Rita H. Mumm

2.1k total citations · 1 hit paper
32 papers, 1.3k citations indexed

About

Rita H. Mumm is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Rita H. Mumm has authored 32 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Plant Science, 17 papers in Genetics and 6 papers in Molecular Biology. Recurrent topics in Rita H. Mumm's work include Genetics and Plant Breeding (14 papers), Genetic Mapping and Diversity in Plants and Animals (13 papers) and Genetic and phenotypic traits in livestock (6 papers). Rita H. Mumm is often cited by papers focused on Genetics and Plant Breeding (14 papers), Genetic Mapping and Diversity in Plants and Animals (13 papers) and Genetic and phenotypic traits in livestock (6 papers). Rita H. Mumm collaborates with scholars based in United States, Kenya and South Africa. Rita H. Mumm's co-authors include Stephen P. Moose, J. W. Dudley, Xiaochun Sun, Kent D. Rausch, Edward S. Buckler, Jeffrey Ross‐Ibarra, Jinliang Yang, Katherine E. Guill, Michael D. McMullen and Sofiane Mezmouk and has published in prestigious journals such as Nature Genetics, PLoS ONE and PLANT PHYSIOLOGY.

In The Last Decade

Rita H. Mumm

31 papers receiving 1.2k citations

Hit Papers

Molecular Plant Breeding as the Foundation for 21st Centu... 2008 2026 2014 2020 2008 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rita H. Mumm United States 17 1.0k 513 312 175 82 32 1.3k
Tileye Feyissa Ethiopia 18 872 0.8× 366 0.7× 372 1.2× 221 1.3× 115 1.4× 127 1.2k
Shailendra Sharma India 20 1.4k 1.4× 476 0.9× 362 1.2× 192 1.1× 90 1.1× 71 1.7k
C T Hash India 16 1.1k 1.1× 706 1.4× 276 0.9× 417 2.4× 75 0.9× 43 1.4k
Asfaliza Ramli Malaysia 12 1.1k 1.0× 219 0.4× 315 1.0× 102 0.6× 83 1.0× 28 1.3k
Romesh Kumar Salgotra India 17 1.1k 1.1× 325 0.6× 370 1.2× 69 0.4× 81 1.0× 96 1.4k
Benjamin Wittkop Germany 22 946 0.9× 340 0.7× 644 2.1× 168 1.0× 59 0.7× 44 1.3k
Elena Benavente Spain 19 1.0k 1.0× 261 0.5× 227 0.7× 143 0.8× 63 0.8× 46 1.2k
Mulatu Geleta Sweden 24 1.2k 1.2× 519 1.0× 312 1.0× 285 1.6× 150 1.8× 92 1.6k
Aluízio Borém Brazil 24 1.5k 1.5× 362 0.7× 238 0.8× 262 1.5× 54 0.7× 130 1.8k
Ndiaga Cissé Senegal 28 2.1k 2.0× 248 0.5× 348 1.1× 341 1.9× 82 1.0× 81 2.3k

Countries citing papers authored by Rita H. Mumm

Since Specialization
Citations

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

Fields of papers citing papers by Rita H. Mumm

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rita H. Mumm. 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 Rita H. Mumm. The network helps show where Rita H. Mumm may publish in the future.

