Mai Tsuda
- Plant Science top 5%
- Genetically Modified Organisms Research 7
- Soybean genetics and cultivation 7
- Plant Genetic and Mutation Studies 3
- Biotechnology top 10%
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- Plant tissue culture and regeneration 10
- CRISPR and Genetic Engineering 9
- Photosynthetic Processes and Mechanisms 3
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- Genetic Mapping and Diversity in Plants and Animals 4
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- Remote Sensing in Agriculture 5
- Co-authors
- Yutaka TabeiKen-ichi KonagayaAyako OkuzakiRyo OhsawaYoshihiko NanasatoMasaaki YoshikawaYuichi TakeuchiKazuo Watanabe
- Partner nations
- JapanUnited StatesSpain
In The Last Decade
Mai Tsuda
36 papers receiving 478 citations
Peers
Comparison fields: 5 of 57
- Plant Science 385
- Biotechnology 88
- Business and International Management 11
- Molecular Biology 326
- Genetics 78
Countries citing papers authored by Mai Tsuda
This map shows the geographic impact of Mai Tsuda'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 Mai Tsuda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mai Tsuda more than expected).
Fields of papers citing papers by Mai Tsuda
This network shows the impact of papers produced by Mai Tsuda. 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 Mai Tsuda. The network helps show where Mai Tsuda may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mai Tsuda, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 7 | |
| 2 | 2024 | 4 | |
| 3 | 2023 | 5 | |
| 4 | 2022 | 10 | |
| 5 | 2022 | 5 | |
| 6 | 2022 | 8 | |
| 7 | 2021 | 3 | |
| 8 | 2020 | 18 | |
| 9 | 2020 | 16 | |
| 10 | 2020 | 9 | |
| 11 | 2019 | 46 | |
| 12 | 2015 | 75 | |
| 13 | Development of methods for risk assessment of transgenic silkworms rearing on biodiversity | 2014 | 1 |
| 14 | A Monitoring Support System for Elderly Person Living Alone through Activity Sensing in Living Space and Its Evaluation | 2014 | 2 |
| 15 | 2013 | 9 | |
| 16 | 2012 | 47 | |
| 17 | 2011 | 27 | |
| 18 | 2008 | 35 | |
| 19 | Changes of rice sodium content due to sodium exclusion and transpiration under salinity. | 2000 | 2 |
| 20 | Sexuality for the teleomorph formation and conidial variability in Curvularia lunata. | 1985 | 4 |
About Mai Tsuda
Mai Tsuda is a scholar working on Plant Science, Biotechnology and Genetics, having authored 36 papers that have together received 498 indexed citations. Recurring topics across this work include Plant tissue culture and regeneration (10 papers), CRISPR and Genetic Engineering (9 papers), Genetically Modified Organisms Research (7 papers), Soybean genetics and cultivation (7 papers), Remote Sensing in Agriculture (5 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers), Photosynthetic Processes and Mechanisms (3 papers) and Plant Genetic and Mutation Studies (3 papers). The work is most often cited by research in Plant Science (385 citations), Biotechnology (88 citations) and Business and International Management (11 citations). Mai Tsuda has collaborated with scholars based in Japan, United States and Spain. Frequent co-authors include Yutaka Tabei, Ken-ichi Konagaya, Ayako Okuzaki, Ryo Ohsawa, Yoshihiko Nanasato, Masaaki Yoshikawa, Yuichi Takeuchi, Kazuo Watanabe, Sugihiro Ando and Akito Kaga. Their work appears in journals such as PLoS ONE, Scientific Reports and Frontiers in Plant Science.
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.