Seth C. Murray

5.7k total citations
104 papers, 2.9k citations indexed

About

Seth C. Murray is a scholar working on Plant Science, Genetics and Ecology. According to data from OpenAlex, Seth C. Murray has authored 104 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Plant Science, 44 papers in Genetics and 24 papers in Ecology. Recurrent topics in Seth C. Murray's work include Genetic Mapping and Diversity in Plants and Animals (43 papers), Genetics and Plant Breeding (37 papers) and Remote Sensing in Agriculture (23 papers). Seth C. Murray is often cited by papers focused on Genetic Mapping and Diversity in Plants and Animals (43 papers), Genetics and Plant Breeding (37 papers) and Remote Sensing in Agriculture (23 papers). Seth C. Murray collaborates with scholars based in United States, China and United Kingdom. Seth C. Murray's co-authors include William L. Rooney, Stephen Kresovich, Sharon E. Mitchell, Patricia E. Klein, Arun Sharma, Steven L. Anderson, Martha T. Hamblin, John E. Mullet, Alper Adak and Timothy J. Herrman and has published in prestigious journals such as Nature, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Seth C. Murray

102 papers receiving 2.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Seth C. Murray United States 30 1.9k 1.0k 770 571 347 104 2.9k
Mitchell R. Tuinstra United States 35 3.1k 1.7× 1.5k 1.5× 1.4k 1.9× 280 0.5× 617 1.8× 110 4.3k
Awais Rasheed Pakistan 31 3.7k 2.0× 1.6k 1.6× 674 0.9× 551 1.0× 429 1.2× 123 4.3k
Arron H. Carter United States 29 2.2k 1.2× 901 0.9× 374 0.5× 490 0.9× 171 0.5× 119 2.6k
Wanneng Yang China 28 2.9k 1.5× 1.1k 1.0× 167 0.2× 932 1.6× 477 1.4× 90 3.5k
Harkamal Walia United States 37 4.2k 2.2× 926 0.9× 275 0.4× 307 0.5× 1.3k 3.7× 91 4.9k
Jens Léon Germany 34 4.1k 2.2× 1.6k 1.5× 764 1.0× 265 0.5× 457 1.3× 134 4.5k
Jack Christopher Australia 33 4.5k 2.4× 548 0.5× 1.4k 1.8× 360 0.6× 543 1.6× 119 5.1k
Márcio F. R. Resende United States 27 2.1k 1.1× 1.5k 1.4× 256 0.3× 296 0.5× 784 2.3× 89 3.4k
Gaëtan F. Tremblay Canada 28 669 0.4× 302 0.3× 1.7k 2.3× 210 0.4× 167 0.5× 151 2.8k
James C. Schnable United States 40 4.6k 2.4× 1.5k 1.5× 322 0.4× 770 1.3× 2.7k 7.6× 160 6.0k

Countries citing papers authored by Seth C. Murray

Since Specialization
Citations

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

Fields of papers citing papers by Seth C. Murray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Seth C. Murray. 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 Seth C. Murray. The network helps show where Seth C. Murray may publish in the future.

