Benjamin Fallen

577 total citations
48 papers, 370 citations indexed

About

Benjamin Fallen is a scholar working on Plant Science, Agronomy and Crop Science and Nutrition and Dietetics. According to data from OpenAlex, Benjamin Fallen has authored 48 papers receiving a total of 370 indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Plant Science, 6 papers in Agronomy and Crop Science and 4 papers in Nutrition and Dietetics. Recurrent topics in Benjamin Fallen's work include Soybean genetics and cultivation (39 papers), Legume Nitrogen Fixing Symbiosis (29 papers) and Nematode management and characterization studies (10 papers). Benjamin Fallen is often cited by papers focused on Soybean genetics and cultivation (39 papers), Legume Nitrogen Fixing Symbiosis (29 papers) and Nematode management and characterization studies (10 papers). Benjamin Fallen collaborates with scholars based in United States, France and Guatemala. Benjamin Fallen's co-authors include Sruthi Narayanan, Vince Pantalone, Vincent R. Pantalone, Ruth Welti, James R. Smith, Rouf Mian, Sachin Rustgi, Qijian Song, David L. Hyten and Arnold M. Saxton and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Frontiers in Plant Science.

In The Last Decade

Benjamin Fallen

41 papers receiving 362 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Benjamin Fallen United States 10 315 37 37 27 23 48 370
Nishtha Rawat India 6 221 0.7× 52 1.4× 35 0.9× 10 0.4× 17 0.7× 7 282
Milan Jocković Serbia 9 247 0.8× 60 1.6× 43 1.2× 7 0.3× 15 0.7× 48 280
Iram Sharif Pakistan 7 243 0.8× 60 1.6× 19 0.5× 6 0.2× 8 0.3× 17 286
Xinyao Xia China 9 201 0.6× 81 2.2× 14 0.4× 11 0.4× 26 1.1× 22 278
Juliana Parisotto Poletine Brazil 11 296 0.9× 37 1.0× 62 1.7× 10 0.4× 5 0.2× 53 329
Caroline Cukier France 9 313 1.0× 86 2.3× 31 0.8× 8 0.3× 12 0.5× 16 354
Rachel A. Mertz United States 5 345 1.1× 101 2.7× 13 0.4× 7 0.3× 17 0.7× 8 386
Ayaz Ali Keerio Pakistan 7 240 0.8× 72 1.9× 17 0.5× 9 0.3× 13 0.6× 11 280
Xihuan Li China 12 416 1.3× 62 1.7× 50 1.4× 5 0.2× 15 0.7× 35 451
Bahram Alizadeh Iran 12 330 1.0× 162 4.4× 39 1.1× 15 0.6× 39 1.7× 49 393

Countries citing papers authored by Benjamin Fallen

Since Specialization
Citations

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

Fields of papers citing papers by Benjamin Fallen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Benjamin Fallen

