Nobuhiro Kotoda

2.5k total citations
55 papers, 1.9k citations indexed

About

Nobuhiro Kotoda is a scholar working on Plant Science, Molecular Biology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Nobuhiro Kotoda has authored 55 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Plant Science, 34 papers in Molecular Biology and 13 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Nobuhiro Kotoda's work include Plant Physiology and Cultivation Studies (27 papers), Plant Reproductive Biology (25 papers) and Plant Molecular Biology Research (20 papers). Nobuhiro Kotoda is often cited by papers focused on Plant Physiology and Cultivation Studies (27 papers), Plant Reproductive Biology (25 papers) and Plant Molecular Biology Research (20 papers). Nobuhiro Kotoda collaborates with scholars based in Japan, Israel and United States. Nobuhiro Kotoda's co-authors include Masato Wada, Junichi Soejima, Kazuyuki Abe, Hiroshi Iwanami, Sae Takahashi, Shigeki Moriya, Tetsuo Masuda, Mitsuru Nishiguchi, Tomohiro Igasaki and K. Abe and has published in prestigious journals such as Scientific Reports, Plant Molecular Biology and Plant and Cell Physiology.

In The Last Decade

Nobuhiro Kotoda

53 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nobuhiro Kotoda Japan 21 1.6k 1.4k 232 167 155 55 1.9k
Tianzhong Li China 28 1.6k 1.0× 1.2k 0.8× 305 1.3× 106 0.6× 136 0.9× 83 1.9k
Hiroshi Iwanami Japan 21 1.3k 0.8× 834 0.6× 157 0.7× 66 0.4× 126 0.8× 72 1.4k
Junichi Soejima Japan 21 1.3k 0.8× 1.0k 0.7× 283 1.2× 180 1.1× 177 1.1× 59 1.5k
Akira Kitajima Japan 17 736 0.4× 588 0.4× 106 0.5× 92 0.6× 92 0.6× 59 923
Peihua Cong China 13 699 0.4× 740 0.5× 85 0.4× 187 1.1× 110 0.7× 31 996
Gaetano Distefano Italy 22 902 0.5× 594 0.4× 200 0.9× 72 0.4× 124 0.8× 75 1.1k
Ikuo Miyajima Japan 15 561 0.3× 709 0.5× 145 0.6× 198 1.2× 55 0.4× 88 921
Weichao Fang China 20 1.0k 0.6× 721 0.5× 88 0.4× 125 0.7× 129 0.8× 58 1.3k
Tomoko Endo Japan 23 1.0k 0.6× 1.1k 0.8× 156 0.7× 190 1.1× 88 0.6× 62 1.6k
F. Dunemann Germany 23 1.2k 0.7× 675 0.5× 291 1.3× 84 0.5× 331 2.1× 57 1.5k

Countries citing papers authored by Nobuhiro Kotoda

Since Specialization
Citations

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

Fields of papers citing papers by Nobuhiro Kotoda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nobuhiro Kotoda

