H. Viinalass

922 total citations
29 papers, 738 citations indexed

About

H. Viinalass is a scholar working on Genetics, Agronomy and Crop Science and Insect Science. According to data from OpenAlex, H. Viinalass has authored 29 papers receiving a total of 738 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Genetics, 6 papers in Agronomy and Crop Science and 4 papers in Insect Science. Recurrent topics in H. Viinalass's work include Genetic and phenotypic traits in livestock (19 papers), Genetic diversity and population structure (11 papers) and Genetic Mapping and Diversity in Plants and Animals (11 papers). H. Viinalass is often cited by papers focused on Genetic and phenotypic traits in livestock (19 papers), Genetic diversity and population structure (11 papers) and Genetic Mapping and Diversity in Plants and Animals (11 papers). H. Viinalass collaborates with scholars based in Estonia, Finland and Latvia. H. Viinalass's co-authors include Juha Kantanen, Miika Tapio, Tatyana Kiselyova, Mirjana Ćinkulov, Mikhail Ozerov, I. Olsaker, Ilma Tapio, Н. С. Марзанов, M. Murawski and Johanna Vilkki and has published in prestigious journals such as Chemosphere, International Journal of Molecular Sciences and Conservation Biology.

In The Last Decade

H. Viinalass

25 papers receiving 677 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
H. Viinalass Estonia 12 572 160 118 109 97 29 738
D. Pilling Italy 9 419 0.7× 114 0.7× 61 0.5× 84 0.8× 37 0.4× 14 655
Vincenzo Landi Spain 17 729 1.3× 178 1.1× 125 1.1× 132 1.2× 64 0.7× 98 977
Carina Visser South Africa 14 549 1.0× 285 1.8× 71 0.6× 53 0.5× 18 0.2× 73 688
Onur Yılmaz Türkiye 14 428 0.7× 122 0.8× 74 0.6× 66 0.6× 18 0.2× 75 570
S.J. Hiemstra Netherlands 14 441 0.8× 126 0.8× 22 0.2× 58 0.5× 17 0.2× 38 590
Coralie Danchin-Burge France 13 528 0.9× 119 0.7× 16 0.1× 44 0.4× 27 0.3× 24 607
Emma Eythórsdóttir Iceland 12 508 0.9× 139 0.9× 41 0.3× 106 1.0× 9 0.1× 26 636
D. Matassino Italy 17 558 1.0× 91 0.6× 52 0.4× 144 1.3× 18 0.2× 51 788
İ̇brahim Cemal Türkiye 14 491 0.9× 117 0.7× 90 0.8× 78 0.7× 9 0.1× 48 614
R. A. Cardellino Brazil 13 350 0.6× 116 0.7× 24 0.2× 50 0.5× 33 0.3× 47 499

Countries citing papers authored by H. Viinalass

Since Specialization
Citations

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

Fields of papers citing papers by H. Viinalass

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of H. Viinalass

This figure shows the co-authorship network connecting the top 25 collaborators of H. Viinalass. A scholar is included among the top collaborators of H. Viinalass 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 H. Viinalass. H. Viinalass 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.
Rossi, Franca, et al.. (2025). Could hive debris samples and qPCR ease the investigation of factors influencing Paenibacillus larvae spore loads?. Journal of Apicultural Research. 65(1). 101–110.
2.
3.
Kilk, Kalle, et al.. (2025). Metabolomic Biomarkers in Bovine Embryo Culture Media and Their Relationship with the Developmental Potential of In Vitro-Produced Embryos. International Journal of Molecular Sciences. 26(5). 2362–2362.
4.
Viinalass, H., et al.. (2024). Genetic Variation and Composition of Two Commercial Estonian Dairy Cattle Breeds Assessed by SNP Data. Animals. 14(7). 1101–1101. 1 indexed citations
5.
Raimets, Risto, Vadims Bartkevičs, Iveta Pugajeva, et al.. (2019). Pesticide residues in beehive matrices are dependent on collection time and matrix type but independent of proportion of foraged oilseed rape and agricultural land in foraging territory. Chemosphere. 238. 124555–124555. 51 indexed citations
6.
Viira, Ants‐Hannes, et al.. (2018). How do herd's genetic level and milk quality affect performance of dairy farms?. Czech Journal of Animal Science. 63(10). 379–388. 3 indexed citations
7.
Karise, Reet, Risto Raimets, Vadims Bartkevičs, et al.. (2017). Are pesticide residues in honey related to oilseed rape treatments?. Chemosphere. 188. 389–396. 52 indexed citations
8.
Kaart, Tanel, et al.. (2012). Composite β-κ-casein genotypes and their effect on composition and coagulation of milk from Estonian Holstein cows. Journal of Dairy Science. 95(11). 6760–6769. 36 indexed citations
9.
Viinalass, H., et al.. (2009). GENETIC DIVERSITY IN MILK PROTEINS AMONG ESTONIAN DAIRY CATTLE. 93–98. 6 indexed citations
10.
Jõudu, Ivi, M. Henno, H. Viinalass, et al.. (2009). Milk rennet coagulation properties in Estonian dairy cattle and factors affecting it. A review.. 20(1). 3–14. 1 indexed citations
11.
Kantanen, Juha, Ceiridwen J. Edwards, Daniel G. Bradley, et al.. (2009). Maternal and paternal genealogy of Eurasian taurine cattle (Bos taurus). Heredity. 103(5). 404–415. 78 indexed citations
12.
Schulman, Nina, Goutam Sahana, Terhi Iso‐Touru, et al.. (2009). Fine mapping of quantitative trait loci for mastitis resistance on bovine chromosome 11. Animal Genetics. 40(4). 509–515. 11 indexed citations
13.
Lund, Mogens Sandø, Goutam Sahana, L. Andersson‐Eklund, et al.. (2007). Joint Analysis of Quantitative Trait Loci for Clinical Mastitis and Somatic Cell Score on Five Chromosomes in Three Nordic Dairy Cattle Breeds. Journal of Dairy Science. 90(11). 5282–5290. 35 indexed citations
14.
Tapio, Miika, Mikhail Ozerov, & H. Viinalass. (2007). Molecular genetic variation in sheep of the central Volga area inhabited by Finno-Ugric peoples. Agricultural and Food Science. 16(2). 157–157. 5 indexed citations
15.
Henno, M., et al.. (2006). Frequencies of κ-Cn AND β-Lg genetic variants among Estonian cattle breeds and their effect on the milk renneting properties.. 1–65. 5 indexed citations
16.
Tapio, Ilma, E. Fimland, T.H.E. Meuwissen, et al.. (2006). Prioritization for Conservation of Northern European Cattle Breeds Based on Analysis of Microsatellite Data. Conservation Biology. 20(6). 1768–1779. 61 indexed citations
17.
Tapio, Miika, Н. С. Марзанов, Mikhail Ozerov, et al.. (2006). Sheep Mitochondrial DNA Variation in European, Caucasian, and Central Asian Areas. Molecular Biology and Evolution. 23(9). 1776–1783. 158 indexed citations
18.
Henno, M., et al.. (2005). Effect of κ-casein and β-lactoglobulin genotypes on the milk rennet coagulation properties. Agronomy Research. 3(1). 55–64. 33 indexed citations
19.
Viinalass, H., et al.. (2005). Bio-economical model application in cattle breeding. Acta agriculturae Slovenica. 86(2). 1 indexed citations
20.
Tapio, Ilma, Miika Tapio, Lars‐Erik Holm, et al.. (2005). Unfolding of population structure in Baltic sheep breeds using microsatellite analysis. Heredity. 94(4). 448–456. 59 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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