Ming‐Hong Lu

581 total citations
22 papers, 431 citations indexed

About

Ming‐Hong Lu is a scholar working on Plant Science, Insect Science and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Ming‐Hong Lu has authored 22 papers receiving a total of 431 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Plant Science, 12 papers in Insect Science and 5 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Ming‐Hong Lu's work include Insect-Plant Interactions and Control (10 papers), Mosquito-borne diseases and control (5 papers) and Plant Parasitism and Resistance (5 papers). Ming‐Hong Lu is often cited by papers focused on Insect-Plant Interactions and Control (10 papers), Mosquito-borne diseases and control (5 papers) and Plant Parasitism and Resistance (5 papers). Ming‐Hong Lu collaborates with scholars based in China, United Kingdom and Vietnam. Ming‐Hong Lu's co-authors include Gao Hu, Baoping Zhai, Wancai Liu, Feng Zhu, Caitríona E. McInerney, Ka S. Lim, Guihua Chen, Fang Lü, Xiaoxi Zhang and Jason W. Chapman and has published in prestigious journals such as PLoS ONE, Scientific Reports and Agricultural and Forest Meteorology.

In The Last Decade

Ming‐Hong Lu

21 papers receiving 425 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming‐Hong Lu China 12 292 212 109 105 63 22 431
Zhai Baoping China 9 301 1.0× 194 0.9× 75 0.7× 136 1.3× 76 1.2× 29 442
Babasaheb B. Fand India 14 460 1.6× 312 1.5× 169 1.6× 124 1.2× 77 1.2× 46 612
Zhaozhi Lü China 12 457 1.6× 284 1.3× 156 1.4× 160 1.5× 99 1.6× 63 613
Edwige Amiens‐Desneux France 14 550 1.9× 382 1.8× 103 0.9× 251 2.4× 75 1.2× 20 661
Jochem Bonte Belgium 10 292 1.0× 169 0.8× 77 0.7× 129 1.2× 79 1.3× 18 409
Greg Baker Australia 11 280 1.0× 173 0.8× 120 1.1× 89 0.8× 79 1.3× 19 424
Asaf Sadeh Israel 13 85 0.3× 98 0.5× 51 0.5× 153 1.5× 91 1.4× 26 364
Abbas Ali Zamani Iran 13 525 1.8× 315 1.5× 65 0.6× 207 2.0× 72 1.1× 43 600
Gregory S. Simmons United States 16 482 1.7× 273 1.3× 129 1.2× 148 1.4× 79 1.3× 40 590
James Hereward Australia 13 389 1.3× 309 1.5× 196 1.8× 204 1.9× 86 1.4× 64 603

Countries citing papers authored by Ming‐Hong Lu

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Hong Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ming‐Hong Lu. 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 Ming‐Hong Lu. The network helps show where Ming‐Hong Lu may publish in the future.

Co-authorship network of co-authors of Ming‐Hong Lu

This figure shows the co-authorship network connecting the top 25 collaborators of Ming‐Hong Lu. A scholar is included among the top collaborators of Ming‐Hong Lu 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 Ming‐Hong Lu. Ming‐Hong Lu 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.
2.
He, Binbin, et al.. (2023). Deep spatial and temporal graph convolutional network for rice planthopper population dynamic forecasting. Computers and Electronics in Agriculture. 210. 107868–107868. 5 indexed citations
3.
Liu, Wancai, et al.. (2022). Development of Two Early Forecasting Models for Predicting Incidence of Rice Panicle Blast in China. Phytopathology. 113(3). 448–459.
4.
He, Binbin, et al.. (2022). Spatial and temporal patterns of rice planthopper populations in South and Southwest China. Computers and Electronics in Agriculture. 194. 106750–106750. 8 indexed citations
5.
Zhao, Hongzhi, Fangzheng Zhang, Linhui Chen, & Ming‐Hong Lu. (2020). A Method of Fast Evaluation of an MC Placement for Network-on-Chip. Journal of Circuits Systems and Computers. 30(7). 2150115–2150115. 2 indexed citations
6.
Zhang, Zhiling, et al.. (2020). The response to flooding of two overwintering rice stem borers likely accounts for their changing impacts. Journal of Pest Science. 94(2). 451–461. 8 indexed citations
7.
8.
Hu, Gao, Ming‐Hong Lu, Don R. Reynolds, et al.. (2018). Long-term seasonal forecasting of a major migrant insect pest: the brown planthopper in the Lower Yangtze River Valley. Journal of Pest Science. 92(2). 417–428. 60 indexed citations
9.
WU, Qiu-lin, John K. Westbrook, Gao Hu, et al.. (2018). Multiscale analyses on a massive immigration process of Sogatella furcifera (Horváth) in south-central China: influences of synoptic-scale meteorological conditions and topography. International Journal of Biometeorology. 62(8). 1389–1406. 15 indexed citations
10.
WU, Qiu-lin, Gao Hu, Xiao Chen, et al.. (2018). Migration patterns and winter population dynamics of rice planthoppers in Indochina: New perspectives from field surveys and atmospheric trajectories. Agricultural and Forest Meteorology. 265. 99–109. 23 indexed citations
11.
Wu, Yan, Xiao Chen, Gao Hu, et al.. (2017). The Influence of the Topography of the Ailao Mountains on Congregated Landings of Airborne Sogatella furcifera (Hemiptera: Delphacidae) Populations. Environmental Entomology. 46(4). 747–756. 7 indexed citations
12.
Wu, Yan, Guo Zhang, Xiao Chen, et al.. (2017). The Influence of Sogatella furcifera (Hemiptera: Delphacidae) Migratory Events on the Southern Rice Black-Streaked Dwarf Virus Epidemics. Journal of Economic Entomology. 110(3). 854–864. 11 indexed citations
13.
Wang, Fengying, Fan Yang, Ming‐Hong Lu, et al.. (2017). Determining the migration duration of rice leaf folder (Cnaphalocrocis medinalis (Guenée)) moths using a trajectory analytical approach. Scientific Reports. 7(1). 39853–39853. 34 indexed citations
14.
Ma, Jian, Ming‐Hong Lu, Guijun Wan, et al.. (2017). Brown planthopper Nilaparvata lugens was concentrated at the rear of the typhoon Soudelor in Eastern China in August 2015. Insect Science. 25(5). 916–926. 15 indexed citations
15.
Lu, Ming‐Hong, Xiao Chen, Wancai Liu, et al.. (2017). Swarms of brown planthopper migrate into the lower Yangtze River Valley under strong western Pacific subtropical highs. Ecosphere. 8(10). 19 indexed citations
16.
17.
Wu, Yan, et al.. (2016). Annual Fluctuations of Early Immigrant Populations ofSogatella furcifera(Hemiptera: Delphacidae) in Jiangxi Province, China. Journal of Economic Entomology. 109(4). 1636–1645. 17 indexed citations
18.
Lu, Ming‐Hong, et al.. (2016). A comparison of models for the short-term prediction of rice stripe virus disease and its association with biological and meteorological factors. Acta Ecologica Sinica. 36(3). 166–171. 5 indexed citations
19.
Hu, Gao, Fang Lü, Baoping Zhai, et al.. (2014). Outbreaks of the Brown Planthopper Nilaparvata lugens (Stål) in the Yangtze River Delta: Immigration or Local Reproduction?. PLoS ONE. 9(2). e88973–e88973. 90 indexed citations
20.
Hu, Gao, et al.. (2013). The Influence of Typhoon Khanun on the Return Migration of Nilaparvata lugens (Stål) in Eastern China. PLoS ONE. 8(2). e57277–e57277. 36 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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