N. Prieto

2.5k total citations
117 papers, 1.9k citations indexed

About

N. Prieto is a scholar working on Animal Science and Zoology, Analytical Chemistry and Agronomy and Crop Science. According to data from OpenAlex, N. Prieto has authored 117 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Animal Science and Zoology, 27 papers in Analytical Chemistry and 21 papers in Agronomy and Crop Science. Recurrent topics in N. Prieto's work include Meat and Animal Product Quality (73 papers), Animal Nutrition and Physiology (30 papers) and Spectroscopy and Chemometric Analyses (27 papers). N. Prieto is often cited by papers focused on Meat and Animal Product Quality (73 papers), Animal Nutrition and Physiology (30 papers) and Spectroscopy and Chemometric Analyses (27 papers). N. Prieto collaborates with scholars based in Canada, Spain and United Kingdom. N. Prieto's co-authors include J.L. Aalhus, Francisco Javier Giráldez, M. E. R. Dugan, Raúl Bodas, Ó. López-Campos, Sonia Andrés, M. Juárez, Olga Pawluczyk, Payam Vahmani and Lara Morán and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Food Chemistry.

In The Last Decade

N. Prieto

110 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
N. Prieto Canada 27 1.0k 496 461 302 296 117 1.9k
M. Juárez Canada 25 1.7k 1.6× 273 0.6× 312 0.7× 360 1.2× 286 1.0× 138 2.3k
C. Gariépy Canada 26 1.5k 1.4× 646 1.3× 499 1.1× 381 1.3× 81 0.3× 85 2.3k
N. Prieto Spain 11 763 0.7× 574 1.2× 275 0.6× 155 0.5× 307 1.0× 14 1.2k
R.A. Mancini United States 32 4.3k 4.1× 216 0.4× 753 1.6× 813 2.7× 166 0.6× 76 5.0k
Xin Luo China 32 1.9k 1.8× 110 0.2× 488 1.1× 709 2.3× 45 0.2× 142 2.8k
Ranjith Ramanathan United States 33 2.2k 2.1× 104 0.2× 432 0.9× 716 2.4× 39 0.1× 140 2.7k
Ambra Rita Di Rosa Italy 18 251 0.2× 107 0.2× 236 0.5× 173 0.6× 79 0.3× 47 949
Lars Wiking Denmark 25 511 0.5× 62 0.1× 97 0.2× 317 1.0× 410 1.4× 93 1.9k
Helmut K. Mayer Austria 27 241 0.2× 141 0.3× 250 0.5× 822 2.7× 203 0.7× 91 1.8k
Leslie Thompson United States 22 954 0.9× 48 0.1× 101 0.2× 242 0.8× 132 0.4× 88 1.9k

Countries citing papers authored by N. Prieto

Since Specialization
Citations

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

Fields of papers citing papers by N. Prieto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of N. Prieto

This figure shows the co-authorship network connecting the top 25 collaborators of N. Prieto. A scholar is included among the top collaborators of N. Prieto 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 N. Prieto. N. Prieto 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
4.
López-Campos, Ó., et al.. (2023). Effects of in-the-bag dry-ageing on meat quality, palatability and volatile compounds of low-value beef cuts. Meat Science. 202. 109219–109219. 6 indexed citations
6.
López-Campos, Ó., I. L. Larsen, N. Prieto, et al.. (2017). Evaluation of Total Lean and Saleable Meat Yield Prediction Equations and Dual Energy X-Ray Absorptiometry for a Rapid, Non-Invasive Yield Prediction in Beef. Meat and Muscle Biology. 1(2). 104–104. 3 indexed citations
7.
López-Campos, Ó., I. L. Larsen, N. Prieto, et al.. (2017). Using Dual Energy X-Ray Absorptiometry (DXA) For A Rapid, Non-Invasive Carcass Fat and Lean Prediction in Beef. Meat and Muscle Biology. 1(2). 96–96. 2 indexed citations
8.
López-Campos, Ó., M. Juárez, I. L. Larsen, et al.. (2017). Dual Energy X-Ray Absorptiometry as a Rapid and Non-Destructive Method for Determination of Lean, Fat and Bone Content in Livestock. Meat and Muscle Biology. 1(3). 107–107. 1 indexed citations
9.
Vahmani, Payam, D. C. Rolland, Tim A. McAllister, et al.. (2016). Feeding steers hay with extruded flaxseed together or sequentially has a profound effect on erythrocyte trans 11-18:1 (vaccenic acid). Canadian Journal of Animal Science. 96(3). 299–301. 5 indexed citations
10.
Prieto, N., et al.. (2015). The elimination of an adult segment by the Hox gene Abdominal-B. Mechanisms of Development. 138. 210–217. 3 indexed citations
11.
Herrera, R. S., et al.. (2014). Effect of re-growth age in the content of secondary metabolites from Neonotonia wightii in the Valle del Cauto, Cuba.. Cuban journal of agricultural science. 48(2). 149–154. 1 indexed citations
12.
Aalhus, J.L., Ó. López-Campos, N. Prieto, et al.. (2014). Review: Canadian beef grading – Opportunities to identify carcass and meat quality traits valued by consumers. Canadian Journal of Animal Science. 94(4). 545–556. 24 indexed citations
13.
Prieto, N., M. E. R. Dugan, Ó. López-Campos, J.L. Aalhus, & B. Uttaro. (2013). At line prediction of PUFA and biohydrogenation intermediates in perirenal and subcutaneous fat from cattle fed sunflower or flaxseed by near infrared spectroscopy. Meat Science. 94(1). 27–33. 18 indexed citations
14.
Blanco, Carolina, Raúl Bodas, N. Prieto, et al.. (2013). Concentrate plus ground barley straw pellets can replace conventional feeding systems for light fattening lambs. Small Ruminant Research. 116(2-3). 137–143. 39 indexed citations
15.
Pulido, Edward J., Francisco Javier Giráldez, Raúl Bodas, Sonia Andrés, & N. Prieto. (2012). Effect of reduction of milking frequency and supplementation of vitamin E and selenium above requirements on milk yield and composition in Assaf ewes. Journal of Dairy Science. 95(7). 3527–3535. 6 indexed citations
16.
Bodas, Raúl, et al.. (2011). The effect of naringin on plasma lipid profile, and liver and intramuscular fat contents of fattening lambs. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 223–226. 3 indexed citations
17.
Prieto, N., E.A. Navajas, R.I. Richardson, et al.. (2010). Predicting beef cuts composition, fatty acids and meat quality characteristics by spiral computed tomography. Meat Science. 86(3). 770–779. 41 indexed citations
18.
Navajas, E.A., R.I. Richardson, C. A. Glasbey, et al.. (2009). Associations betwen beef density by X-ray computed tomography, intramuscular fat and fatty acid composition: preliminary results. Bristol Research (University of Bristol). 2009. 3 indexed citations
19.
Alarcón, Teresa, et al.. (2002). Actividad in vitro de claritromicina y metronidazol frente a Helicobacter pylori en diferentes atmósferas de incubación. Revista española de quimioterapia. Suplemento. 15(4). 341–345. 2 indexed citations
20.
Prieto, N., et al.. (2001). Management of an olive crop in a semiarid environment using sown or resident leguminous covers. DIGITAL.CSIC (Spanish National Research Council (CSIC)). 419–423. 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.

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