C. S. Tan

5.4k total citations · 1 hit paper
137 papers, 4.3k citations indexed

About

C. S. Tan is a scholar working on Soil Science, Environmental Chemistry and Plant Science. According to data from OpenAlex, C. S. Tan has authored 137 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Soil Science, 45 papers in Environmental Chemistry and 32 papers in Plant Science. Recurrent topics in C. S. Tan's work include Soil and Water Nutrient Dynamics (45 papers), Soil Carbon and Nitrogen Dynamics (31 papers) and Irrigation Practices and Water Management (30 papers). C. S. Tan is often cited by papers focused on Soil and Water Nutrient Dynamics (45 papers), Soil Carbon and Nitrogen Dynamics (31 papers) and Irrigation Practices and Water Management (30 papers). C. S. Tan collaborates with scholars based in Canada, Malaysia and United States. C. S. Tan's co-authors include C. F. Drury, W. D. Reynolds, X.M. Yang, T. W. Welacky, T. Q. Zhang, J. D. Gaynor, C. A. Fox, T. Andrew Black, T. O. Oloya and T.Q. Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and Ecology.

In The Last Decade

C. S. Tan

129 papers receiving 4.0k citations

Hit Papers

Use of indicators and pore volume-function characteristic... 2009 2026 2014 2020 2009 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
C. S. Tan Canada 35 2.4k 1.3k 1.0k 928 699 137 4.3k
Kristofor R. Brye United States 33 1.8k 0.8× 1.0k 0.8× 1.3k 1.2× 522 0.6× 442 0.6× 246 3.9k
D. E. Radcliffe United States 34 1.5k 0.6× 1.1k 0.8× 646 0.6× 719 0.8× 902 1.3× 123 3.7k
Chandra A. Madramootoo Canada 38 2.4k 1.0× 1.3k 1.0× 1.4k 1.4× 654 0.7× 1.3k 1.9× 251 5.4k
Jan Diels Belgium 41 1.7k 0.7× 562 0.4× 1.2k 1.1× 711 0.8× 580 0.8× 172 4.3k
Francesco Morari Italy 36 1.8k 0.7× 717 0.6× 756 0.8× 844 0.9× 319 0.5× 146 3.8k
Chunsheng Hu China 46 3.0k 1.2× 1.0k 0.8× 1.7k 1.7× 572 0.6× 444 0.6× 228 5.8k
Norman R. Fausey United States 36 1.9k 0.8× 2.1k 1.7× 592 0.6× 670 0.7× 1.7k 2.5× 143 4.2k
Zhiming Qi Canada 31 1.5k 0.6× 708 0.6× 1.0k 1.0× 429 0.5× 847 1.2× 172 3.2k
Liwang Ma United States 43 2.5k 1.1× 1.1k 0.8× 1.8k 1.8× 1.0k 1.1× 1.4k 2.0× 184 5.4k
D. W. Meek United States 31 1.5k 0.6× 1.1k 0.8× 954 0.9× 324 0.3× 759 1.1× 72 3.6k

Countries citing papers authored by C. S. Tan

Since Specialization
Citations

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

Fields of papers citing papers by C. S. Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of C. S. Tan

This figure shows the co-authorship network connecting the top 25 collaborators of C. S. Tan. A scholar is included among the top collaborators of C. S. Tan 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 C. S. Tan. C. S. Tan 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.
Li, Wen, C. S. Tan, Zhaodi Jiang, et al.. (2025). Plasma membrane-associated ARAF condensates fuel RAS-related cancer drug resistance. Nature Chemical Biology. 21(8). 1226–1237. 5 indexed citations
2.
Premkumar, M., R. Sowmya, Tengku Juhana Tengku Hashim, C. S. Tan, & Rabeh Abbassi. (2024). Fitness-guided particle swarm optimization with adaptive Newton-Raphson for photovoltaic model parameter estimation. Applied Soft Computing. 167. 112295–112295. 5 indexed citations
4.
Premkumar, M., et al.. (2024). Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm. Scientific Reports. 14(1). 20979–20979. 10 indexed citations
5.
Tan, C. S., Abhishek Gupta, & Chi Xu. (2022). Are Two Heads Always Better Than One? Human-AI Complementarity in Multi-criteria Order Planning. 2022 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). 939–943. 2 indexed citations
6.
Zhang, T.Q., Jan J. H. Ciborowski, Yingming Zhao, et al.. (2020). Characterization of sedimentary phosphorus in Lake Erie and on-site quantification of internal phosphorus loading. Water Research. 188. 116525–116525. 40 indexed citations
7.
Wang, Zhaozhi, T.Q. Zhang, C. S. Tan, et al.. (2018). Simulating crop yield, surface runoff, tile drainage and phosphorus loss in a clay loam soil of the Lake Erie region using EPIC. Agricultural Water Management. 204. 212–221. 16 indexed citations
8.
Wang, Zhaozhi, T.Q. Zhang, C. S. Tan, et al.. (2018). Modeling phosphorus losses from soils amended with cattle manures and chemical fertilizers. The Science of The Total Environment. 639. 580–587. 24 indexed citations
9.
Zhang, T.Q., et al.. (2017). Drainage water management combined with cover crop enhances reduction of soil phosphorus loss. The Science of The Total Environment. 586. 362–371. 29 indexed citations
10.
Zhang, T.Q., et al.. (2016). Soil phosphorus loss in tile drainage water from long-term conventional- and non-tillage soils of Ontario with and without compost addition. The Science of The Total Environment. 580. 9–16. 21 indexed citations
11.
Yang, Xueming, et al.. (2014). Organic carbon and nitrogen stocks in a clay loam soil 10 years after a single compost application. Canadian Journal of Plant Science. 5 indexed citations
12.
Zheng, Z. M., T.Q. Zhang, Guoqi Wen, et al.. (2014). Soil Testing to Predict Dissolved Reactive Phosphorus Loss in Surface Runoff from Organic Soils. Soil Science Society of America Journal. 78(5). 1786–1796. 15 indexed citations
13.
Tan, C. S., et al.. (2014). Assessment of the consciousness levels on renewable energy resources in the Sultanate of Oman. Renewable and Sustainable Energy Reviews. 40. 1081–1089. 15 indexed citations
15.
Zhang, T. Q., et al.. (2010). Evaluation of Agronomic and Economic Effects of Nitrogen and Phosphorus Additions to Green Pepper with Drip Fertigation. Agronomy Journal. 102(5). 1434–1440. 7 indexed citations
16.
Gaynor, J. D., C. S. Tan, C. F. Drury, & T. W. Welacky. (1993). Assessment of water quality employing intercrop, water table control and tillage management for corn production with band application of atrazine, metribuzin and metolachlor. 206. 59. 1 indexed citations
17.
Pelletier, Geneviève & C. S. Tan. (1993). Determining Irrigation Wetting Patterns Using Time Domain Reflectometry. HortScience. 28(4). 338–339. 9 indexed citations
18.
Tan, C. S. & J. M. Fulton. (1985). Water Uptake and Root Distribution by Corn and Tomato at Different Depths. HortScience. 20(4). 686–688. 5 indexed citations
19.
Tan, C. S., et al.. (1981). Transpiration, stomatal conductance, and photosynthesis of tomato plants with various proportions of root system supplied with water [Varieties]. Journal of the American Society for Horticultural Science. 7 indexed citations
20.
Gee, G.W., et al.. (1973). A Chamber for Applying Pressure to Roots of Intact Plants. PLANT PHYSIOLOGY. 52(5). 472–474. 6 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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