Shawn M. Kaeppler

16.6k total citations · 3 hit papers
162 papers, 9.8k citations indexed

About

Shawn M. Kaeppler is a scholar working on Plant Science, Genetics and Agronomy and Crop Science. According to data from OpenAlex, Shawn M. Kaeppler has authored 162 papers receiving a total of 9.8k indexed citations (citations by other indexed papers that have themselves been cited), including 130 papers in Plant Science, 70 papers in Genetics and 46 papers in Agronomy and Crop Science. Recurrent topics in Shawn M. Kaeppler's work include Genetic Mapping and Diversity in Plants and Animals (67 papers), Genetics and Plant Breeding (34 papers) and Chromosomal and Genetic Variations (29 papers). Shawn M. Kaeppler is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (67 papers), Genetics and Plant Breeding (34 papers) and Chromosomal and Genetic Variations (29 papers). Shawn M. Kaeppler collaborates with scholars based in United States, China and United Kingdom. Shawn M. Kaeppler's co-authors include Jonathan P. Lynch, Natalia de León, Heidi F. Kaeppler, C. Robin Buell, R. L. Phillips, Rajandeep S. Sekhon, Jinming Zhu, Kathleen M. Brown, Nathan M. Springer and Yong Rhee and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Shawn M. Kaeppler

158 papers receiving 9.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Epigenetic aspects of somaclonal variation in plants

2000 562 citations Shawn M. Kaeppler, Heidi F. Kaeppler et al. profile →
Shovelomics: high throughput phenotyping of maize (Zea mays L.) root architecture in the field

2010 490 citations Shawn M. Kaeppler, Kathleen M. Brown et al. profile →
Insights into the Maize Pan-Genome and Pan-Transcriptome

2014 360 citations Candice N. Hirsch, James M. Johnson et al. The Plant Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shawn M. Kaeppler United States	55	8.2k	3.6k	2.5k	1.6k	541	162	9.8k
Katrien M. Devos United Kingdom	49	9.6k 1.2×	3.2k 0.9×	3.7k 1.5×	959 0.6×	252 0.5×	129	10.6k
Jianbing Yan China	65	11.6k 1.4×	4.0k 1.1×	7.2k 2.9×	1.2k 0.7×	288 0.5×	208	14.5k
Thomas Lübberstedt United States	47	6.2k 0.8×	2.0k 0.6×	3.0k 1.2×	924 0.6×	296 0.5×	258	7.3k
Patricia E. Klein United States	39	4.8k 0.6×	1.5k 0.4×	2.3k 0.9×	1.9k 1.2×	384 0.7×	119	6.1k
Mark E. Sorrells United States	86	23.2k 2.8×	3.9k 1.1×	13.0k 5.2×	2.3k 1.4×	559 1.0×	289	26.7k
Ronald R. Sederoff United States	60	7.0k 0.9×	7.7k 2.1×	1.6k 0.6×	570 0.3×	2.2k 4.1×	156	12.2k
Bin Han China	56	10.9k 1.3×	5.4k 1.5×	4.8k 1.9×	609 0.4×	337 0.6×	127	13.3k
Stephen J. Powers United Kingdom	46	5.5k 0.7×	2.5k 0.7×	373 0.1×	524 0.3×	208 0.4×	138	7.1k
John Mackay Canada	40	2.5k 0.3×	2.9k 0.8×	810 0.3×	390 0.2×	972 1.8×	143	5.3k
Patrick J. Brown United States	35	5.8k 0.7×	1.4k 0.4×	3.7k 1.5×	1.2k 0.8×	248 0.5×	91	7.3k

Countries citing papers authored by Shawn M. Kaeppler

Since Specialization

Citations

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

Fields of papers citing papers by Shawn M. Kaeppler

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shawn M. Kaeppler. 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 Shawn M. Kaeppler. The network helps show where Shawn M. Kaeppler may publish in the future.

