T.R. Mackle

1.1k total citations
16 papers, 881 citations indexed

About

T.R. Mackle is a scholar working on Agronomy and Crop Science, Genetics and Nutrition and Dietetics. According to data from OpenAlex, T.R. Mackle has authored 16 papers receiving a total of 881 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Agronomy and Crop Science, 10 papers in Genetics and 7 papers in Nutrition and Dietetics. Recurrent topics in T.R. Mackle's work include Ruminant Nutrition and Digestive Physiology (11 papers), Reproductive Physiology in Livestock (7 papers) and Genetic and phenotypic traits in livestock (7 papers). T.R. Mackle is often cited by papers focused on Ruminant Nutrition and Digestive Physiology (11 papers), Reproductive Physiology in Livestock (7 papers) and Genetic and phenotypic traits in livestock (7 papers). T.R. Mackle collaborates with scholars based in United States, New Zealand and Ireland. T.R. Mackle's co-authors include D.E. Bauman, M.J. Auldist, D.A. Dwyer, J.K. Kay, N.A. Thomson, A. M. Bryant, K.L. Ingvartsen, P.Y. Chouinard, D.A. Ross and Jeremy P. Hill and has published in prestigious journals such as Journal of Dairy Science, New Zealand Journal of Agricultural Research and Proceedings of the New Zealand Society of Animal Production.

In The Last Decade

T.R. Mackle

16 papers receiving 803 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.R. Mackle United States 14 636 336 311 149 98 16 881
A. Ollier France 12 667 1.0× 300 0.9× 370 1.2× 166 1.1× 70 0.7× 41 862
Marie-Claude Nicot France 12 603 0.9× 254 0.8× 298 1.0× 160 1.1× 44 0.4× 18 718
Y. Chilliard France 13 880 1.4× 330 1.0× 733 2.4× 284 1.9× 102 1.0× 13 1.2k
Gerardo Antonio Gagliostro Argentina 14 572 0.9× 211 0.6× 300 1.0× 181 1.2× 36 0.4× 35 713
Liliana S. Piperova United States 13 747 1.2× 303 0.9× 595 1.9× 163 1.1× 237 2.4× 16 1.2k
H. Hagemeister Germany 18 501 0.8× 214 0.6× 162 0.5× 277 1.9× 165 1.7× 64 978
R. W. Mellenberger United States 14 339 0.5× 175 0.5× 136 0.4× 115 0.8× 90 0.9× 20 620
G.F. Schroeder United States 13 514 0.8× 213 0.6× 182 0.6× 171 1.1× 34 0.3× 23 624
Paola Piantoni United States 15 512 0.8× 342 1.0× 159 0.5× 158 1.1× 111 1.1× 21 718
W.M. Stoop Netherlands 8 508 0.8× 645 1.9× 194 0.6× 155 1.0× 62 0.6× 11 841

Countries citing papers authored by T.R. Mackle

Since Specialization
Citations

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

Fields of papers citing papers by T.R. Mackle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of T.R. Mackle

