J. Visscher

816 total citations
23 papers, 578 citations indexed

About

J. Visscher is a scholar working on Animal Science and Zoology, Genetics and Small Animals. According to data from OpenAlex, J. Visscher has authored 23 papers receiving a total of 578 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Animal Science and Zoology, 12 papers in Genetics and 5 papers in Small Animals. Recurrent topics in J. Visscher's work include Animal Nutrition and Physiology (12 papers), Genetic and phenotypic traits in livestock (12 papers) and Genetic Mapping and Diversity in Plants and Animals (7 papers). J. Visscher is often cited by papers focused on Animal Nutrition and Physiology (12 papers), Genetic and phenotypic traits in livestock (12 papers) and Genetic Mapping and Diversity in Plants and Animals (7 papers). J. Visscher collaborates with scholars based in Netherlands, Germany and France. J. Visscher's co-authors include Piter Bijma, E.D. Ellen, J.A.M. van Arendonk, Katrijn Peeters, Eddy Decuypere, P. Coucke, Josse De Baerdemaeker, Bart De Ketelaere, T.B. Rodenburg and H.A. Mulder and has published in prestigious journals such as Genetics, Poultry Science and Heredity.

In The Last Decade

J. Visscher

20 papers receiving 544 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
J. Visscher Netherlands	13	367	249	140	82	60	23	578
M.G. Gil Spain	15	377 1.0×	134 0.5×	169 1.2×	44 0.5×	41 0.7×	45	645
R. Preisinger Germany	13	532 1.4×	225 0.9×	146 1.0×	32 0.4×	62 1.0×	38	732
Ewa Sell‐Kubiak Poland	12	211 0.6×	282 1.1×	162 1.2×	37 0.5×	38 0.6×	38	471
Martin Wilhelmson Sweden	12	277 0.8×	176 0.7×	52 0.4×	77 0.9×	56 0.9×	29	414
P. M. Hocking United Kingdom	20	1.0k 2.8×	238 1.0×	224 1.6×	68 0.8×	116 1.9×	39	1.2k
Isabel Cristina Boleli Brazil	18	503 1.4×	113 0.5×	71 0.5×	69 0.8×	70 1.2×	62	777
Rob Bergsma Netherlands	17	442 1.2×	424 1.7×	364 2.6×	74 0.9×	57 0.9×	37	778
M. O. Ozoje Nigeria	16	420 1.1×	363 1.5×	40 0.3×	58 0.7×	41 0.7×	69	739
Md Azharul Hoque Bangladesh	14	309 0.8×	471 1.9×	87 0.6×	54 0.7×	85 1.4×	84	732
Türker Savaş Türkiye	15	321 0.9×	226 0.9×	155 1.1×	19 0.2×	70 1.2×	76	601

Countries citing papers authored by J. Visscher

Since Specialization

Citations

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

Fields of papers citing papers by J. Visscher

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J. Visscher

This figure shows the co-authorship network connecting the top 25 collaborators of J. Visscher. A scholar is included among the top collaborators of J. Visscher 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 J. Visscher. J. Visscher is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Berghof, T.V.L., Nicolas Bédère, Katrijn Peeters, et al.. (2024). The genetics of resilience and its relationships with egg production traits and antibody traits in chickens. Genetics Selection Evolution. 56(1). 20–20. 3 indexed citations

Berghof, T.V.L., M.H.P.W. Visker, J.A.J. Arts, et al.. (2022). Divergent selection for natural antibodies in poultry in the presence of a major gene. Genetics Selection Evolution. 54(1). 24–24. 4 indexed citations

Bédère, Nicolas, T.V.L. Berghof, Katrijn Peeters, et al.. (2022). Using egg production longitudinal recording to study the genetic background of resilience in purebred and crossbred laying hens. Genetics Selection Evolution. 54(1). 26–26. 27 indexed citations

Doekes, Harmen P., et al.. (2022). Research Note: Genome-wide association study for natural antibodies and resilience in a purebred layer chicken line. Poultry Science. 102(1). 102312–102312. 7 indexed citations

Bink, M.C.A.M., M.P.L. Calus, Martijn F. L. Derks, J. Visscher, & B.C. Perez. (2022). 304. Predictive ability of genomic prediction in layers when including CADD scores as genome function information. Socio-Environmental Systems Modeling. 1278–1281. 1 indexed citations

Schokker, Dirkjan, J. Visscher, & H. Woelders. (2021). Changes in Blood Metabolites, Intestinal Microbiota Composition and Gene Expression of 95 Weeks Old Laying Hens Differing in Egg Production and Egg Breaking Strength. Animals. 11(11). 3012–3012.

Derks, Martijn F. L., Hendrik‐Jan Megens, Mirte Bosse, et al.. (2018). A survey of functional genomic variation in domesticated chickens. Genetics Selection Evolution. 50(1). 17–17. 20 indexed citations

Mulder, H.A., et al.. (2016). Estimating the purebred–crossbred genetic correlation for uniformity of eggshell color in laying hens. Genetics Selection Evolution. 48(1). 39–39. 24 indexed citations

Calus, M.P.L., et al.. (2014). Genomic prediction based on data from three layer lines: a comparison between linear methods. Genetics Selection Evolution. 46(1). 57–57. 22 indexed citations

10.

Bijma, Piter, et al.. (2014). Plumage condition in laying hens: genetic parameters for direct and indirect effects in two purebred layer lines. Genetics Selection Evolution. 46(1). 33–33. 22 indexed citations

11.

Ellen, E.D., T.B. Rodenburg, G.A.A. Albers, et al.. (2014). The prospects of selection for social genetic effects to improve welfare and productivity in livestock. Frontiers in Genetics. 5. 377–377. 72 indexed citations

12.

Bijma, Piter, Brian Kinghorn, Addie Vereijken, et al.. (2013). Prediction of heterosis using genome-wide SNP-marker data: application to egg production traits in white Leghorn crosses. Heredity. 111(6). 530–538. 15 indexed citations

13.

Visscher, J.. (2010). Breeding laying hens for improved field performance.. 18(5). 39–41. 1 indexed citations

14.

Ellen, E.D., J. Visscher, Piter Bijma, & T.B. Rodenburg. (2010). Selection Against Mortality Due To Cannibalism In Layers, Does It Work?. Socio-Environmental Systems Modeling. 339–339.

15.

Visscher, J.. (2010). Verlenging groeiseizoen grasland. Socio-Environmental Systems Modeling. 1 indexed citations

16.

Ellen, E.D., J. Visscher, J.A.M. van Arendonk, & Piter Bijma. (2008). Survival of Laying Hens: Genetic Parameters for Direct and Associative Effects in Three Purebred Layer Lines. Poultry Science. 87(2). 233–239. 85 indexed citations

17.

Evers, A.G., et al.. (2006). Handboek Melkveehouderij 2006. Socio-Environmental Systems Modeling. 2 indexed citations

18.

Buitenhuis, Bart, T.B. Rodenburg, J. Visscher, et al.. (2004). Genetic and Phenotypic Correlations Between Feather Pecking Behavior, Stress Response, Immune Response, and Egg Quality Traits in Laying Hens. Poultry Science. 83(7). 1077–1082. 52 indexed citations

19.

Ketelaere, Bart De, et al.. (2002). Measuring the eggshell strength of 6 different genetic strains of laying hens: Techniques and comparisons. British Poultry Science. 43(2). 238–244. 122 indexed citations

20.

Albers, G. A. A., et al.. (2002). Role of genotype × environment interactions in applied breeding programmes.. 1–4. 1 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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