Andrew Scaboo

1.1k total citations
48 papers, 697 citations indexed

About

Andrew Scaboo is a scholar working on Plant Science, Agronomy and Crop Science and Ecology. According to data from OpenAlex, Andrew Scaboo has authored 48 papers receiving a total of 697 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Plant Science, 5 papers in Agronomy and Crop Science and 3 papers in Ecology. Recurrent topics in Andrew Scaboo's work include Soybean genetics and cultivation (39 papers), Legume Nitrogen Fixing Symbiosis (31 papers) and Nematode management and characterization studies (15 papers). Andrew Scaboo is often cited by papers focused on Soybean genetics and cultivation (39 papers), Legume Nitrogen Fixing Symbiosis (31 papers) and Nematode management and characterization studies (15 papers). Andrew Scaboo collaborates with scholars based in United States, Ghana and Germany. Andrew Scaboo's co-authors include Vincent R. Pantalone, Pengyin Chen, Henry T. Nguyen, Kristin Bilyeu, Jing Zhou, H. R. Boerma, Clinton G. Meinhardt, David R. Walker, Tri D. Vuong and Jason D. Gillman and has published in prestigious journals such as Nature Communications, Journal of Agricultural and Food Chemistry and Food Chemistry.

In The Last Decade

Andrew Scaboo

44 papers receiving 674 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew Scaboo United States 16 599 73 63 50 48 48 697
Vuk Đorđević Serbia 14 396 0.7× 59 0.8× 86 1.4× 10 0.2× 41 0.9× 47 513
Minsu Kim South Korea 10 240 0.4× 32 0.4× 37 0.6× 10 0.2× 34 0.7× 21 283
Komaki Inoue Japan 14 480 0.8× 71 1.0× 190 3.0× 31 0.6× 80 1.7× 25 658
Kuldeep Tripathi India 14 587 1.0× 12 0.2× 49 0.8× 23 0.5× 22 0.5× 98 660
Maoni Chao China 13 429 0.7× 32 0.4× 178 2.8× 89 1.8× 54 1.1× 27 533
Yudelsy Antonia Tandrón Moya Germany 9 488 0.8× 63 0.9× 141 2.2× 19 0.4× 18 0.4× 10 561
Masaki Okamura Japan 14 533 0.9× 20 0.3× 146 2.3× 12 0.2× 80 1.7× 38 614
Ruineng Xu China 10 595 1.0× 29 0.4× 76 1.2× 7 0.1× 86 1.8× 14 664
Kerry Clark United States 11 252 0.4× 36 0.5× 71 1.1× 6 0.1× 17 0.4× 20 381
E. Gregová Slovakia 11 411 0.7× 9 0.1× 94 1.5× 10 0.2× 38 0.8× 54 521

Countries citing papers authored by Andrew Scaboo

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Scaboo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Scaboo

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Scaboo. A scholar is included among the top collaborators of Andrew Scaboo 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 Andrew Scaboo. Andrew Scaboo 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.
Viana, João Paulo Gomes, et al.. (2024). Genome scans for selection signatures identify candidate virulence genes for adaptation of the soybean cyst nematode to host resistance. Molecular Ecology. 33(17). e17490–e17490. 2 indexed citations
2.
Kim, Jeong Hwa, Andrew Scaboo, Katy Martin Rainey, Felix Fritschi, & Kristin Bilyeu. (2024). Redesigning soybean with improved oil and meal traits. Theoretical and Applied Genetics. 137(10). 218–218.
3.
Bilyeu, Kristin, et al.. (2024). Allele-tagged TaqMan® PCR genotyping assays for high-throughput detection of soybean cyst nematode resistance. Molecular Biology Reports. 52(1). 33–33.
4.
Chigeza, Godfree, et al.. (2024). Evaluating genetic diversity and seed composition stability within Pan‐African Soybean Variety Trials. Crop Science. 64(6). 3272–3292. 4 indexed citations
5.
Meinhardt, Clinton G., Jason D. Gillman, Kristin Bilyeu, et al.. (2023). Loss-of-function of an α-SNAP gene confers resistance to soybean cyst nematode. Nature Communications. 14(1). 7629–7629. 17 indexed citations
6.
Zhou, Jing, et al.. (2023). Assessment of Soybean Lodging Using UAV Imagery and Machine Learning. Plants. 12(16). 2893–2893. 12 indexed citations
7.
Mamidi, Sujan, et al.. (2023). Identification of loci associated with water use efficiency and symbiotic nitrogen fixation in soybean. Frontiers in Plant Science. 14. 1271849–1271849. 7 indexed citations
8.
Bilyeu, Kristin, Clinton G. Meinhardt, Qijian Song, et al.. (2023). Cataloging SCN resistance loci in North American public soybean breeding programs. Frontiers in Plant Science. 14. 1270546–1270546. 3 indexed citations
9.
Kim, Jeong Hwa, Andrew Scaboo, Vincent R. Pantalone, Zenglu Li, & Kristin Bilyeu. (2022). Utilization of Plant Architecture Genes in Soybean to Positively Impact Adaptation to High Yield Environments. Frontiers in Plant Science. 13. 891587–891587. 12 indexed citations
10.
Zhou, Jing, Eduardo Beche, Caio Canella Vieira, et al.. (2022). Improve Soybean Variety Selection Accuracy Using UAV-Based High-Throughput Phenotyping Technology. Frontiers in Plant Science. 12. 768742–768742. 11 indexed citations
11.
Meinhardt, Clinton G., Jason D. Gillman, Trupti Joshi, et al.. (2022). Epistatic interaction between Rhg1-a and Rhg2 in PI 90763 confers resistance to virulent soybean cyst nematode populations. Theoretical and Applied Genetics. 135(6). 2025–2039. 15 indexed citations
12.
Gillman, Jason D., et al.. (2022). Linkage analysis and residual heterozygotes derived near isogenic lines reveals a novel protein quantitative trait loci from a Glycine soja accession. Frontiers in Plant Science. 13. 938100–938100. 6 indexed citations
13.
Beche, Eduardo, Jason D. Gillman, Qijian Song, et al.. (2021). Genomic prediction using training population design in interspecific soybean populations. Molecular Breeding. 41(2). 15–15. 12 indexed citations
14.
Beche, Eduardo, Jason D. Gillman, Qijian Song, et al.. (2020). Nested association mapping of important agronomic traits in three interspecific soybean populations. Theoretical and Applied Genetics. 133(3). 1039–1054. 11 indexed citations
15.
16.
Zhou, Jing, et al.. (2019). Estimation of the Maturity Date of Soybean Breeding Lines Using UAV-Based Multispectral Imagery. Remote Sensing. 11(18). 2075–2075. 65 indexed citations
17.
Tuyen, D., Tri D. Vuong, David Dunn, et al.. (2018). Mapping and confirmation of loci for salt tolerance in a novel soybean germplasm, Fiskeby III. Default journal. 513–524. 2 indexed citations
18.
Tuyen, D., Tri D. Vuong, David Dunn, et al.. (2017). Mapping and confirmation of loci for salt tolerance in a novel soybean germplasm, Fiskeby III. Theoretical and Applied Genetics. 131(3). 513–524. 48 indexed citations
19.
Kadam, Suhas, Tri D. Vuong, Dan Qiu, et al.. (2015). Genomic-assisted phylogenetic analysis and marker development for next generation soybean cyst nematode resistance breeding. Plant Science. 242. 342–350. 67 indexed citations
20.
Chen, Pengyin, et al.. (2011). Heritability and correlations among food‐grade traits in soybean. Plant Breeding. 130(6). 647–652. 27 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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