Bruno Studer

4.8k total citations · 2 hit papers
131 papers, 2.5k citations indexed

About

Bruno Studer is a scholar working on Plant Science, Agronomy and Crop Science and Molecular Biology. According to data from OpenAlex, Bruno Studer has authored 131 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 100 papers in Plant Science, 36 papers in Agronomy and Crop Science and 32 papers in Molecular Biology. Recurrent topics in Bruno Studer's work include Wheat and Barley Genetics and Pathology (37 papers), Genetic Mapping and Diversity in Plants and Animals (22 papers) and Plant pathogens and resistance mechanisms (20 papers). Bruno Studer is often cited by papers focused on Wheat and Barley Genetics and Pathology (37 papers), Genetic Mapping and Diversity in Plants and Animals (22 papers) and Plant pathogens and resistance mechanisms (20 papers). Bruno Studer collaborates with scholars based in Switzerland, United States and Denmark. Bruno Studer's co-authors include Roland Kölliker, Torben Asp, Thomas Lübberstedt, Achim Walter, Stephen Byrne, Steven Yates, Franco Widmer, Christian Bendixen, Lukas Wille and Monika Messmer and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and Bioinformatics.

In The Last Decade

Bruno Studer

116 papers receiving 2.4k citations

Hit Papers

Pathways for advancing pesticide policies 2020 2026 2022 2024 2020 2024 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bruno Studer Switzerland 28 1.8k 598 499 478 461 131 2.5k
Torben Asp Denmark 31 1.9k 1.1× 811 1.4× 680 1.4× 349 0.7× 497 1.1× 96 2.6k
Yong‐Bi Fu Canada 32 2.5k 1.4× 590 1.0× 1.1k 2.2× 272 0.6× 376 0.8× 141 3.2k
Philippe Barré France 23 1.0k 0.6× 245 0.4× 431 0.9× 322 0.7× 343 0.7× 82 1.6k
J. H. A. Barker United Kingdom 18 879 0.5× 466 0.8× 499 1.0× 224 0.5× 251 0.5× 33 1.6k
Dave Skinner United States 24 2.0k 1.1× 1.0k 1.7× 363 0.7× 264 0.6× 688 1.5× 91 2.6k
N. J. Chatterton United States 31 2.1k 1.2× 550 0.9× 221 0.4× 578 1.2× 611 1.3× 108 3.3k
Fulvia Rizza Italy 29 3.3k 1.9× 537 0.9× 467 0.9× 831 1.7× 171 0.4× 60 3.6k
Allan K. Fritz United States 34 3.1k 1.8× 340 0.6× 794 1.6× 917 1.9× 246 0.5× 105 3.4k
C.C.M. van de Wiel Netherlands 26 2.2k 1.2× 895 1.5× 314 0.6× 255 0.5× 195 0.4× 70 2.7k
Nilda R. Burgos United States 37 5.0k 2.8× 1.2k 2.1× 435 0.9× 814 1.7× 330 0.7× 163 5.4k

Countries citing papers authored by Bruno Studer

Since Specialization
Citations

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

Fields of papers citing papers by Bruno Studer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bruno Studer

