Ming‐Hsin Lai

547 total citations
23 papers, 354 citations indexed

About

Ming‐Hsin Lai is a scholar working on Plant Science, Ecology and Cell Biology. According to data from OpenAlex, Ming‐Hsin Lai has authored 23 papers receiving a total of 354 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Plant Science, 6 papers in Ecology and 6 papers in Cell Biology. Recurrent topics in Ming‐Hsin Lai's work include Remote Sensing in Agriculture (6 papers), Plant Pathogens and Fungal Diseases (6 papers) and Smart Agriculture and AI (6 papers). Ming‐Hsin Lai is often cited by papers focused on Remote Sensing in Agriculture (6 papers), Plant Pathogens and Fungal Diseases (6 papers) and Smart Agriculture and AI (6 papers). Ming‐Hsin Lai collaborates with scholars based in Taiwan, India and Philippines. Ming‐Hsin Lai's co-authors include Dong‐Hong Wu, Chin-Ying Yang, Ming‐Der Yang, Yu‐Chun Hsu, Men-Chi Chang, Hung‐Chi Chen, Chia‐Lin Chung, Wei-Cheng Tseng, Hsin-Hung Tseng and Szu‐Yu Chen and has published in prestigious journals such as PLoS ONE, International Journal of Molecular Sciences and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Ming‐Hsin Lai

23 papers receiving 348 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‐Hsin Lai Taiwan 13 295 83 64 55 39 23 354
Brian L. Lehman United States 12 402 1.4× 98 1.2× 128 2.0× 125 2.3× 21 0.5× 20 509
Kaijie Xu China 11 310 1.1× 69 0.8× 55 0.9× 30 0.5× 95 2.4× 16 347
Max Feldman United States 8 428 1.5× 121 1.5× 100 1.6× 26 0.5× 98 2.5× 18 529
Komaki Inoue Japan 14 480 1.6× 190 2.3× 71 1.1× 30 0.5× 80 2.1× 25 658
Conghao Wang China 6 239 0.8× 55 0.7× 139 2.2× 44 0.8× 23 0.6× 8 313
Sally Vail Canada 15 364 1.2× 58 0.7× 96 1.5× 36 0.7× 11 0.3× 38 470
Maximilian J. Feldman United States 5 202 0.7× 52 0.6× 75 1.2× 15 0.3× 48 1.2× 6 257
Kristina Petrović Serbia 12 279 0.9× 50 0.6× 46 0.7× 145 2.6× 20 0.5× 35 330
Afef Marzougui United States 10 209 0.7× 20 0.2× 133 2.1× 28 0.5× 24 0.6× 15 291
J. Melichar United Kingdom 7 463 1.6× 60 0.7× 97 1.5× 62 1.1× 120 3.1× 7 507

Countries citing papers authored by Ming‐Hsin Lai

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Hsin Lai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming‐Hsin Lai