Co-authorship network of co-authors of Rita H. Mumm

This figure shows the co-authorship network connecting the top 25 collaborators of Rita H. Mumm. A scholar is included among the top collaborators of Rita H. Mumm 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 Rita H. Mumm. Rita H. Mumm 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.
Amombo, Erick, et al.. (2025). Enhancing Crop Nutrition in Arid and Semiarid Regions of Africa Through Genome Editing Using CRISPR /Cas. Food and Energy Security. 14(3). 1 indexed citations
2.
Gerrano, Abe Shegro, et al.. (2022). Expression of Nutritional Traits in Vegetable Cowpea Grown under Various South African Agro-Ecological Conditions. Plants. 11(11). 1422–1422. 3 indexed citations
3.
Riggins, Chance W. & Rita H. Mumm. (2021). Amaranths. Current Biology. 31(13). R834–R835. 4 indexed citations
4.
Mumm, Rita H. & Eric Yirenkyi Danquah. (2020). The African Plant Breeders of Tomorrow. African Journal of Food Agriculture Nutrition and Development. 19(5). 15116–15120.
5.
Jamnadass, Ramni, Rita H. Mumm, Iago Hale, et al.. (2020). Enhancing African orphan crops with genomics. Nature Genetics. 52(4). 356–360. 57 indexed citations
6.
Okello, David Kalule, et al.. (2020). Past, Present and Future Perspectives on Groundnut Breeding in Burkina Faso. Agronomy. 10(5). 704–704. 10 indexed citations
7.
Kandhola, Gurshagan, et al.. (2018). High-throughput, Microscale Protocol for the Analysis of Processing Parameters and Nutritional Qualities in Maize (<em>Zea mays</em> L.). Journal of Visualized Experiments. 1 indexed citations
8.
Sogbohossou, Dêêdi E. O., Enoch G. Achigan‐Dako, Patrick Maundu, et al.. (2018). A roadmap for breeding orphan leafy vegetable species: a case study of Gynandropsis gynandra (Cleomaceae). Horticulture Research. 5(1). 2–2. 52 indexed citations
9.
Yang, Jinliang, Sofiane Mezmouk, Andy Baumgarten, et al.. (2017). Incomplete dominance of deleterious alleles contributes substantially to trait variation and heterosis in maize. PLoS Genetics. 13(9). e1007019–e1007019. 121 indexed citations
10.
Baenziger, P. Stephen, et al.. (2017). Plant breeding and genetics: a paper in the series on The Need for Agricultural Innovation to Sustainably Feed the World by 2050.. 1 indexed citations
11.
Mumm, Rita H., et al.. (2017). Concentration of Beneficial Phytochemicals in Harvested Grain of U.S. Yellow Dent Maize (Zea mays L.) Germplasm. Journal of Agricultural and Food Chemistry. 65(38). 8311–8318. 11 indexed citations
12.
Sun, Xiaochun & Rita H. Mumm. (2016). Method to represent the distribution of QTL additive and dominance effects associated with quantitative traits in computer simulation. BMC Bioinformatics. 17(1). 73–73. 8 indexed citations
13.
Sun, Xiaochun & Rita H. Mumm. (2015). Optimized breeding strategies for multiple trait integration: III. Parameters for success in version testing. Molecular Breeding. 35(10). 201–201. 6 indexed citations
14.
Mumm, Rita H., Peter Goldsmith, Kent D. Rausch, & Hans H Stein. (2014). Land usage attributed to corn ethanol production in the United States: sensitivity to technological advances in corn grain yield, ethanol conversion, and co-product utilization. Biotechnology for Biofuels. 7(1). 61–61. 44 indexed citations
15.
Sun, Xiaochun, et al.. (2013). Optimized breeding strategies for multiple trait integration: II. Process efficiency in event pyramiding and trait fixation. Molecular Breeding. 33(1). 105–115. 21 indexed citations
16.
Sun, Xiaochun, et al.. (2013). Optimized breeding strategies for multiple trait integration: I. Minimizing linkage drag in single event introgression. Molecular Breeding. 33(1). 89–104. 39 indexed citations
17.
Sun, Xiaochun, Ping Ma, & Rita H. Mumm. (2012). Nonparametric Method for Genomics-Based Prediction of Performance of Quantitative Traits Involving Epistasis in Plant Breeding. PLoS ONE. 7(11). e50604–e50604. 15 indexed citations
18.
Carbonero, Christine Hayot, et al.. (2012). Improving in vivo maize doubled haploid production efficiency through early detection of false positives. Plant Breeding. 131(3). 399–401. 28 indexed citations
19.
Moose, Stephen P. & Rita H. Mumm. (2008). Molecular Plant Breeding as the Foundation for 21st Century Crop Improvement. PLANT PHYSIOLOGY. 147(3). 969–977. 503 indexed citations breakdown →
20.
Mumm, Rita H., Lawrence J. Hubert, & J. W. Dudley. (1994). A Classification of 148 U.S. Maize Inbreds: II. Validation of Cluster Analysis Based on RFLPs. Crop Science. 34(4). 852–865. 18 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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