Michael P. Pound

3.8k total citations · 1 hit paper
50 papers, 2.3k citations indexed

About

Michael P. Pound is a scholar working on Plant Science, Environmental Engineering and Ecology. According to data from OpenAlex, Michael P. Pound has authored 50 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Plant Science, 12 papers in Environmental Engineering and 10 papers in Ecology. Recurrent topics in Michael P. Pound's work include Smart Agriculture and AI (16 papers), Plant nutrient uptake and metabolism (10 papers) and Remote Sensing in Agriculture (9 papers). Michael P. Pound is often cited by papers focused on Smart Agriculture and AI (16 papers), Plant nutrient uptake and metabolism (10 papers) and Remote Sensing in Agriculture (9 papers). Michael P. Pound collaborates with scholars based in United Kingdom, United States and France. Michael P. Pound's co-authors include Tony Pridmore, Darren M. Wells, Andrew P. French, Jonathan A. Atkinson, Malcolm J. Bennett, Erik H. Murchie, Marcus Griffiths, Robail Yasrab, Alexander L. Bowler and Alexandra J. Burgess and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and The Plant Cell.

In The Last Decade

Michael P. Pound

45 papers receiving 2.2k 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.

Uncovering the hidden half of plants using new advances in root phenotyping

2018 241 citations Jonathan A. Atkinson, Michael P. Pound et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael P. Pound United Kingdom	21	1.8k	444	341	299	165	50	2.3k
Xavier Sirault Australia	22	1.7k 0.9×	673 1.5×	292 0.9×	429 1.4×	120 0.7×	38	2.2k
Hanno Scharr Germany	25	2.1k 1.1×	870 2.0×	298 0.9×	347 1.2×	185 1.1×	87	2.9k
Jonathan A. Atkinson United Kingdom	18	1.5k 0.8×	250 0.6×	259 0.8×	130 0.4×	96 0.6×	35	1.8k
Darren M. Wells United Kingdom	32	3.6k 2.0×	419 0.9×	1.3k 3.7×	228 0.8×	115 0.7×	70	4.2k
S. Ninomiya Japan	28	1.8k 1.0×	771 1.7×	164 0.5×	415 1.4×	479 2.9×	176	2.7k
Hemerson Pistori Brazil	24	1.4k 0.8×	773 1.7×	152 0.4×	381 1.3×	410 2.5×	104	2.6k
Weiliang Wen China	19	1.0k 0.6×	507 1.1×	70 0.2×	368 1.2×	129 0.8×	90	1.4k
Xiongkui He China	30	1.7k 0.9×	280 0.6×	171 0.5×	204 0.7×	70 0.4×	153	2.5k
Guillaume Lobet Belgium	24	2.2k 1.2×	236 0.5×	544 1.6×	214 0.7×	40 0.2×	56	2.8k
W. Clint Hoffmann United States	25	1.4k 0.8×	341 0.8×	180 0.5×	234 0.8×	112 0.7×	89	2.1k

Countries citing papers authored by Michael P. Pound

Since Specialization

Citations

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

Fields of papers citing papers by Michael P. Pound

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael P. Pound. 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 Michael P. Pound. The network helps show where Michael P. Pound may publish in the future.

Co-authorship network of co-authors of Michael P. Pound

This figure shows the co-authorship network connecting the top 25 collaborators of Michael P. Pound. A scholar is included among the top collaborators of Michael P. Pound 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 Michael P. Pound. Michael P. Pound 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

Ubbens, Jordan, Ian Stavness, Michael P. Pound, & Wei Guo. (2025). Deep learning in plant phenotyping: the first ten years. Plant Phenomics. 7(4). 100062–100062.

Maggi, Silvia, et al.. (2025). Whale Vision: A tool for identifying sperm whales and other cetaceans by their flank or fluke. Ecological Informatics. 91. 103384–103384.

