Shunzo MIYOSHI

606 total citations
37 papers, 473 citations indexed

About

Shunzo MIYOSHI is a scholar working on Animal Science and Zoology, Genetics and Small Animals. According to data from OpenAlex, Shunzo MIYOSHI has authored 37 papers receiving a total of 473 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Animal Science and Zoology, 13 papers in Genetics and 5 papers in Small Animals. Recurrent topics in Shunzo MIYOSHI's work include Animal Nutrition and Physiology (18 papers), Genetic and phenotypic traits in livestock (13 papers) and Meat and Animal Product Quality (6 papers). Shunzo MIYOSHI is often cited by papers focused on Animal Nutrition and Physiology (18 papers), Genetic and phenotypic traits in livestock (13 papers) and Meat and Animal Product Quality (6 papers). Shunzo MIYOSHI collaborates with scholars based in Japan, United States and United Kingdom. Shunzo MIYOSHI's co-authors include Keigo KUCHIDA, Mitsuyoshi Suzuki, D.L. Palmquist, J. L. Pate, L.D. Van Vleck, Tsuyoshi Endo, Satoru Shimizu, Suminori Kono, Masuo Nakano and Michihiro Fukushima and has published in prestigious journals such as Journal of Animal Science, Poultry Science and Animal Feed Science and Technology.

In The Last Decade

Shunzo MIYOSHI

35 papers receiving 371 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shunzo MIYOSHI Japan 12 227 181 137 53 51 37 473
M. Oravcová Slovakia 13 271 1.2× 305 1.7× 262 1.9× 46 0.9× 32 0.6× 51 508
Roger D. Shanks United States 11 129 0.6× 195 1.1× 242 1.8× 83 1.6× 45 0.9× 17 473
B. Hulsegge Netherlands 14 397 1.7× 194 1.1× 64 0.5× 217 4.1× 74 1.5× 31 569
T V RAJA India 12 170 0.7× 162 0.9× 97 0.7× 53 1.0× 138 2.7× 64 425
S. L. Northcutt United States 8 226 1.0× 318 1.8× 120 0.9× 64 1.2× 15 0.3× 11 423
Clemente Lemus Flores Mexico 10 251 1.1× 140 0.8× 50 0.4× 91 1.7× 43 0.8× 87 487
D. Zapletal Czechia 13 223 1.0× 84 0.5× 116 0.8× 36 0.7× 63 1.2× 37 395
Jesús Ángel Baró de la Fuente Spain 13 157 0.7× 363 2.0× 307 2.2× 47 0.9× 47 0.9× 42 565
Marcia del Campo Uruguay 9 239 1.1× 78 0.4× 80 0.6× 108 2.0× 21 0.4× 17 353
Frédéric Colinet Belgium 14 290 1.3× 417 2.3× 388 2.8× 61 1.2× 58 1.1× 43 676

