G. J. Greer

617 total citations
20 papers, 489 citations indexed

About

G. J. Greer is a scholar working on Genetics, Animal Science and Zoology and Agronomy and Crop Science. According to data from OpenAlex, G. J. Greer has authored 20 papers receiving a total of 489 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Genetics, 7 papers in Animal Science and Zoology and 7 papers in Agronomy and Crop Science. Recurrent topics in G. J. Greer's work include Genetic and phenotypic traits in livestock (15 papers), Ruminant Nutrition and Digestive Physiology (6 papers) and Genetic Mapping and Diversity in Plants and Animals (5 papers). G. J. Greer is often cited by papers focused on Genetic and phenotypic traits in livestock (15 papers), Ruminant Nutrition and Digestive Physiology (6 papers) and Genetic Mapping and Diversity in Plants and Animals (5 papers). G. J. Greer collaborates with scholars based in New Zealand, Spain and Uruguay. G. J. Greer's co-authors include John C. McEwan, W. E. Bain, K. G. Dodds, Allan M. Crawford, P. F. Fennessy, J. M. Everett-Hincks, S. M. Hickey, Theresa Wilson, P. D. Johnstone and Orla M. Keane and has published in prestigious journals such as Bone, Journal of Animal Science and BMC Genomics.

In The Last Decade

G. J. Greer

20 papers receiving 472 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
G. J. Greer New Zealand 12 307 153 130 127 97 20 489
Nigel P. Jay New Zealand 11 248 0.8× 118 0.8× 181 1.4× 124 1.0× 116 1.2× 19 499
Sarah Laguna Conceição Meirelles Brazil 14 356 1.2× 156 1.0× 39 0.3× 112 0.9× 76 0.8× 41 538
Md Azharul Hoque Bangladesh 14 471 1.5× 309 2.0× 87 0.7× 211 1.7× 38 0.4× 84 732
A. Tomás Spain 13 379 1.2× 145 0.9× 43 0.3× 77 0.6× 88 0.9× 26 530
Erhard Kallweit Germany 13 166 0.5× 219 1.4× 148 1.1× 124 1.0× 79 0.8× 70 617
B. J. McLeod New Zealand 14 225 0.7× 84 0.5× 73 0.6× 328 2.6× 141 1.5× 48 671
J. Rátky Hungary 19 315 1.0× 145 0.9× 183 1.4× 344 2.7× 209 2.2× 67 1.1k
Lucas Lima Verardo Brazil 13 398 1.3× 151 1.0× 36 0.3× 112 0.9× 109 1.1× 41 539
C. Grøndahl Denmark 21 123 0.4× 28 0.2× 92 0.7× 121 1.0× 267 2.8× 41 1.0k
María Consuelo Mura Italy 19 397 1.3× 188 1.2× 34 0.3× 395 3.1× 95 1.0× 65 891

Countries citing papers authored by G. J. Greer

Since Specialization
Citations

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

Fields of papers citing papers by G. J. Greer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. J. Greer

