Kevin M. Folta

9.1k total citations
127 papers, 5.9k citations indexed

About

Kevin M. Folta is a scholar working on Plant Science, Molecular Biology and Cell Biology. According to data from OpenAlex, Kevin M. Folta has authored 127 papers receiving a total of 5.9k indexed citations (citations by other indexed papers that have themselves been cited), including 112 papers in Plant Science, 76 papers in Molecular Biology and 10 papers in Cell Biology. Recurrent topics in Kevin M. Folta's work include Berry genetics and cultivation research (42 papers), Plant Molecular Biology Research (40 papers) and Light effects on plants (37 papers). Kevin M. Folta is often cited by papers focused on Berry genetics and cultivation research (42 papers), Plant Molecular Biology Research (40 papers) and Light effects on plants (37 papers). Kevin M. Folta collaborates with scholars based in United States, Spain and China. Kevin M. Folta's co-authors include Edgar P. Spalding, Sofia D. Carvalho, Yihai Wang, Thomas M. Davis, Susan E. Gardiner, Amit Dhingra, Vance M. Whitaker, Tingting Zhang, Lon S. Kaufman and Thomas A. Colquhoun and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Plant Cell.

In The Last Decade

Kevin M. Folta

125 papers receiving 5.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kevin M. Folta United States 44 4.8k 2.8k 428 332 302 127 5.9k
Tsuyoshi Nakagawa Japan 40 4.0k 0.8× 4.4k 1.6× 418 1.0× 177 0.5× 256 0.8× 105 6.3k
Curtis G. Wilkerson United States 45 3.0k 0.6× 4.3k 1.5× 836 2.0× 298 0.9× 122 0.4× 73 6.7k
Miguel Ángel Medina Torres Spain 26 8.9k 1.9× 4.3k 1.5× 623 1.5× 270 0.8× 102 0.3× 44 10.3k
Miguel A. Botella Spain 49 5.5k 1.2× 3.4k 1.2× 736 1.7× 159 0.5× 449 1.5× 97 7.0k
N. H. Battey United Kingdom 32 2.6k 0.5× 1.7k 0.6× 303 0.7× 319 1.0× 152 0.5× 87 3.4k
Danny Geelen Belgium 51 6.1k 1.3× 4.3k 1.5× 1.1k 2.5× 777 2.3× 75 0.2× 180 7.8k
Paulo Arruda Brazil 45 3.6k 0.8× 2.9k 1.0× 266 0.6× 240 0.7× 105 0.3× 136 5.8k
Stéphane Rombauts Belgium 42 4.4k 0.9× 4.4k 1.6× 267 0.6× 347 1.0× 71 0.2× 84 6.8k
Hiroshi Ezura Japan 49 6.8k 1.4× 5.0k 1.8× 167 0.4× 219 0.7× 328 1.1× 275 8.6k
Liming Xiong United States 46 10.8k 2.2× 6.7k 2.4× 203 0.5× 257 0.8× 136 0.5× 84 12.6k

Countries citing papers authored by Kevin M. Folta

Since Specialization
Citations

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

Fields of papers citing papers by Kevin M. Folta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kevin M. Folta

