Juqing Jia

545 total citations
21 papers, 371 citations indexed

About

Juqing Jia is a scholar working on Plant Science, Molecular Biology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Juqing Jia has authored 21 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Plant Science, 6 papers in Molecular Biology and 2 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Juqing Jia's work include Wheat and Barley Genetics and Pathology (15 papers), Plant Disease Resistance and Genetics (13 papers) and Chromosomal and Genetic Variations (5 papers). Juqing Jia is often cited by papers focused on Wheat and Barley Genetics and Pathology (15 papers), Plant Disease Resistance and Genetics (13 papers) and Chromosomal and Genetic Variations (5 papers). Juqing Jia collaborates with scholars based in China, United States and Australia. Juqing Jia's co-authors include Zhenglin Yang, Huijuan Guo, Haixian Zhan, Xin Li, Xiaojun Zhang, Zhijian Chang, Guangrong Li, Linyi Qiao, Jian Ming Wang and Jie Liu and has published in prestigious journals such as PLoS ONE, International Journal of Molecular Sciences and Frontiers in Plant Science.

In The Last Decade

Juqing Jia

18 papers receiving 366 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Juqing Jia China 11 368 77 72 39 7 21 371
Niharika Mallick India 10 253 0.7× 51 0.7× 70 1.0× 38 1.0× 8 1.1× 36 267
Daxing Xu China 4 221 0.6× 101 1.3× 69 1.0× 31 0.8× 6 0.9× 7 260
Tatiana Suprunova Israel 5 299 0.8× 106 1.4× 52 0.7× 43 1.1× 7 1.0× 7 315
Benoît Darrier France 6 261 0.7× 129 1.7× 64 0.9× 19 0.5× 6 0.9× 8 280
Meicheng Zhao China 8 262 0.7× 84 1.1× 94 1.3× 31 0.8× 14 2.0× 14 285
Sanyang Liu China 2 208 0.6× 83 1.1× 69 1.0× 24 0.6× 4 0.6× 2 238
Monu Kumar India 9 281 0.8× 58 0.8× 108 1.5× 27 0.7× 6 0.9× 18 291
Jianbo Li China 13 371 1.0× 84 1.1× 89 1.2× 47 1.2× 4 0.6× 30 412
Éva Szakács Hungary 14 382 1.0× 75 1.0× 105 1.5× 41 1.1× 10 1.4× 32 401
Zhenglong Ren China 9 312 0.8× 50 0.6× 59 0.8× 19 0.5× 7 1.0× 13 318

Countries citing papers authored by Juqing Jia

Since Specialization
Citations

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

Fields of papers citing papers by Juqing Jia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Juqing Jia

