D. G. Butler

581 citations
13 papers · 408 indexed · h-index 8
Topics
Genetics and Plant Breeding (7 papers)Wheat and Barley Genetics and Pathology (4 papers)Agricultural pest management studies (3 papers)
Journals
Agricultural and Forest MeteorologyAustralian Journal of Agricultural ResearchAustralian Journal of Experimental Agriculture
Partner nations
Australia

In The Last Decade

D. G. Butler

13 papers receiving 372 citations

Peers

D. G. Butler
Comparison fields: 5 of 30
  • Plant Science 363
  • Genetics 181
  • Agronomy and Crop Science 161
  • Ecology, Evolution, Behavior and Systematics 80
  • Global and Planetary Change 30
Replace Jorgelina Cárcova with:
Jorgelina Cárcova Argentina
Jessica Hyles Australia
M. L. Peterson United States
Thomas C. Barker United States
C. S. Moore United Kingdom
L. L. Carrigan United States
M. Derieux France
Yukiko Naruoka United States
Qiuqian Hu China
IA Dawson Australia
D. G. Butler relative to Jorgelina Cárcova Argentina Jorgelina Cárcova's profile →
Citations per field
00.5×3.2×
Jorgelina Cárcova · 1×
Citations per year

Countries citing papers authored by D. G. Butler

Since Specialization
Citations

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

Fields of papers citing papers by D. G. Butler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. G. Butler

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

All Works

13 of 13 papers shown
#WorkIndexed citations
1
ASReml-R estimates variance components under a general linear mixed model by residual maximum likelihood (REML)
6
2 85
3 9
4 6
5 12
6 138
7 65
8
Integrating physiological understanding and plant breeding via crop modelling and optimization.
20
9 4
10 9
11 4
12 44
13 6

About D. G. Butler

D. G. Butler is a scholar working on Plant Science, Agronomy and Crop Science and Genetics, having authored 13 papers that have together received 408 indexed citations. Recurring topics across this work include Genetics and Plant Breeding (7 papers), Wheat and Barley Genetics and Pathology (4 papers) and Agricultural pest management studies (3 papers). The work is most often cited by research in Agronomy and Crop Science (161 citations), Plant Science (363 citations) and Genetics (181 citations). D. G. Butler has collaborated with scholars based in Australia. Frequent co-authors include Mark Cooper, Scott Chapman, Graeme Hammer, R. G. Henzell, P. S. Brennan, DE Byth, RJ Redden, I. H. DeLacy, Holger Meinke and P. G. Allsopp. Their work appears in journals such as Agricultural and Forest Meteorology, Australian Journal of Agricultural Research and Australian Journal of Experimental Agriculture.

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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