, Using Nested Association Mapping. Phytopathology. 114(6). 1346–1355. 2 indexed citations
2.
Pandey, Manish K., Sunil S. Gangurde, Yaduru Shasidhar, et al.. (2024). High-throughput diagnostic markers for foliar fungal disease resistance and high oleic acid content in groundnut. BMC Plant Biology. 24(1). 262–262. 5 indexed citations
4.
Pandey, Manish K., Manish K. Vishwakarma, Yaduru Shasidhar, et al.. (2020). Identification of quantitative trait loci associated with iron deficiency chlorosis resistance in groundnut (Arachis hypogaea). Plant Breeding. 139(4). 790–803. 5 indexed citations
5.
Kumar, Rakesh, Pasupuleti Janila, Manish K. Vishwakarma, et al.. (2019). Whole‐genome resequencing‐based QTL‐seq identified candidate genes and molecular markers for fresh seed dormancy in groundnut. Plant Biotechnology Journal. 18(4). 992–1003. 63 indexed citations
6.
Manohar, Surendra S., Manish K. Pandey, Murali T. Variath, et al.. (2019). Genomic regions associated with resistance to peanut bud necrosis disease (PBND) in a recombinant inbred line (RIL) population. Plant Breeding. 138(6). 748–760. 2 indexed citations
7.
Gangurde, Sunil S., Hui Wang, Yaduru Shasidhar, et al.. (2019). Nested‐association mapping (NAM)‐based genetic dissection uncovers candidate genes for seed and pod weights in peanut ( Arachis hypogaea ). Plant Biotechnology Journal. 18(6). 1457–1471. 79 indexed citations
8.
Shasidhar, Yaduru, Murali T. Variath, Manish K. Vishwakarma, et al.. (2019). Improvement of three popular Indian groundnut varieties for foliar disease resistance and high oleic acid using SSR markers and SNP array in marker-assisted backcrossing. The Crop Journal. 8(1). 1–15. 42 indexed citations
9.
Agarwal, Gaurav, Josh Clevenger, Manish K. Pandey, et al.. (2018). High‐density genetic map using whole‐genome resequencing for fine mapping and candidate gene discovery for disease resistance in peanut. Plant Biotechnology Journal. 16(11). 1954–1967. 70 indexed citations
10.
Bera, S. K., Surendra S. Manohar, Murali T. Variath, et al.. (2018). Assessing variability for disease resistance and nutritional quality traits in an interspecific collection of groundnut (Arachis hypogaea). Plant Breeding. 137(6). 883–894. 4 indexed citations
11.
Shasidhar, Yaduru, Manish K. Vishwakarma, Manish K. Pandey, et al.. (2017). Molecular Mapping of Oil Content and Fatty Acids Using Dense Genetic Maps in Groundnut (Arachis hypogaea L.). Frontiers in Plant Science. 8. 794–794. 62 indexed citations
12.
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
13.
Vishwakarma, Manish K., Sandip M. Kale, Manda Sriswathi, et al.. (2017). Genome-Wide Discovery and Deployment of Insertions and Deletions Markers Provided Greater Insights on Species, Genomes, and Sections Relationships in the Genus Arachis. Frontiers in Plant Science. 8. 2064–2064. 23 indexed citations
14.
Vishwakarma, Manish K., Manish K. Pandey, Yaduru Shasidhar, et al.. (2016). Identification of two major quantitative trait locus for fresh seed dormancy using the diversity arrays technology and diversity arrays technology‐seq based genetic map in Spanish‐type peanuts. Plant Breeding. 135(3). 367–375. 22 indexed citations
15.
Pandey, Manish K., Aamir W. Khan, Vikas Kumar Singh, et al.. (2016). QTL‐seq approach identified genomic regions and diagnostic markers for rust and late leaf spot resistance in groundnut (Arachis hypogaea L.). Plant Biotechnology Journal. 15(8). 927–941. 148 indexed citations
16.
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

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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