D.W. Ross

1.4k total citations · 1 hit paper
24 papers, 1.0k citations indexed

About

D.W. Ross is a scholar working on Animal Science and Zoology, Genetics and Agronomy and Crop Science. According to data from OpenAlex, D.W. Ross has authored 24 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Animal Science and Zoology, 10 papers in Genetics and 6 papers in Agronomy and Crop Science. Recurrent topics in D.W. Ross's work include Meat and Animal Product Quality (16 papers), Genetic and phenotypic traits in livestock (10 papers) and Animal Nutrition and Physiology (7 papers). D.W. Ross is often cited by papers focused on Meat and Animal Product Quality (16 papers), Genetic and phenotypic traits in livestock (10 papers) and Animal Nutrition and Physiology (7 papers). D.W. Ross collaborates with scholars based in United Kingdom, New Zealand and Brazil. D.W. Ross's co-authors include R. Roehe, E.A. Navajas, J. J. Hyslop, R.I. Richardson, G. Simm, I. M. Nevison, David J. Roberts, S.A. Edwards, A.B. Lawrence and Suzanne Jarvis and has published in prestigious journals such as Applied Energy, PLoS Genetics and Journal of Animal Science.

In The Last Decade

D.W. Ross

24 papers receiving 975 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Bovine Host Genetic Variation Influences Rumen Microbial Methane Production with Best Selection Criterion for Low Methane Emitting and Efficiently Feed Converting Hosts Based on Metagenomic Gene Abundance

2016 240 citations R. Roehe, R.J. Dewhurst et al. PLoS Genetics profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
D.W. Ross United Kingdom	14	597	373	291	285	151	24	1.0k
Severiano Silva Portugal	19	730 1.2×	305 0.8×	320 1.1×	191 0.7×	123 0.8×	77	1.2k
J. J. Hyslop United Kingdom	17	437 0.7×	404 1.1×	201 0.7×	161 0.6×	121 0.8×	54	790
D.W. Pethick Australia	18	929 1.6×	222 0.6×	350 1.2×	169 0.6×	37 0.2×	56	1.1k
D.L. De Brabander Belgium	18	411 0.7×	703 1.9×	304 1.0×	135 0.5×	30 0.2×	54	1.0k
F. Abeni Italy	18	628 1.1×	430 1.2×	256 0.9×	303 1.1×	32 0.2×	53	1.1k
V. Fedele Italy	16	362 0.6×	395 1.1×	222 0.8×	165 0.6×	21 0.1×	31	907
C. Castríllo Spain	25	418 0.7×	1.1k 2.9×	374 1.3×	184 0.6×	21 0.1×	80	1.5k
A. A. K. Salama Spain	22	735 1.2×	672 1.8×	347 1.2×	261 0.9×	18 0.1×	71	1.3k
T. H. Montgomery United States	15	558 0.9×	234 0.6×	181 0.6×	201 0.7×	16 0.1×	24	799
Bülent Ekiz Türkiye	20	826 1.4×	414 1.1×	596 2.0×	174 0.6×	11 0.1×	109	1.2k

Countries citing papers authored by D.W. Ross

Since Specialization

Citations

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

Fields of papers citing papers by D.W. Ross

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D.W. Ross. 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 D.W. Ross. The network helps show where D.W. Ross may publish in the future.

Co-authorship network of co-authors of D.W. Ross

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

All Works

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20 of 20 papers shown

Gomes, Marina de Nadai Bonin, Saulo da Luz e Silva, L. Bünger, et al.. (2020). Predicting the shear value and intramuscular fat in meat from Nellore cattle using Vis-NIR spectroscopy. Meat Science. 163. 108077–108077. 25 indexed citations

Gomes, Marina de Nadai Bonin, Victor Breno Pedrosa, Saulo da Luz e Silva, et al.. (2020). Genetic parameters associated with meat quality of Nellore cattle at different anatomical points of longissimus: Brazilian standards. Meat Science. 171. 108281–108281. 16 indexed citations

Burns, S. J., et al.. (2017). Exploring multi-objective trade-offs in the design space of a waste heat recovery system. Applied Energy. 195. 114–124. 7 indexed citations

