Steven A. Cryer

830 total citations
43 papers, 680 citations indexed

About

Steven A. Cryer is a scholar working on Plant Science, Pollution and Computational Mechanics. According to data from OpenAlex, Steven A. Cryer has authored 43 papers receiving a total of 680 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Plant Science, 13 papers in Pollution and 10 papers in Computational Mechanics. Recurrent topics in Steven A. Cryer's work include Pesticide and Herbicide Environmental Studies (13 papers), Plant Surface Properties and Treatments (10 papers) and Plant Disease Management Techniques (10 papers). Steven A. Cryer is often cited by papers focused on Pesticide and Herbicide Environmental Studies (13 papers), Plant Surface Properties and Treatments (10 papers) and Plant Disease Management Techniques (10 papers). Steven A. Cryer collaborates with scholars based in United States, United Kingdom and Norway. Steven A. Cryer's co-authors include I. J. van Wesenbeeck, Cheryl B. Cleveland, Monte A. Mayes, Paul H. Steen, John W. Raymond, J. A. Knuteson, Piyush Singh, Jeffrey D. Wolt, Stephen Wilson and C. V. Eadsforth and has published in prestigious journals such as The Science of The Total Environment, Journal of Agricultural and Food Chemistry and Environmental Pollution.

In The Last Decade

Steven A. Cryer

39 papers receiving 598 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Steven A. Cryer United States 15 280 215 112 108 95 43 680
Xiao Xiao China 21 120 0.4× 66 0.3× 24 0.2× 131 1.2× 66 0.7× 93 1.2k
John W. Barry United States 12 195 0.7× 63 0.3× 78 0.7× 42 0.4× 74 0.8× 38 482
G. J. Dorr Australia 13 585 2.1× 211 1.0× 56 0.5× 164 1.5× 37 0.4× 31 788
W. Alison Forster New Zealand 16 676 2.4× 232 1.1× 110 1.0× 135 1.3× 64 0.7× 42 872
J.C. van de Zande Netherlands 17 815 2.9× 105 0.5× 147 1.3× 149 1.4× 131 1.4× 110 984
Katrijn Baetens Belgium 13 893 3.2× 221 1.0× 91 0.8× 220 2.0× 79 0.8× 32 1.1k
C. R. Glass United Kingdom 20 788 2.8× 67 0.3× 156 1.4× 65 0.6× 275 2.9× 117 1.1k
R. D. Brazee United States 18 775 2.8× 130 0.6× 46 0.4× 175 1.6× 98 1.0× 65 939
N. M. Western United Kingdom 17 636 2.3× 93 0.4× 78 0.7× 101 0.9× 121 1.3× 56 746
Eva Brusselman Belgium 14 358 1.3× 77 0.4× 60 0.5× 73 0.7× 150 1.6× 33 574

Countries citing papers authored by Steven A. Cryer

Since Specialization
Citations

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

Fields of papers citing papers by Steven A. Cryer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Steven A. Cryer. 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 Steven A. Cryer. The network helps show where Steven A. Cryer may publish in the future.

