T. Mutsvangwa

2.1k total citations
64 papers, 1.6k citations indexed

About

T. Mutsvangwa is a scholar working on Agronomy and Crop Science, Genetics and Animal Science and Zoology. According to data from OpenAlex, T. Mutsvangwa has authored 64 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Agronomy and Crop Science, 21 papers in Genetics and 12 papers in Animal Science and Zoology. Recurrent topics in T. Mutsvangwa's work include Ruminant Nutrition and Digestive Physiology (51 papers), Reproductive Physiology in Livestock (36 papers) and Genetic and phenotypic traits in livestock (21 papers). T. Mutsvangwa is often cited by papers focused on Ruminant Nutrition and Digestive Physiology (51 papers), Reproductive Physiology in Livestock (36 papers) and Genetic and phenotypic traits in livestock (21 papers). T. Mutsvangwa collaborates with scholars based in Canada, South Africa and United States. T. Mutsvangwa's co-authors include G.B. Penner, K. A. Beauchemin, G.N. Gozho, B.W. McBride, Gwinyai E Chibisa, David A. Christensen, T.F. Duffield, J. H. Topps, I. E. S. Edwards and J. J. McKinnon and has published in prestigious journals such as Journal of Nutrition, Journal of Dairy Science and British Journal Of Nutrition.

In The Last Decade

T. Mutsvangwa

59 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
T. Mutsvangwa Canada 23 1.4k 551 373 201 153 64 1.6k
M. J. Cecava United States 23 1.4k 1.0× 708 1.3× 437 1.2× 143 0.7× 138 0.9× 45 1.8k
J.A. Guada Spain 25 1.3k 0.9× 461 0.8× 469 1.3× 163 0.8× 108 0.7× 69 1.7k
F. Dohme Switzerland 17 1.2k 0.9× 336 0.6× 346 0.9× 193 1.0× 157 1.0× 23 1.5k
P. A. Ludden United States 17 880 0.6× 385 0.7× 665 1.8× 131 0.7× 143 0.9× 30 1.4k
R. A. Zinn Mexico 13 1.2k 0.9× 461 0.8× 464 1.2× 73 0.4× 108 0.7× 24 1.4k
F. D. DeB. Hovell United Kingdom 22 1.5k 1.1× 560 1.0× 501 1.3× 218 1.1× 135 0.9× 53 1.9k
G.I. Zanton United States 19 935 0.7× 464 0.8× 285 0.8× 140 0.7× 80 0.5× 56 1.1k
Peter Lebzien Germany 23 1.2k 0.8× 348 0.6× 270 0.7× 115 0.6× 172 1.1× 122 1.7k
Mogens Larsen Denmark 22 998 0.7× 408 0.7× 291 0.8× 160 0.8× 130 0.8× 82 1.4k
S.J. Mabjeesh Israel 22 760 0.5× 384 0.7× 408 1.1× 144 0.7× 163 1.1× 66 1.3k

Countries citing papers authored by T. Mutsvangwa

Since Specialization
Citations

This map shows the geographic impact of T. Mutsvangwa'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 T. Mutsvangwa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Mutsvangwa more than expected).

Fields of papers citing papers by T. Mutsvangwa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T. Mutsvangwa

