C. A. Kimbeng

1.4k total citations
69 papers, 976 citations indexed

About

C. A. Kimbeng is a scholar working on Plant Science, Surgery and Biomedical Engineering. According to data from OpenAlex, C. A. Kimbeng has authored 69 papers receiving a total of 976 indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Plant Science, 32 papers in Surgery and 22 papers in Biomedical Engineering. Recurrent topics in C. A. Kimbeng's work include Sugarcane Cultivation and Processing (54 papers), Natural Products and Biological Research (32 papers) and Biofuel production and bioconversion (22 papers). C. A. Kimbeng is often cited by papers focused on Sugarcane Cultivation and Processing (54 papers), Natural Products and Biological Research (32 papers) and Biofuel production and bioconversion (22 papers). C. A. Kimbeng collaborates with scholars based in United States, South Africa and Australia. C. A. Kimbeng's co-authors include K. A. Gravois, John C. Veremis, J. W. Hoy, M. J. Pontif, Niranjan Baisakh, K. P. Bischoff, Anna L. Hale, Jie Arro, T. E. Reagan and Marvellous Zhou and has published in prestigious journals such as Scientific Reports, Frontiers in Plant Science and Theoretical and Applied Genetics.

In The Last Decade

C. A. Kimbeng

63 papers receiving 913 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
C. A. Kimbeng United States	20	911	347	346	111	110	69	976
S. B. Milligan United States	16	764 0.8×	157 0.5×	323 0.9×	72 0.6×	55 0.5×	36	802
Luciana Rossini Pinto Brazil	19	1.0k 1.1×	449 1.3×	312 0.9×	174 1.6×	30 0.3×	61	1.1k
Neil C. Glynn United States	20	1.0k 1.1×	327 0.9×	214 0.6×	163 1.5×	24 0.2×	55	1.1k
Zuhu Deng China	16	550 0.6×	177 0.5×	113 0.3×	148 1.3×	18 0.2×	54	614
K. P. Bischoff United States	11	517 0.6×	194 0.6×	192 0.6×	58 0.5×	77 0.7×	19	550
Jean-Yves Hoarau France	14	935 1.0×	509 1.5×	298 0.9×	65 0.6×	18 0.2×	29	968
Thiago G. Marconi United States	13	464 0.5×	199 0.6×	143 0.4×	58 0.5×	12 0.1×	22	522
A. Selvi India	16	764 0.8×	345 1.0×	262 0.8×	147 1.3×	20 0.2×	35	828
K. M. Oliveira Brazil	13	763 0.8×	346 1.0×	242 0.7×	80 0.7×	40 0.4×	14	818
B. J. Croft Australia	16	674 0.7×	142 0.4×	111 0.3×	76 0.7×	17 0.2×	68	710

Countries citing papers authored by C. A. Kimbeng

Since Specialization

Citations

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

Fields of papers citing papers by C. A. Kimbeng

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C. A. Kimbeng. 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 C. A. Kimbeng. The network helps show where C. A. Kimbeng may publish in the future.

Co-authorship network of co-authors of C. A. Kimbeng

This figure shows the co-authorship network connecting the top 25 collaborators of C. A. Kimbeng. A scholar is included among the top collaborators of C. A. Kimbeng 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 C. A. Kimbeng. C. A. Kimbeng 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

Shahi, Dipendra, James Todd, K. A. Gravois, et al.. (2024). Exploiting historical agronomic data to develop genomic prediction strategies for early clonal selection in the Louisiana sugarcane variety development program. The Plant Genome. 18(1). e20545–e20545. 1 indexed citations

Uchimiya, Minori, et al.. (2024). Freeze response indicators in sugarcane (Saccharum spp. hybrids). Micron. 188. 103726–103726. 2 indexed citations

Jongrungklang, Nakorn, et al.. (2023). Analysis of sugarcane × Saccharum spontaneum progeny for sugar and biomass traits. Agronomy Journal. 116(1). 18–35.

