Dandan Pu

2.0k citations
42 papers · 1.5k · 1 hit paper · h-index 20

Impact in

Papers in

Dandan Pu

41 papers receiving 1.5k citations

Dandan Pu's Hit Papers

Recent advances and application of machine learning in food flavor prediction and regulation 2023 · 140 citations
1400+1+2Years since publication4080120

Peers

Dandan Pu
Comparison fields: 5 of 94
  • Sensory Systems 215
  • Nutrition and Dietetics 602
  • Animal Science and Zoology 415
  • Biochemistry 208
  • Food Science 653
Replace Philippe Pollien with:
Philippe Pollien Switzerland
Shuang Bi China
Deborah D. Roberts Switzerland
Tingting Zou China
E. Guichard France
Elisabeth Guichard France
Haiyan Yu China
María Ángeles Pozo‐Bayón Spain
Monika Christlbauer Germany
Dandan Pu relative to Philippe Pollien Switzerland Philippe Pollien's profile →
Citations per field
00.5×10×14.3×
Philippe Pollien · 1×
Citations per year

Countries citing papers authored by Dandan Pu

Since Specialization
Citations

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

Fields of papers citing papers by Dandan Pu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Dandan Pu, 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 Dandan Pu Line = papers co-authored together Dandan Pu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Recent advances and application of machine learning in food flavor prediction and regulation
Hit paper breakdown →
2023140
2 2022132
3 2018129
4 202092
5 202390
6 202088
7 202288
8 201982
9 202067
10 202064
11 202263
12 202254
13 201951
14 202043
15 202341
16 201933
17 202431
18 202031
19 202227
20 202426

About Dandan Pu

Dandan Pu is a scholar working on Nutrition and Dietetics, Biomedical Engineering, Animal Science and Zoology, Food Science and Sensory Systems, having authored 42 papers that have together received 1.5k indexed citations. Recurring topics across this work include Biochemical Analysis and Sensing Techniques (22 papers), Advanced Chemical Sensor Technologies (21 papers), Meat and Animal Product Quality (19 papers), Fermentation and Sensory Analysis (13 papers), Olfactory and Sensory Function Studies (12 papers), Sensory Analysis and Statistical Methods (6 papers), Phytochemicals and Antioxidant Activities (3 papers) and Plant biochemistry and biosynthesis (2 papers). The work is most often cited by research in Sensory Systems (215 citations), Nutrition and Dietetics (602 citations), Animal Science and Zoology (415 citations), Biochemistry (208 citations) and Food Science (653 citations). Dandan Pu has collaborated with scholars based in China, Hong Kong and Macao. Frequent co-authors include Yuyu Zhang, Baoguo Sun, Fazheng Ren, Haitao Chen, Yizhuang Tang, Yan Huang, Huiying Zhang, Yimeng Shan, Huiying Zhang and Lili Zhang. Their work appears in journals such as Foods, Food Chemistry, Food Research International, Journal of Agricultural and Food Chemistry and Journal of Food Processing and Preservation.

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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