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin M. Folta. A scholar is included among the top collaborators of Kevin M. Folta 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 Kevin M. Folta. Kevin M. Folta 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.
Loizzo, Jamie, et al.. (2024). Scientists’ side of the microphone: An examination of agricultural and natural resources podcast guests’ experiences. SHILAP Revista de lepidopterología. 5(3). 39–54. 1 indexed citations
2.
McFadden, Brandon R., Joy N. Rumble, Kathryn A. Stofer, & Kevin M. Folta. (2024). U.S. public opinion about the safety of gene editing in the agriculture and medical fields and the amount of evidence needed to improve opinions. Frontiers in Bioengineering and Biotechnology. 12. 1340398–1340398. 10 indexed citations
3.
Loizzo, Jamie, et al.. (2023). Podcasts in Production: An Examination of Current and Best Practices for Agricultural and Natural Resource Podcast Producers. Journal of Applied Communications. 106(4). 3 indexed citations
4.
Xia, Liang, Wei Feng, Chunmei Gong, et al.. (2023). A point mutation in the gene encoding magnesium chelatase I subunit influences strawberry leaf color and metabolism. PLANT PHYSIOLOGY. 192(4). 2737–2755. 28 indexed citations
5.
McFadden, Brandon R., et al.. (2023). A randomized group approach to identifying label effects. Journal of Choice Modelling. 48. 100435–100435. 2 indexed citations
6.
Thiel, Robert, et al.. (2022). Impact of teaching methods on learner preferences and knowledge gained when informing adults about gene editing. SHILAP Revista de lepidopterología. 3(1). 70–86. 1 indexed citations
7.
Gaston, Amélia, Silvia Sabbadini, Frédéric Delmas, et al.. (2021). The FveFT2 florigen/FveTFL1 antiflorigen balance is critical for the control of seasonal flowering in strawberry while FveFT3 modulates axillary meristem fate and yield. New Phytologist. 232(1). 372–387. 29 indexed citations
8.
McFadden, Brandon R., et al.. (2021). Gene editing isn’t just about food: comments from U.S. focus groups. GM crops & food. 12(2). 616–626. 7 indexed citations
9.
Feng, Chao, Jing Wang, AJ Harris, et al.. (2020). Tracing the Diploid Ancestry of the Cultivated Octoploid Strawberry. Molecular Biology and Evolution. 38(2). 478–485. 59 indexed citations
10.
Rumble, Joy N., et al.. (2019). Can Anyone Hear Us? An Exploration of Echo Chambers at a Land-Grant University. Journal of Applied Communications. 103(2). 7 indexed citations
11.
Barbey, Christopher R., Seonghee Lee, Sujeet Verma, et al.. (2019). Disease Resistance Genetics and Genomics in Octoploid Strawberry. G3 Genes Genomes Genetics. 9(10). 3315–3332. 28 indexed citations
12.
Folta, Kevin M.. (2015). Molecular-genetic Extensions of Vavilov’s Predictions. HortScience. 50(6). 777–779. 6 indexed citations
13.
Amaya, Iraida, Jérémy Pillet, & Kevin M. Folta. (2015). Identification of Genes Responsible for Natural Variation in Volatile Content Using Next-Generation Sequencing Technology. Methods in molecular biology. 1363. 37–45. 3 indexed citations
14.
Colquhoun, Thomas A., et al.. (2012). Framing the perfect strawberry: An exercise in consumer-assisted selection of fruit crops. Journal of Berry Research. 2(1). 45–61. 43 indexed citations
15.
Chambers, Alan, Vance M. Whitaker, Brian Gibbs, Anne Plotto, & Kevin M. Folta. (2012). Detection of the linalool‐producing NES1 variant across diverse strawberry (Fragaria spp.) accessions. Plant Breeding. 131(3). 437–443. 16 indexed citations
16.
Zhang, Tingting, et al.. (2011). Green Light Induces Shade Avoidance Symptoms   . PLANT PHYSIOLOGY. 157(3). 1528–1536. 138 indexed citations
17.
Mayfield, John D., Kevin M. Folta, Anna‐Lisa Paul, & Robert J. Ferl. (2007). The 14-3-3 Proteins μ and υ Influence Transition to Flowering and Early Phytochrome Response. PLANT PHYSIOLOGY. 145(4). 1692–1702. 89 indexed citations
18.
Folta, Kevin M.. (2004). Green Light Stimulates Early Stem Elongation, Antagonizing Light-Mediated Growth Inhibition. PLANT PHYSIOLOGY. 135(3). 1407–1416. 147 indexed citations
19.
20.
Folta, Kevin M. & Lon S. Kaufman. (2003). Phototropin 1 is required for high-fluence blue-light-mediated mRNA destabilization. Plant Molecular Biology. 51(4). 609–618. 46 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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