H. Winzeler

2.2k total citations
75 papers, 1.6k citations indexed

About

H. Winzeler is a scholar working on Plant Science, Nuclear and High Energy Physics and Agronomy and Crop Science. According to data from OpenAlex, H. Winzeler has authored 75 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Plant Science, 23 papers in Nuclear and High Energy Physics and 14 papers in Agronomy and Crop Science. Recurrent topics in H. Winzeler's work include Wheat and Barley Genetics and Pathology (20 papers), Particle physics theoretical and experimental studies (17 papers) and High-Energy Particle Collisions Research (14 papers). H. Winzeler is often cited by papers focused on Wheat and Barley Genetics and Pathology (20 papers), Particle physics theoretical and experimental studies (17 papers) and High-Energy Particle Collisions Research (14 papers). H. Winzeler collaborates with scholars based in Switzerland, United States and Netherlands. H. Winzeler's co-authors include M. Winzeler, Beat Keller, G. Schachermayr, Monika Messmer, J. E. Schmid, Phillip Owens, James R. Schupp, P. M. Fried, M. D. Gale and M. Nikolić and has published in prestigious journals such as The Science of The Total Environment, Water Resources Research and Nuclear Physics B.

In The Last Decade

H. Winzeler

74 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
H. Winzeler Switzerland 23 974 356 216 189 136 75 1.6k
Alex Martin United States 27 1.4k 1.5× 178 0.5× 452 2.1× 185 1.0× 25 0.2× 123 2.6k
J. W. Wilson Australia 23 1.2k 1.2× 46 0.1× 132 0.6× 184 1.0× 20 0.1× 100 2.2k
Carel W. Windt Germany 19 901 0.9× 186 0.5× 28 0.1× 139 0.7× 16 0.1× 33 1.4k
K. Ohki Japan 24 591 0.6× 108 0.3× 60 0.3× 397 2.1× 7 0.1× 96 1.7k
J. Černý Czechia 24 536 0.6× 865 2.4× 261 1.2× 122 0.6× 4 0.0× 122 2.0k
M. Hossain Ali Bangladesh 18 599 0.6× 122 0.3× 164 0.8× 24 0.1× 4 0.0× 82 1.4k
T R Barrass 5 246 0.3× 110 0.3× 19 0.1× 15 0.1× 15 0.1× 7 1.0k
Vincent P. Gutschick United States 25 953 1.0× 11 0.0× 83 0.4× 90 0.5× 47 0.3× 58 2.3k
Anil C. Seth United States 39 146 0.1× 249 0.7× 17 0.1× 66 0.3× 12 0.1× 142 4.2k
Unnati Gupta India 23 787 0.8× 905 2.5× 265 1.2× 11 0.1× 6 0.0× 69 2.3k

Countries citing papers authored by H. Winzeler

Since Specialization
Citations

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

Fields of papers citing papers by H. Winzeler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by H. Winzeler. 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 H. Winzeler. The network helps show where H. Winzeler may publish in the future.

