M. Olsen

2.0k total citations · 2 hit papers
25 papers, 1.3k citations indexed

About

M. Olsen is a scholar working on Plant Science, Genetics and Agronomy and Crop Science. According to data from OpenAlex, M. Olsen has authored 25 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Plant Science, 15 papers in Genetics and 9 papers in Agronomy and Crop Science. Recurrent topics in M. Olsen's work include Genetics and Plant Breeding (19 papers), Genetic Mapping and Diversity in Plants and Animals (15 papers) and Crop Yield and Soil Fertility (9 papers). M. Olsen is often cited by papers focused on Genetics and Plant Breeding (19 papers), Genetic Mapping and Diversity in Plants and Animals (15 papers) and Crop Yield and Soil Fertility (9 papers). M. Olsen collaborates with scholars based in Kenya, United States and Mexico. M. Olsen's co-authors include Jill E. Cairns, Mainassara Zaman‐Allah, J. L. Araus, Shawn C. Kefauver, B. M. Prasanna, Cosmos Magorokosho, Amsal Tarekegne, Manje Gowda, B. Vivek and Dan Makumbi and has published in prestigious journals such as Scientific Reports, International Journal of Molecular Sciences and Trends in Plant Science.

In The Last Decade

M. Olsen

23 papers receiving 1.3k citations

Hit Papers

Translating High-Throughput Phenotyping into Genetic Gain 2018 2026 2020 2023 2018 2021 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. Olsen Kenya 14 1.1k 445 264 249 142 25 1.3k
Amsal Tarekegne Kenya 19 1.5k 1.4× 781 1.8× 412 1.6× 321 1.3× 88 0.6× 49 1.8k
Jackie C. Rudd United States 26 2.1k 1.9× 562 1.3× 384 1.5× 162 0.7× 204 1.4× 88 2.2k
Joshua N. Cobb Philippines 12 1.2k 1.1× 636 1.4× 92 0.3× 136 0.5× 150 1.1× 19 1.4k
Fouad Maalouf Syria 20 1.2k 1.1× 188 0.4× 271 1.0× 121 0.5× 79 0.6× 51 1.3k
Yüksel Kaya Türkiye 14 950 0.9× 214 0.5× 302 1.1× 111 0.4× 47 0.3× 36 1.0k
Leonardo Crespo‐Herrera Mexico 25 1.7k 1.6× 602 1.4× 384 1.5× 109 0.4× 146 1.0× 67 1.9k
Long‐Xi Yu United States 20 1.1k 1.0× 410 0.9× 228 0.9× 56 0.2× 209 1.5× 48 1.3k
Carolina Saint Pierre Mexico 15 1000 0.9× 372 0.8× 301 1.1× 88 0.4× 86 0.6× 37 1.1k
B. S. Dhillon India 17 902 0.8× 335 0.8× 269 1.0× 81 0.3× 57 0.4× 100 1.0k
Roberto Fritsche‐Neto Brazil 26 1.9k 1.8× 1.1k 2.6× 360 1.4× 103 0.4× 167 1.2× 142 2.2k

Countries citing papers authored by M. Olsen

Since Specialization
Citations

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

Fields of papers citing papers by M. Olsen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Olsen