This figure shows the co-authorship network connecting the top 25 collaborators of Nobuhiro Kotoda. A scholar is included among the top collaborators of Nobuhiro Kotoda 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 Nobuhiro Kotoda. Nobuhiro Kotoda 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.
Iwasaki, Takaya, et al.. (2025). Subfamily evolution analysis using nuclear and chloroplast data from the same reads. Scientific Reports. 15(1). 687–687.
2.
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Kotoda, Nobuhiro, et al.. (2022). Citrus VASCULAR PLANT ONE-ZINC FINGER1 (VOZ1) interacts with CuFT1 and CuFT3, affecting flowering in transgenic Arabidopsis. Scientia Horticulturae. 310. 111702–111702. 3 indexed citations
4.
Zohra, Fatema Tuz, et al.. (2020). Accumulation of Polymethoxyflavones and <i>O</i>-methyltransferase Gene Expression in Various Citrus Cultivars. The Horticulture Journal. 89(3). 225–236. 11 indexed citations
5.
Nagano, Yukio, Takashi Mimura, Nobuhiro Kotoda, et al.. (2018). Phylogenetic relationships of Aurantioideae (Rutaceae) based on RAD-Seq. Tree Genetics & Genomes. 14(1). 22 indexed citations
6.
Abe, K., Hiroshi Iwanami, Nobuhiro Kotoda, et al.. (2018). New apple cultivar 'Ruby Sweet'.. 9–17. 1 indexed citations
7.
Okawa, Katsuya, Hitoshi Ohara, Satoru Kondo, et al.. (2013). Application of an Analog of 9, 10-ketol-octadecadienoic acid (KODA), Affected Flower Bud Formation and MdTFL1 and MdFT1 Gene Expressions in Apple Buds under Heavy-crop and Shade Conditions. Journal of the American Society for Horticultural Science. 138(2). 102–107. 3 indexed citations
8.
Minamikawa, Mai F., et al.. (2013). Identification of an S-RNase binding protein1 (SBP1) homolog of apple (Malus^|^times;domestica). Plant Biotechnology. 30(2). 119–123. 3 indexed citations
9.
Mimida, Naozumi, Shin‐ichiro Kidou, Hiroshi Iwanami, et al.. (2011). Apple FLOWERING LOCUS T proteins interact with transcription factors implicated in cell growth and organ development. Tree Physiology. 31(5). 555–566. 58 indexed citations
10.
Minamikawa, Mai F., Hiroyuki Kakui, Sanhong Wang, et al.. (2010). Apple S locus region represents a large cluster of related, polymorphic and pollen-specific F-box genes. Plant Molecular Biology. 74(1-2). 143–154. 65 indexed citations
11.
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Iwanami, Hiroshi, Shigeki Moriya, Nobuhiro Kotoda, Sae Takahashi, & Kazuyuki Abe. (2008). Estimations of Heritability and Breeding Value for Postharvest Fruit Softening in Apple. Journal of the American Society for Horticultural Science. 133(1). 92–99. 13 indexed citations
13.
Iwanami, Hiroshi, Shigeki Moriya, Nobuhiro Kotoda, & Kazuyuki Abe. (2008). Turgor Closely Relates to Postharvest Fruit Softening and Can Be a Useful Index to Select a Parent for Producing Cultivars with Good Storage Potential in Apple. HortScience. 43(5). 1377–1381. 19 indexed citations
14.
Iwanami, Hiroshi, Shigeki Moriya, Nobuhiro Kotoda, Sae Takahashi, & Kazuyuki Abe. (2008). Storability in Cold Temperatures Can Be Evaluated Based on Changes in Fruit Quality in Apple Genotypes Under Shelf Life Conditions. HortScience. 43(3). 655–660. 5 indexed citations
15.
Igasaki, Tomohiro, Yumiko Watanabe, Mitsuru Nishiguchi, & Nobuhiro Kotoda. (2008). The FLOWERING LOCUS T/TERMINAL FLOWER 1 Family in Lombardy Poplar. Plant and Cell Physiology. 49(3). 291–300. 92 indexed citations
16.
Abe, K., Nobuhiro Kotoda, Hidenori Kato, & Junichi Soejima. (2007). Resistance sources to Valsa canker (Valsa ceratosperma) in a germplasm collection of diverseMalusspecies. Plant Breeding. 126(4). 449–453. 74 indexed citations
17.
Iwanami, Hiroshi, Shigeki Moriya, Nobuhiro Kotoda, Sae Takahashi, & Kazuyuki Abe. (2005). Influence of Mealiness on the Firmness of Apples after Harvest. HortScience. 40(7). 2091–2095. 20 indexed citations
18.
Iwanami, Hiroshi, et al.. (2004). Evaluation of Differences in Softening of Apple Genotypes by Linear Regression. HortScience. 39(6). 1185–1188. 6 indexed citations
19.
Wada, Masato, et al.. (2002). Apple has two orthologues of FLORICAULA/LEAFY involved in flowering. Plant Molecular Biology. 49(6). 567–577. 126 indexed citations
20.
Kotoda, Nobuhiro, Masato Wada, Sadao Komori, et al.. (2000). Expression Pattern of Homologues of Floral Meristem Identity Genes LFY and AP1 during Flower Development in Apple. Journal of the American Society for Horticultural Science. 125(4). 398–403. 82 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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