M. L. Galyean

9.4k total citations · 2 hit papers
234 papers, 7.1k citations indexed

About

M. L. Galyean is a scholar working on Agronomy and Crop Science, Animal Science and Zoology and Genetics. According to data from OpenAlex, M. L. Galyean has authored 234 papers receiving a total of 7.1k indexed citations (citations by other indexed papers that have themselves been cited), including 173 papers in Agronomy and Crop Science, 97 papers in Animal Science and Zoology and 56 papers in Genetics. Recurrent topics in M. L. Galyean's work include Ruminant Nutrition and Digestive Physiology (162 papers), Genetic and phenotypic traits in livestock (56 papers) and Animal Nutrition and Physiology (52 papers). M. L. Galyean is often cited by papers focused on Ruminant Nutrition and Digestive Physiology (162 papers), Genetic and phenotypic traits in livestock (56 papers) and Animal Nutrition and Physiology (52 papers). M. L. Galyean collaborates with scholars based in United States, China and South Africa. M. L. Galyean's co-authors include Joe D. Wallace, J. T. Vasconcelos, F. T. McCollum, A.L. Goetsch, Don C. Adams, M. E. Hubbert, R.C. Cochran, F. N. Owens, M. E. Branine and Glenn C Duff and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Agricultural and Food Chemistry and Journal of Dairy Science.

In The Last Decade

M. L. Galyean

225 papers receiving 6.6k citations

Hit Papers

Predicting Digestibility of Different Diets with Internal... 1986 2026 1999 2012 1986 2016 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. L. Galyean United States 46 5.0k 3.0k 2.0k 888 710 234 7.1k
W.P. Weiss United States 45 5.5k 1.1× 2.2k 0.7× 1.8k 0.9× 807 0.9× 797 1.1× 190 7.8k
F. N. Owens United States 45 6.5k 1.3× 3.6k 1.2× 3.1k 1.6× 745 0.8× 570 0.8× 190 9.1k
Terry J. Klopfenstein United States 46 7.2k 1.4× 3.0k 1.0× 2.7k 1.4× 515 0.6× 1.0k 1.5× 607 9.5k
Denis O. Krause Canada 43 4.6k 0.9× 1.6k 0.5× 1.3k 0.7× 1.2k 1.4× 454 0.6× 101 8.1k
Evan C. Titgemeyer United States 42 4.7k 1.0× 1.7k 0.6× 1.8k 0.9× 516 0.6× 264 0.4× 232 6.3k
À. Bach Spain 49 5.2k 1.0× 2.4k 0.8× 2.0k 1.0× 1.9k 2.1× 420 0.6× 185 7.7k
S. Calsamiglia Spain 43 6.2k 1.2× 2.2k 0.7× 1.4k 0.7× 511 0.6× 487 0.7× 125 8.2k
S. Tamminga Netherlands 55 7.5k 1.5× 3.0k 1.0× 2.9k 1.5× 686 0.8× 968 1.4× 291 10.6k
J.L. Firkins United States 50 6.6k 1.3× 1.4k 0.5× 2.3k 1.2× 395 0.4× 1.2k 1.6× 167 8.2k
D. G. Fox United States 40 7.6k 1.5× 2.8k 0.9× 3.3k 1.7× 409 0.5× 1.0k 1.4× 109 9.2k

Countries citing papers authored by M. L. Galyean

Since Specialization
Citations

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

Fields of papers citing papers by M. L. Galyean

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. L. Galyean. 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 M. L. Galyean. The network helps show where M. L. Galyean may publish in the future.

