Kim M. Moore

1.2k total citations
9 papers, 819 citations indexed

About

Kim M. Moore is a scholar working on Plant Science, Inorganic Chemistry and Molecular Biology. According to data from OpenAlex, Kim M. Moore has authored 9 papers receiving a total of 819 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Plant Science, 5 papers in Inorganic Chemistry and 3 papers in Molecular Biology. Recurrent topics in Kim M. Moore's work include Peanut Plant Research Studies (9 papers), Agricultural pest management studies (6 papers) and Coconut Research and Applications (5 papers). Kim M. Moore is often cited by papers focused on Peanut Plant Research Studies (9 papers), Agricultural pest management studies (6 papers) and Coconut Research and Applications (5 papers). Kim M. Moore collaborates with scholars based in United States, China and India. Kim M. Moore's co-authors include D. A. Knauft, Sook Jung, G L Powell, Marcos A. Gimenes, Gary Kochert, Catalina Romero Lopes, H. T. Stalker, Albert G. Abbott, Mili Patel and D. W. Gorbet and has published in prestigious journals such as Journal of Agricultural and Food Chemistry, Theoretical and Applied Genetics and American Journal of Botany.

In The Last Decade

Kim M. Moore

9 papers receiving 751 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kim M. Moore United States	9	749	413	349	132	37	9	819
Yogendra Khedikar India	10	467 0.6×	186 0.5×	152 0.4×	41 0.3×	41 1.1×	14	535
Arturo López‐Villalobos Canada	7	298 0.4×	59 0.1×	344 1.0×	276 2.1×	13 0.4×	11	521
W. R. Thornley United States	12	201 0.3×	48 0.1×	118 0.3×	23 0.2×	128 3.5×	17	364
Kunkun Zhao China	11	301 0.4×	54 0.1×	167 0.5×	12 0.1×	12 0.3×	30	401
Quanxi Sun China	13	357 0.5×	52 0.1×	247 0.7×	28 0.2×	4 0.1×	34	444
Myoung Ryoul Park South Korea	11	430 0.6×	43 0.1×	196 0.6×	7 0.1×	11 0.3×	21	536
Sarvamangala Cholin India	8	476 0.6×	223 0.5×	125 0.4×	4 0.0×	26 0.7×	41	506
Longhua Zhou China	11	313 0.4×	12 0.0×	283 0.8×	112 0.8×	5 0.1×	28	457
Zhanji Liu China	11	261 0.3×	10 0.0×	181 0.5×	59 0.4×	11 0.3×	22	345
P. Montalbini Italy	16	377 0.5×	23 0.1×	252 0.7×	7 0.1×	7 0.2×	36	528

Countries citing papers authored by Kim M. Moore

Since Specialization

Citations

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

Fields of papers citing papers by Kim M. Moore

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kim M. Moore. 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 Kim M. Moore. The network helps show where Kim M. Moore may publish in the future.

Co-authorship network of co-authors of Kim M. Moore

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

All Works

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9 of 9 papers shown

Wang, Hui, Pawan Khera, Bingyan Huang, et al.. (2015). Analysis of genetic diversity and population structure of peanut cultivars and breeding lines from China, India and the US using simple sequence repeat markers. Journal of Integrative Plant Biology. 58(5). 452–465. 22 indexed citations

Patel, Mili, Sook Jung, Kim M. Moore, et al.. (2004). High-oleate peanut mutants result from a MITE insertion into the FAD2 gene. Theoretical and Applied Genetics. 108(8). 1492–1502. 93 indexed citations

Pattee, H. E., T. G. Isleib, Kim M. Moore, Daniel W. Gorbet, & Francis G. Giesbrecht. (2002). Effect of High-Oleic Trait and Paste Storage Variables on Sensory Attribute Stability of Roasted Peanuts. Journal of Agricultural and Food Chemistry. 50(25). 7366–7370. 28 indexed citations

Pattee, H. E., T. G. Isleib, Daniel W. Gorbet, et al.. (2002). Effect of the High-Oleic Trait on Roasted Peanut Flavor in Backcross-Derived Breeding Lines. Journal of Agricultural and Food Chemistry. 50(25). 7362–7365. 14 indexed citations

Jung, Sook, G L Powell, Kim M. Moore, & Albert G. Abbott. (2000). The high oleate trait in the cultivated peanut [Arachis hypogaea L.]. II. Molecular basis and genetics of the trait. Molecular and General Genetics MGG. 263(5). 806–811. 103 indexed citations

Jung, Sook, Mili Patel, Florence Teulé, et al.. (2000). The high oleate trait in the cultivated peanut [Arachis hypogaea L.]. I. Isolation and characterization of two genes encoding microsomal oleoyl-PC desaturases. Molecular and General Genetics MGG. 263(5). 796–805. 122 indexed citations

Kochert, Gary, et al.. (1996). RFLP AND CYTOGENETIC EVIDENCE ON THE ORIGIN AND EVOLUTION OF ALLOTETRAPLOID DOMESTICATED peanut, Arachis hypogaea (Leguminosae). American Journal of Botany. 83(10). 1282–1291. 250 indexed citations

Knauft, D. A., Kim M. Moore, & D. W. Gorbet. (1993). Further Studies On The Inheritance Of Fatty Acid Composition In Peanut1. Peanut Science. 20(2). 74–76. 50 indexed citations

Moore, Kim M. & D. A. Knauft. (1989). The Inheritance of High Oleic Acid in Peanut. Journal of Heredity. 80(3). 252–253. 137 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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