Roehe, R., R.J. Dewhurst, Carol-Anne Duthie, et al.. (2016). Bovine Host Genetic Variation Influences Rumen Microbial Methane Production with Best Selection Criterion for Low Methane Emitting and Efficiently Feed Converting Hosts Based on Metagenomic Gene Abundance. PLoS Genetics. 12(2). e1005846–e1005846. 240 indexed citations breakdown →

Hunt, Ian, et al.. (2016). Optimising a Waste Heat Recovery System using Multi-Objective Evolutionary Algorithm. Research Output (Edinburgh Napier University). 913–920. 2 indexed citations

Troy, Shane M., Carol-Anne Duthie, D.W. Ross, et al.. (2015). A comparison of methane emissions from beef cattle measured using methane hoods with those measured using respiration chambers. Animal Feed Science and Technology. 211. 227–240. 14 indexed citations

Chagunda, M.G.G., D.W. Ross, John Rooke, et al.. (2013). Measurement of enteric methane from ruminants using a hand-held laser methane detector. Acta Agriculturae Scandinavica Section A – Animal Science. 63(2). 68–75. 36 indexed citations

Turner, Simon P., E.A. Navajas, J. J. Hyslop, et al.. (2011). Associations between response to handling and growth and meat quality in frequently handled Bos taurus beef cattle1. Journal of Animal Science. 89(12). 4239–4248. 65 indexed citations

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

10.

Prieto, N., D.W. Ross, E.A. Navajas, et al.. (2010). Online prediction of fatty acid profiles in crossbred Limousin and Aberdeen Angus beef cattle using near infrared reflectance spectroscopy. animal. 5(1). 155–165. 36 indexed citations

11.

Navajas, E.A., R.I. Richardson, A.V. Fisher, et al.. (2010). Predicting beef carcass composition using tissue weights of a primal cut assessed by computed tomography. animal. 4(11). 1810–1817. 12 indexed citations

12.

Lambe, N.R., D.W. Ross, E.A. Navajas, et al.. (2010). The prediction of carcass composition and tissue distribution in beef cattle using ultrasound scanning at the start and/or end of the finishing period. Livestock Science. 131(2-3). 193–202. 16 indexed citations

13.

Prieto, N., D.W. Ross, E.A. Navajas, et al.. (2010). Prediction of beef carcass and selected primal subcutaneous fat yields using data from images captured on-line in abattoir. Advances in Animal Biosciences. 1(1). 285–285. 1 indexed citations

14.

Craigie, C., D.W. Ross, C. A. Maltin, et al.. (2010). The relationship between beef quality and carcass quality attributes measured under commercial conditions. Advances in Animal Biosciences. 1(1). 129–129. 2 indexed citations

15.

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

16.

Navajas, E.A., C. A. Glasbey, A.V. Fisher, et al.. (2009). Assessing beef carcass tissue weights using computed tomography spirals of primal cuts. Meat Science. 84(1). 30–38. 17 indexed citations

17.

Prieto, N., D.W. Ross, E.A. Navajas, et al.. (2009). On-line application of visible and near infrared reflectance spectroscopy to predict chemical–physical and sensory characteristics of beef quality. Meat Science. 83(1). 96–103. 79 indexed citations

18.

Navajas, E.A., R.I. Richardson, C. A. Glasbey, et al.. (2009). Associations between beef density by X-ray computed tomography, intramuscular fat and fatty acid composition: preliminary results. Proceedings of the British Society of Animal Science. 2009. 117–117. 1 indexed citations

19.

Prieto, N., D.W. Ross, E.A. Navajas, et al.. (2009). On-line prediction of the fatty acid content of beef meat by near infrared reflectance spectroscopy. Proceedings of the British Society of Animal Science. 2009. 116–116. 1 indexed citations

20.

Baxter, Emma, Suzanne Jarvis, Richard B. D’Eath, et al.. (2008). Investigating the behavioural and physiological indicators of neonatal survival in pigs. Theriogenology. 69(6). 773–783. 237 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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