K. Słoniewski

456 total citations
29 papers, 346 citations indexed

About

K. Słoniewski is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology. According to data from OpenAlex, K. Słoniewski has authored 29 papers receiving a total of 346 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Genetics, 13 papers in Agronomy and Crop Science and 6 papers in Animal Science and Zoology. Recurrent topics in K. Słoniewski's work include Genetic and phenotypic traits in livestock (16 papers), Reproductive Physiology in Livestock (8 papers) and Ruminant Nutrition and Digestive Physiology (6 papers). K. Słoniewski is often cited by papers focused on Genetic and phenotypic traits in livestock (16 papers), Reproductive Physiology in Livestock (8 papers) and Ruminant Nutrition and Digestive Physiology (6 papers). K. Słoniewski collaborates with scholars based in Poland, Pakistan and Spain. K. Słoniewski's co-authors include Tomasz Sakowski, Beata Kuczyńska, Kamila Puppel, I.L. Mao, Just Jensen, Per Madsen, L. Zwierzchowski, Aleksandra Górecka-Bruzda, Marcin Gołębiewski and Tadeusz Jezierski and has published in prestigious journals such as Journal of Dairy Science, Journal of the Science of Food and Agriculture and Animal Reproduction Science.

In The Last Decade

K. Słoniewski

27 papers receiving 325 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K. Słoniewski Poland 11 134 128 83 44 42 29 346
Elizabeth A. Staiger United States 11 199 1.5× 43 0.3× 47 0.6× 24 0.5× 72 1.7× 22 345
Guilherme Rizzoto Brazil 12 100 0.7× 147 1.1× 185 2.2× 29 0.7× 24 0.6× 39 494
B. Emmanuel Iran 13 74 0.6× 226 1.8× 104 1.3× 89 2.0× 20 0.5× 37 455
Hyeok Joong Kang South Korea 12 156 1.2× 142 1.1× 252 3.0× 24 0.5× 8 0.2× 25 480
Byung-Wook Cho South Korea 12 132 1.0× 37 0.3× 72 0.9× 27 0.6× 45 1.1× 65 416
Ricardo da Fonseca Brazil 10 194 1.4× 85 0.7× 120 1.4× 7 0.2× 44 1.0× 46 316
Mitsuto MATSUMOTO Japan 13 98 0.7× 251 2.0× 97 1.2× 58 1.3× 8 0.2× 45 456
K.-H. Südekum Germany 9 127 0.9× 234 1.8× 118 1.4× 25 0.6× 3 0.1× 18 377
Uğur Şen Türkiye 12 195 1.5× 137 1.1× 184 2.2× 19 0.4× 3 0.1× 49 395
Asghar Mogheiseh Iran 11 58 0.4× 81 0.6× 13 0.2× 12 0.3× 30 0.7× 58 323

Countries citing papers authored by K. Słoniewski

Since Specialization
Citations

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

Fields of papers citing papers by K. Słoniewski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of K. Słoniewski

This figure shows the co-authorship network connecting the top 25 collaborators of K. Słoniewski. A scholar is included among the top collaborators of K. Słoniewski 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 K. Słoniewski. K. Słoniewski 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.
Kowalski, Z.M., et al.. (2015). Novel model of monitoring of subclinical ketosis in dairy herds in Poland based on monthly milk recording and estimation of ketone bodies in milk by FTIR spectroscopy technology.. 25–30. 3 indexed citations
2.
Górka, P., et al.. (2013). Expression of PC, PCK1, PCK2, LDHB, FBP1 and G6PC genes in the liver of cows in the transition from pregnancy to lactation.. Animal Science Papers and Reports. 31(4). 281–290. 4 indexed citations
3.
Brzozowska, Anna, K. Słoniewski, J. Oprządek, Przemysław Sobiech, & Z.M. Kowalski. (2013). Why are dairy cows not able to cope with the subacute ruminal acidosis?. Polish Journal of Veterinary Sciences. 16(4). 813–821. 4 indexed citations
4.
5.
Sakowski, Tomasz, et al.. (2012). Relationships between physiological indicators in blood, and their yield, as well as chemical composition of milk obtained from organic dairy cows. Journal of the Science of Food and Agriculture. 92(14). 2905–2912. 25 indexed citations
6.
Kuczyńska, Beata, et al.. (2012). Differences in whey protein content between cow's milk collected in late pasture and early indoor feeding season from conventional and organic farms in Poland. Journal of the Science of Food and Agriculture. 92(14). 2899–2904. 46 indexed citations
7.
Słoniewski, K., et al.. (2009). The effect of polymorphisms in the intron 12 of CAST gene on meat quality of young bulls. Animal Science Papers and Reports. 27(4). 281–292. 5 indexed citations
8.
Słoniewski, K., et al.. (2008). Macro- and microelements in milk and hair of cows from conventional vs. organic farms. Animal Science Papers and Reports. 26(3). 199–209. 27 indexed citations
9.
Górecka-Bruzda, Aleksandra, et al.. (2006). Heritability of hair whorl position on the forehead in Konik horses. Journal of Animal Breeding and Genetics. 123(6). 396–398. 15 indexed citations
10.
Kuczyńska, Beata, et al.. (2005). Functional components of milk produced by Polish Black-and-White, Polish Red and Simmental cows. 8(3). 9 indexed citations
11.
Strzałkowska, Nina, et al.. (2005). Effect of the DGATI gene polymorphism on milk production traits in Black-and-White (Friesian) cows.. Animal Science Papers and Reports. 23(3). 189–197. 11 indexed citations
12.
Jóźwik, Artur, Emilia Bagnicka, Nina Strzałkowska, et al.. (2004). Activity of selected aminopeptidases of whole milk in cows as related to feeding season (autumn/winter vs spring/summer). Animal Science Papers and Reports. 22(4). 4 indexed citations
13.
Flisikowski, Krzysztof, et al.. (2004). Association of a sequence nucleotide polymorphism in exon 16 of the STAT5A gene with milk production traits in Polish Black-and-White (Polish Friesian) cows. Animal Science Papers and Reports. 22(4). 16 indexed citations
14.
Mao, I.L., K. Słoniewski, Per Madsen, & Just Jensen. (2004). Changes in body condition score and in its genetic variation during lactation. Livestock Production Science. 89(1). 55–65. 36 indexed citations
15.
Dasiewicz, Krzysztof, et al.. (2003). The attempt of video image analysis use for estimation of meat quality of beef breeds bulls. 6(2). 2 indexed citations
16.
Sakowski, Tomasz, et al.. (2002). Using digital image analysis and ultrasound measurements for a pre-slaughter evaluation of carcass qualitative traits in cattle. Animal Science Papers and Reports. 20(2). 2 indexed citations
17.
Słoniewski, K., et al.. (2001). Use of in vivo ultrasound measurements for predicting the slaughter value of beef bulls. Animal Science Papers and Reports. 19(1). 1 indexed citations
18.
Oprządek, J., et al.. (2001). A note on the effect of breed on beef cattle carcass traits. Animal Science Papers and Reports. 19(1). 79–89. 15 indexed citations
19.
Oprządek, J., et al.. (2001). Growth rate, feed intake and feed conversion in fattening bulls of main beef breeds kept in Poland. Animal Science Papers and Reports. 19(3). 5 indexed citations
20.
Jaszczak, K., et al.. (1998). Two morphologic form of chromosome Y in piedmontese cattle. Animal Science Papers and Reports. 16(1). 5–11. 3 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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