This figure shows the co-authorship network connecting the top 25 collaborators of Ming‐Hsin Lai. A scholar is included among the top collaborators of Ming‐Hsin Lai 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‐Hsin Lai. Ming‐Hsin Lai 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.
Chang, Che-Hao, et al.. (2024). Hybrid Deep Neural Networks with Multi-Tasking for Rice Yield Prediction Using Remote Sensing Data. Agriculture. 14(4). 513–513. 10 indexed citations
2.
Yang, Ming‐Der, Yu‐Chun Hsu, Wei-Cheng Tseng, Hsin-Hung Tseng, & Ming‐Hsin Lai. (2024). Precision assessment of rice grain moisture content using UAV multispectral imagery and machine learning. Computers and Electronics in Agriculture. 230. 109813–109813. 13 indexed citations
3.
Chang, Yen‐Jen, et al.. (2024). Target-Aware Yield Prediction (TAYP) Model Used to Improve Agriculture Crop Productivity. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–11. 1 indexed citations
4.
Wu, Dong‐Hong, Shou‐Horng Huang, Menghsiao Meng, et al.. (2023). The Bph45 Gene Confers Resistance against Brown Planthopper in Rice by Reducing the Production of Limonene. International Journal of Molecular Sciences. 24(2). 1798–1798. 12 indexed citations
5.
Chen, Szu‐Yu, Ming‐Hsin Lai, Dong‐Hong Wu, et al.. (2023). Identification of qBK2.1, a novel QTL controlling rice resistance against Fusarium fujikuroi. Botanical studies. 64(1). 11–11. 2 indexed citations
6.
Wu, Dong‐Hong, et al.. (2022). Controlling the lodging risk of rice based on a plant height dynamic model. Botanical studies. 63(1). 25–25. 23 indexed citations
7.
8.
Yang, Ming‐Der, Yu‐Chun Hsu, Wei-Cheng Tseng, et al.. (2021). Assessment of Grain Harvest Moisture Content Using Machine Learning on Smartphone Images for Optimal Harvest Timing. Sensors. 21(17). 5875–5875. 13 indexed citations
9.
Yang, Ming‐Der, Hsin-Hung Tseng, Yu‐Chun Hsu, et al.. (2021). A UAV Open Dataset of Rice Paddies for Deep Learning Practice. Remote Sensing. 13(7). 1358–1358. 34 indexed citations
10.
Wu, Cheng‐Chieh, et al.. (2020). Studies of rice Hd1 haplotypes worldwide reveal adaptation of flowering time to different environments. PLoS ONE. 15(9). e0239028–e0239028. 20 indexed citations
11.
Chen, Szu‐Yu, et al.. (2020). Transcriptome Analysis of Early Defenses in Rice against Fusarium fujikuroi. Rice. 13(1). 65–65. 20 indexed citations
12.
Yang, Chin-Ying, Ming‐Der Yang, Wei-Cheng Tseng, et al.. (2020). Assessment of Rice Developmental Stage Using Time Series UAV Imagery for Variable Irrigation Management. Sensors. 20(18). 5354–5354. 27 indexed citations
13.
Chen, Szu‐Yu, Chun‐Wei Liu, Dong‐Hong Wu, et al.. (2020). Invasion and Colonization Pattern of Fusarium fujikuroi in Rice. Phytopathology. 110(12). 1934–1945. 14 indexed citations
14.
Chen, Szu‐Yu, Ming‐Hsin Lai, Chih‐Wei Tung, et al.. (2019). Genome-wide association mapping of gene loci affecting disease resistance in the rice-Fusarium fujikuroi pathosystem. Rice. 12(1). 85–85. 14 indexed citations
15.
Lin, Yan‐Cheng, et al.. (2019). Studies of a rice sterile mutant sstl from the TRIM collection. Botanical studies. 60(1). 12–12. 4 indexed citations
16.
Wu, Dong‐Hong, David R. Gealy, Melissa H. Jia, et al.. (2019). Phylogenetic origin and dispersal pattern of Taiwan weedy rice. Pest Management Science. 76(5). 1639–1651. 8 indexed citations
17.
18.
Chen, Hung‐Chi, Pei‐Chun Liao, Wan‐Hsing Cheng, et al.. (2017). The function of OsbHLH068 is partially redundant with its homolog, AtbHLH112, in the regulation of the salt stress response but has opposite functions to control flowering in Arabidopsis. Plant Molecular Biology. 94(4-5). 531–548. 46 indexed citations
19.
Wu, Hshin‐Ping, Fu‐Jin Wei, Cheng‐Chieh Wu, et al.. (2017). Large-scale phenomics analysis of a T-DNA tagged mutant population. GigaScience. 6(8). 1–7. 8 indexed citations
20.
Wei, Fu‐Jin, Yuan Chen, Hshin‐Ping Wu, et al.. (2016). Lack of Genotype and Phenotype Correlation in a Rice T-DNA Tagged Line Is Likely Caused by Introgression in the Seed Source. PLoS ONE. 11(5). e0155768–e0155768. 5 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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