J. Špička

518 total citations
26 papers, 409 citations indexed

About

J. Špička is a scholar working on Agronomy and Crop Science, Nutrition and Dietetics and Genetics. According to data from OpenAlex, J. Špička has authored 26 papers receiving a total of 409 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Agronomy and Crop Science, 15 papers in Nutrition and Dietetics and 11 papers in Genetics. Recurrent topics in J. Špička's work include Fatty Acid Research and Health (15 papers), Ruminant Nutrition and Digestive Physiology (13 papers) and Genetic and phenotypic traits in livestock (11 papers). J. Špička is often cited by papers focused on Fatty Acid Research and Health (15 papers), Ruminant Nutrition and Digestive Physiology (13 papers) and Genetic and phenotypic traits in livestock (11 papers). J. Špička collaborates with scholars based in Czechia, United States and Poland. J. Špička's co-authors include Eva Samková, Oto Hanuš, Tamara Pelikánová, Martin Křı́žek, Pavel Kalač, J. Frelich, Martin Šlachta, Sara Bover‐Cid, František Vácha and Petr Roubal and has published in prestigious journals such as SHILAP Revista de lepidopterología, Food Chemistry and Journal of Food Protection.

In The Last Decade

J. Špička

25 papers receiving 385 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J. Špička Czechia 12 162 145 134 122 116 26 409
Grażyna Czyżak‐Runowska Poland 11 107 0.7× 135 0.9× 103 0.8× 161 1.3× 90 0.8× 34 419
V. Jimeno Spain 8 164 1.0× 222 1.5× 42 0.3× 213 1.7× 93 0.8× 10 450
Myriam Fiori Italy 11 116 0.7× 173 1.2× 85 0.6× 148 1.2× 82 0.7× 23 370
Seok Ki Im South Korea 8 40 0.2× 49 0.3× 150 1.1× 233 1.9× 102 0.9× 16 393
G. J. Miller United States 14 122 0.8× 99 0.7× 93 0.7× 290 2.4× 54 0.5× 44 462
Alessandra Fernandes Rosa Brazil 11 35 0.2× 47 0.3× 129 1.0× 331 2.7× 74 0.6× 28 438
Yanru Hou China 10 25 0.2× 61 0.4× 118 0.9× 242 2.0× 25 0.2× 32 354
Jérôme Normand France 11 91 0.6× 136 0.9× 50 0.4× 249 2.0× 66 0.6× 16 340
Karine Méteau France 13 68 0.4× 33 0.2× 81 0.6× 428 3.5× 56 0.5× 21 501
Daniel Silva Antonelo Brazil 12 23 0.1× 45 0.3× 95 0.7× 259 2.1× 45 0.4× 32 324

Countries citing papers authored by J. Špička

Since Specialization
Citations

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

Fields of papers citing papers by J. Špička

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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