Co-authorship network of co-authors of M. L. Galyean

This figure shows the co-authorship network connecting the top 25 collaborators of M. L. Galyean. A scholar is included among the top collaborators of M. L. Galyean 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 M. L. Galyean. M. L. Galyean 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.
Galyean, M. L.. (2025). Relationships Between Fiber in Feedlot Diets and Growth Performance of Beef Cattle. Animals. 15(22). 3266–3266.
2.
Sanchez, Nicole C Burdick, T.E. Lawrence, T. G. Nagaraja, et al.. (2024). 473 Evaluation of hematology outcomes as indicators of liver abscess formation in beef × dairy cross steers. Journal of Animal Science. 102(Supplement_3). 385–386. 1 indexed citations
3.
Broadway, Paul R., et al.. (2024). Liver abscesses—New perspectives on a historic fed-cattle issue*†‡. Applied Animal Science. 40(3). 237–243. 11 indexed citations
5.
Hales, Kristin E, Xiaorong Shi, T. G. Nagaraja, et al.. (2024). Development of an experimental model for liver abscess induction in Holstein steers using an acidotic diet challenge and bacterial inoculation. Journal of Animal Science. 102. 6 indexed citations
6.
Galyean, M. L., W. T. Nichols, M. N. Streeter, & J. P. Hutcheson. (2023). Effects of extended days on feed on rate of change in performance and carcass characteristics of feedlot steers and heifers and Holstein steers. Applied Animal Science. 39(2). 69–78. 10 indexed citations
7.
Tedeschi, Luís O & M. L. Galyean. (2023). A practical method to account for outliers in simple linear regression using the median of slopes. Scientia Agricola. 81. 1 indexed citations
8.
Hales, Kristin E, T. G. Nagaraja, T.E. Lawrence, et al.. (2023). Short communication: evaluation of an endotoxin challenge and intraruminal bacterial inoculation model to induce liver abscesses in Holstein steers. Journal of Animal Science. 101. 1 indexed citations
9.
Galyean, M. L., et al.. (2022). Effects of altering prepartum and postpartum dietary cation–anion difference on calcium concentrations and blood metabolites of Holstein dairy cows. Animal Science Journal. 93(1). e13715–e13715. 1 indexed citations
11.
Galyean, M. L.. (2014). INVITED REVIEW: Nutrient requirements of ruminants: Derivation, validation, and application. The Professional Animal Scientist. 30(2). 125–128. 4 indexed citations
12.
Chung, Ki Yong, J. P. Hutcheson, W. T. Nichols, et al.. (2010). Dose and release pattern of anabolic implants affects growth of finishing beef steers across days on feed1. Journal of Animal Science. 89(3). 863–873. 31 indexed citations
13.
Vasconcelos, J. T., et al.. (2007). Effects of wet corn gluten feed and roughage levels on performance, carcass characteristics, and feeding behavior of feedlot cattle1. Journal of Animal Science. 85(11). 3079–3089. 17 indexed citations
14.
Rivera, J, M. L. Galyean, & W. T. Nichols. (2005). REVIEW: Dietary Roughage Concentration and Health of Newly Received Cattle. The Professional Animal Scientist. 21(5). 345–351. 32 indexed citations
15.
Montgomery, J. L., M. L. Galyean, R.L. Horst, et al.. (2004). Supplemental vitamin D3 concentration and biological type of beef steers. I. Feedlot performance and carcass traits1. Journal of Animal Science. 82(7). 2050–2058. 16 indexed citations
16.
Defoor, P. J., N. A. Cole, M. L. Galyean, & O. R. Jones. (2001). Effects of grain sorghum planting density and processing method on nutrient digestibility and retention by ruminants.. Journal of Animal Science. 79(1). 19–19. 11 indexed citations
17.
Gunter, S. A. & M. L. Galyean. (2000). Using a Segmented Model to DescribeIn situNutrient Disappearance. Journal of Applied Animal Research. 18(1). 1–14. 1 indexed citations
18.
Galyean, M. L., E. E. Hatfield, & T.L. Stanton. (1999). Review: Restricted and Programmed Feeding of Beef Cattle—Definitions, Application, and Research Results. The Professional Animal Scientist. 15(1). 1–6. 45 indexed citations
19.
Galyean, M. L., et al.. (1996). Roughage Source and Level in Beef Cattle Finishing Diets. The Professional Animal Scientist. 12(3). 192–198. 12 indexed citations
20.
Galyean, M. L., et al.. (1992). Early aspects of locoweed toxicosis and evaluation of a mineral supplement or clinoptilolite as dietary treatments2. Journal of Animal Science. 70(10). 3125–3132. 24 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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