Co-authorship network of co-authors of Shawn M. Kaeppler

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Fan, Jiahao, et al.. (2025). Mitigating NDVI saturation in imagery of dense and healthy vegetation. ISPRS Journal of Photogrammetry and Remote Sensing. 227. 234–250. 1 indexed citations

He, Cheng, Jacob D. Washburn, Heidi F. Kaeppler, et al.. (2024). Trait association and prediction through integrative k ‐mer analysis. The Plant Journal. 120(2). 833–850. 1 indexed citations

León, Natalia de, et al.. (2024). Modeling the impact of resource allocation decisions on genomic prediction using maize multi‐environment data. Crop Science. 64(5). 2748–2767. 1 indexed citations

Qiu, Yinjie, et al.. (2023). Genetic analysis of pericarp pigmentation variation in Corn Belt dent maize. G3 Genes Genomes Genetics. 14(1). 1 indexed citations

Lopez‐Cruz, Marco, Jacob D. Washburn, Natalia de León, et al.. (2023). Leveraging data from the Genomes-to-Fields Initiative to investigate genotype-by-environment interactions in maize in North America. Nature Communications. 14(1). 6904–6904. 18 indexed citations

Schneider, Hannah, Vai S. Lor, Xia Zhang, et al.. (2023). Transcription factor bHLH121 regulates root cortical aerenchyma formation in maize. Proceedings of the National Academy of Sciences. 120(12). e2219668120–e2219668120. 32 indexed citations

Zhou, Jing, et al.. (2023). Plot-Level Maize Early Stage Stand Counting and Spacing Detection Using Advanced Deep Learning Algorithms Based on UAV Imagery. Agronomy. 13(7). 1728–1728. 11 indexed citations

Martinell, Brian, et al.. (2023). A practical method to improve the efficiency of pollination in maize breeding and genetics research. Crop Science. 63(5). 2778–2792.

Liu, Wenxin, et al.. (2022). IntegrateNet: A Deep Learning Network for Maize Stand Counting From UAV Imagery by Integrating Density and Local Count Maps. IEEE Geoscience and Remote Sensing Letters. 19. 1–5. 16 indexed citations

10.

Fan, Jiahao, et al.. (2022). Estimation of Maize Yield and Flowering Time Using Multi-Temporal UAV-Based Hyperspectral Data. Remote Sensing. 14(13). 3052–3052. 40 indexed citations

11.

Hundley, Hope, Vasanth Singan, Yuko Yoshinaga, et al.. (2022). Genetic mapping and prediction of flowering time and plant height in a maize Stiff Stalk MAGIC population. Genetics. 221(2). 8 indexed citations

12.

Li, Zhi, Peng Zhou, Rafael Della Coletta, et al.. (2020). Single‐parent expression drives dynamic gene expression complementation in maize hybrids. The Plant Journal. 105(1). 93–107. 21 indexed citations

13.

Han, Zhaoxue, et al.. (2018). Heritable Epigenomic Changes to the Maize Methylome Resulting from Tissue Culture. Genetics. 209(4). 983–995. 54 indexed citations

14.

Gage, Joseph L., Michael White, Jode W. Edwards, Shawn M. Kaeppler, & Natalia de León. (2018). Selection Signatures Underlying Dramatic Male Inflorescence Transformation During Modern Hybrid Maize Breeding. Genetics. 210(3). 1125–1138. 38 indexed citations

15.

Gage, Joseph L., Nathan D. Miller, Edgar P. Spalding, Shawn M. Kaeppler, & Natalia de León. (2017). TIPS: a system for automated image-based phenotyping of maize tassels. Plant Methods. 13(1). 21–21. 53 indexed citations

16.

Emanuelli, Francesco, Linda Zamariola, Silvia Giuliani, et al.. (2017). Cloning of Vgt3, a major QTL for flowering time in maize. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 37–37. 1 indexed citations

17.

Hirsch, Candice N., Cory D. Hirsch, Alex B. Brohammer, et al.. (2016). Draft Assembly of Elite Inbred Line PH207 Provides Insights into Genomic and Transcriptome Diversity in Maize. The Plant Cell. 28(11). 2700–2714. 107 indexed citations

18.

Li, Qing, Steven R. Eichten, Peter J. Hermanson, et al.. (2014). Genetic Perturbation of the Maize Methylome. The Plant Cell. 26(12). 4602–4616. 139 indexed citations

19.

Johnson, James M., et al.. (2012). A high-throughput core sampling device for the evaluation of maize stalk composition. Biotechnology for Biofuels. 5(1). 27–27. 9 indexed citations

20.

Kaeppler, Shawn M., Roberto Tuberosa, Nathan M. Springer, et al.. (2009). Ronald L. Phillips: pioneer, scholar, mentor, and gentleman.. Maydica. 54(4). 365–373. 1 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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