J.E. Pryce

12.1k total citations · 1 hit paper
262 papers, 8.9k citations indexed

About

J.E. Pryce is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology. According to data from OpenAlex, J.E. Pryce has authored 262 papers receiving a total of 8.9k indexed citations (citations by other indexed papers that have themselves been cited), including 221 papers in Genetics, 150 papers in Agronomy and Crop Science and 73 papers in Animal Science and Zoology. Recurrent topics in J.E. Pryce's work include Genetic and phenotypic traits in livestock (219 papers), Reproductive Physiology in Livestock (102 papers) and Genetic Mapping and Diversity in Plants and Animals (80 papers). J.E. Pryce is often cited by papers focused on Genetic and phenotypic traits in livestock (219 papers), Reproductive Physiology in Livestock (102 papers) and Genetic Mapping and Diversity in Plants and Animals (80 papers). J.E. Pryce collaborates with scholars based in Australia, United Kingdom and New Zealand. J.E. Pryce's co-authors include Ben J. Hayes, Michael E. Goddard, M. Haile‐Mariam, M.P. Coffey, R.F. Veerkamp, G. Simm, Sunduimijid Bolormaa, M.D. Royal, D.P. Berry and E. Wall and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

J.E. Pryce

252 papers receiving 8.5k citations

Hit Papers

align trajectories sort by overperformance

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.

Genetics and genomics of reproductive performance in dairy and beef cattle

2014 306 citations E. Wall, J.E. Pryce et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
J.E. Pryce	7.1k	4.7k	2.6k	1.2k	833	262	8.9k
R.F. Veerkamp	8.6k 1.2×	5.3k 1.1×	2.7k 1.1×	1.8k 1.5×	1.1k 1.3×	290	10.2k
John B. Cole	6.1k 0.9×	2.9k 0.6×	1.8k 0.7×	1.3k 1.1×	649 0.8×	186	7.7k
F. Miglior	5.0k 0.7×	4.0k 0.8×	2.0k 0.8×	572 0.5×	991 1.2×	260	6.6k
K.A. Weigel	7.7k 1.1×	3.9k 0.8×	2.0k 0.8×	2.7k 2.3×	817 1.0×	254	9.3k
Flávio S. Schenkel	8.1k 1.1×	3.1k 0.7×	2.4k 0.9×	2.1k 1.8×	777 0.9×	351	10.0k
Nicolas Gengler	4.4k 0.6×	3.3k 0.7×	2.8k 1.1×	599 0.5×	752 0.9×	359	6.4k
John Woolliams	7.9k 1.1×	2.5k 0.5×	1.6k 0.6×	2.6k 2.3×	749 0.9×	366	10.3k
Dorian J. Garrick	7.9k 1.1×	2.1k 0.4×	2.2k 0.8×	3.0k 2.6×	787 0.9×	318	10.2k
J.R. Roche	4.0k 0.6×	6.3k 1.3×	2.0k 0.8×	377 0.3×	1.2k 1.5×	211	8.2k
G.R. Wiggans	8.3k 1.2×	3.6k 0.8×	1.6k 0.6×	2.6k 2.3×	629 0.8×	225	9.2k

Countries citing papers authored by J.E. Pryce

Since Specialization

Citations

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

Fields of papers citing papers by J.E. Pryce

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J.E. Pryce

This figure shows the co-authorship network connecting the top 25 collaborators of J.E. Pryce. A scholar is included among the top collaborators of J.E. Pryce 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.E. Pryce. J.E. Pryce 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

Sheedy, David B., H.M. Golder, Simone Rochfort, et al.. (2026). A large, multisite investigation into the lipidomics of survival in dairy cows. Journal of Dairy Science. 109(3). 2969–2988.

Sheedy, David B., H.M. Golder, S.C. García, et al.. (2025). Associations among body condition score, body weight, and serum biochemistry in dairy cows. Journal of Dairy Science. 108(4). 4131–4148.

Reimer, Christian, Zengting Liu, J.E. Pryce, et al.. (2025). Sequence-based genome-wide association study and fine-mapping in German Holstein reveal new quantitative trait loci for health traits. Journal of Dairy Science. 108(7). 7310–7328.

