Eiji Kanda

711 total citations
28 papers, 528 citations indexed

About

Eiji Kanda is a scholar working on Plant Science, Ecology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Eiji Kanda has authored 28 papers receiving a total of 528 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Plant Science, 9 papers in Ecology and 6 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Eiji Kanda's work include Rice Cultivation and Yield Improvement (9 papers), Spectroscopy and Chemometric Analyses (4 papers) and Climate change impacts on agriculture (4 papers). Eiji Kanda is often cited by papers focused on Rice Cultivation and Yield Improvement (9 papers), Spectroscopy and Chemometric Analyses (4 papers) and Climate change impacts on agriculture (4 papers). Eiji Kanda collaborates with scholars based in Japan, Türkiye and Egypt. Eiji Kanda's co-authors include Hiroyuki Shimono, Yoichi Torigoe, Ichiro Arakawa, Takashi Kobayashi, Masumi Okada, K. Ishiguro, Seiki Takatsuki, Yamato Tsuji, Noboru Machida and Takashi Nakamura and has published in prestigious journals such as Field Crops Research, Biomass and Bioenergy and Crop Science.

In The Last Decade

Eiji Kanda

27 papers receiving 504 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Eiji Kanda Japan	12	276	187	103	103	88	28	528
Jeremy S. Johnson United States	13	108 0.4×	93 0.5×	69 0.7×	50 0.5×	7 0.1×	25	410
Julio Di Rienzo Argentina	12	308 1.1×	93 0.5×	63 0.6×	36 0.3×	7 0.1×	27	501
Sip van Wieren Netherlands	6	74 0.3×	208 1.1×	88 0.9×	21 0.2×	11 0.1×	7	369
Andrea Sciarretta Italy	21	538 1.9×	223 1.2×	245 2.4×	87 0.8×	7 0.1×	71	1.0k
Christian R. González Chile	12	101 0.4×	103 0.6×	171 1.7×	37 0.4×	5 0.1×	101	623
Ivan V. Seryodkin Russia	17	59 0.2×	503 2.7×	73 0.7×	248 2.4×	3 0.0×	80	819
Steve D. Langton United Kingdom	11	30 0.1×	422 2.3×	162 1.6×	54 0.5×	5 0.1×	14	617
Gerardo R. Camilo United States	11	91 0.3×	196 1.0×	219 2.1×	51 0.5×	2 0.0×	34	433
C. A. Gilligan United Kingdom	16	420 1.5×	73 0.4×	120 1.2×	96 0.9×	2 0.0×	27	673
Carlos Fabián Vargas-Mendoza Mexico	16	222 0.8×	73 0.4×	331 3.2×	107 1.0×	2 0.0×	41	549

Countries citing papers authored by Eiji Kanda

Since Specialization

Citations

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

Fields of papers citing papers by Eiji Kanda

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eiji Kanda

This figure shows the co-authorship network connecting the top 25 collaborators of Eiji Kanda. A scholar is included among the top collaborators of Eiji Kanda 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 Eiji Kanda. Eiji Kanda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Yamaguchi, Hiromichi, Eiji Kanda, H. Sekiya, et al.. (2016). Maps Obtained Using Developmental-Stage Models and Mesh Temperature Data to Forecast Heading Dates of Forage Rice Cultivars Direct-seeded in the Tohoku Region. Japanese Journal of Crop Science. 85(2). 193–197.

