Tom De Swaef

1.9k total citations
61 papers, 1.3k citations indexed

About

Tom De Swaef is a scholar working on Plant Science, Global and Planetary Change and Soil Science. According to data from OpenAlex, Tom De Swaef has authored 61 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Plant Science, 22 papers in Global and Planetary Change and 16 papers in Soil Science. Recurrent topics in Tom De Swaef's work include Greenhouse Technology and Climate Control (22 papers), Plant Water Relations and Carbon Dynamics (20 papers) and Irrigation Practices and Water Management (13 papers). Tom De Swaef is often cited by papers focused on Greenhouse Technology and Climate Control (22 papers), Plant Water Relations and Carbon Dynamics (20 papers) and Irrigation Practices and Water Management (13 papers). Tom De Swaef collaborates with scholars based in Belgium, Spain and Colombia. Tom De Swaef's co-authors include Kathy Steppe, Veerle De Schepper, Ingvar Bauweraerts, Peter Lootens, Isabel Roldán-Ruíz, Maurits W. Vandegehuchte, Raoul Lemeur, Jonas Aper, J. Baert and Irene Borra‐Serrano and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Agricultural and Food Chemistry and Scientific Reports.

In The Last Decade

Tom De Swaef

56 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tom De Swaef Belgium 19 837 519 260 185 173 61 1.3k
Olga M. Grant United Kingdom 18 1.0k 1.2× 566 1.1× 318 1.2× 169 0.9× 104 0.6× 32 1.4k
Matthew M. Conley United States 15 970 1.2× 410 0.8× 417 1.6× 167 0.9× 147 0.8× 30 1.3k
Peixi Su China 15 730 0.9× 386 0.7× 201 0.8× 241 1.3× 122 0.7× 76 1.3k
G. S. Zhou China 10 808 1.0× 480 0.9× 224 0.9× 129 0.7× 129 0.7× 14 1.2k
P.H.B. de Visser Netherlands 23 1.7k 2.0× 507 1.0× 279 1.1× 194 1.0× 65 0.4× 81 2.1k
Andrea Pitacco Italy 19 678 0.8× 834 1.6× 202 0.8× 233 1.3× 312 1.8× 61 1.5k
Jean Dauzat France 24 941 1.1× 697 1.3× 327 1.3× 134 0.7× 74 0.4× 66 1.6k
Javier Gulías Spain 20 1.2k 1.5× 934 1.8× 299 1.1× 125 0.7× 194 1.1× 49 1.9k
Jhonathan E. Ephrath Israel 22 862 1.0× 302 0.6× 111 0.4× 286 1.5× 71 0.4× 63 1.3k
Gaëlle Damour France 12 702 0.8× 752 1.4× 92 0.4× 163 0.9× 275 1.6× 25 1.2k

Countries citing papers authored by Tom De Swaef

Since Specialization
Citations

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

Fields of papers citing papers by Tom De Swaef

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom De Swaef. 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 Tom De Swaef. The network helps show where Tom De Swaef may publish in the future.

