J.M. Tricárico

4.7k total citations · 4 hit papers
59 papers, 3.4k citations indexed

About

J.M. Tricárico is a scholar working on Agronomy and Crop Science, Ecology and Genetics. According to data from OpenAlex, J.M. Tricárico has authored 59 papers receiving a total of 3.4k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Agronomy and Crop Science, 25 papers in Ecology and 11 papers in Genetics. Recurrent topics in J.M. Tricárico's work include Ruminant Nutrition and Digestive Physiology (37 papers), Agriculture Sustainability and Environmental Impact (25 papers) and Genetic and phenotypic traits in livestock (10 papers). J.M. Tricárico is often cited by papers focused on Ruminant Nutrition and Digestive Physiology (37 papers), Agriculture Sustainability and Environmental Impact (25 papers) and Genetic and phenotypic traits in livestock (10 papers). J.M. Tricárico collaborates with scholars based in United States, Netherlands and Italy. J.M. Tricárico's co-authors include E. Kebreab, Peter A. Vadas, W.P. Weiss, J.R. Knapp, A.N. Hristov, J. Dijkstra, G. C. Waghorn, J.L. Firkins, H.P.S. Makkar and J. Oh and has published in prestigious journals such as SHILAP Revista de lepidopterología, Environmental Science & Technology and PLoS ONE.

In The Last Decade

J.M. Tricárico

56 papers receiving 3.3k citations

Hit Papers

Invited review: Enteric m... 2013 2026 2017 2021 2014 2013 2022 2021 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
J.M. Tricárico United States 23 2.2k 1.2k 733 565 319 59 3.4k
J. Oh United States 26 2.4k 1.1× 963 0.8× 793 1.1× 558 1.0× 291 0.9× 66 3.4k
Peter Lund Denmark 33 2.3k 1.0× 627 0.5× 741 1.0× 836 1.5× 347 1.1× 162 3.7k
C. Grainger Australia 32 2.2k 1.0× 1.1k 0.9× 531 0.7× 827 1.5× 203 0.6× 57 3.7k
T. Yan United Kingdom 34 2.8k 1.3× 1.0k 0.8× 1.1k 1.5× 1.2k 2.1× 248 0.8× 161 3.8k
Richard Eckard Australia 37 2.5k 1.2× 1.9k 1.5× 748 1.0× 474 0.8× 584 1.8× 132 4.8k
David R. Yáñez-Ruíz Spain 31 2.6k 1.2× 454 0.4× 658 0.9× 512 0.9× 414 1.3× 101 3.5k
T.M. Boland Ireland 34 2.8k 1.3× 905 0.7× 667 0.9× 1.1k 1.9× 246 0.8× 168 3.6k
N. E. Odongo Canada 28 1.9k 0.9× 442 0.4× 738 1.0× 539 1.0× 318 1.0× 96 2.7k
J.R. Newbold United Kingdom 26 2.6k 1.2× 447 0.4× 578 0.8× 702 1.2× 284 0.9× 61 3.3k
R. S. Hegarty Australia 33 2.5k 1.2× 1.0k 0.8× 1.2k 1.6× 1.1k 2.0× 142 0.4× 123 3.6k

