Edward M. Barnes

5.4k total citations · 2 hit papers
95 papers, 4.0k citations indexed

About

Edward M. Barnes is a scholar working on Plant Science, Soil Science and Ecology. According to data from OpenAlex, Edward M. Barnes has authored 95 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 64 papers in Plant Science, 30 papers in Soil Science and 22 papers in Ecology. Recurrent topics in Edward M. Barnes's work include Research in Cotton Cultivation (25 papers), Irrigation Practices and Water Management (23 papers) and Remote Sensing in Agriculture (22 papers). Edward M. Barnes is often cited by papers focused on Research in Cotton Cultivation (25 papers), Irrigation Practices and Water Management (23 papers) and Remote Sensing in Agriculture (22 papers). Edward M. Barnes collaborates with scholars based in United States, Chile and Australia. Edward M. Barnes's co-authors include M. Susan Moran, Yoshio Inoue, Paul J. Pinter, Douglas J. Hunsaker, Peter Waller, Bruce A. Kimball, Thomas R. Clarke, Craig S. T. Daughtry, Paul D. Colaizzi and Christopher Y. Choi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and Scientific Reports.

In The Last Decade

Edward M. Barnes

89 papers receiving 3.6k citations

Hit Papers

Opportunities and limitations for image-based remote sens... 1997 2026 2006 2016 1997 2000 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Edward M. Barnes United States 27 2.2k 2.1k 1.2k 1.2k 781 95 4.0k
Raffaele Casa Italy 32 1.7k 0.8× 1.6k 0.7× 1.2k 1.0× 696 0.6× 429 0.5× 108 3.4k
Xiuliang Jin China 37 2.5k 1.2× 2.2k 1.0× 1.4k 1.2× 857 0.7× 337 0.4× 91 4.2k
V. González-Dugo Spain 35 2.5k 1.1× 2.6k 1.2× 1.0k 0.9× 1.7k 1.5× 603 0.8× 65 4.3k
Xiaojun Liu China 33 1.9k 0.9× 2.1k 1.0× 829 0.7× 555 0.5× 483 0.6× 125 3.4k
Aditya Singh United States 31 1.6k 0.8× 1.1k 0.5× 573 0.5× 839 0.7× 392 0.5× 141 3.3k
Qiang Cao China 35 2.4k 1.1× 2.3k 1.1× 1.3k 1.1× 560 0.5× 372 0.5× 119 3.8k
V. Alchanatis Israel 39 1.9k 0.9× 3.1k 1.5× 750 0.6× 1.2k 1.0× 458 0.6× 126 5.0k
Guerric Le Maire France 44 3.6k 1.7× 2.1k 1.0× 1.7k 1.5× 3.4k 2.9× 703 0.9× 135 6.7k
Paulo Eduardo Teodoro Brazil 30 1.3k 0.6× 2.6k 1.2× 450 0.4× 1.0k 0.9× 401 0.5× 471 4.6k
José A. Jiménez-Berni Spain 29 3.2k 1.5× 2.8k 1.3× 1.9k 1.6× 1.5k 1.3× 301 0.4× 49 5.2k

Countries citing papers authored by Edward M. Barnes

Since Specialization
Citations

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

Fields of papers citing papers by Edward M. Barnes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Edward M. Barnes

