Micheal D. K. Owen

4.9k total citations
135 papers, 3.4k citations indexed

About

Micheal D. K. Owen is a scholar working on Plant Science, Pollution and Molecular Biology. According to data from OpenAlex, Micheal D. K. Owen has authored 135 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 128 papers in Plant Science, 40 papers in Pollution and 25 papers in Molecular Biology. Recurrent topics in Micheal D. K. Owen's work include Weed Control and Herbicide Applications (102 papers), Pesticide and Herbicide Environmental Studies (40 papers) and Legume Nitrogen Fixing Symbiosis (23 papers). Micheal D. K. Owen is often cited by papers focused on Weed Control and Herbicide Applications (102 papers), Pesticide and Herbicide Environmental Studies (40 papers) and Legume Nitrogen Fixing Symbiosis (23 papers). Micheal D. K. Owen collaborates with scholars based in United States, Canada and United Kingdom. Micheal D. K. Owen's co-authors include Ian A. Zelaya, Jerry M. Green, Ramón G. León, Douglas D. Buhler, Bryan G. Young, Stephen C. Weller, David L. Jordan, Rob Wilson, David Shaw and Mark J. VanGessel and has published in prestigious journals such as Journal of Agricultural and Food Chemistry, Scientific Reports and Ecological Economics.

In The Last Decade

Micheal D. K. Owen

127 papers receiving 3.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Micheal D. K. Owen United States 33 3.1k 1.1k 873 600 279 135 3.4k
Stephen C. Weller United States 32 2.7k 0.9× 908 0.8× 933 1.1× 425 0.7× 249 0.9× 105 3.2k
Theodore M. Webster United States 29 4.2k 1.4× 1.4k 1.2× 908 1.0× 1.0k 1.7× 327 1.2× 129 4.6k
Ian Heap United States 13 4.0k 1.3× 1.7k 1.6× 1.1k 1.3× 735 1.2× 361 1.3× 18 4.3k
Bryan G. Young United States 30 2.7k 0.9× 1.2k 1.1× 573 0.7× 571 1.0× 191 0.7× 152 2.9k
Kassim Al‐Khatib United States 33 3.4k 1.1× 1.1k 0.9× 681 0.8× 617 1.0× 297 1.1× 167 3.6k
Nilda R. Burgos United States 37 5.0k 1.6× 1.7k 1.5× 1.2k 1.4× 814 1.4× 330 1.2× 163 5.4k
Peter H. Sikkema Canada 31 4.3k 1.4× 2.0k 1.8× 533 0.6× 1.1k 1.8× 278 1.0× 402 4.7k
Carol Mallory‐Smith United States 34 3.6k 1.2× 1.1k 1.0× 1.5k 1.7× 618 1.0× 514 1.8× 155 4.0k
Rene C. Van Acker Canada 28 2.7k 0.9× 387 0.3× 562 0.6× 1.0k 1.7× 303 1.1× 113 3.0k
Alan C. York United States 30 3.4k 1.1× 1.5k 1.3× 754 0.9× 681 1.1× 163 0.6× 160 3.6k

Countries citing papers authored by Micheal D. K. Owen

Since Specialization
Citations

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

Fields of papers citing papers by Micheal D. K. Owen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Micheal D. K. Owen. 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 Micheal D. K. Owen. The network helps show where Micheal D. K. Owen may publish in the future.