Xiang, Ruidong, Edmond J. Breen, Sunduimijid Bolormaa, et al.. (2025). Integrating extensive functional annotations and multiomics of cattle enhances climate resilience prediction and mapping. Proceedings of the National Academy of Sciences. 122(49). e2514736122–e2514736122.

Haile‐Mariam, M., et al.. (2024). Optimizing genetic diversity in Australian Holsteins and Jerseys: A comparative analysis of whole-genome and regional inbreeding depression effects. Journal of Dairy Science. 108(3). 2658–2668. 1 indexed citations

Khansefid, Majid, et al.. (2023). Genome-wide assessment and mapping of inbreeding depression identifies candidate genes associated with semen traits in Holstein bulls. BMC Genomics. 24(1). 230–230. 13 indexed citations

Bolormaa, Sunduimijid, M. Haile‐Mariam, Leah C. Marett, et al.. (2023). Use of dry-matter intake recorded at multiple time periods during lactation increases the accuracy of genomic prediction for dry-matter intake and residual feed intake in dairy cattle. Animal Production Science. 63(11). 1113–1125. 1 indexed citations

Grelet, Clément, Phuong N. Ho, J.E. Pryce, et al.. (2021). Multiple Country Approach to Improve the Test-Day Prediction of Dairy Cows’ Dry Matter Intake. Animals. 11(5). 1316–1316. 12 indexed citations

Manzanilla-Pech, C.I.V., Peter Løvendahl, Gareth F. Difford, et al.. (2021). Breeding for reduced methane emission and feed-efficient Holstein cows: An international response. Journal of Dairy Science. 104(8). 8983–9001. 70 indexed citations

10.

Grelet, Clément, Phuong N. Ho, J.E. Pryce, et al.. (2021). Validation of Dairy Cow Bodyweight Prediction Using Traits Easily Recorded by Dairy Herd Improvement Organizations and Its Potential Improvement Using Feature Selection Algorithms. Animals. 11(5). 1288–1288. 13 indexed citations

11.

MacLeod, Iona M., Amanda J. Chamberlain, Christy J. Vander Jagt, et al.. (2020). Mitochondrial protein gene expression and the oxidative phosphorylation pathway associated with feed efficiency and energy balance in dairy cattle. Journal of Dairy Science. 104(1). 575–587. 19 indexed citations

12.

Pryce, J.E., et al.. (2018). Cost benefit analysis of a dairy genomic reference population. Proceedings of the World Congress on Genetics Applied to Livestock Production. 200. 2 indexed citations

13.

Pryce, J.E., et al.. (2017). A Comparison of the Economic Value for Enteric Methane Emissions with other Biological Traits Associated With Dairy Cows. 7 indexed citations

14.

Heringstad, B., C. Egger-Danner, K.F. Stock, et al.. (2017). Genetic evaluation of claw health – challenges and recommendations. Open Repository and Bibliography (University of Liège). 1 indexed citations

15.

Pryce, J.E., et al.. (2016). American Research Journal of Agriculture. Nottingham ePrints (University of Nottingham). 2(1). 13 indexed citations

16.

Pryce, J.E.. (2014). World Trends in Dairy Cow Fertility. 9 indexed citations

17.

Stock, K.F., John B. Cole, J.E. Pryce, et al.. (2013). Standardization of health data. ICAR guidelines including health key. Open Repository and Bibliography (University of Liège). 18 indexed citations

18.

Bolormaa, Sunduimijid, J.E. Pryce, Kathryn E. Kemper, et al.. (2013). Detection of quantitative trait loci in Bos indicus and Bos taurus cattle using genome-wide association studies. Genetics Selection Evolution. 45(1). 43–43. 47 indexed citations

19.

Bryant, J.R., N. López‐Villalobos, J.E. Pryce, C. W. Holmes, & D. L. Johnson. (2007). Quantifying the effect of thermal environment on production traits in three breeds of dairy cattle in New Zealand. New Zealand Journal of Agricultural Research. 50(3). 327–338. 69 indexed citations

20.

Bryant, J.R., N. López‐Villalobos, J.E. Pryce, C. W. Holmes, & D. L. Johnson. (2006). Reaction norms used to quantify the responses of New Zealand dairy cattle of mixed breeds to nutritional environment. New Zealand Journal of Agricultural Research. 49(4). 371–381. 19 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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