Co-authorship network of co-authors of Seth C. Murray

This figure shows the co-authorship network connecting the top 25 collaborators of Seth C. Murray. A scholar is included among the top collaborators of Seth C. Murray 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 Seth C. Murray. Seth C. Murray 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.
Daigh, Aaron Lee M., Samira H. Daroub, Peter Kyveryga, et al.. (2025). The value and broader impacts of agricultural and environmental scientific meetings. Agricultural & Environmental Letters. 10(1).
2.
Adak, Alper, et al.. (2025). A computational framework for modeling and predicting maize senescence: integrating UAV phenotyping, logistic growth, and genomics. Computers and Electronics in Agriculture. 237. 110471–110471. 1 indexed citations
3.
Adak, Alper, Seth C. Murray, Jode W. Edwards, et al.. (2025). Phenotypic plasticity in maize grain yield: Genetic and environmental insights of response to environmental gradients. The Plant Genome. 18(3). e70078–e70078. 1 indexed citations
4.
Adak, Alper, Seth C. Murray, Nithya Subramanian, et al.. (2024). Photoperiod associated late flowering reaction norm: Dissecting loci and genomic-enviromic associated prediction in maize. Field Crops Research. 311. 109380–109380. 2 indexed citations
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Adak, Alper, Dinakaran Elango, Soumyashree Kar, et al.. (2023). Unoccupied aerial systems imagery for phenotyping in cotton, maize, soybean, and wheat breeding. Crop Science. 63(4). 1722–1749. 36 indexed citations
8.
Adak, Alper, Seth C. Murray, Nithya Subramanian, et al.. (2023). Genetic mapping and prediction for novel lesion mimic in maize demonstrates quantitative effects from genetic background, environment and epistasis. Theoretical and Applied Genetics. 136(7). 155–155. 5 indexed citations
9.
Adak, Alper, Seth C. Murray, & Steven L. Anderson. (2022). Temporal phenomic predictions from unoccupied aerial systems can outperform genomic predictions. G3 Genes Genomes Genetics. 13(1). 27 indexed citations
10.
Murray, Seth C., et al.. (2022). Control of aflatoxin using atoxigenic strains and irrigation management is complicated by maize hybrid diversity. Crop Science. 62(2). 867–879. 2 indexed citations
11.
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Anderson, Steven L. & Seth C. Murray. (2020). R/UAStools::plotshpcreate: Create Multi-Polygon Shapefiles for Extraction of Research Plot Scale Agriculture Remote Sensing Data. Frontiers in Plant Science. 11. 511768–511768. 21 indexed citations
13.
Zhang, Meiping, et al.. (2020). Analysis of the genes controlling three quantitative traits in three diverse plant species reveals the molecular basis of quantitative traits. Scientific Reports. 10(1). 10074–10074. 33 indexed citations
14.
Zhang, Meiping, Yanru Cui, Yunhua Liu, et al.. (2019). Accurate prediction of maize grain yield using its contributing genes for gene-based breeding. Genomics. 112(1). 225–236. 18 indexed citations
15.
Anderson, Steven L., Seth C. Murray, Lonesome Malambo, et al.. (2019). Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems. 2(1). 1–15. 56 indexed citations
16.
Warburton, Marilyn L., Erika Womack, Juliet D. Tang, et al.. (2017). Genome‐Wide Association and Metabolic Pathway Analysis of Corn Earworm Resistance in Maize. The Plant Genome. 11(1). 20 indexed citations
17.
Murray, Seth C., et al.. (2017). Rust and Thinning Management Effect on Cup Quality and Plant Performance for Two Cultivars of Coffea arabica L. Journal of Agricultural and Food Chemistry. 66(21). 5281–5292. 14 indexed citations
18.
Fuente, Gerald N. De La, Seth C. Murray, Thomas Isakeit, et al.. (2015). Genome Wide Association Study for Drought, Aflatoxin Resistance, and Important Agronomic Traits of Maize Hybrids in the Sub-Tropics. PLoS ONE. 10(2). e0117737–e0117737. 75 indexed citations
19.
Yang, Liyi, et al.. (2015). Influence of Genetic Background on Anthocyanin and Copigment Composition and Behavior during Thermoalkaline Processing of Maize. Journal of Agricultural and Food Chemistry. 63(22). 5528–5538. 38 indexed citations
20.
Washburn, Jacob D., Seth C. Murray, Byron L. Burson, Robert R. Klein, & Russell W. Jessup. (2012). Targeted mapping of quantitative trait locus regions for rhizomatousness in chromosome SBI-01 and analysis of overwintering in a Sorghum bicolor × S. propinquum population. Molecular Breeding. 31(1). 153–162. 24 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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