Mito Kokawa

1.0k total citations
79 papers, 791 citations indexed

About

Mito Kokawa is a scholar working on Food Science, Analytical Chemistry and Plant Science. According to data from OpenAlex, Mito Kokawa has authored 79 papers receiving a total of 791 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Food Science, 28 papers in Analytical Chemistry and 16 papers in Plant Science. Recurrent topics in Mito Kokawa's work include Spectroscopy and Chemometric Analyses (26 papers), Food composition and properties (13 papers) and Meat and Animal Product Quality (10 papers). Mito Kokawa is often cited by papers focused on Spectroscopy and Chemometric Analyses (26 papers), Food composition and properties (13 papers) and Meat and Animal Product Quality (10 papers). Mito Kokawa collaborates with scholars based in Japan, United States and Taiwan. Mito Kokawa's co-authors include Yutaka Kitamura, Mizuki Tsuta, Junichi Sugiyama, Kaori Fujita, Md Zohurul Islam, Mario Shibata, Tetsuya Araki, Hiroshi Nabetani, Masatoshi Yoshimura and Po-Yuan Chiang and has published in prestigious journals such as Food Chemistry, Carbohydrate Polymers and Food Hydrocolloids.

In The Last Decade

Mito Kokawa

75 papers receiving 767 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mito Kokawa Japan 15 379 245 205 135 127 79 791
Chengye Ma China 16 371 1.0× 193 0.8× 212 1.0× 108 0.8× 124 1.0× 55 821
Ofelia Gabriela Meza‐Márquez Mexico 15 305 0.8× 232 0.9× 70 0.3× 119 0.9× 196 1.5× 34 762
Changmou Xu United States 12 425 1.1× 82 0.3× 258 1.3× 64 0.5× 103 0.8× 21 778
Mustafa Mortaş Türkiye 16 355 0.9× 99 0.4× 123 0.6× 72 0.5× 191 1.5× 32 636
Xinman Lou China 18 388 1.0× 65 0.3× 136 0.7× 97 0.7× 152 1.2× 35 717
Muhammad Haseeb Ahmad Pakistan 14 255 0.7× 78 0.3× 145 0.7× 48 0.4× 71 0.6× 44 554
Cristina Guimarães Pereira Brazil 11 254 0.7× 147 0.6× 46 0.2× 98 0.7× 132 1.0× 26 524
Marina Contini Italy 10 186 0.5× 151 0.6× 174 0.8× 92 0.7× 52 0.4× 15 522
Wenfei Tian China 14 161 0.4× 163 0.7× 186 0.9× 50 0.4× 68 0.5× 37 560
Valeria Sileoni Italy 21 691 1.8× 87 0.4× 296 1.4× 96 0.7× 153 1.2× 48 1.1k

Countries citing papers authored by Mito Kokawa

Since Specialization
Citations

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

Fields of papers citing papers by Mito Kokawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mito Kokawa