Countries citing papers authored by J.M. Tricárico

Since Specialization
Citations

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

Fields of papers citing papers by J.M. Tricárico

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J.M. Tricárico

This figure shows the co-authorship network connecting the top 25 collaborators of J.M. Tricárico. A scholar is included among the top collaborators of J.M. Tricárico 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 J.M. Tricárico. J.M. Tricárico 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
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2.
Pelton, Rylie E. O., et al.. (2025). Spatially Resolved Greenhouse Gas Emissions of U.S. Milk Production in 2020. Environmental Science & Technology. 59(19). 9552–9564. 1 indexed citations
3.
4.
Hristov, A.N., et al.. (2023). A global dataset of enteric methane mitigation experiments with lactating and non-lactating dairy cows conducted from 1963 to 2022. Data in Brief. 49. 109459–109459. 7 indexed citations
5.
Beauchemin, K. A., Emilio M. Ungerfeld, Adibe Luiz Abdalla, et al.. (2022). Invited review: Current enteric methane mitigation options. Journal of Dairy Science. 105(12). 9297–9326. 166 indexed citations breakdown →
6.
Niles, Meredith T., et al.. (2022). Manure management strategies are interconnected with complexity across U.S. dairy farms. PLoS ONE. 17(6). e0267731–e0267731. 6 indexed citations
7.
Li, Jinghui, et al.. (2021). The Ruminant Farm Systems Animal Module: A Biophysical Description of Animal Management. Animals. 11(5). 1373–1373. 18 indexed citations
8.
Miller, Gregory D., et al.. (2020). Food System Sustainability. Nutrition Today. 55(2). 82–85. 1 indexed citations
9.
Niles, Meredith T., et al.. (2019). A review of determinants for dairy farmer decision making on manure management strategies in high-income countries. Environmental Research Letters. 14(5). 53004–53004. 20 indexed citations
10.
Lingen, Henk J. van, J.G. Fadel, A. Bannink, et al.. (2018). Multi-criteria evaluation of dairy cattle feed resources and animal characteristics for nutritive and environmental impacts. animal. 12(s2). s310–s320. 8 indexed citations
11.
Martin, N. P., Michael P. Russelle, J. M. Powell, et al.. (2017). Invited review: Sustainable forage and grain crop production for the US dairy industry. Journal of Dairy Science. 100(12). 9479–9494. 66 indexed citations
12.
Moraes, L.E., J.G. Fadel, A.R. Castillo, et al.. (2015). Modeling the trade-off between diet costs and methane emissions: A goal programming approach. Journal of Dairy Science. 98(8). 5557–5571. 24 indexed citations
13.
Knapp, J.R., et al.. (2014). Invited review: Enteric methane in dairy cattle production: Quantifying the opportunities and impact of reducing emissions. Journal of Dairy Science. 97(6). 3231–3261. 714 indexed citations breakdown →
14.
Gerber, Pierre, A.N. Hristov, B. Henderson, et al.. (2013). Technical options for the mitigation of direct methane and nitrous oxide emissions from livestock: a review. animal. 7. 220–234. 320 indexed citations
15.
Kalscheur, K. F., et al.. (2012). Soybean meal substitution with a yeast-derived microbial protein source in dairy cow diets. Journal of Dairy Science. 95(10). 5888–5900. 17 indexed citations
16.
Tedeschi, Luís O, et al.. (2012). Effects of a slow-release urea product on performance, carcass characteristics, and nitrogen balance of steers fed steam-flaked corn. Journal of Animal Science. 90(11). 3914–3923. 23 indexed citations
17.
Tricárico, J.M., Jonathan D. Johnston, & K. A. Dawson. (2007). Dietary supplementation of ruminant diets with an Aspergillus oryzae α-amylase. Animal Feed Science and Technology. 145(1-4). 136–150. 51 indexed citations
18.
Moran, Colm A., et al.. (2006). Fermentation of wheat: Effects of backslopping different proportions of pre-fermented wheat on the microbialand chemical composition. Archives of Animal Nutrition. 60(2). 158–169. 35 indexed citations
19.
DeFrain, J.M., A. R. Hippen, K. F. Kalscheur, & J.M. Tricárico. (2005). Effects of Dietary α-Amylase on Metabolism and Performance of Transition Dairy Cows. Journal of Dairy Science. 88(12). 4405–4413. 32 indexed citations
20.
Tricárico, J.M., Jonathan D. Johnston, K. A. Dawson, et al.. (2005). The effects of anAspergillus oryzaeextract containing alpha-amylase activity on ruminal fermentation and milk production in lactating Holstein cows. Animal Science. 81(3). 365–374. 59 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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