This figure shows the co-authorship network connecting the top 25 collaborators of Bruno Studer. A scholar is included among the top collaborators of Bruno Studer 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 Bruno Studer. Bruno Studer 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
2.
Kölliker, Roland, et al.. (2025). Higher seed yield through selection for reduced seed shattering in Italian ryegrass. Crop Science. 65(1).
3.
Keller, Beat, et al.. (2024). The genetic basis of apple shape and size unraveled by digital phenotyping. G3 Genes Genomes Genetics. 14(5). 3 indexed citations
4.
Kirchgeßner, Norbert, et al.. (2024). FruitPhenoBox – a device for rapid and automated fruit phenotyping of small sample sizes. Plant Methods. 20(1). 74–74. 6 indexed citations
5.
Jha, Rintu, Kaixuan Zhang, Yuqi He, et al.. (2024). Global nutritional challenges and opportunities: Buckwheat, a potential bridge between nutrient deficiency and food security. Trends in Food Science & Technology. 145. 104365–104365. 47 indexed citations breakdown →
7.
Keller, Beat, Bodo Raatz, Bruno Studer, et al.. (2023). Linking photosynthesis and yield reveals a strategy to improve light use efficiency in a climbing bean breeding population. Journal of Experimental Botany. 75(3). 901–916. 13 indexed citations
8.
Grieder, Christoph, et al.. (2023). Perspectives for reducing seed shattering in ryegrasses. Grass and Forage Science. 78(4). 425–437. 2 indexed citations
9.
Kneřová, Jana, Z. Zwierzykowski, Martin Duchoslav, et al.. (2023). Both male and female meiosis contribute to non‐Mendelian inheritance of parental chromosomes in interspecific plant hybrids (Lolium × Festuca). New Phytologist. 238(2). 624–636. 8 indexed citations
10.
Turchetta, Matteo, Daniel Ariza-Suárez, Steven Yates, et al.. (2023). ChromaX: a fast and scalable breeding program simulator. Bioinformatics. 39(12). 4 indexed citations
11.
Keller, Beat, Morgane Roth, María José Aranzana, et al.. (2022). Genetic architecture and genomic predictive ability of apple quantitative traits across environments. Horticulture Research. 9. 24 indexed citations
12.
Ariza-Suárez, Daniel, Beat Keller, Héctor Fabio Buendía, et al.. (2022). Genetic analysis of resistance to bean leaf crumple virus identifies a candidate LRR‐RLK gene. The Plant Journal. 114(1). 23–38. 5 indexed citations
13.
Ruttink, Tom, Leif Skøt, Christoph Grieder, et al.. (2022). Phenotypic variation and quantitative trait loci for resistance to southern anthracnose and clover rot in red clover. Theoretical and Applied Genetics. 135(12). 4337–4349. 15 indexed citations
14.
Yates, Steven, Chloé Manzanares, Simon E. Bull, et al.. (2022). Callus Induction from Diverse Explants and Genotypes Enables Robust Transformation of Perennial Ryegrass (Lolium perenne L.). Plants. 11(15). 2054–2054. 6 indexed citations
15.
Manzanares, Chloé, Steven Yates, Daniel Thorogood, et al.. (2022). Fine-Mapping and Comparative Genomic Analysis Reveal the Gene Composition at the S and Z Self-incompatibility Loci in Grasses. Molecular Biology and Evolution. 40(1). 7 indexed citations
16.
Studer, Bruno, et al.. (2021). A multispecies amplicon sequencing approach for genetic diversity assessments in grassland plant species. Molecular Ecology Resources. 22(5). 1725–1745. 7 indexed citations
17.
Yates, Steven, Alexey Mikaberidze, Simon G. Krattinger, et al.. (2019). Precision Phenotyping Reveals Novel Loci for Quantitative Resistance to Septoria Tritici Blotch. Plant Phenomics. 2019. 3285904–3285904. 41 indexed citations
18.
Manzanares, Chloé, Susanne Barth, Daniel Thorogood, et al.. (2015). A Gene Encoding a DUF247 Domain Protein Cosegregates with the S Self-Incompatibility Locus in Perennial Ryegrass. Molecular Biology and Evolution. 33(4). 870–884. 56 indexed citations
19.
Hund, Andreas, et al.. (2014). Die Schweizer Pflanzenzüchtung – eine räumliche, zeitliche und thematische Analyse des Umfeldes. Agrarforschung Schweiz. 5(9). 366–373. 1 indexed citations
20.
Walter, Achim, et al.. (2014). The Swiss plant breeding sector - a spatial, temporal and thematic analysis. Agrarforschung Schweiz. 5(9). 366–373. 2 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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