This figure shows the co-authorship network connecting the top 25 collaborators of T. Mutsvangwa. A scholar is included among the top collaborators of T. Mutsvangwa 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 T. Mutsvangwa. T. Mutsvangwa 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.
Damiran, Daalkhaijav, G.B. Penner, T. Mutsvangwa, et al.. (2025). Comparison of canola meal versus soybean meal on growth performance and carcass quality of feedlot cattle. Canadian Journal of Animal Science. 105. 1–11.
2.
Santschi, D.E., T.F. Duffield, M.A. Steele, et al.. (2024). Farm-level nutritional factors associated with milk production and milking behavior on Canadian farms with automated milking systems. Journal of Dairy Science. 107(7). 4409–4425. 3 indexed citations
3.
Santschi, D.E., T.F. Duffield, M.A. Steele, et al.. (2024). Farm-level risk factors associated with increased milk β-hydroxybutyrate and hyperketolactia prevalence on farms with automated milking systems. Journal of Dairy Science. 107(10). 8286–8298.
4.
Ribeiro, Gabriel O, et al.. (2024). Severity of rolling reconstituted high-moisture barley on ensiling characteristics and in vitro ruminal fermentation. Journal of Dairy Science. 107(12). 10738–10750. 1 indexed citations
5.
6.
Chikwanha, Obert C., et al.. (2020). Comparative effects of feeding citrus pulp and grape pomace on nutrient digestibility and utilization in steers. animal. 15(1). 100020–100020. 18 indexed citations
7.
Chikwanha, Obert C., et al.. (2019). Influence of feeding fruit by-products as alternative dietary fibre sources to wheat bran on beef production and quality of Angus steers. Meat Science. 161. 107969–107969. 36 indexed citations
8.
McKinnon, J. J., et al.. (2017). 255 Evaluation of canola meal versus soybean meal as a protein supplement on performance and carcass characteristics of growing and finishing beef cattle. Journal of Animal Science. 95(suppl_4). 125–126. 1 indexed citations
9.
Castillo‐Lopez, Ezequias, Hugo Ramírez, David A. Christensen, et al.. (2017). Effect of partially replacing a barley-based concentrate with flaxseed-based products on the rumen bacterial population of lactating Holstein dairy cows. Journal of Applied Microbiology. 124(1). 42–57. 13 indexed citations
10.
Mutsvangwa, T.. (2014). Effects of feeding canola meal (CM) and wheat dried distillers grains with solubles (W-DDGS) as the major protein source in low or high crude protein diets on ruminal nitrogen utilization, omasal nutrient flow, and milk production in dairy cows. 2014 ADSA-ASAS-CSAS Joint Annual Meeting.
11.
12.
Chibisa, Gwinyai E, David A. Christensen, & T. Mutsvangwa. (2012). Effects of replacing canola meal as the major protein source with wheat dried distillers grains with solubles on ruminal function, microbial protein synthesis, omasal flow, and milk production in cows. Journal of Dairy Science. 95(2). 824–841. 31 indexed citations
13.
Mutsvangwa, T., et al.. (2009). Nitrogen utilization in growing lambs fed oscillating dietary protein concentrations. Animal Feed Science and Technology. 152(1-2). 33–41. 16 indexed citations
14.
AlZahal, Ousama, N. E. Odongo, T. Mutsvangwa, et al.. (2008). Effects of Monensin and Dietary Soybean Oil on Milk Fat Percentage and Milk Fatty Acid Profile in Lactating Dairy Cows. Journal of Dairy Science. 91(3). 1166–1174. 75 indexed citations
15.
16.
Mutsvangwa, T., et al.. (2007). Effects of barley grain processing and dietary ruminally degradable protein on urea nitrogen recycling and nitrogen metabolism in growing lambs1. Journal of Animal Science. 85(12). 3391–3399. 27 indexed citations
17.
Soita, H. W., et al.. (2005). Effects of Corn Silage Particle Length and Forage:Concentrate Ratio on Milk Fatty Acid Composition in Dairy Cows Fed Supplemental Flaxseed. Journal of Dairy Science. 88(8). 2813–2819. 25 indexed citations
18.
Mutsvangwa, T. & H. Hamudikuwanda. (1994). A note on comparison of reproductive performance in dairy cows bred before and after 60 days post partum. 32(1). 99–102. 1 indexed citations
19.
Mutsvangwa, T. & H. Hamudikuwanda. (1993). The influence of dietary protein concentration on milk production and quality, and ruminal and blood characteristics in holstein cows during early lactation. 31(2). 115–124. 1 indexed citations
20.

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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