French, Andrew P., et al.. (2023). Addressing multiple salient object detection via dual-space long-range dependencies. Computer Vision and Image Understanding. 235. 103776–103776. 2 indexed citations

Griffiths, Marcus, Nathan Mellor, Craig J. Sturrock, et al.. (2022). X‐ray CT reveals 4D root system development and lateral root responses to nitrate in soil. SHILAP Revista de lepidopterología. 5(1). 15 indexed citations

Jackson, Aaron S., et al.. (2021). GANana: Unsupervised Domain Adaptation for Volumetric Regression of Fruit. Plant Phenomics. 2021. 9874597–9874597. 12 indexed citations

Pound, Michael P., et al.. (2021). A fusion spatial attention approach for few-shot learning. Information Fusion. 81. 187–202. 19 indexed citations

Ghareeb, Hassan, Mohamed A. El-Sayed, Michael P. Pound, et al.. (2020). Quantitative Hormone Signaling Output Analyses of Arabidopsis thaliana Interactions With Virulent and Avirulent Hyaloperonospora arabidopsidis Isolates at Single-Cell Resolution. Frontiers in Plant Science. 11. 603693–603693. 6 indexed citations

Yasrab, Robail, Jonathan A. Atkinson, Darren M. Wells, et al.. (2019). RootNav 2.0: Deep learning for automatic navigation of complex plant root architectures. GigaScience. 8(11). 90 indexed citations

Pound, Michael P., et al.. (2019). Active Vision and Surface Reconstruction for 3D Plant Shoot Modelling. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 17(6). 1907–1917. 32 indexed citations

10.

Burgess, Alexandra J., et al.. (2019). Recovering Wind-Induced Plant Motion in Dense Field Environments via Deep Learning and Multiple Object Tracking. PLANT PHYSIOLOGY. 181(1). 28–42. 17 indexed citations

11.

Wu, Rui, Lina Duan, José L. Pruneda-Paz, et al.. (2018). The 6xABRE Synthetic Promoter Enables the Spatiotemporal Analysis of ABA-Mediated Transcriptional Regulation. PLANT PHYSIOLOGY. 177(4). 1650–1665. 83 indexed citations

12.

Pound, Michael P., et al.. (2018). Plant Phenotyping: An Active Vision Cell for Three-Dimensional Plant Shoot Reconstruction. PLANT PHYSIOLOGY. 178(2). 524–534. 43 indexed citations

13.

Pound, Michael P., Jonathan A. Atkinson, Alexandra J. Townsend, et al.. (2017). Deep machine learning provides state-of-the-art performance in image-based plant phenotyping. GigaScience. 6(10). 1–10. 246 indexed citations

14.

Pound, Michael P., et al.. (2017). AutoRoot: open-source software employing a novel image analysis approach to support fully-automated plant phenotyping. Plant Methods. 13(1). 12–12. 12 indexed citations

15.

Holroyd, Geoff H., Andrew P. French, Michael P. Pound, et al.. (2017). The Microphenotron: a robotic miniaturized plant phenotyping platform with diverse applications in chemical biology. Plant Methods. 13(1). 10–10. 16 indexed citations

16.

Burgess, Alexandra J., Renata Retkutė, Michael P. Pound, Sean Mayes, & Erik H. Murchie. (2016). Image-based 3D canopy reconstruction to determine potential productivity in complex multi-species crop systems. Annals of Botany. 119(4). mcw242–mcw242. 29 indexed citations

17.

Pound, Michael P., et al.. (2015). Three-dimensional reconstruction of plant shoots from multiple images using an active vision system. Repository@Nottingham (University of Nottingham). 1 indexed citations

18.

Burgess, Alexandra J., Renata Retkutė, Michael P. Pound, et al.. (2015). High-Resolution Three-Dimensional Structural Data Quantify the Impact of Photoinhibition on Long-Term Carbon Gain in Wheat Canopies in the Field. PLANT PHYSIOLOGY. 169(2). 1192–1204. 54 indexed citations

19.

Atkinson, Jonathan A., Luzie U. Wingen, Marcus Griffiths, et al.. (2015). Phenotyping pipeline reveals major seedling root growth QTL in hexaploid wheat. Journal of Experimental Botany. 66(8). 2283–2292. 166 indexed citations

20.

Lobet, Guillaume, Michael P. Pound, Christophe Pradal, et al.. (2015). Root System Markup Language: Toward a Unified Root Architecture Description Language. PLANT PHYSIOLOGY. 167(3). 617–627. 86 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.

Explore authors with similar magnitude of impact