Co-authorship network of co-authors of Micheal D. K. Owen

This figure shows the co-authorship network connecting the top 25 collaborators of Micheal D. K. Owen. A scholar is included among the top collaborators of Micheal D. K. Owen 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 Micheal D. K. Owen. Micheal D. K. Owen 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.
Hartzler, Robert U., et al.. (2024). Confirmation of a four-way herbicide-resistant Palmer amaranth (Amaranthus palmeri) population in Iowa. Weed Science. 72(4). 330–338. 1 indexed citations
2.
3.
Dixon, Philip M., et al.. (2023). Monitoring the temporal changes in herbicide‐resistant Amaranthus tuberculatus : a landscape‐scale probability‐based estimation in Iowa. Pest Management Science. 79(12). 4819–4827. 4 indexed citations
4.
Gibson, David J., Karla L. Gage, Joseph L. Matthews, et al.. (2023). Exploring the effect of region on diversity and composition of weed seedbanks in herbicide‐resistant crop systems in the United States. Pest Management Science. 80(3). 1446–1453. 2 indexed citations
5.
Owen, Micheal D. K., et al.. (2023). Differential susceptibility of Iowa waterhemp (Amaranthus tuberculatus) populations to 2,4-D, dicamba, and glufosinate. Canadian Journal of Plant Science. 103(6). 595–599. 4 indexed citations
6.
Everman, Wesley J., et al.. (2023). Rapid evolution of competitive ability in giant foxtail (Setaria faberi) over 34 years. Weed Science. 71(1). 59–68. 3 indexed citations
7.
8.
Hurley, Terrance M., Katherine Dentzman, David E. Ervin, et al.. (2017). Economic and Behavioral Drivers of Herbicide Resistance Management in the U.S.. AgEcon Search (University of Minnesota, USA). 1 indexed citations
9.
Lamichhane, Jay Ram, Yann Devos, Hugh J. Beckie, et al.. (2016). Integrated weed management systems with herbicide-tolerant crops in the European Union: lessons learnt from home and abroad. Critical Reviews in Biotechnology. 37(4). 459–475. 65 indexed citations
10.
Shaw, David R., Michael E. Newman, Stephen C. Weller, et al.. (2011). Benchmark study on glyphosate‐resistant cropping systems in the United States. Part 3: Grower awareness, information sources, experiences and management practices regarding glyphosate‐resistant weeds. Pest Management Science. 67(7). 758–770. 24 indexed citations
11.
Owen, Micheal D. K., Bryan G. Young, David R. Shaw, et al.. (2011). Benchmark study on glyphosate‐resistant crop systems in the United States. Part 2: Perspectives. Pest Management Science. 67(7). 747–757. 22 indexed citations
12.
Shaw, David, Micheal D. K. Owen, Philip M. Dixon, et al.. (2011). Benchmark study on glyphosate‐resistant cropping systems in the United States. Part 1: Introduction to 2006–2008. Pest Management Science. 67(7). 741–746. 29 indexed citations
13.
Owen, Micheal D. K.. (2008). Weed species shifts in glyphosate‐resistant crops. Pest Management Science. 64(4). 377–387. 147 indexed citations
14.
Owen, Micheal D. K., et al.. (2004). Weed Seedbank Comparison in Conservation Reserve Program and Adjacent Fields Under Continuous Cultivation1. Weed Technology. 18(1). 45–51. 3 indexed citations
15.
Zelaya, Ian A., Micheal D. K. Owen, H. S. Jacob, J. Dodd, & J. H. Moore. (2002). Amaranthus tuberculatus (Mq. ex DC) J.D.Sauer: potential for selection of glyphosate resistance.. 630–633. 6 indexed citations
16.
Owen, Micheal D. K., et al.. (2002). Effect of Location and Burial Depth on Woolly Cupgrass (Eriochloa villosa) Seed Germination1. Weed Technology. 16(4). 719–723. 1 indexed citations
17.
Owen, Micheal D. K.. (2001). Importance of weed population shifts and herbicide resistance in the Midwest USA corn belt.. 407–412. 7 indexed citations
18.
Hall, J. Christopher, Laura L. Van Eerd, Stephen D. Miller, et al.. (2000). Future Research Directions for Weed Science1. Weed Technology. 14(3). 647–658. 35 indexed citations
19.
Cruse, Richard M., et al.. (1992). Strip intercropping systems. Iowa State University Digital Repository (Iowa State University). 1 indexed citations
20.
Owen, Micheal D. K.. (1992). Theory and Practice: Weed Management In No Tillage Soybeans. Proceedings of the Integrated Crop Management Conference. 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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