This figure shows the co-authorship network connecting the top 25 collaborators of Juqing Jia. A scholar is included among the top collaborators of Juqing Jia 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 Juqing Jia. Juqing Jia 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, Yuzhuo, Tian Lin, Congcong Shen, et al.. (2025). Identification of Advantaged Genes for Low-Nitrogen-Tolerance-Related Traits in Rice Using a Genome-Wide Association Study. International Journal of Molecular Sciences. 26(12). 5749–5749.
2.
Wang, Yuechen, Juqing Jia, Haigang Wang, et al.. (2025). An optimized protocol for in vitro regeneration and genetic transformation of broomcorn millet. BMC Genomics. 26(1). 725–725.
3.
4.
Zhang, Xiaojun, Jianbo Li, Haixia Guan, et al.. (2022). Molecular cytogenetic characterization of a new wheat-Thinopyrum intermedium homoeologous group-6 chromosome disomic substitution line with resistance to leaf rust and stripe rust. Frontiers in Plant Science. 13. 1006281–1006281. 3 indexed citations
5.
Jiang, Wenxi, Weiguang Yuan, Meijun Zhang, et al.. (2021). A universal karyotypic system for hexaploid and diploid Avena species brings oat cytogenetics into the genomics era. BMC Plant Biology. 21(1). 213–213. 16 indexed citations
6.
Han, Ran, Zhiwei Chen, Jianbo Li, et al.. (2021). Identification and Evaluation of Wheat–Aegilops bicornis Lines with Resistance to Powdery Mildew and Stripe Rust. Plant Disease. 106(3). 864–871. 3 indexed citations
7.
Liu, Kevin X., et al.. (2021). Mating-Type Genes Control Sexual Reproduction, Conidial Germination, and Virulence in Cochliobolus lunatus. Phytopathology. 112(5). 1055–1062. 1 indexed citations
8.
Mishina, Kohei, Juqing Jia, Assaf Distelfeld, et al.. (2020). The Brittle Rachis Trait in Species Belonging to the Triticeae and Its Controlling Genes Btr1 and Btr2. Frontiers in Plant Science. 11. 1000–1000. 13 indexed citations
9.
Jia, Juqing, Xiaojun Zhang, Xin Li, et al.. (2016). Molecular Mapping of the Stripe Rust Resistance Gene Yr69 on Wheat Chromosome 2AS. Plant Disease. 100(8). 1717–1724. 43 indexed citations
10.
Zhan, Haixian, Xiaojun Zhang, Guangrong Li, et al.. (2015). Molecular Characterization of a New Wheat-Thinopyrum intermedium Translocation Line with Resistance to Powdery Mildew and Stripe Rust. International Journal of Molecular Sciences. 16(1). 2162–2173. 20 indexed citations
11.
Zhang, Xiaojun, Xin Li, Juqing Jia, et al.. (2015). Mapping of Powdery Mildew Resistance Gene pmCH89 in a Putative Wheat-Thinopyrum intermedium Introgression Line. International Journal of Molecular Sciences. 16(8). 17231–17244. 9 indexed citations
12.
Zhan, Haixian, Guangrong Li, Xiaojun Zhang, et al.. (2014). Chromosomal Location and Comparative Genomics Analysis of Powdery Mildew Resistance Gene Pm51 in a Putative Wheat-Thinopyrum ponticum Introgression Line. PLoS ONE. 9(11). e113455–e113455. 68 indexed citations
13.
Guo, Huijuan, Xiaojun Zhang, Juqing Jia, et al.. (2013). Molecular Mapping of Powdery Mildew Resistance Gene pmCH83 in a Putative?Wheat- Thinopyrum intermedium Cryptic Introgression Line. ACTA AGRONOMICA SINICA. 39(12). 2107–2107. 1 indexed citations
14.
Liu, Jie, Zhijian Chang, Xiaojun Zhang, et al.. (2012). Putative Thinopyrum intermedium-derived stripe rust resistance gene Yr50 maps on wheat chromosome arm 4BL. Theoretical and Applied Genetics. 126(1). 265–274. 102 indexed citations
15.
Jia, Juqing, et al.. (2011). Characterization of wheat yellow rust resistance geneYr17using EST-SSR and rice syntenic region. Cereal Research Communications. 39(1). 88–99. 22 indexed citations
16.
Jia, Juqing, Guangrong Li, Cheng Liu, Jianping Zhou, & Zhenglin Yang. (2010). New PCR based markers allowed to identify Secale chromatin in wheat-Secale africanum introgression lines. Frontiers in Biology. 5(2). 187–192. 1 indexed citations
17.
Jia, Juqing, Guangrong Li, Cheng Liu, Jianping Zhou, & Zhenglin Yang. (2010). Sequence variations of PDHA1 gene in Triticeae species allow for identifying wheat-alien introgression lines. Frontiers of Agriculture in China. 4(2). 137–144. 4 indexed citations
18.
Liu, Cheng, Guangrong Li, Sunish K. Sehgal, et al.. (2010). Genome relationships in the genus Dasypyrum: evidence from molecular phylogenetic analysis and in situ hybridization. Plant Systematics and Evolution. 288(3-4). 149–156. 19 indexed citations
19.
20.
Li, Guangrong, Cheng Liu, Zixian Zeng, et al.. (2008). Identification of α-gliadin genes in Dasypyrum in relation to evolution and breeding. Euphytica. 165(1). 14 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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