C. Egger-Danner

1.8k total citations
96 papers, 1.4k citations indexed

About

C. Egger-Danner is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology. According to data from OpenAlex, C. Egger-Danner has authored 96 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Genetics, 50 papers in Agronomy and Crop Science and 34 papers in Animal Science and Zoology. Recurrent topics in C. Egger-Danner's work include Genetic and phenotypic traits in livestock (61 papers), Milk Quality and Mastitis in Dairy Cows (27 papers) and Effects of Environmental Stressors on Livestock (27 papers). C. Egger-Danner is often cited by papers focused on Genetic and phenotypic traits in livestock (61 papers), Milk Quality and Mastitis in Dairy Cows (27 papers) and Effects of Environmental Stressors on Livestock (27 papers). C. Egger-Danner collaborates with scholars based in Austria, Belgium and Germany. C. Egger-Danner's co-authors include C. Fuerst, Birgit Fuerst‐Waltl, B. Heringstad, J.E. Pryce, Nicolas Gengler, K.F. Stock, John B. Cole, A. Koeck, W. Obritzhauser and Andrew Bradley and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Dairy Science.

In The Last Decade

C. Egger-Danner

91 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
C. Egger-Danner Austria 18 955 784 454 365 150 96 1.4k
L.B. Hansen United States 27 1.6k 1.7× 1.6k 2.0× 498 1.1× 358 1.0× 103 0.7× 63 2.0k
Kerstin Brügemann Germany 18 458 0.5× 491 0.6× 466 1.0× 308 0.8× 57 0.4× 51 978
A.J. Seykora United States 20 788 0.8× 882 1.1× 332 0.7× 284 0.8× 78 0.5× 28 1.1k
A. Koeck Canada 20 807 0.8× 742 0.9× 330 0.7× 244 0.7× 43 0.3× 40 1.0k
J.R. Wright United States 19 929 1.0× 872 1.1× 392 0.9× 193 0.5× 119 0.8× 48 1.2k
M. A. Kossaibati United Kingdom 11 615 0.6× 817 1.0× 280 0.6× 364 1.0× 59 0.4× 20 1.1k
O. Reksen Norway 21 587 0.6× 945 1.2× 371 0.8× 349 1.0× 35 0.2× 54 1.3k
D.Z. Caraviello United States 17 916 1.0× 1.1k 1.3× 362 0.8× 175 0.5× 48 0.3× 21 1.3k
S. J. Bartle United States 18 273 0.3× 637 0.8× 496 1.1× 228 0.6× 63 0.4× 55 1.0k
A.H. Sanders United States 7 512 0.5× 534 0.7× 184 0.4× 124 0.3× 53 0.4× 10 720

Countries citing papers authored by C. Egger-Danner

Since Specialization
Citations

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

Fields of papers citing papers by C. Egger-Danner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C. Egger-Danner. 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. Egger-Danner. The network helps show where C. Egger-Danner may publish in the future.

Co-authorship network of co-authors of C. Egger-Danner

This figure shows the co-authorship network connecting the top 25 collaborators of C. Egger-Danner. A scholar is included among the top collaborators of C. Egger-Danner 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. Egger-Danner. C. Egger-Danner 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.
Brito, Luiz F., B. Heringstad, Ilka Christine Klaas, et al.. (2025). Invited review: Using data from sensors and other precision farming technologies to enhance the sustainability of dairy cattle breeding programs. Journal of Dairy Science. 108(10). 10447–10474. 2 indexed citations
2.
Costa, Angela, C. Egger-Danner, Birgit Fuerst‐Waltl, et al.. (2024). Mastitis has a cumulative and lasting effect on milk yield and lactose content in dairy cows. Journal of Dairy Science. 108(1). 635–650. 8 indexed citations
3.
Klimek, Peter, et al.. (2024). A key-feature-based clustering approach to assess the impact of technology integration on cow health in Austrian dairy farms. SHILAP Revista de lepidopterología. 5. 2 indexed citations
4.
5.
Egger-Danner, C., et al.. (2023). Importance of Mid-Infrared Spectra Regions for the Prediction of Mastitis and Ketosis in Dairy Cows. Animals. 13(7). 1193–1193. 3 indexed citations
6.
Werner, Thomas, Annemarie Käsbohrer, Sebastian G. Vetter, et al.. (2023). Antimicrobial resistance and its relationship with antimicrobial use on Austrian dairy farms. Frontiers in Veterinary Science. 10. 1225826–1225826. 2 indexed citations
7.
Egger-Danner, C., Nicolas Gengler, Clément Grelet, et al.. (2022). Prediction of Acute and Chronic Mastitis in Dairy Cows Based on Somatic Cell Score and Mid-Infrared Spectroscopy of Milk. Animals. 12(14). 1830–1830. 10 indexed citations
8.
9.
Gruber, L., et al.. (2019). Analysis of lactating cows on commercial Austrian dairy farms: the influence of genotype and body weight on efficiency parameters. Archives animal breeding/Archiv für Tierzucht. 62(2). 491–500. 10 indexed citations
10.
Werner, Andreas, et al.. (2019). "KetoMIR2" - modelling of ketosis risk using vets diagnosis and mir spectra for dairy cows in early lactation.. 303–307. 1 indexed citations
11.
Gruber, L., et al.. (2018). Body weight prediction using body size measurements in Fleckvieh, Holstein, and Brown Swiss dairy cows in lactation and dry periods. Archives animal breeding/Archiv für Tierzucht. 61(4). 413–424. 16 indexed citations
12.
Egger-Danner, C., et al.. (2018). Indirect traits for feed efficiency.. Züchtungskunde. 90(6). 467–475. 1 indexed citations
13.
Heringstad, B., C. Egger-Danner, K.F. Stock, et al.. (2017). Genetic evaluation of claw health – challenges and recommendations. Open Repository and Bibliography (University of Liège). 1 indexed citations
14.
Fuerst‐Waltl, Birgit, Klemens Fuchs, Martin Mayerhofer, et al.. (2016). Exchange of data to improve dairy cattle health: farmers’ and veterinarians’ needs. 7–11. 2 indexed citations
15.
Fuerst‐Waltl, Birgit, et al.. (2016). Genetic parameters for body weight, body condition score and lameness in Austrian dairy cows. Bulletin - International Bull Evaluation Service/Interbull bulletin. 1 indexed citations
16.
Stock, K.F., John B. Cole, J.E. Pryce, et al.. (2013). Standardization of health data. ICAR guidelines including health key. Open Repository and Bibliography (University of Liège). 18 indexed citations
17.
Fuerst, C., A. Koeck, C. Egger-Danner, & Birgit Fuerst‐Waltl. (2011). Routine genetic evaluation for direct health traits in Austria and Germany. Bulletin - International Bull Evaluation Service/Interbull bulletin. 13 indexed citations
18.
Sölkner, Johann, Elisabeth Jonas, Georg Thaller, et al.. (2010). Estimation of individual levels of admixture in crossbred populations from SNP chip data: examples with sheep and cattle populations. Bulletin - International Bull Evaluation Service/Interbull bulletin. 62. 15 indexed citations
19.
Gredler, Birgit, et al.. (2009). Genomic selection in Fleckvieh/Simmental - First results. Bulletin - International Bull Evaluation Service/Interbull bulletin. 209. 2 indexed citations
20.
Fuerst, C. & C. Egger-Danner. (2003). Multivariate genetic evaluation for calving ease and stillbirth in Austria and Germany. Bulletin - International Bull Evaluation Service/Interbull bulletin. 47. 12 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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