Kimbeng, C. A., et al.. (2023). Phenotypic plasticity and genetic trends in the past 30 years of sugarcane genetic improvement in Louisiana. Crop Science. 64(1). 44–54. 4 indexed citations

Uchimiya, Minori, et al.. (2023). Early Detection Cold Markers to Expedite the Sugarcane (Saccharum spp. Hybrids) Breeding. ACS Agricultural Science & Technology. 3(12). 1117–1124. 4 indexed citations

Pontif, M. J., C. A. Kimbeng, K. A. Gravois, et al.. (2022). Registration of ‘L 12‐201’ sugarcane. Journal of Plant Registrations. 16(2). 363–377. 9 indexed citations

Hale, Anna L., James Todd, K. A. Gravois, et al.. (2021). Sugarcane Breeding Programs in the USA. Sugar Tech. 24(1). 97–111. 17 indexed citations

Parco, Arnold, Anna L. Hale, M. J. Pontif, et al.. (2020). An enriched sugarcane diversity panel for utilization in genetic improvement of sugarcane. Scientific Reports. 10(1). 13390–13390. 11 indexed citations

Verma, Mohit, et al.. (2018). Genome-wide association mapping identifies markers associated with cane yield components and sucrose traits in the Louisiana sugarcane core collection. Genomics. 111(6). 1794–1801. 35 indexed citations

10.

Gutiérrez, Andrés, J. W. Hoy, C. A. Kimbeng, & Niranjan Baisakh. (2018). Identification of Genomic Regions Controlling Leaf Scald Resistance in Sugarcane Using a Bi-parental Mapping Population and Selective Genotyping by Sequencing. Frontiers in Plant Science. 9. 877–877. 20 indexed citations

11.

Kimbeng, C. A., et al.. (2015). Developing energycane varieties for the bioenergy and bioproducts industry.. 58(2). 10–11. 1 indexed citations

12.

Kimbeng, C. A., et al.. (2015). Performance of energycane varieties for power generation and biofuel production.. 58(2). 16–17.

13.

Barbosa, Márcio Henrique Pereira, et al.. (2014). Relationships between methods of variety adaptability and stability in sugarcane. Genetics and Molecular Research. 13(2). 4216–4225. 12 indexed citations

14.

Pan, Yong‐Bao, et al.. (2011). Genetic analysis of the sugarcane (Saccharum spp.) cultivar ‘LCP 85-384’. I. Linkage mapping using AFLP, SSR, and TRAP markers. Theoretical and Applied Genetics. 123(1). 77–93. 47 indexed citations

15.

Gravois, K. A., K. P. Bischoff, J. W. Hoy, et al.. (2009). Registration of ‘L 99‐233’ Sugarcane. Journal of Plant Registrations. 3(3). 248–252. 22 indexed citations

16.

Kimbeng, C. A., et al.. (2009). Genotype × environment interactions and resource allocation in sugarcane yield trials in the Rio Grande Valley region of Texas.. 29. 11–24. 24 indexed citations

17.

Kimbeng, C. A., et al.. (2008). Molecular Markers Associated with Resistance toAspergillus flavusin Maize Grain: QTL and Discriminant Analyses. Journal of New Seeds. 9(1). 1–18. 19 indexed citations

18.

Hale, Anna L., Mark W. Farnham, M. Ndambe Nzaramba, & C. A. Kimbeng. (2007). Heterosis for horticultural traits in Broccoli. Theoretical and Applied Genetics. 115(3). 351–360. 31 indexed citations

19.

Arro, Jie, et al.. (2006). Target Region Amplification Polymorphism (TRAP) for Assessing Genetic Diversity in Sugarcane Germplasm Collections. Crop Science. 46(1). 448–455. 88 indexed citations

20.

Kimbeng, C. A., T. A. McRae, M. C. Cox, & D. M. Hogarth. (2001). Optimising early generation selection in sugarcane breeding.. 488–494. 3 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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