This figure shows the co-authorship network connecting the top 25 collaborators of G. J. Greer. A scholar is included among the top collaborators of G. J. Greer 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 G. J. Greer. G. J. Greer 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.
Rowe, Suzanne J., S. M. Hickey, G. J. Greer, et al.. (2022). Can we have our steak and eat it: The impact of breeding for lowered environmental impact on yield and meat quality in sheep. Frontiers in Genetics. 13. 911355–911355. 3 indexed citations
2.
Hickey, S. M., W. E. Bain, Timothy P. Bilton, et al.. (2022). Impact of breeding for reduced methane emissions in New Zealand sheep on maternal and health traits. Frontiers in Genetics. 13. 910413–910413. 7 indexed citations
3.
McRae, Kathryn M., S. M. Hickey, G. J. Greer, et al.. (2022). 41. The impact of selection for divergence in methane emissions on alimentary tract measures of eight-month-old sheep. 211–214. 2 indexed citations
4.
Jonker, Arjan, S. M. Hickey, Suzanne J. Rowe, et al.. (2018). Genetic parameters of methane emissions determined using portable accumulation chambers in lambs and ewes grazing pasture and genetic correlations with emissions determined in respiration chambers1. Journal of Animal Science. 96(8). 3031–3042. 50 indexed citations
5.
Everett-Hincks, J. M., et al.. (2014). Genetic parameters for lamb birth weight, survival and death risk traits 1. Journal of Animal Science. 92(7). 2885–2895. 56 indexed citations
6.
Johnson, Patricia L., K. G. Dodds, W. E. Bain, et al.. (2009). Investigations into the GDF8 g+6723G-A polymorphism in New Zealand Texel sheep1. Journal of Animal Science. 87(6). 1856–1864. 58 indexed citations
7.
McLean, Neil J., Patricia L. Johnson, W. E. Bain, G. J. Greer, & K. G. Dodds. (2009). Genetic parameters for colour stability of chilled lamb.. 69. 220–222. 4 indexed citations
8.
Bain, W. E., G. J. Greer, K. G. Dodds, et al.. (2008). BRIEF COMMUNICATION: Effect of MyoMAX® on carcass lean and fat. 2 indexed citations
9.
French, Michelle C., R. P. Littlejohn, G. J. Greer, et al.. (2006). Growth hormone and ghrelin receptor genes are differentially expressed between genetically lean and fat selection lines of sheep. Journal of Animal Science. 84(2). 324–331. 19 indexed citations
10.
Crawford, Allan M., Korena A. Paterson, K. G. Dodds, et al.. (2006). Discovery of quantitative trait loci for resistance to parasitic nematode infection in sheep: I. Analysis of outcross pedigrees. BMC Genomics. 7(1). 178–178. 73 indexed citations
11.
Keane, Orla M., Amonida Zadissa, Theresa Wilson, et al.. (2006). Gene expression profiling of Naïve sheep genetically resistant and susceptible to gastrointestinal nematodes. BMC Genomics. 7(1). 81 indexed citations
12.
Campbell, A. W., W. E. Bain, Allan F. McRae, et al.. (2003). Bone density in sheep: genetic variation and quantitative trait loci localisation. Bone. 33(4). 540–548. 34 indexed citations
13.
Campbell, A. W., W. E. Bain, Allan F. McRae, et al.. (2002). DETECTION OF QUANTITATIVE TRAIT LOCI FOR BONE MINERAL DENSITY IN COOPWORTH SHEEP. 0–4. 1 indexed citations
14.
McEwan, John C., C. A. Morris, P. F. Fennessy, et al.. (2001). Selection for high or low backfat depth in Coopworth sheep: breeding-ewe traits. Animal Science. 73(2). 241–252. 13 indexed citations
15.
Greer, G. J., et al.. (2000). Lamb survival traits in Coopworth sheep selected for high or low backfat depth. 60. 61–64. 3 indexed citations
16.
Broad, T. E., B. C. Glass, G. J. Greer, et al.. (2000). Search for a locus near to myostatin that increases muscling in Texel sheep in New Zealand. 60. 110–112. 28 indexed citations
17.
Morris, C. A., John C. McEwan, P. F. Fennessy, et al.. (1997). Selection for high or low backfat depth in Coopworth sheep: juvenile traits. Animal Science. 65(1). 93–103. 27 indexed citations
18.
Fennessy, P. F., G. J. Greer, W. E. Bain, & P. D. Johnstone. (1993). Progeny test of ram lambs selected for low ultrasonic backfat thickness or high post-weaning growth rate. Livestock Production Science. 33(1-2). 105–118. 12 indexed citations
19.
Fennessy, P. F., W. E. Bain, G. J. Greer, & P. D. Johnstone. (1992). Carcass characteristics of progeny from ram lambs selected for high or low ultrasonic backfat thickness. New Zealand Journal of Agricultural Research. 35(2). 177–183. 11 indexed citations
20.
Fennessy, P. F., John C. McEwan, E.A. Lord, et al.. (1990). Effect of Cimaterol implants on lamb growth and carcass traits. New Zealand Journal of Agricultural Research. 33(3). 413–427. 5 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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