I. De Barbieri

408 total citations
42 papers, 278 citations indexed

About

I. De Barbieri is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology. According to data from OpenAlex, I. De Barbieri has authored 42 papers receiving a total of 278 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Genetics, 26 papers in Agronomy and Crop Science and 21 papers in Animal Science and Zoology. Recurrent topics in I. De Barbieri's work include Genetic and phenotypic traits in livestock (27 papers), Ruminant Nutrition and Digestive Physiology (22 papers) and Reproductive Physiology in Livestock (15 papers). I. De Barbieri is often cited by papers focused on Genetic and phenotypic traits in livestock (27 papers), Ruminant Nutrition and Digestive Physiology (22 papers) and Reproductive Physiology in Livestock (15 papers). I. De Barbieri collaborates with scholars based in Uruguay, New Zealand and France. I. De Barbieri's co-authors include F. Montossi, V. H. Oddy, C. Viñoles, P. R. Kenyon, R. S. Hegarty, Gabriel Ciappesoni, Georgget Banchero, RS Hegarty, D. Ouwerkerk and Athol V. Klieve and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Animal Science and Animal Feed Science and Technology.

In The Last Decade

I. De Barbieri

34 papers receiving 269 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
I. De Barbieri Uruguay 10 189 129 92 49 28 42 278
S. J. Falck United States 10 343 1.8× 149 1.2× 64 0.7× 29 0.6× 29 1.0× 16 387
Gary A Ducharme United States 8 280 1.5× 105 0.8× 55 0.6× 35 0.7× 15 0.5× 11 353
D. V. Dhuyvetter United States 7 275 1.5× 110 0.9× 75 0.8× 20 0.4× 24 0.9× 9 318
C.T. Westwood Australia 10 414 2.2× 293 2.3× 104 1.1× 74 1.5× 14 0.5× 13 489
Christel Marie‐Etancelin France 12 109 0.6× 173 1.3× 170 1.8× 40 0.8× 21 0.8× 27 330
J. F. Wilkins Australia 12 323 1.7× 297 2.3× 110 1.2× 46 0.9× 13 0.5× 32 467
M.A. Galina Mexico 13 274 1.4× 175 1.4× 123 1.3× 14 0.3× 15 0.5× 36 397
Mehmet Akif Çam Türkiye 11 266 1.4× 276 2.1× 165 1.8× 41 0.8× 8 0.3× 27 532
Pedro L P Fontes United States 10 248 1.3× 165 1.3× 61 0.7× 30 0.6× 10 0.4× 51 298
Nevena Maksimović Serbia 10 128 0.7× 155 1.2× 115 1.3× 32 0.7× 14 0.5× 76 299

Countries citing papers authored by I. De Barbieri

Since Specialization
Citations

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

Fields of papers citing papers by I. De Barbieri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by I. De Barbieri. 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 I. De Barbieri. The network helps show where I. De Barbieri may publish in the future.