This figure shows the co-authorship network connecting the top 25 collaborators of Benjamin Fallen. A scholar is included among the top collaborators of Benjamin Fallen 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 Benjamin Fallen. Benjamin Fallen 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.
Momen, Shima, et al.. (2025). Effects of genetic diversity on physicochemical and functional properties of soybean proteins. Journal of Agriculture and Food Research. 21. 101878–101878.
2.
Patel, Jinesh D., et al.. (2025). Soybean genome‑wide association study of seed weight, protein, and oil content in the southeastern USA. Molecular Genetics and Genomics. 300(1). 43–43. 1 indexed citations
3.
Ali, Muhammad, Thien Vu, Lisa L. Dean, et al.. (2024). Effects of high oleic full-fat soybean meal on broiler live performance, carcass and parts yield, and fatty acid composition of breast fillets. Poultry Science. 103(3). 103399–103399. 2 indexed citations
4.
Toomer, Ondulla T., E.O. Oviedo-Rondón, Muhammad Ali, et al.. (2024). Full-Fat Soybean Meals as an Alternative Poultry Feed Ingredient—Feed Processing Methods and Utilization—Review and Perspective. Animals. 14(16). 2366–2366. 6 indexed citations
5.
Fallen, Benjamin, et al.. (2024). Multi‐sensor and multi‐temporal high‐throughput phenotyping for monitoring and early detection of water‐limiting stress in soybean. SHILAP Revista de lepidopterología. 7(1). e70009–e70009. 6 indexed citations
6.
Song, Qijian, et al.. (2024). Genetic mapping reveals the complex genetic architecture controlling slow canopy wilting in soybean. Theoretical and Applied Genetics. 137(5). 107–107. 3 indexed citations
7.
Mian, Rouf, et al.. (2024). Registration of USDA‐N6006 soybean germplasm combining high yield, flood tolerance, and elevated oil content. Journal of Plant Registrations. 18(2). 436–443.
8.
Taliercio, Earl, et al.. (2024). Glycine soja, PI424025, is a valuable genetic resource to improve soybean seed-protein content and composition. PLoS ONE. 19(11). e0310544–e0310544. 1 indexed citations
9.
Jiang, Guo‐Liang, et al.. (2024). Evaluation of 10 Edamame Breeding Lines to Determine Yield, Agronomic, and Seed Composition Traits. HortScience. 59(12). 1789–1794. 1 indexed citations
10.
Fallen, Benjamin, et al.. (2023). Registration of USDA‐N7006 soybean germplasm with increased tolerance to drought stress and 37.5% pedigree from Asian accessions PI 416937 and PI 407859‐2. Journal of Plant Registrations. 17(3). 573–579. 5 indexed citations
11.
Taliercio, Earl, et al.. (2023). Parental choice and seed size impact the uprightness of progeny from interspecific Glycine hybridizations. Crop Science. 63(4). 2184–2195. 1 indexed citations
12.
Toomer, Ondulla T., E.O. Oviedo-Rondón, Muhammad Ali, et al.. (2023). Current Agronomic Practices, Harvest & Post-Harvest Processing of Soybeans (Glycine max)—A Review. Agronomy. 13(2). 427–427. 22 indexed citations
13.
Mian, Rouf, et al.. (2023). Registration of high‐yielding maturity group V germplasm USDA‐N5001 with high seed and meal protein contents. Journal of Plant Registrations. 17(3). 567–572.
14.
Fletcher, Elizabeth J., Robert Patterson, Jeffrey C. Dunne, Christopher Saski, & Benjamin Fallen. (2023). Evaluating the Effects of Flooding Stress during Multiple Growth Stages in Soybean. Agronomy. 13(5). 1243–1243. 7 indexed citations
15.
16.
Bilyeu, Kristin, et al.. (2023). Selecting recombinants to stack high protein with high oleic acid and low linoleic acid in soybean (Glycine max). Plant Breeding. 142(4). 477–488. 3 indexed citations
17.
Miller, Mark J., Qijian Song, Benjamin Fallen, & Zenglu Li. (2023). Genomic prediction of optimal cross combinations to accelerate genetic improvement of soybean (Glycine max). Frontiers in Plant Science. 14. 1171135–1171135. 11 indexed citations
18.
Fallen, Benjamin, et al.. (2022). Parsimonious root systems and better root distribution can improve biomass production and yield of soybean. PLoS ONE. 17(6). e0270109–e0270109. 5 indexed citations
19.
Saski, Christopher, et al.. (2020). Quantitative Trait Loci Associated withRotylenchulusreniformisHost Suitability in Soybean. Phytopathology. 110(9). 1511–1521. 8 indexed citations
20.
Narayanan, Sruthi, et al.. (2019). Evaluation of soybean [Glycine max (L.) Merr.] genotypes for yield, water use efficiency, and root traits. PLoS ONE. 14(2). e0212700–e0212700. 56 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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