Fade Li

588 citations
43 papers · 421 indexed · h-index 11

Impact in

Papers in

Fade Li

41 papers receiving 409 citations

Peers

Fade Li
Comparison fields: 5 of 78
  • Physiology 56
  • Biotechnology 88
  • Food Science 142
  • Small Animals 37
  • Animal Science and Zoology 34
Replace C.J. Schaschke with:
C.J. Schaschke United Kingdom
Tim Brown United Kingdom
Israel Muñoz Spain
K. Ratish Ramanan India
L. E. Stetson United States
A. O. Raji Nigeria
S.M. Shafaei Iran
Howard Q. Zhang United States
Fatih Kalkan Türkiye
D.J. van Zuilichem Netherlands
Fade Li relative to C.J. Schaschke United Kingdom C.J. Schaschke's profile →
Citations per field
00.5×10×15×18.5×
C.J. Schaschke · 1×
Citations per year

Countries citing papers authored by Fade Li

Since Specialization
Citations

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

Fields of papers citing papers by Fade Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200365
2 200553
3 202233
4 201632
5 200529
6 202129
7 201519
8 201519
9 202214
10 202111
11 202011
12 20129
13 20229
14 20228
15 20218
16
Effects of frequency and voltage of high voltage pulsed electric field on improving vigor of aged cotton seed.
20176
17 20216
18 20245
19
Physiological mechanisms of improving rice ('Oryza sativa' L.) seed vigor through arc-tooth-shaped corona discharge field treatment
20145
20 20205

About Fade Li

Fade Li is a scholar working on Mechanical Engineering, Plant Science, Physiology, Civil and Structural Engineering and Biotechnology, having authored 43 papers that have together received 421 indexed citations. Recurring topics across this work include Magnetic and Electromagnetic Effects (10 papers), Soil Mechanics and Vehicle Dynamics (9 papers), Microbial Inactivation Methods (7 papers), Agricultural Engineering and Mechanization (7 papers), Granular flow and fluidized beds (4 papers), Food Supply Chain Traceability (3 papers), Smart Agriculture and AI (3 papers) and Plant Genetic and Mutation Studies (3 papers). The work is most often cited by research in Physiology (56 citations), Biotechnology (88 citations), Food Science (142 citations), Small Animals (37 citations) and Animal Science and Zoology (34 citations). Fade Li has collaborated with scholars based in China, Japan and Australia. Frequent co-authors include LI Li-te, Eizo Tatsumi, Jianfeng Sun, Zaigui Li, Yinfa Yan, Zhenwei Yu, Guoliang Jia, Hui Xu, Yuehua Liu and Benhai Xiong. Their work appears in journals such as Journal of Food Science, IEEE Access, Applied Sciences, Journal of Food Engineering and Energy.

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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