Daigo Makihara

587 total citations
42 papers, 407 citations indexed

About

Daigo Makihara is a scholar working on Plant Science, Genetics and Agronomy and Crop Science. According to data from OpenAlex, Daigo Makihara has authored 42 papers receiving a total of 407 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Plant Science, 11 papers in Genetics and 6 papers in Agronomy and Crop Science. Recurrent topics in Daigo Makihara's work include Rice Cultivation and Yield Improvement (30 papers), GABA and Rice Research (16 papers) and Plant responses to water stress (11 papers). Daigo Makihara is often cited by papers focused on Rice Cultivation and Yield Improvement (30 papers), GABA and Rice Research (16 papers) and Plant responses to water stress (11 papers). Daigo Makihara collaborates with scholars based in Japan, Kenya and Philippines. Daigo Makihara's co-authors include Hunja Murage, Elijah Ateka, Akira Yamauchi, Hiroshi Ehara, Hitoshi Naito, Makoto Tsuda, Kazuyuki Doi, Hiroaki Samejima, Mana Kano‐Nakata and Keisuke Katsura and has published in prestigious journals such as Field Crops Research, Applied Soil Ecology and Plant Disease.

In The Last Decade

Daigo Makihara

41 papers receiving 395 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daigo Makihara Japan 12 359 84 44 38 35 42 407
Manjula Bandara Canada 11 295 0.8× 40 0.5× 78 1.8× 29 0.8× 61 1.7× 26 403
Veronica Giorgi Italy 9 314 0.9× 117 1.4× 37 0.8× 52 1.4× 150 4.3× 27 420
Shailesh Kumar Singh India 10 357 1.0× 126 1.5× 42 1.0× 32 0.8× 54 1.5× 18 423
T. R. Cary United States 12 462 1.3× 29 0.3× 25 0.6× 23 0.6× 56 1.6× 24 496
Alain Ramanantsoanirina Madagascar 12 295 0.8× 69 0.8× 57 1.3× 88 2.3× 20 0.6× 20 381
Fatih Özdemir Türkiye 10 566 1.6× 134 1.6× 28 0.6× 44 1.2× 33 0.9× 24 633
Mohd Anwar Khan India 9 333 0.9× 78 0.9× 12 0.3× 27 0.7× 71 2.0× 32 411
Marie‐Odile Bancal France 13 439 1.2× 45 0.5× 17 0.4× 47 1.2× 45 1.3× 21 483
Zhongwen Rang China 7 364 1.0× 65 0.8× 67 1.5× 72 1.9× 76 2.2× 11 445
Luis Inostroza Chile 12 352 1.0× 108 1.3× 26 0.6× 19 0.5× 40 1.1× 34 418

Countries citing papers authored by Daigo Makihara

Since Specialization
Citations

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

Fields of papers citing papers by Daigo Makihara

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daigo Makihara

This figure shows the co-authorship network connecting the top 25 collaborators of Daigo Makihara. A scholar is included among the top collaborators of Daigo Makihara 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 Daigo Makihara. Daigo Makihara 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.
Sekiya, Nobuhito, et al.. (2025). Effects of nitrogen application in upland rice cultivars: Balancing sink-source relationships for sustainable yield in water-limited environments. Field Crops Research. 332. 110012–110012. 4 indexed citations
2.
Reyes, Vincent P., et al.. (2024). Evaluation of Grain-Filling-Related Traits Using Taichung 65 x DV85 Chromosome Segment Substitution Lines (TD-CSSLs) of Rice. Plants. 13(2). 289–289. 1 indexed citations
3.
Samejima, Hiroaki, Kazuyuki Doi, Motoyuki Ashikari, et al.. (2023). Contribution of genes related to grain number (Gn1a and WFP) introgressed into NERICA 1 to grain yield under tropical highland conditions in central Kenya. Plant Production Science. 26(3). 309–319. 2 indexed citations
4.
5.
Samejima, Hiroaki, et al.. (2023). Yield Responses of Upland Rice Varieties to Low N Conditions in Central Kenya. Journal of Agricultural Science. 15(6). 19–19. 1 indexed citations
6.
Reyes, Vincent P., et al.. (2022). Utilization of Genotyping-by-Sequencing (GBS) for Rice Pre-Breeding and Improvement: A Review. Life. 12(11). 1752–1752. 12 indexed citations
7.
Gorfer, Markus, Luigimaria Borruso, Daigo Makihara, et al.. (2022). The effect of environmental parameters and fertilization practices on yield and soil microbial diversity in a Kenyan paddy rice field. Applied Soil Ecology. 176. 104495–104495. 3 indexed citations
8.
Reyes, Vincent P., Rosalyn B. Angeles‐Shim, Merlyn S. Mendioro, et al.. (2021). Marker-Assisted Introgression and Stacking of Major QTLs Controlling Grain Number (Gn1a) and Number of Primary Branching (WFP) to NERICA Cultivars. Plants. 10(5). 844–844. 30 indexed citations
9.
Makihara, Daigo, et al.. (2020). Sago palm (Metroxylon sagu Rottb.) response to drought condition in terms of leaf gas exchange and chlorophyll a fluorescence. Plant Production Science. 24(1). 65–72. 13 indexed citations
10.
Onyango, John Collins, et al.. (2019). Effect of nitrogen application on the expression of drought-induced root plasticity of upland NERICA rice. Plant Production Science. 22(2). 180–191. 11 indexed citations
11.
Fukuta, Yoshimichi, Seiji Yanagihara, Mitsuhiro Obara, et al.. (2019). Genetic variation of blast (<i>Pyricularia oryzae</i> Cavara) resistance in rice (<i>Oryza sativa</i> L.) accessions widely used in Kenya. Breeding Science. 69(4). 672–679. 6 indexed citations
12.
Sato, Kuniaki, et al.. (2017). An Assessement of Paddy Production System in Central Kenya with Special Reference to Micronutrients. Journal of Agricultural Science. 9(6). 49–49. 2 indexed citations
13.
Murage, Hunja, et al.. (2013). Investigating the impact of rice blast disease on the livelihood of the local farmers in greater Mwea region of Kenya. SpringerPlus. 2(1). 308–308. 75 indexed citations
14.
Makihara, Daigo, et al.. (2001). Plant water relation and silicon concentration in two rice varieties differing in salinity tolerance. Nettai Nogyo/Nettai nougyou. 45(4). 259–265. 5 indexed citations
15.
16.
Makihara, Daigo, et al.. (2001). Evaluation of Salinity Tolerance in Rice. Photosynthesis of Excised Leaves in Relation to Sodium Accumulation.. Japanese Journal of Crop Science. 70(1). 78–83. 4 indexed citations
17.
Makihara, Daigo, et al.. (2001). Effect of Saline Irrigation During Grain-Fillin Period on Dry-Matter Increase of Hulled Rice.. Japanese Journal of Crop Science. 70(1). 71–77. 1 indexed citations
18.
Makihara, Daigo, et al.. (2000). Changes of rice sodium content due to sodium exclusion and transpiration under salinity.. Okayama University Scientific Achievement Repository (Okayama University). 31–37. 2 indexed citations
19.
Tsuda, Makoto, et al.. (2000). The Involvement of Silicon Deposition in Salinity-Induced White Head in Rice (Oryza sativaL.). Plant Production Science. 3(3). 328–334. 8 indexed citations
20.
Makihara, Daigo, et al.. (1999). Effect of Salinity on the Growth and Development of Rice (Oryza sativa L.) Varieties. Nettai Nogyo/Nettai nougyou. 43(4). 285–294. 20 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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