Co-authorship network of co-authors of Tom De Swaef

This figure shows the co-authorship network connecting the top 25 collaborators of Tom De Swaef. A scholar is included among the top collaborators of Tom De Swaef 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 Tom De Swaef. Tom De Swaef 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.
Panozzo, Anna, Paul Quataert, Tom De Swaef, et al.. (2025). A meta-analysis on the impact of trees on yield of intercrops in alley-cropping systems of temperate climates. Agricultural Systems. 232. 104578–104578.
2.
Rockwell, Fulton E., Annika E. Huber, I. P. Wu, et al.. (2025). Loss of conductance between mesophyll symplasm and intercellular air spaces explains nonstomatal control of transpiration. Proceedings of the National Academy of Sciences. 122(47). e2504862122–e2504862122. 1 indexed citations
3.
Blanchy, Guillaume, Tom De Swaef, Peter Lootens, et al.. (2025). Closing the phenotyping gap with non-invasive belowground field phenotyping. SOIL. 11(1). 67–84. 4 indexed citations
4.
Swaef, Tom De, Jan Vanderborght, Eric Laloy, et al.. (2025). Modeling quinoa growth under saline and water-limiting conditions using SWAP-WOFOST. Agricultural Water Management. 309. 109356–109356.
5.
Vanderborght, Jan, et al.. (2024). Exploring tolerance mechanisms and root morphological development of New Zealand spinach and quinoa across salinity levels. South African Journal of Botany. 171. 10–20. 2 indexed citations
6.
Stock, Michiel, et al.. (2024). Plant science in the age of simulation intelligence. Frontiers in Plant Science. 14. 1299208–1299208. 7 indexed citations
7.
Muylle, Hilde, et al.. (2024). Phenotypic characterization of drought responses in red clover (Trifolium pratense L.). Frontiers in Plant Science. 14. 1304411–1304411. 6 indexed citations
8.
Borra‐Serrano, Irene, Paul Quataert, Tom De Swaef, et al.. (2024). Quantification of species composition in grass-clover swards using RGB and multispectral UAV imagery and machine learning. Frontiers in Plant Science. 15. 1414181–1414181. 1 indexed citations
9.
Gebremikael, Mesfin Tsegaye, Kenneth Dumack, Tom De Swaef, et al.. (2023). Root traits explain multitrophic interactions of belowground microfauna on soil nitrogen mineralization and plant productivity. Soil Biology and Biochemistry. 184. 109093–109093. 6 indexed citations
10.
Cruz, Daniel Felipe, Tom De Swaef, Peter Lootens, et al.. (2023). Predicting yield of individual field-grown rapeseed plants from rosette-stage leaf gene expression. PLoS Computational Biology. 19(5). e1011161–e1011161. 8 indexed citations
11.
Frenne, Pieter De, et al.. (2023). Usefulness of cultivar-level calibration of AquaCrop for vegetables depends on the crop and data availability. Frontiers in Plant Science. 14. 1094677–1094677. 6 indexed citations
12.
Swaef, Tom De, Irene Borra‐Serrano, Valentin Couvreur, et al.. (2022). On the pivotal role of water potential to model plant physiological processes. Lirias (KU Leuven). 4(1). 30 indexed citations
13.
Swaef, Tom De, et al.. (2022). Leveraging plant physiological dynamics using physical reservoir computing. Scientific Reports. 12(1). 12594–12594. 13 indexed citations
14.
Sanczuk, Pieter, et al.. (2021). MIRRA: A Modular and Cost-Effective Microclimate Monitoring System for Real-Time Remote Applications. Sensors. 21(13). 4615–4615. 11 indexed citations
15.
Borra‐Serrano, Irene, Tom De Swaef, Paul Quataert, et al.. (2020). Closing the Phenotyping Gap: High Resolution UAV Time Series for Soybean Growth Analysis Provides Objective Data from Field Trials. Remote Sensing. 12(10). 1644–1644. 49 indexed citations
16.
Debode, Jane, Caroline De Tender, Pieter Cremelie, et al.. (2018). Trichoderma-Inoculated Miscanthus Straw Can Replace Peat in Strawberry Cultivation, with Beneficial Effects on Disease Control. Frontiers in Plant Science. 9. 213–213. 26 indexed citations
17.
Swaef, Tom De, et al.. (2014). High light decreases xylem contribution to fruit growth in tomato. Plant Cell & Environment. 38(3). 487–498. 28 indexed citations
18.
19.
Swaef, Tom De, Steven M. Driever, Lieven Van Meulebroek, et al.. (2012). Understanding the effect of carbon status on stem diameter variations. Annals of Botany. 111(1). 31–46. 34 indexed citations
20.
Swaef, Tom De & Kathy Steppe. (2009). Prediction of stem turgor and water potential based on stem diameter variations and sap flow in tomato.. PubMed. 74(4). 115–20. 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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