Co-authorship network of co-authors of I. De Barbieri

This figure shows the co-authorship network connecting the top 25 collaborators of I. De Barbieri. A scholar is included among the top collaborators of I. De Barbieri 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 I. De Barbieri. I. De Barbieri 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.
Navajas, E.A., I. De Barbieri, O. Ravagnolo, et al.. (2025). Genetic selection and livestock sustainability. 29(NE2). e1480–e1480.
2.
Lambe, N.R., F. McGovern, E.A. Navajas, et al.. (2025). Comparison of country-specific predictions of feed intake and methane emissions in sheep using different proxies. Livestock Science. 296. 105716–105716.
3.
Garrick, Dorian J., H. T. Blair, I. De Barbieri, et al.. (2025). Genetic Trends for Production and Reproduction Traits in Ultrafine Merino Sheep of Uruguay. Journal of Animal Breeding and Genetics. 142(6). 685–692.
4.
Savian, Jean Víctor, et al.. (2024). Using faecal nitrogen as a marker to estimate intake and digestibility in sheep fed multi-species native forage. Animal Feed Science and Technology. 314. 115996–115996.
5.
Barbieri, I. De, et al.. (2024). Feed conversion efficiency does not negatively affect young sheep and ewe performance. SHILAP Revista de lepidopterología. 5.
6.
Ferreira, Josiel, Alfonso Juventino Chay‐Canul, I. De Barbieri, & Ricardo Lopes Dias da Costa. (2024). Compilations and updates on residual feed intake in sheep. Tropical Animal Health and Production. 56(5). 172–172. 2 indexed citations
7.
8.
Barbieri, I. De, et al.. (2023). PL-8 A review of sheep resilience. Animal - science proceedings. 14(1). 11–12. 2 indexed citations
9.
Garrick, Dorian J., H. T. Blair, I. De Barbieri, et al.. (2023). Genetic and phenotypic relationships between ewe reproductive performance and wool and growth traits in Uruguayan Ultrafine Merino sheep. Journal of Animal Science. 101. 10 indexed citations
10.
Barbieri, I. De, et al.. (2022). Residual feed intake for Australian Merino sheep estimated in less than 42 days of trial. Livestock Science. 258. 104889–104889. 12 indexed citations
11.
Barbieri, I. De, et al.. (2022). High performance of growing lambs grazing Paspalum notatum INIA Sepé with energy-protein supplement including sorghum-DDGS. SHILAP Revista de lepidopterología. 26(1). e549–e549. 3 indexed citations
12.
Barbieri, I. De, et al.. (2022). Effect of temporary weaning and creep feeding on calf growth and the reproductive efficiency of their Hereford dams. Animal Bioscience. 35(10). 1524–1534. 2 indexed citations
13.
Blair, H. T., et al.. (2021). Productivity and Reproductive Performance of Mixed-Age Ewes across 20 Years of Selection for Ultrafine Wool in Uruguay. Agriculture. 11(8). 712–712. 6 indexed citations
14.
Blair, H. T., et al.. (2021). Phenotypic Responses to Selection for Ultrafine Wool in Uruguayan Yearling Lambs. Agriculture. 11(2). 179–179. 4 indexed citations
15.
Barbieri, I. De, C. Viñoles, F. Montossi, Santiago Luzardo, & Gabriel Ciappesoni. (2021). Productive and reproductive consequences of crossbreeding Dohne Merino with Corriedale in Uruguayan sheep production systems. Animal Production Science. 62(1). 29–39. 4 indexed citations
16.
Ciappesoni, Gabriel, et al.. (2021). Feed conversion efficiency in sheep genetically selected for resistance to gastrointestinal nematodes. Animal Production Science. 61(8). 754–760. 6 indexed citations
17.
Barbieri, I. De, F. Montossi, C. Viñoles, & P. R. Kenyon. (2017). Time of shearing the ewe not only affects lamb live weight and survival at birth and weaning, but also ewe wool production and quality. New Zealand Journal of Agricultural Research. 61(1). 57–66. 11 indexed citations
18.
Barbieri, I. De, R. S. Hegarty, V. H. Oddy, et al.. (2014). Sheep of divergent genetic merit for wool growth do not differ in digesta kinetics while on restricted intakes. Animal Production Science. 54(9). 1243–1247. 6 indexed citations
19.
Viñoles, C., et al.. (2013). Effect of creep feeding and stocking rate on the productivity of beef cattle grazing grasslands. New Zealand Journal of Agricultural Research. 56(4). 279–287. 9 indexed citations
20.
Ravagnolo, O., et al.. (2006). Estimation of Genetic Parameters and Genetic Trends for Wool Production and Quality for the Uruguayan Merino.. 2 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by S. J. Falck Breakdown of academic impact, for papers by Gary A Ducharme Breakdown of academic impact, for papers by D. V. Dhuyvetter Breakdown of academic impact, for papers by C.T. Westwood Breakdown of academic impact, for papers by Christel Marie‐Etancelin Breakdown of academic impact, for papers by J. F. Wilkins Breakdown of academic impact, for papers by M.A. Galina Breakdown of academic impact, for papers by Mehmet Akif Çam Breakdown of academic impact, for papers by Pedro L P Fontes Breakdown of academic impact, for papers by Nevena Maksimović
Rankless by CCL
2026