This figure shows the co-authorship network connecting the top 25 collaborators of T.R. Mackle. A scholar is included among the top collaborators of T.R. Mackle 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.R. Mackle. T.R. Mackle is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Kay, J.K., T.R. Mackle, D.E. Bauman, N.A. Thomson, & L.H. Baumgard. (2007). Effects of a Supplement Containing Trans-10, Cis-12 Conjugated Linoleic Acid on Bioenergetic and Milk Production Parameters in Grazing Dairy Cows Offered Ad Libitum or Restricted Pasture. Journal of Dairy Science. 90(2). 721–730. 22 indexed citations
2.
Kay, J.K., T.R. Mackle, M.J. Auldist, N.A. Thomson, & D.E. Bauman. (2004). Endogenous Synthesis of cis-9, trans-11 Conjugated Linoleic Acid in Dairy Cows Fed Fresh Pasture. Journal of Dairy Science. 87(2). 369–378. 212 indexed citations
3.
Block, Stephanie S., Robert P. Rhoads, D.E. Bauman, et al.. (2003). Demonstration of a Role for Insulin in the Regulation of Leptin in Lactating Dairy Cows. Journal of Dairy Science. 86(11). 3508–3515. 52 indexed citations
4.
Mackle, T.R., et al.. (2003). Effects of Abomasal Infusion of Conjugated Linoleic Acid on Milk Fat Concentration and Yield from Pasture-Fed Dairy Cows. Journal of Dairy Science. 86(2). 644–652. 63 indexed citations
5.
Kay, J.K., T.R. Mackle, M.J. Auldist, N.A. Thomson, & D.E. Bauman. (2002). Endogenous synthesis and enhancement of conjugated linolieic acid in pasture-fed dairy cows. Proceedings of the New Zealand Society of Animal Production. 62. 12–15. 8 indexed citations
6.
Mackle, T.R., D.A. Dwyer, K.L. Ingvartsen, et al.. (2000). Evaluation of Whole Blood and Plasma in the Interorgan Supply of Free Amino Acids for the Mammary Gland of Lactating Dairy Cows. Journal of Dairy Science. 83(6). 1300–1309. 24 indexed citations
7.
Mackle, T.R., D.A. Dwyer, K.L. Ingvartsen, et al.. (2000). Effects of Insulin and Postruminal Supply of Protein on Use of Amino Acids by the Mammary Gland for Milk Protein Synthesis. Journal of Dairy Science. 83(1). 93–105. 120 indexed citations
8.
Auldist, M.J., N.A. Thomson, T.R. Mackle, Jeremy P. Hill, & Colin G. Prosser. (2000). Effects of Pasture Allowance on the Yield and Composition of Milk from Cows of Different β-Lactoglobulin Phenotypes. Journal of Dairy Science. 83(9). 2069–2074. 39 indexed citations
9.
Mackle, T.R., D.A. Dwyer, & D.E. Bauman. (2000). Intramammary Infusion of Insulin or Long R3 Insulin-like Growth Factor-I did not Increase Milk Protein Yield in Dairy Cows. Journal of Dairy Science. 83(8). 1740–1749. 13 indexed citations
10.
Mackle, T.R., et al.. (1999). Variation in the composition of milk protein from pasture‐fed dairy cows in late lactation and the effect of grain and silage supplementation. New Zealand Journal of Agricultural Research. 42(2). 147–154. 51 indexed citations
11.
Mackle, T.R., et al.. (1999). Nutritional Influences on the Composition of Milk from Cows of Different Protein Phenotypes in New Zealand. Journal of Dairy Science. 82(1). 172–180. 58 indexed citations
12.
Mackle, T.R., D.A. Dwyer, & D.E. Bauman. (1999). Effects of Branched-Chain Amino Acids and Sodium Caseinate on Milk Protein Concentration and Yield from Dairy Cows. Journal of Dairy Science. 82(1). 161–171. 54 indexed citations
13.
Mackle, T.R., D.A. Dwyer, K.L. Ingvartsen, et al.. (1999). Effects of Insulin and Amino Acids on Milk Protein Concentration and Yield from Dairy Cows. Journal of Dairy Science. 82(7). 1512–1524. 80 indexed citations
14.
Mackle, T.R., et al.. (1997). Variation in the characteristics of milkfat from pasture‐fed dairy cows during late spring and the effects of grain supplementation.. New Zealand Journal of Agricultural Research. 40(3). 349–359. 17 indexed citations
15.
Mackle, T.R., et al.. (1996). Nitrogen fertiliser effects on milk yield and composition, pasture intake, nitrogen and energy partitioning, and rumen fermentation parameters of dairy cows in early lactation. New Zealand Journal of Agricultural Research. 39(3). 341–356. 31 indexed citations
16.
Mackle, T.R., et al.. (1996). Feed conversion efficiency, daily pasture intake, and milk production of primiparous Friesian and Jersey cows calved at two different liveweights. New Zealand Journal of Agricultural Research. 39(3). 357–370. 37 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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