This figure shows the co-authorship network connecting the top 25 collaborators of Mito Kokawa. A scholar is included among the top collaborators of Mito Kokawa 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 Mito Kokawa. Mito Kokawa 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.
2.
Kitamura, Yutaka, et al.. (2023). Utilization of multiple-dilution fluorescence fingerprint facilitates prediction of chemical attributes in spice extracts. Food Chemistry. 438. 138028–138028. 1 indexed citations
3.
Kokawa, Mito, et al.. (2023). Estimation of Apple Mealiness by Means of Laser Scattering Measurement. Food and Bioprocess Technology. 16(11). 2483–2496. 3 indexed citations
4.
Takahashi, Kana, et al.. (2023). A milk coffee flavor lexicon developed based on the perceptions of Japanese consumers and its application to check-all-that-apply questions. Food Science and Technology Research. 29(3). 197–209. 1 indexed citations
5.
Kokawa, Mito, et al.. (2021). Establishment of a cultivation method for sprouted brown rice and elucidation of its functional food characteristics. Food Science and Technology Research. 27(3). 341–349. 2 indexed citations
6.
Kitamura, Yutaka, et al.. (2020). Quantitative and Qualitative Evaluation of Fatty Acids in Coffee Oil and Coffee Residue. Food Science and Technology Research. 26(4). 545–552. 6 indexed citations
7.
Shibata, Mario, et al.. (2018). Manufacturing Condition Effects on Dynamic Viscoelastic Properties of High-amylose Rice Gel by High-speed Shear Treatment. Food Science and Technology Research. 24(4). 739–746. 2 indexed citations
8.
Kokawa, Mito, et al.. (2017). The Effects of Mixing and Fermentation Times on Chemical and Physical Properties of White Pan Bread. Food Science and Technology Research. 23(2). 181–191. 9 indexed citations
9.
Li, Xinyue, Mito Kokawa, & Yutaka Kitamura. (2017). Formation of Phosphatidic Acid in Japanese Mustard Spinach (Komatsuna) during the Milling Process. Food Science and Technology Research. 23(4). 517–523. 7 indexed citations
10.
Sugiyama, Junichi, et al.. (2017). Effect of Emulsification on the Physical Properties of High-amylose Rice Gel. Food Science and Technology Research. 23(2). 221–228. 4 indexed citations
11.
Nakamura, Misaki, Yutaka Kitamura, & Mito Kokawa. (2016). Development of a Cheese-type Food Using Rice Milk. Food Science and Technology Research. 22(5). 605–609. 12 indexed citations
12.
Kokawa, Mito, et al.. (2015). Measuring Cheese Maturation with the Fluorescence Fingerprint. Food Science and Technology Research. 21(4). 549–555. 10 indexed citations
13.
Fujita, Kaori, Junichi Sugiyama, Mizuki Tsuta, et al.. (2013). Detection of Aflatoxins B1, B2, G1 and G2 in Nutmeg Extract Using Fluorescence Fingerprint. Food Science and Technology Research. 19(4). 539–545. 12 indexed citations
14.
Kokawa, Mito, Junichi Sugiyama, Mizuki Tsuta, et al.. (2013). Fluorescence Fingerprint Imaging of Gluten and Starch in Wheat Flour Dough with Consideration of Total Constituent Ratio. Food Science and Technology Research. 19(6). 933–938. 2 indexed citations
15.
Shibata, Mario, Mizuki Tsuta, Junichi Sugiyama, et al.. (2013). Image Analysis of Bread Crumb Structure in Relation to Mechanical Properties. International Journal of Food Engineering. 9(1). 115–120. 6 indexed citations
16.
Fujita, Kaori, Junichi Sugiyama, Mizuki Tsuta, et al.. (2012). Nondestructive Method for Detection of Mycotoxins in Wheat. Agricultural Information Research. 21(1). 11–19. 2 indexed citations
17.
Shibata, Mario, Junichi Sugiyama, Kaori Fujita, et al.. (2012). Effect of Amylose Content of Rice on the Physical Properties of Rice Porridge Bread. Nippon Shokuhin Kagaku Kogaku Kaishi. 59(10). 503–508. 2 indexed citations
18.
Shibata, Mario, Junichi Sugiyama, Chia-Ling Tsai, et al.. (2011). Viscoelastic Properties and Air-bubble Structure of Bread Containing Gelatinized Rice Porridge. Nippon Shokuhin Kagaku Kogaku Kaishi. 58(5). 196–201. 4 indexed citations
19.
Shibata, Mario, Junichi Sugiyama, Mizuki Tsuta, et al.. (2010). Development of Quantitative Analysis for Relationships between Viscoelasticity and Air-bubble Structure of Bread. Nippon Shokuhin Kagaku Kogaku Kaishi. 57(7). 296–303. 1 indexed citations
20.
Sugiyama, Takehiro, Kaori Fujita, Mizuki Tsuta, et al.. (2010). Prediction for Mixture Rate of Buckwheat Flour Against Wheat Flour Using Excitation-emission Matrix (EEM). Nippon Shokuhin Kagaku Kogaku Kaishi. 57(6). 238–242. 5 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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