This figure shows the co-authorship network connecting the top 25 collaborators of Edward M. Barnes. A scholar is included among the top collaborators of Edward M. Barnes 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 Edward M. Barnes. Edward M. Barnes 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.
Barnes, Edward M., et al.. (2024). Utilizing John Deere’s Harvest Identification System in Cotton Fiber Quality Mapping. Applied Engineering in Agriculture. 40(4). 377–384.
3.
Singh, Jasdeep, Srinivasulu Ale, Paul B. DeLaune, & Edward M. Barnes. (2023). Simulated effects of cover crops with no-tillage on soil and crop productivity in rainfed semi-arid cotton production systems. Soil and Tillage Research. 230. 105709–105709. 11 indexed citations
4.
Maja, Joe Mari, Michael W. Marshall, Matthew Cutulle, et al.. (2023). The Next Generation of Cotton Defoliation Sprayer. AgriEngineering. 5(1). 441–459. 4 indexed citations
5.
Maja, Joe Mari, et al.. (2023). Agricultural Harvesting Robot Concept Design and System Components: A Review. AgriEngineering. 5(2). 777–800. 21 indexed citations
6.
Himanshu, Sushil Kumar, et al.. (2022). Assessing the Effects of a Winter Wheat Cover Crop on Soil Water Use, Cotton Yield, and Soil Organic Carbon in No-Till Cotton Production Systems. Journal of the ASABE. 65(5). 1163–1177. 2 indexed citations
8.
Wanjura, John D., et al.. (2021). An Integrated Plastic Contamination Monitoring System for Cotton Module Feeders. AgriEngineering. 3(4). 907–923. 3 indexed citations
9.
Griffin, Terry, Glenn J. Fitzgerald, James Lowenberg‐DeBoer, & Edward M. Barnes. (2020). Modeling local and global spatial correlation in field‐scale experiments. Agronomy Journal. 112(4). 2708–2721. 2 indexed citations
10.
Fue, Kadeghe G., Wesley M. Porter, Edward M. Barnes, Changying Li, & Glen C. Rains. (2020). Evaluation of a Stereo Vision System for Cotton Row Detection and Boll Location Estimation in Direct Sunlight. Agronomy. 10(8). 1137–1137. 19 indexed citations
11.
Hardin, Robert G., et al.. (2018). Effects of Gin Machinery on Cotton Quality. ˜The œjournal of cotton science/Journal of cotton science. 5 indexed citations
12.
Raper, Tyson B., Derrick M. Oosterhuis, & Edward M. Barnes. (2016). In-Season Cotton Drought-Stress Quantification: Previous Approaches and Future Directions. ˜The œjournal of cotton science/Journal of cotton science. 20(3). 179–194. 3 indexed citations
13.
Qiao, Xin, Hamid J. Farahani, Ahmad Khalilian, & Edward M. Barnes. (2016). Cotton Water Productivity and Growth Parameters in the Humid Southeast: Experimentation and Modeling. Transactions of the ASABE. 59(3). 949–962. 5 indexed citations
14.
Thorp, Kelly R., Srinivasulu Ale, Michael Bange, et al.. (2014). Development and Application of Process-based Simulation Models for Cotton Production: A Review of Past, Present, and Future Directions. ˜The œjournal of cotton science/Journal of cotton science. 18(1). 10–47. 66 indexed citations
15.
Buser, Michael D., et al.. (2010). Predicting Fiber Quality After Commercial Ginning Based on Fiber Obtained With Laboratory-Scale Gin Stands. ˜The œjournal of cotton science/Journal of cotton science.
16.
Sui, Ruixiu, et al.. (2010). Effect of Machine-Fiber Interaction on Cotton Fiber Quality and Foreign-Matter Particle Attachment to Fiber. ˜The œjournal of cotton science/Journal of cotton science. 14(3). 145–153. 13 indexed citations
17.
Barnes, Edward M., et al.. (2009). Harvesting and Seed Cotton Cleaning of a Cotton Variety with a Fragile Seed Coat. ˜The œjournal of cotton science/Journal of cotton science. 13(2). 158–165. 4 indexed citations
18.
Barnes, Edward M., et al.. (2006). Ginning a Cotton with a Fragile Seed Coat. ˜The œjournal of cotton science/Journal of cotton science. 10(1). 9 indexed citations
19.
Fitzgerald, Glenn J., et al.. (2006). Directed sampling using remote sensing with a response surface sampling design for site-specific agriculture. Computers and Electronics in Agriculture. 53(2). 98–112. 27 indexed citations
20.
Waller, Peter, Julio Haberland, Paul D. Colaizzi, et al.. (2003). GROUNDBASED REMOTE SENSING OF WATER AND NITROGEN STRESS. Transactions of the ASAE. 46(1). 38 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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