Meichen Feng

1.5k citations
92 papers · 1.1k · h-index 19

Impact in

Papers in

    • Leaf Properties and Growth Measurement 17
    • Wheat and Barley Genetics and Pathology 7
    • Smart Agriculture and AI 7
    • Remote Sensing in Agriculture 38

Meichen Feng

89 papers receiving 1.1k citations

Peers

Meichen Feng
Comparison fields: 5 of 97
  • Analytical Chemistry 317
  • Ecology 513
  • Environmental Engineering 238
  • Plant Science 462
  • Soil Science 118
Replace Wude Yang with:
Wude Yang China
Li He China
Lantao Li China
Xiaohe Gu China
Reddy Pullanagari New Zealand
Fábio Henrique Rojo Baio Brazil
Philippe Vigneault Canada
Jun Ni China
Shanyu Huang China
Ittai Herrmann Israel
Meichen Feng relative to Wude Yang China Wude Yang's profile →
Citations per field
00.5×1.5×
Wude Yang · 1×
Citations per year

Countries citing papers authored by Meichen Feng

Since Specialization
Citations

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

Fields of papers citing papers by Meichen Feng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202164
2 201661
3 201753
4 201944
5 202037
6 201736
7 200936
8 202134
9 202234
10 202332
11 201732
12 202231
13 202129
14 201629
15 202226
16 202124
17 202020
18 202418
19 202118
20 202217

About Meichen Feng

Meichen Feng is a scholar working on Plant Science, Ecology, Analytical Chemistry, Environmental Engineering and Atmospheric Science, having authored 92 papers that have together received 1.1k indexed citations. Recurring topics across this work include Remote Sensing in Agriculture (38 papers), Spectroscopy and Chemometric Analyses (31 papers), Leaf Properties and Growth Measurement (17 papers), Remote Sensing and Land Use (16 papers), Soil Geostatistics and Mapping (13 papers), Wheat and Barley Genetics and Pathology (7 papers), Smart Agriculture and AI (7 papers) and Crop Yield and Soil Fertility (6 papers). The work is most often cited by research in Analytical Chemistry (317 citations), Ecology (513 citations), Environmental Engineering (238 citations), Plant Science (462 citations) and Soil Science (118 citations). Meichen Feng has collaborated with scholars based in China, Pakistan and United States. Frequent co-authors include Wude Yang, Lujie Xiao, Guangwei Ding, Meijun Zhang, Chao Wang, Xiaoyan Song, Hui Sun, Xingxing Qiao, Chenbo Yang and Jingjing Sun. Their work appears in journals such as Computers and Electronics in Agriculture, Frontiers in Plant Science, PLoS ONE, Agronomy and Scientific Reports.

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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