This figure shows the co-authorship network connecting the top 25 collaborators of M. Olsen. A scholar is included among the top collaborators of M. Olsen 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 M. Olsen. M. Olsen 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
2.
Beyene, Yoseph, Beatrice Elohor Ifie, Manje Gowda, et al.. (2024). Agronomic Performance and Resistance to Maize Lethal Necrosis in Maize Hybrids Derived from Doubled Haploid Lines. Agronomy. 14(10). 2443–2443. 1 indexed citations
3.
Collinson, Sarah, Jill E. Cairns, Marc C. Albertsen, et al.. (2024). Ms44-SPT: unique genetic technology simplifies and improves hybrid maize seed production in sub-Saharan Africa. Scientific Reports. 14(1). 32125–32125.
4.
Collinson, Sarah, Rachel C. Voss, Frédéric Baudron, et al.. (2024). Validating a novel genetic technology for hybrid maize seed production under management practices associated with resource‐poor farmers in Zimbabwe. Plants People Planet. 7(3). 801–815. 3 indexed citations
5.
Groote, Hugo De, et al.. (2023). Kenyan farmers appreciate the higher yield of 50% non-pollen producing Maize (Zea mays) hybrids. Experimental Agriculture. 59. 1 indexed citations
6.
Voss, Rachel C., et al.. (2023). Innovative approaches to integrating gender into conventional maize breeding: lessons from the Seed Production Technology for Africa project. Frontiers in Sociology. 8. 1254595–1254595. 6 indexed citations
7.
Collinson, Sarah, et al.. (2022). Incorporating male sterility increases hybrid maize yield in low input African farming systems. Communications Biology. 5(1). 729–729. 10 indexed citations
8.
Prasanna, B. M., Jill E. Cairns, P.H. Zaidi, et al.. (2021). Beat the stress: breeding for climate resilience in maize for the tropical rainfed environments. Theoretical and Applied Genetics. 134(6). 1729–1752. 131 indexed citations breakdown →
9.
Gowda, Manje, Yoseph Beyene, Juan Burgueño, et al.. (2020). Hybrid Breeding for MLN Resistance: Heterosis, Combining Ability, and Hybrid Prediction. Plants. 9(4). 468–468. 16 indexed citations
10.
Prasanna, B. M., Natalia Palacios‐Rojas, Firoz Hossain, et al.. (2020). Molecular Breeding for Nutritionally Enriched Maize: Status and Prospects. Frontiers in Genetics. 10. 1392–1392. 146 indexed citations
11.
Suresh, L. M., Yoseph Beyene, Dan Makumbi, et al.. (2020). Maize lethal necrosis (MLN): Efforts toward containing the spread and impact of a devastating transboundary disease in sub-Saharan Africa. Virus Research. 282. 197943–197943. 67 indexed citations
12.
Olsen, M., Juan Burgueño, José Crossa, et al.. (2020). Maximizing efficiency of genomic selection in CIMMYT’s tropical maize breeding program. Theoretical and Applied Genetics. 134(1). 279–294. 45 indexed citations
13.
14.
Gowda, Manje, Yoseph Beyene, Dan Makumbi, et al.. (2019). Genome-Wide Analyses and Prediction of Resistance to MLN in Large Tropical Maize Germplasm. Genes. 11(1). 16–16. 36 indexed citations
15.
Araus, J. L., Shawn C. Kefauver, Mainassara Zaman‐Allah, M. Olsen, & Jill E. Cairns. (2018). Translating High-Throughput Phenotyping into Genetic Gain. Trends in Plant Science. 23(5). 451–466. 486 indexed citations breakdown →
16.
Zaman‐Allah, Mainassara, Jill E. Cairns, Cosmos Magorokosho, et al.. (2018). High-Throughput Phenotyping of Canopy Cover and Senescence in Maize Field Trials Using Aerial Digital Canopy Imaging. Remote Sensing. 10(2). 330–330. 96 indexed citations
17.
Biljon, Angeline van, Jill E. Cairns, Biswanath Das, et al.. (2017). Genetic Diversity among Selected Elite CIMMYT Maize Hybrids in East and Southern Africa. Crop Science. 57(5). 2395–2404. 14 indexed citations
18.
Magorokosho, Cosmos, M. Olsen, G. N. Atlin, et al.. (2016). Gains in Maize Genetic Improvement in Eastern and Southern Africa: II. CIMMYT Open‐Pollinated Variety Breeding Pipeline. Crop Science. 57(1). 180–191. 63 indexed citations
19.
Atlin, G. N., M. Olsen, Cosmos Magorokosho, et al.. (2016). Gains in Maize Genetic Improvement in Eastern and Southern Africa: I. CIMMYT Hybrid Breeding Pipeline. Crop Science. 57(1). 168–179. 93 indexed citations
20.
Semagn, Kassa, Yoseph Beyene, Raman Babu, et al.. (2014). QTL Mapping and Molecular Breeding for Developing Stress Resilient Maize for Sub-Saharan Africa. 2 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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