Gerrit Koop

1.7k total citations
50 papers, 1.1k citations indexed

About

Gerrit Koop is a scholar working on Agronomy and Crop Science, Food Science and Microbiology. According to data from OpenAlex, Gerrit Koop has authored 50 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Agronomy and Crop Science, 26 papers in Food Science and 19 papers in Microbiology. Recurrent topics in Gerrit Koop's work include Milk Quality and Mastitis in Dairy Cows (38 papers), Probiotics and Fermented Foods (22 papers) and Microbial infections and disease research (19 papers). Gerrit Koop is often cited by papers focused on Milk Quality and Mastitis in Dairy Cows (38 papers), Probiotics and Fermented Foods (22 papers) and Microbial infections and disease research (19 papers). Gerrit Koop collaborates with scholars based in Netherlands, Bangladesh and United Kingdom. Gerrit Koop's co-authors include T. van Werven, M. Nielen, Len J.A. Lipman, Pascal Rainard, T.J.G.M. Lam, J. Ross Fitzgerald, Gilles Foucras, Jeffrey L. Watts, John R. Middleton and H. Hogeveen and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and PLoS ONE.

In The Last Decade

Gerrit Koop

45 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gerrit Koop Netherlands 20 688 492 257 243 208 50 1.1k
K. Supré Belgium 20 1.0k 1.5× 724 1.5× 328 1.3× 420 1.7× 269 1.3× 32 1.3k
Guilherme Nunes de Souza Brazil 21 395 0.6× 267 0.5× 237 0.9× 133 0.5× 158 0.8× 82 1.1k
Vesa Myllys Finland 17 833 1.2× 540 1.1× 210 0.8× 304 1.3× 250 1.2× 27 1.2k
Heli Simojoki Finland 19 1.0k 1.5× 628 1.3× 179 0.7× 412 1.7× 313 1.5× 47 1.4k
S. Waage Norway 21 793 1.2× 337 0.7× 324 1.3× 195 0.8× 298 1.4× 40 1.2k
Carlos Santisteban United States 14 780 1.1× 588 1.2× 157 0.6× 225 0.9× 330 1.6× 26 1.2k
Volker Krömker Germany 24 1.4k 2.0× 912 1.9× 155 0.6× 444 1.8× 388 1.9× 132 1.8k
Anna Pitkälä Finland 10 682 1.0× 602 1.2× 182 0.7× 288 1.2× 213 1.0× 12 952
Priscilla Anne Melville Brazil 18 534 0.8× 341 0.7× 128 0.5× 153 0.6× 213 1.0× 65 906
Fred J. DeGraves United States 20 621 0.9× 337 0.7× 144 0.6× 356 1.5× 179 0.9× 37 1.2k

Countries citing papers authored by Gerrit Koop

Since Specialization
Citations

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

Fields of papers citing papers by Gerrit Koop

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gerrit Koop

This figure shows the co-authorship network connecting the top 25 collaborators of Gerrit Koop. A scholar is included among the top collaborators of Gerrit Koop 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 Gerrit Koop. Gerrit Koop 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.
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Oosterhuis, Koen, et al.. (2025). Effect of bluetongue serotype 3 vaccines on probability of viremia and NSAID usage in Dutch dairy cattle herds. Frontiers in Veterinary Science. 12. 1619614–1619614.
3.
Koop, Gerrit, Fabrizio Ceciliani, María Filippa Addis, et al.. (2024). Pathogen group-specific risk factors for intramammary infection in water buffalo. PLoS ONE. 19(4). e0299929–e0299929. 5 indexed citations
4.
Scherpenisse, Peter, Lidwien A.M. Smit, Alex Bossers, et al.. (2024). Total bacterial count and somatic cell count in bulk and individual goat milk around kidding: Two longitudinal observational studies. Journal of Dairy Science. 107(8). 5427–5437.
5.
6.
Bari, Md Saiful, Ylva Persson, Marjolein Derks, et al.. (2022). Subclinical mastitis in dairy cows in south-Asian countries: a review of risk factors and etiology to prioritize control measures. Veterinary Research Communications. 46(3). 621–640. 25 indexed citations
7.
Deng, Zhaoju, Gerrit Koop, H. Hogeveen, et al.. (2021). Transmission dynamics of Staphylococcus aureus and Streptococcus agalactiae in a Dutch dairy herd using an automatic milking system. Preventive Veterinary Medicine. 192. 105384–105384. 4 indexed citations
8.
Shittu, Aminu, et al.. (2021). Dynamics of intramammary infections in suckler ewes during early lactation. Journal of Dairy Science. 104(5). 5979–5987. 4 indexed citations
9.
Deng, Zhaoju, T.J.G.M. Lam, H. Hogeveen, & Gerrit Koop. (2021). Regularly fluctuating somatic cell count pattern in dairy herds. Journal of Dairy Science. 104(10). 11126–11134. 1 indexed citations
10.
Deng, Zhaoju, T.J.G.M. Lam, H. Hogeveen, et al.. (2020). Antimicrobial use and farmers' attitude toward mastitis treatment on dairy farms with automatic or conventional milking systems. Journal of Dairy Science. 103(8). 7302–7314. 16 indexed citations
11.
Rutten, Victor P. M. G., et al.. (2019). Differences between Staphylococcus aureus lineages isolated from ovine and caprine mastitis but not between isolates from clinical or subclinical mastitis. Journal of Dairy Science. 102(6). 5430–5437. 18 indexed citations
12.
Jong, Nienke W. M. de, Manouk Vrieling, Brandon L. Garcia, et al.. (2018). Identification of a staphylococcal complement inhibitor with broad host specificity in equid Staphylococcus aureus strains. Journal of Biological Chemistry. 293(12). 4468–4477. 35 indexed citations
13.
Koop, Gerrit, et al.. (2017). Prevalence of subclinical mastitis and associated risk factors at cow and herd level in dairy farms in North-West Ethiopia. Preventive Veterinary Medicine. 145. 23–31. 53 indexed citations
14.
Hogerwerf, Lenny, Gerrit Koop, Don Klinkenberg, et al.. (2014). Test and cull of high risk Coxiella burnetii infected pregnant dairy goats is not feasible due to poor test performance. The Veterinary Journal. 200(2). 343–345. 13 indexed citations
15.
Bikker, Floris J., et al.. (2014). Tailor made plasmin substrates as potential diagnostic tool to test for mastitis. Veterinary Research Communications. 38(4). 271–277. 4 indexed citations
16.
17.
Koop, Gerrit, Sarne De Vliegher, A. De Visscher, et al.. (2012). Differences between coagulase-negative Staphylococcus species in persistence and in effect on somatic cell count and milk yield in dairy goats. Journal of Dairy Science. 95(9). 5075–5084. 48 indexed citations
18.
Koop, Gerrit, T. van Werven, Nils Toft, & M. Nielen. (2011). Estimating test characteristics of somatic cell count to detect Staphylococcus aureus-infected dairy goats using latent class analysis. Journal of Dairy Science. 94(6). 2902–2911. 33 indexed citations
19.
Koop, Gerrit, et al.. (2010). The effect of subclinical mastitis on milk yield in dairy goats. Journal of Dairy Science. 93(12). 5809–5817. 64 indexed citations
20.
Koop, Gerrit, M. Nielen, & T. van Werven. (2009). Bulk milk somatic cell counts are related to bulk milk total bacterial counts and several herd-level risk factors in dairy goats. Journal of Dairy Science. 92(9). 4355–4364. 43 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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