This figure shows the co-authorship network connecting the top 25 collaborators of J. Špička. A scholar is included among the top collaborators of J. Špička 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. Špička. J. Špička 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.
Špička, J., et al.. (2021). IMPACT OF LACTATION STAGE ON MILK FAT FATTY ACIDS PROFILE IN GRAZING DAIRY COWS. SHILAP Revista de lepidopterología. 2021. 1164–1174.
2.
Samková, Eva, J. Čítek, Oto Hanuš, et al.. (2021). Associations among Farm, Breed, Lactation Stage and Parity, Gene Polymorphisms and the Fatty Acid Profile of Milk from Holstein, Simmental and Their Crosses. Animals. 11(11). 3284–3284. 5 indexed citations
3.
Samková, Eva, J. Špička, Oto Hanuš, et al.. (2020). Comparison of Fatty Acid Proportions Determined by Mid-Infrared Spectroscopy and Gas Chromatography in Bulk and Individual Milk Samples. Animals. 10(6). 1095–1095. 13 indexed citations
4.
Křížová, Ludmila, Oto Hanuš, J. Špička, et al.. (2016). Alternative supplemental mixture for organic dairy herds to maintain desirable milk fatty acid profile throughout the indoor feeding period.. Animal Science Papers and Reports. 34(1). 25–39. 4 indexed citations
5.
Špička, J., et al.. (2016). Identification of furan fatty acids in the lipids of common carp (Cyprinus carpio L.). Food Chemistry. 200. 183–188. 11 indexed citations
6.
Hanuš, Oto, et al.. (2016). The effect of cattle breed, season and type of diet on the fatty acid profile of raw milk. Archives animal breeding/Archiv für Tierzucht. 59(3). 373–380. 31 indexed citations
7.
Křı́žek, Martin, et al.. (2015). Changes in the Content of Biogenic Amines and Fatty Acids in High Pressure-Processed Carp Flesh (). Journal of Food Protection. 78(8). 1592–1596. 6 indexed citations
8.
Samková, Eva, et al.. (2014). Eighteen-carbon fatty acids in milk fat of Czech Fleckvieh and Holstein cows following feeding with fresh lucerne (Medicago sativa L.)*. Animal Science Papers and Reports. 32(3). 209–218. 7 indexed citations
9.
Hanuš, Oto, et al.. (2014). Relationship between concentration of health important groups of fatty acids and components and technological properties in cow milk. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis. 58(5). 137–154. 4 indexed citations
10.
Frelich, J., et al.. (2013). Quality of goat pasture in less-favoured areas (LFA) of the Czech Republic and its effect on fatty acid content of goat milk and cheese*. Animal Science Papers and Reports. 31(4). 331–345. 3 indexed citations
11.
Špička, J., et al.. (2012). MILK FAT FATTY ACIDS IN RELATION TO MILK PRODUCTION AND QUALITY. SHILAP Revista de lepidopterología. 1 indexed citations
12.
Frelich, J., Martin Šlachta, Oto Hanuš, et al.. (2012). Seasonal variation in fatty acid composition of cow milk in relation to the feeding system. Animal Science Papers and Reports. 30(3). 219–229. 29 indexed citations
13.
Samková, Eva, et al.. (2012). Animal factors affecting fatty acid composition of cow milk fat: A review. South African Journal of Animal Science. 42(2). 83–100. 57 indexed citations
14.
Stejskal, Vlastimil, et al.. (2011). Sensory and textural attributes and fatty acid profiles of fillets of extensively and intensively farmed Eurasian perch (Perca fluviatilis L.). Food Chemistry. 129(3). 1054–1059. 34 indexed citations
15.
Špička, J., et al.. (2009). THE EFFECT OF THE STRUCTURE OF THE PASTURE GROWTH ON THE SUBSTITUTION OF FATTY ACIDS IN THE MILK OF GRAZING DAIRY COW. SHILAP Revista de lepidopterología. 2 indexed citations
16.
Frelich, J., Martin Šlachta, Oto Hanuš, J. Špička, & Eva Samková. (2009). Fatty acid composition of cow milk fat produced on low-input mountain farms. Czech Journal of Animal Science. 54(12). 532–539. 34 indexed citations
17.
Samková, Eva, et al.. (2006). Fatty acids and composition of their important groups in milk fat of Czech Pied cattle. Czech Journal of Animal Science. 51(5). 181–188. 18 indexed citations
18.
Špička, J., Pavel Kalač, Sara Bover‐Cid, & Martin Křı́žek. (2002). Application of lactic acid bacteria starter cultures for decreasing the biogenic amine levels in sauerkraut. European Food Research and Technology. 215(6). 509–514. 39 indexed citations
19.
Kalač, Pavel, Martin Křı́žek, J. Špička, et al.. (2001). Biogenic amines in sauerkraut.. 217–220. 3 indexed citations
20.
Kalač, Pavel, et al.. (1999). Concentrations of seven biogenic amines in sauerkraut. Food Chemistry. 67(3). 275–280. 40 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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