Kanda, Eiji, et al.. (2016). Assessment of Rice Panicle Blast Disease Using Airborne Hyperspectral Imagery. The Open Agriculture Journal. 10(1). 28–34. 17 indexed citations

Watanabe, Masahiro, et al.. (2013). MIROC5 predictions of Yamase (cold northeasterly winds causing cool summers in northern Japan). Journal of Agricultural Meteorology. 69(3). 117–125. 6 indexed citations

Kanda, Eiji. (2012). An Early-Warning System Against Cool-Weather Damage in Rice Production. 190–200. 1 indexed citations

Hayashi, Yousay, et al.. (2008). Impact of global warming on rice yield in Heilongjiang Province and strategic studies. 17(3). 41–48. 2 indexed citations

Shimono, Hiroyuki & Eiji Kanda. (2008). Does Regional Temperature Difference before the Panicle Initiation Affect the Tolerance for Low Temperature-Induced Sterility in Rice?. Plant Production Science. 11(4). 430–433. 11 indexed citations

Takatsuki, Seiki, et al.. (2007). A comparison of the point-frame method with the frequency method in fecal analysis of an omnivorous mammal, the raccoon dog. Mammal Study. 32(1). 1–5. 9 indexed citations

Kanda, Eiji, et al.. (2007). Lung Worms of Wild Boars in the Western Region of Tokyo, Japan. Journal of Veterinary Medical Science. 69(4). 417–420. 9 indexed citations

Kanda, Eiji, Yoichi Torigoe, Tetsuhisa Miwa, & Takashi Kobayashi. (2007). Estimation of Sterility Percentage Caused by Cool Temperature in Rice Plants Using Nonparametric Regression. Japanese Journal of Crop Science. 76(2). 279–287. 1 indexed citations

10.

Kanda, Eiji, Yoichi Torigoe, & Takashi Kobayashi. (2005). Method of Estimating the Variation of Growth Stages on the Basis of the Regularity of Morphogenesis in Rice Plants. Japanese Journal of Crop Science. 74(3). 276–284. 1 indexed citations

11.

Shibata, Akiko, et al.. (2003). Chorioptic Mange in a Wild Japanese Serow. Journal of Wildlife Diseases. 39(2). 437–440. 7 indexed citations

12.

Kanda, Eiji, et al.. (2003). Ratio of rice reflectance for estimating leaf blast severity with a multispectral radiometer. Journal of General Plant Pathology. 69(1). 17–22. 18 indexed citations

13.

Doi, Rikuo, Hajime Matsuda, Akihiko UCHIDA, et al.. (2003). [Possibility of invasion of Echinococcus into Honshu with pet dogs from Hokkaido and overseas].. PubMed. 50(7). 639–49. 8 indexed citations

14.

Kanda, Eiji, Yoichi Torigoe, & Takashi Kobayashi. (2002). A Simple Model to Predict the Developmental Stages of Rice Panicles Using the Effective Accumulative Temperature.. Japanese Journal of Crop Science. 71(3). 394–402. 8 indexed citations

15.

UCHIDA, Akihiko, et al.. (2001). Epidemiological Surveys of Helminths in Wild Mammals of Central Japan. Journal of the Japan Veterinary Medical Association. 54(8). 635–638. 2 indexed citations

16.

Kobayashi, Takashi, et al.. (2001). Detection of Rice Panicle Blast with Multispectral Radiometer and the Potential of Using Airborne Multispectral Scanners. Phytopathology. 91(3). 316–323. 116 indexed citations

17.

Doi, Rikuo, Eiji Kanda, Naoko Nihei, & Akihiko UCHIDA. (2000). [Occurrence of alveolar hydatid disease (multilocular echinococcosis) outside of Hokkaido and a proposal for its prevention].. PubMed. 47(2). 111–26. 8 indexed citations

18.

Nakagaki, Kazuhide, et al.. (2000). Prevalence of dirofilarial infection in raccoon dogs in Japan. Parasitology International. 49(3). 253–256. 12 indexed citations

19.

Kanda, Eiji, Yoichi Torigoe, & Takashi Kobayashi. (2000). A Model to Estimate the Increase of Leaf Number on the Main Culm of the Rice Plant.. Japanese Journal of Crop Science. 69(4). 540–546. 8 indexed citations

20.

Machida, Noboru, et al.. (1993). Pathology and epidemiology of canine distemper in raccoon dogs (Nyctereutes procyonoides). Journal of Comparative Pathology. 108(4). 383–392. 35 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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