Co-authorship network of co-authors of Steven A. Cryer

This figure shows the co-authorship network connecting the top 25 collaborators of Steven A. Cryer. A scholar is included among the top collaborators of Steven A. Cryer 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 Steven A. Cryer. Steven A. Cryer 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.
Xavier, Alencar, et al.. (2025). Scalable Prediction of Northern Corn Leaf Blight and Gray Leaf Spot Diseases to Predict Fungicide Spray Timing in Corn. Agronomy. 15(2). 328–328. 2 indexed citations
2.
Hanspal, Navraj & Steven A. Cryer. (2024). The Use of Computational Fluid Dynamics (CFD) within the Agricultural Industry to Address General and Manufacturing Problems. Fluids. 9(8). 186–186. 1 indexed citations
3.
Cryer, Steven A. & John W. Raymond. (2024). Interpreting Image Patterns for Agricultural Sprays Using Statistics and Machine Learning Techniques. Fluids. 9(2). 40–40.
4.
Cryer, Steven A., et al.. (2024). Identifying bound compounds in non-extractable residues of pesticides in soil by 4-pool kinetic analysis. The Science of The Total Environment. 955. 176814–176814.
5.
Cryer, Steven A., et al.. (2022). Spray atomisation in multiphase flows with reference to tank mixes of agricultural products. Biosystems Engineering. 223. 232–248. 6 indexed citations
6.
Cryer, Steven A., et al.. (2020). Video and image classification using atomisation spray image patterns and deep learning. Biosystems Engineering. 200. 13–22. 21 indexed citations
7.
Cryer, Steven A., et al.. (2018). Generalized Management Strategies to Delay Herbicide Resistance: A Simulation Approach. Weed Science. 66(4). 530–539. 1 indexed citations
8.
Wesenbeeck, I. J. van, et al.. (2016). Comparison of regional air dispersion simulation and ambient air monitoring data for the soil fumigant 1,3-dichloropropene. The Science of The Total Environment. 569-570. 603–610. 9 indexed citations
9.
Cryer, Steven A., et al.. (2016). Modeling Pesticide Runoff from Small Watersheds through Field-Scale Management Practices: Minnesota Watershed Case Study with Chlorpyrifos. Air Soil and Water Research. 9. ASWR.S32777–ASWR.S32777. 7 indexed citations
10.
Cryer, Steven A., et al.. (2014). MECHANISMS, EXPERIMENT, AND THEORY OF LIQUID SHEET BREAKUP AND DROP SIZE FROM AGRICULTURAL NOZZLES. Atomization and Sprays. 24(8). 695–721. 41 indexed citations
11.
Wesenbeeck, I. J. van, et al.. (2011). Use of SOFEA to Predict 1,3‐D Concentrations in Air in High‐Use Regions of California. Journal of Environmental Quality. 40(5). 1462–1469. 5 indexed citations
12.
Cryer, Steven A., et al.. (2008). Estimating Soil Fumigant Permeability of Agricultural Films Using Empty Soil Columns. Environmental Engineering Science. 26(1). 171–182. 2 indexed citations
13.
Cryer, Steven A., et al.. (2003). Direct Treatment of Uncertainty: I—Applications in Aquatic Invertebrate Risk Assessment and Soil Metabolism for Chlorpyrifos. Environmental Engineering Science. 20(3). 155–167. 6 indexed citations
14.
Cryer, Steven A., et al.. (2003). Direct Treatment of Uncertainty: II—Applications in Pesticide Runoff, Leaching and Spray Drift Exposure Modeling. Environmental Engineering Science. 20(3). 169–181. 11 indexed citations
15.
Cryer, Steven A., et al.. (2003). Observations and process parameter sensitivities in fluid‐bed granulation. AIChE Journal. 49(11). 2802–2809. 29 indexed citations
16.
Wolt, Jeffrey D., et al.. (2002). Sensitivity analysis for validating expert opinion as to ideal data set criteria for transport modeling. Environmental Toxicology and Chemistry. 21(8). 1558–1565. 23 indexed citations
17.
Cleveland, Cheryl B., Monte A. Mayes, & Steven A. Cryer. (2001). An ecological risk assessment for spinosad use on cotton. Pest Management Science. 58(1). 70–84. 84 indexed citations
18.
Cryer, Steven A. & I. J. van Wesenbeeck. (2001). Predicted 1,3‐Dichloropropene Air Concentrations Resulting from Tree and Vine Applications in California. Journal of Environmental Quality. 30(6). 1887–1895. 13 indexed citations
19.
Cryer, Steven A.. (1999). Modeling agglomeration processes in fluid‐bed granulation. AIChE Journal. 45(10). 2069–2078. 62 indexed citations
20.
Wauchope, R. D., et al.. (1995). Pesticides report 34. Pesticide runoff: Methods and interpretation of field studies (Technical Report). Pure and Applied Chemistry. 67(12). 2089–2108. 30 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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