Co-authorship network of co-authors of H. Winzeler

This figure shows the co-authorship network connecting the top 25 collaborators of H. Winzeler. A scholar is included among the top collaborators of H. Winzeler 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 H. Winzeler. H. Winzeler 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.
Mack, Brian M., H. Winzeler, Matthew D. Lebar, et al.. (2025). Prediction of aflatoxin contamination outbreaks in Texas corn using mechanistic and machine learning models. Frontiers in Microbiology. 16. 1528997–1528997. 4 indexed citations
2.
Mosher, Gretchen A., Charles R. Hurburgh, Kanniah Rajasekaran, et al.. (2024). Predicting fumonisins in Iowa corn: Gradient boosting machine learning. Cereal Chemistry. 101(6). 1261–1272. 2 indexed citations
3.
Libohova, Zamir, et al.. (2024). Influence of sample size, model selection, and land use on prediction accuracy of soil properties. Geoderma Regional. 36. e00766–e00766. 11 indexed citations
4.
Winzeler, H., Marcelo Mancini, Zamir Libohova, et al.. (2024). Vegetation Masking of Remote Sensing Data Aids Machine Learning for Soil Fertility Prediction. Remote Sensing. 16(17). 3297–3297. 2 indexed citations
5.
Adhikari, Kabindra, Marcelo Mancini, Zamir Libohova, et al.. (2024). Heavy metals concentration in soils across the conterminous USA: Spatial prediction, model uncertainty, and influencing factors. The Science of The Total Environment. 919. 170972–170972. 29 indexed citations
6.
Mosher, Gretchen A., Charles R. Hurburgh, Phillip Owens, et al.. (2023). Gradient boosting machine learning model to predict aflatoxins in Iowa corn. Frontiers in Microbiology. 14. 1248772–1248772. 19 indexed citations
7.
Winzeler, H., Noemi Vergopolan, M. Focker, et al.. (2023). Dynamic geospatial modeling of mycotoxin contamination of corn in Illinois: unveiling critical factors and predictive insights with machine learning. Frontiers in Microbiology. 14. 1283127–1283127. 15 indexed citations
8.
Winzeler, H., Phillip Owens, Tulsi P. Kharel, Amanda J. Ashworth, & Zamir Libohova. (2023). Identification and Delineation of Broad-Base Agricultural Terraces in Flat Landscapes in Northeastern Oklahoma, USA. Land. 12(2). 486–486. 4 indexed citations
9.
Winzeler, H., Phillip Owens, Quentin D. Read, et al.. (2022). Topographic Wetness Index as a Proxy for Soil Moisture in a Hillslope Catena: Flow Algorithms and Map Generalization. Land. 11(11). 2018–2018. 34 indexed citations
10.
Schupp, James R., et al.. (2012). 1-Aminocyclopropane Carboxylic Acid Shows Promise as a Chemical Thinner for Apple. HortScience. 47(9). 1308–1311. 19 indexed citations
11.
Greene, Duane W., James R. Schupp, & H. Winzeler. (2011). Effect of Abscisic Acid and Benzyladenine on Fruit Set and Fruit Quality of Apples. HortScience. 46(4). 604–609. 28 indexed citations
12.
Winzeler, H. & James R. Schupp. (2011). Image Analysis of Blush Coverage Extent and Measures of Categorical Blush Intensity in ‘Honeycrisp’ Apples. HortScience. 46(5). 705–709. 3 indexed citations
13.
Baugher, Tara A., et al.. (2010). Mechanical String Thinner Reduces Crop Load at Variable Stages of Bloom Development of Peach and Nectarine Trees. HortScience. 45(9). 1327–1331. 9 indexed citations
14.
Schachermayr, G., et al.. (1994). Identification and localization of molecular markers linked to the Lr9 leaf rust resistance gene of wheat. Theoretical and Applied Genetics. 88(1). 110–115. 160 indexed citations
15.
Messmer, Monika, et al.. (1994). Genetic diversity in European wheat and spelt breeding material based on RFLP data. Theoretical and Applied Genetics. 88(8). 994–1003. 81 indexed citations
16.
Winzeler, H., et al.. (1990). Studies on the germination behaviour of spelt (Triticum spelta L.) and wheat (Triticum aestivum L.) under stress conditions.. Seed Science and Technology. 18(2). 311–320. 17 indexed citations
17.
Schmid, J. E. & H. Winzeler. (1990). Genetic studies of crosses between common wheat (Triticum aestivum L.) and spelt (Triticum spelta L.).. Journal of genetics & breeding. 44(2). 75–80. 19 indexed citations
18.
Winzeler, H. & J. Nösberger. (1980). Dry matter production and content of nonstructural carbohydrates during the grain filling period as influenced by different pre-grainfilling temperatures in two spring wheat cultivars.. 149(4). 318–327.
19.
Vegni, G., et al.. (1965). Coherent 6 GeV/ c π+ interactions on deuteron. Physics Letters. 19(6). 526–528. 22 indexed citations
20.
Teucher, M., et al.. (1956). ON THE MASS OF THE K$sup -$-MESON. Il Nuovo Cimento. 3 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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