Geng Bai

1.4k total citations
37 papers, 990 citations indexed

About

Geng Bai is a scholar working on Plant Science, Ecology and Global and Planetary Change. According to data from OpenAlex, Geng Bai has authored 37 papers receiving a total of 990 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Plant Science, 15 papers in Ecology and 10 papers in Global and Planetary Change. Recurrent topics in Geng Bai's work include Remote Sensing in Agriculture (15 papers), Smart Agriculture and AI (10 papers) and Irrigation Practices and Water Management (8 papers). Geng Bai is often cited by papers focused on Remote Sensing in Agriculture (15 papers), Smart Agriculture and AI (10 papers) and Irrigation Practices and Water Management (8 papers). Geng Bai collaborates with scholars based in United States, China and Japan. Geng Bai's co-authors include Yufeng Ge, George L. Graef, James C. Schnable, Vincent Stoerger, P. Stephen Baenziger, Waseem Hussain, Haijun Yan, Yeyin Shi, Md. Didarul Islam and Wenan Yuan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of Experimental Botany.

In The Last Decade

Geng Bai

33 papers receiving 961 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Geng Bai United States 13 696 393 148 137 130 37 990
Chengming Sun China 21 845 1.2× 505 1.3× 227 1.5× 279 2.0× 54 0.4× 99 1.3k
Xianju Lu China 17 581 0.8× 175 0.4× 109 0.7× 80 0.6× 134 1.0× 63 869
Benoît Mercatoris Belgium 19 374 0.5× 227 0.6× 143 1.0× 117 0.9× 62 0.5× 50 973
Jiangchuan Fan China 15 593 0.9× 315 0.8× 274 1.9× 90 0.7× 54 0.4× 34 946
Yeyin Shi United States 23 1.1k 1.6× 823 2.1× 436 2.9× 235 1.7× 48 0.4× 80 1.8k
Juan Landivar United States 22 993 1.4× 765 1.9× 498 3.4× 106 0.8× 147 1.1× 59 1.4k
Murilo Maeda United States 17 826 1.2× 794 2.0× 522 3.5× 113 0.8× 53 0.4× 31 1.3k
Jun Ni China 17 540 0.8× 396 1.0× 185 1.3× 139 1.0× 63 0.5× 59 868
Anna Chlingaryan Australia 10 682 1.0× 481 1.2× 176 1.2× 209 1.5× 58 0.4× 22 1.2k

Countries citing papers authored by Geng Bai

Since Specialization
Citations

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

Fields of papers citing papers by Geng Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Geng Bai

This figure shows the co-authorship network connecting the top 25 collaborators of Geng Bai. A scholar is included among the top collaborators of Geng Bai 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 Geng Bai. Geng Bai 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.
Liu, Mingyang, Hailong You, Cong Li, et al.. (2025). An efficient machine learning-enhanced DTCO framework for low-power and high-performance circuit design. SHILAP Revista de lepidopterología. 3(3). 194–209.
2.
3.
Li, Jiating, Yufeng Ge, Laila A. Puntel, et al.. (2024). Devising optimized maize nitrogen stress indices in complex field conditions from UAV hyperspectral imagery. Precision Agriculture. 26(1). 2 indexed citations
4.
5.
Bai, Geng, et al.. (2024). Enhancing estimation of cover crop biomass using field-based high-throughput phenotyping and machine learning models. Frontiers in Plant Science. 14. 1277672–1277672. 6 indexed citations
6.
Sahay, Seema, et al.. (2024). Up-regulation of non-photochemical quenching improves water use efficiency and reduces whole-plant water consumption under drought in Nicotiana tabacum. Journal of Experimental Botany. 75(13). 3959–3972. 11 indexed citations
7.
Bai, Geng, Suat Irmak, Joe D. Luck, et al.. (2024). High-throughput physiological phenotyping of crop evapotranspiration at the plot scale. Field Crops Research. 316. 109507–109507. 4 indexed citations
8.
Heeren, Derek M., et al.. (2023). Toward automated irrigation management with integrated crop water stress index and spatial soil water balance. Precision Agriculture. 24(6). 2223–2247. 10 indexed citations
9.
Li, Cong, Hailong You, Linying Zhang, et al.. (2023). Semi-Supervised Transfer Learning Framework for Aging-Aware Library Characterization. IEEE Transactions on Circuits & Systems II Express Briefs. 71(3). 1156–1160. 2 indexed citations
10.
Yu, Hongfeng, et al.. (2023). Transforming Agriculture with Intelligent Data Management and Insights. 3489–3498. 1 indexed citations
11.
Bai, Geng, et al.. (2023). Goniometer in the air: Enabling BRDF measurement of crop canopies using a cable-suspended plant phenotyping platform. Biosystems Engineering. 230. 344–360. 7 indexed citations
12.
Islam, Md. Didarul, et al.. (2022). Ag-IoT for crop and environment monitoring: Past, present, and future. Agricultural Systems. 203. 103497–103497. 132 indexed citations
13.
Vuran, Mehmet C., et al.. (2022). Millimeter-Wave Agricultural Channel Measurements in Corn and Soybean Fields at Different Growth Stages. 2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting (AP-S/URSI). 6 indexed citations
14.
Wang, Lin, Jiating Li, Lin Zhao, et al.. (2021). Investigate the potential of UAS-based thermal infrared imagery for maize leaf area index estimation. 1–1. 3 indexed citations
15.
Lo, Tsz Him, Daran R. Rudnick, Kendall C. DeJonge, et al.. (2020). Differences in soil water changes and canopy temperature under varying water × nitrogen sufficiency for maize. Irrigation Science. 38(5-6). 519–534. 14 indexed citations
16.
Heeren, Derek M., Daran R. Rudnick, Wayne Woldt, et al.. (2020). Soil Structure and Texture Effects on the Precision of Soil Water Content Measurements with a Capacitance- Based Electromagnetic Sensor. Transactions of the ASABE. 63(1). 141–152. 13 indexed citations
17.
Yuan, Wenan, et al.. (2019). Early Prediction of Soybean Traits through Color and Texture Features of Canopy RGB Imagery. Scientific Reports. 9(1). 14089–14089. 46 indexed citations
18.
Bai, Geng, et al.. (2018). Field-Based Scoring of Soybean Iron Deficiency Chlorosis Using RGB Imaging and Statistical Learning. Frontiers in Plant Science. 9. 1002–1002. 52 indexed citations
19.
Ge, Yufeng, Geng Bai, Vincent Stoerger, & James C. Schnable. (2016). Temporal dynamics of maize plant growth, water use, and leaf water content using automated high throughput RGB and hyperspectral imaging. Computers and Electronics in Agriculture. 127. 625–632. 209 indexed citations
20.
Bai, Geng, Yufeng Ge, Waseem Hussain, P. Stephen Baenziger, & George L. Graef. (2016). A multi-sensor system for high throughput field phenotyping in soybean and wheat breeding. Computers and Electronics in Agriculture. 128. 181–192. 186 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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