Countries citing papers authored by Shunzo MIYOSHI

Since Specialization
Citations

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

Fields of papers citing papers by Shunzo MIYOSHI

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shunzo MIYOSHI

This figure shows the co-authorship network connecting the top 25 collaborators of Shunzo MIYOSHI. A scholar is included among the top collaborators of Shunzo MIYOSHI 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 Shunzo MIYOSHI. Shunzo MIYOSHI 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.
KUCHIDA, Keigo, et al.. (2004). . Nihon Chikusan Gakkaiho. 75(1). 53–60. 9 indexed citations
2.
KUCHIDA, Keigo, et al.. (2004). . Nihon Chikusan Gakkaiho. 75(1). 11–16. 13 indexed citations
3.
KUCHIDA, Keigo, et al.. (2003). Evaluation Method for the Shape of M. longissimus thoracis by Computer Image Analysis and Effect of Sire on the Shape in Japanese Black.. Nihon Chikusan Gakkaiho. 74(1). 23–29. 8 indexed citations
4.
KUCHIDA, Keigo, et al.. (2002). Primary Investigation of Evaluating Beef Meat Color Using Computer Monitor.. Nihon Chikusan Gakkaiho. 73(4). 521–528. 1 indexed citations
5.
KUCHIDA, Keigo, Mitsuyoshi Suzuki, & Shunzo MIYOSHI. (2002). Evaluation of Coarseness of Marbling in the Beef Ribeye by Computer Image Analysis. Nihon Chikusan Gakkaiho. 73(1). 9–17. 16 indexed citations
6.
MIYOSHI, Shunzo, Kaori Yamashita, Mamoru Yamanishi, et al.. (2002). Functions of the D-Ribosyl Moiety and the Lower Axial Ligand of the Nucleotide Loop of Coenzyme B12 in Diol Dehydratase and Ethanolamine Ammonia-lyase Reactions. The Journal of Biochemistry. 132(6). 935–943. 13 indexed citations
7.
KUCHIDA, Keigo, et al.. (2001). Prediction of Beef Color Standard Number from Digital Image Obtained by Using Photographing Equipment for the Cross Section of Carcass. Nihon Chikusan Gakkaiho. 72(9). 321–328. 6 indexed citations
8.
KUCHIDA, Keigo, Mitsuyoshi Suzuki, & Shunzo MIYOSHI. (2001). Development of Photographing Equipment for the Cross Section of Carcass and Prediction of BMS Number by Using Obtained Image from that Equipment. Nihon Chikusan Gakkaiho. 72(8). 224–231. 10 indexed citations
9.
MIYOSHI, Shunzo, J. L. Pate, & D.L. Palmquist. (2001). Effects of propylene glycol drenching on energy balance, plasma glucose, plasma insulin, ovarian function and conception in dairy cows. Animal Reproduction Science. 68(1-2). 29–43. 111 indexed citations
10.
KUCHIDA, Keigo, Koji Kato, Mitsuyoshi Suzuki, & Shunzo MIYOSHI. (2000). Utilization of the Information from M. semispinalis capitis and M. semispinalis dorsi by Computer Image Analysis on BMS Number Prediction. Nihon Chikusan Gakkaiho. 71(9). 305–310. 1 indexed citations
11.
12.
KUCHIDA, Keigo, et al.. (1999). Effect of Breeds on the Relationship between Beef Marbling Standard and Fat Percentage in Ribeye of Beef. Nihon Chikusan Gakkaiho. 70(8). 106–110. 1 indexed citations
13.
KUCHIDA, Keigo, S. Tsuruta, L.D. Van Vleck, Mitsuyoshi Suzuki, & Shunzo MIYOSHI. (1999). Prediction Method of Beef Marbling Standard Number Using Parameters Obtained from Image Analysis for Beef Ribeye. Nihon Chikusan Gakkaiho. 70(3). 107–112. 8 indexed citations
14.
KUCHIDA, Keigo, et al.. (1999). Nondestructive prediction method for yolk:albumen ratio in chicken eggs by computer image analysis. Poultry Science. 78(6). 909–913. 10 indexed citations
15.
KUCHIDA, Keigo, et al.. (1997). Computer Image Analysis Method for Evaluation of Marbling of Rib-Eye Area. Nihon Chikusan Gakkaiho. 68(9). 878–882. 4 indexed citations
16.
MIYOSHI, Shunzo, et al.. (1996). Application of Non-linear Models to Egg Production Curves in Chickens.. Japanese poultry science. 33(3). 178–184. 13 indexed citations
17.
MIYOSHI, Shunzo, et al.. (1995). The Influence of Artificially Removed Albumen of Egg on Hatching, Body Weight, and Internal Components Weight of Chick.. Japanese poultry science. 32(6). 408–414. 1 indexed citations
18.
Muramatsu, Tatsuo, et al.. (1992). Genetic differences in steroid-induced protein synthesis in vivo of the liver and magnum in immature chicks (Gallus domesticus). Comparative Biochemistry and Physiology Part B Comparative Biochemistry. 102(4). 905–909. 5 indexed citations
19.
Muramatsu, Takashi, et al.. (1990). Importance of albumen content in whole‐body protein synthesis of the chicken embryo during incubation. British Poultry Science. 31(1). 101–106. 34 indexed citations
20.
MIYOSHI, Shunzo, et al.. (1980). Selection for High and Low Yolk-albumen Ratio in Chickens. Japanese poultry science. 17(5). 219–227. 10 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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