Xiaoning Dai

668 citations
8 papers · 249 · h-index 7

Impact in

  • Food Science top 10%
    • Proteins in Food Systems
    • Microencapsulation and Drying Processes
    • Polysaccharides Composition and Applications
    • Additive Manufacturing and 3D Printing Technologies

Papers in

    • Protein Hydrolysis and Bioactive Peptides 4
    • Plant biochemistry and biosynthesis 1
    • Metabolomics and Mass Spectrometry Studies 1
    • Proteins in Food Systems 4
    • Microencapsulation and Drying Processes 2

Xiaoning Dai

8 papers receiving 244 citations

Peers

Xiaoning Dai
Comparison fields: 5 of 57
  • Food Science 107
  • Automotive Engineering 62
  • Animal Science and Zoology 32
  • Pharmacology 23
  • Biomaterials 31
Replace Anica Bebek Markovinović with:
Anica Bebek Markovinović Croatia
Shijian Dong China
Jinxin Yan China
Gaopeng Zhang China
Marta Vinha Vieira Portugal
Fangfang Yuan China
Jianchun Han China
Andrea Sarrica Italy
Qian Lin China
Hayam M. Abbas Egypt
Xiaoning Dai relative to Anica Bebek Markovinović Croatia Anica Bebek Markovinović's profile →
Citations per field
00.5×1.5×2.3×
Anica Bebek Markovinović · 1×
Citations per year

Countries citing papers authored by Xiaoning Dai

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoning Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Xiaoning Dai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiaoning Dai Line = papers co-authored together Xiaoning Dai links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 201895
2 199641
3 201838
4 202036
5 202016
6 202014
7 20187
8 20172

About Xiaoning Dai

Xiaoning Dai is a scholar working on Molecular Biology, Food Science, Biotechnology, Automotive Engineering and Pharmacology, having authored 8 papers that have together received 249 indexed citations. Recurring topics across this work include Proteins in Food Systems (4 papers), Protein Hydrolysis and Bioactive Peptides (4 papers), Enzyme Production and Characterization (2 papers), Microencapsulation and Drying Processes (2 papers), Electrospun Nanofibers in Biomedical Applications (1 paper), Insect and Arachnid Ecology and Behavior (1 paper), Plant biochemistry and biosynthesis (1 paper) and Metabolomics and Mass Spectrometry Studies (1 paper). The work is most often cited by research in Food Science (107 citations), Automotive Engineering (62 citations), Animal Science and Zoology (32 citations), Pharmacology (23 citations) and Biomaterials (31 citations). Xiaoning Dai has collaborated with scholars based in China, Australia and Japan. Frequent co-authors include Yuanyuan Meng, Yang Zhu, Lili Liu, Lili Liu, Sangeeta Prakash, Takashi Kudo, Li Yu, Daisuke Tomura, Hirofumi Shoun and Yunfeng Xu. Their work appears in journals such as International Journal of Food Properties, Food and Bioprocess Technology, Food Science and Human Wellness, Journal of Food Processing and Preservation and Biochimie.

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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