D. Struss

1.9k total citations
33 papers, 1.1k citations indexed

About

D. Struss is a scholar working on Plant Science, Molecular Biology and Cell Biology. According to data from OpenAlex, D. Struss has authored 33 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Plant Science, 12 papers in Molecular Biology and 7 papers in Cell Biology. Recurrent topics in D. Struss's work include Plant Disease Resistance and Genetics (10 papers), Chromosomal and Genetic Variations (8 papers) and Plant Physiology and Cultivation Studies (7 papers). D. Struss is often cited by papers focused on Plant Disease Resistance and Genetics (10 papers), Chromosomal and Genetic Variations (8 papers) and Plant Physiology and Cultivation Studies (7 papers). D. Struss collaborates with scholars based in Germany, United States and Thailand. D. Struss's co-authors include Joerg Plieske, G. Röbbelen, Stephen M. Southwick, Carlos F. Quirós, Amy Iezzoni, Bernhard Saal, Claudio Cantini, Riaz Ahmad, Warren F. Lamboy and Riaz Ahmad and has published in prestigious journals such as The Plant Journal, Theoretical and Applied Genetics and PeerJ.

In The Last Decade

D. Struss

31 papers receiving 996 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Struss Germany 19 962 427 313 166 81 33 1.1k
Amy K. Szewc‐McFadden United States 9 804 0.8× 324 0.8× 333 1.1× 170 1.0× 132 1.6× 12 922
Robert Ballard United States 15 784 0.8× 451 1.1× 177 0.6× 220 1.3× 210 2.6× 28 982
Bernard Prins United States 11 1.0k 1.1× 265 0.6× 175 0.6× 122 0.7× 121 1.5× 16 1.2k
O. Lain Italy 11 504 0.5× 290 0.7× 166 0.5× 99 0.6× 59 0.7× 28 669
M.A. Viruel Spain 15 670 0.7× 313 0.7× 147 0.5× 142 0.9× 161 2.0× 25 882
G. Kahl Germany 15 835 0.9× 288 0.7× 192 0.6× 159 1.0× 313 3.9× 29 1.1k
Edward Fickus United States 12 2.2k 2.3× 314 0.7× 695 2.2× 101 0.6× 38 0.5× 15 2.4k
Maria Teresa Dettori Italy 17 1.3k 1.3× 698 1.6× 183 0.6× 427 2.6× 196 2.4× 36 1.5k
Jonathan Fresnedo‐Ramírez United States 16 522 0.5× 251 0.6× 99 0.3× 155 0.9× 86 1.1× 39 670
Marta Matvienko United States 15 703 0.7× 499 1.2× 160 0.5× 34 0.2× 72 0.9× 18 932

Countries citing papers authored by D. Struss

Since Specialization
Citations

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

Fields of papers citing papers by D. Struss

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Struss

This figure shows the co-authorship network connecting the top 25 collaborators of D. Struss. A scholar is included among the top collaborators of D. Struss 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 D. Struss. D. Struss 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.
Struss, D., et al.. (2023). Marker-assisted Selection to Combine Alleles for Four Disease Resistance Genes of Tomato Collocated on Chromosome 11. HortScience. 58(5). 495–501. 2 indexed citations
2.
Hesselink, Thamara, Hetty C. van den Broeck, Jan Cordewener, et al.. (2023). Genome architecture and genetic diversity of allopolyploid okra ( Abelmoschus esculentus ). The Plant Journal. 118(1). 225–241. 3 indexed citations
3.
4.
Struss, D., et al.. (2019). Identification of Single Nucleotide Polymorphism Markers Associated with Northern Corn Leaf Blight Resistance in Sweet Corn. Chiang Mai University Journal of Natural Sciences. 19(1). 155–162. 1 indexed citations
5.
Saal, Bernhard & D. Struss. (2005). RGA- and RAPD-derived SCAR markers for a Brassica B-genome introgression conferring resistance to blackleg in oilseed rape. Theoretical and Applied Genetics. 111(2). 281–290. 26 indexed citations
6.
Struss, D., et al.. (2003). Analysis of Sweet Cherry (Prunus avium L.) Cultivars Using SSR and AFLP Markers. Journal of the American Society for Horticultural Science. 128(6). 904–909. 3 indexed citations
7.
Ahmad, Riaz, D. Struss, & Stephen M. Southwick. (2003). Development and Characterization of Microsatellite Markers in Citrus. Journal of the American Society for Horticultural Science. 128(4). 584–590. 1 indexed citations
8.
Struss, D., et al.. (2003). Analysis of Sweet Cherry (Prunus avium L.) Cultivars Using SSR and AFLP Markers. Journal of the American Society for Horticultural Science. 128(6). 904–909. 93 indexed citations
9.
Parfitt, Dan E., et al.. (2003). Intraspecific olive diversity assessed with AFLP. Plant Breeding. 122(2). 173–177. 34 indexed citations
10.
Struss, D., et al.. (2002). Microsatellite Markers Differentiate Eight Giessen Cherry Rootstocks. HortScience. 37(1). 191–193. 27 indexed citations
11.
Struss, D., et al.. (2001). Detection of genetic diversity among populations of sweet cherry (Prunus aviumL.) by AFLPs. The Journal of Horticultural Science and Biotechnology. 76(3). 362–367. 23 indexed citations
12.
Cantini, Claudio, et al.. (2001). DNA Fingerprinting of Tetraploid Cherry Germplasm Using Simple Sequence Repeats. Journal of the American Society for Horticultural Science. 126(2). 205–209. 129 indexed citations
13.
Plieske, Joerg & D. Struss. (2001). Microsatellite markers for genome analysis in Brassica. I. development in Brassica napus and abundance in Brassicaceae species. Theoretical and Applied Genetics. 102(5). 689–694. 94 indexed citations
14.
Plieske, Joerg & D. Struss. (2001). STS markers linked to Phoma resistance genes of the Brassica B-genome revealed sequence homology between Brassica nigra and Brassica napus. Theoretical and Applied Genetics. 102(4). 483–488. 19 indexed citations
15.
Hu, J., et al.. (1999). SCAR and RAPD markers associated with 18‐carbon fatty acids in rapeseed, Brassica napus. Plant Breeding. 118(2). 145–150. 24 indexed citations
16.
Plieske, Joerg, D. Struss, & G. Röbbelen. (1998). Inheritance of resistance derived from the B-genome of Brassica against Phoma lingam in rapeseed and the development of molecular markers. Theoretical and Applied Genetics. 97(5-6). 929–936. 41 indexed citations
17.
Struss, D., Carlos F. Quirós, Joerg Plieske, & G. Röbbelen. (1996). Construction of Brassica B genome synteny groups based on chromosomes extracted from three different sources by phenotypic, isozyme and molecular markers. Theoretical and Applied Genetics. 93(7). 1026–1032. 40 indexed citations
18.
Struss, D., et al.. (1996). Rapid screening of selected European winter wheat varieties and segregating populations for the Glu‐D1d allele using PCR. Plant Breeding. 115(6). 451–454. 18 indexed citations
19.
Struss, D., Carlos F. Quirós, & G. Röbbelen. (1992). Mapping of Molecular Markers on Brassica B‐Genome Chromosomes Added to Brassica napus. Plant Breeding. 108(4). 320–323. 19 indexed citations
20.
Struss, D., et al.. (1991). Development of B‐Genome Chromosome Addition Lines of B. napus Using Different Interspecific Brassica Hybrids. Plant Breeding. 106(3). 209–214. 44 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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