Pengshan Zhao

527 total citations
32 papers, 413 citations indexed

About

Pengshan Zhao is a scholar working on Plant Science, Genetics and Molecular Biology. According to data from OpenAlex, Pengshan Zhao has authored 32 papers receiving a total of 413 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Plant Science, 9 papers in Genetics and 8 papers in Molecular Biology. Recurrent topics in Pengshan Zhao's work include Plant Stress Responses and Tolerance (7 papers), Plant responses to water stress (6 papers) and GABA and Rice Research (5 papers). Pengshan Zhao is often cited by papers focused on Plant Stress Responses and Tolerance (7 papers), Plant responses to water stress (6 papers) and GABA and Rice Research (5 papers). Pengshan Zhao collaborates with scholars based in China, Kazakhstan and United States. Pengshan Zhao's co-authors include Guoxiong Chen, Xin Zhao, Xiaofei Ma, Ji‐Wei Zhang, Qin Zhou, Heng Liu, Yong Shi, Fei Liu, Zheng Guo-chang and Pengfei Jia and has published in prestigious journals such as PLoS ONE, International Journal of Molecular Sciences and Journal of Experimental Botany.

In The Last Decade

Pengshan Zhao

29 papers receiving 404 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pengshan Zhao China 13 279 158 56 46 32 32 413
Xiaolong Huang China 15 466 1.7× 291 1.8× 60 1.1× 25 0.5× 31 1.0× 32 598
Kaede C. Wada Japan 14 559 2.0× 285 1.8× 50 0.9× 23 0.5× 27 0.8× 21 657
Yan Zhuang China 8 307 1.1× 182 1.2× 54 1.0× 14 0.3× 32 1.0× 11 459
Xing Han China 15 535 1.9× 210 1.3× 27 0.5× 90 2.0× 11 0.3× 43 681
Hongxing Xiao China 14 199 0.7× 243 1.5× 101 1.8× 43 0.9× 19 0.6× 37 459
Maren E. Veatch‐Blohm United States 9 369 1.3× 107 0.7× 66 1.2× 44 1.0× 7 0.2× 22 472
Songfeng Diao China 12 243 0.9× 253 1.6× 35 0.6× 24 0.5× 9 0.3× 42 408
Md. Motiar Rohman Bangladesh 14 537 1.9× 92 0.6× 40 0.7× 26 0.6× 25 0.8× 54 606
Lidia López‐Serrano Spain 8 379 1.4× 105 0.7× 14 0.3× 28 0.6× 15 0.5× 14 463
Qianqian Li China 11 457 1.6× 173 1.1× 14 0.3× 41 0.9× 15 0.5× 25 541

Countries citing papers authored by Pengshan Zhao

Since Specialization
Citations

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

Fields of papers citing papers by Pengshan Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pengshan Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Pengshan Zhao. A scholar is included among the top collaborators of Pengshan Zhao 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 Pengshan Zhao. Pengshan Zhao 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.
Li, Xiaofeng, et al.. (2025). Monocot-like leaf structure and trichome-water relations in early growth stages of the C3 plant sand rice (Agriophyllum squarrosum). Plant Science. 355. 112480–112480. 1 indexed citations
2.
3.
Yang, Yi, Xin Liang, Nawal Shrestha, et al.. (2025). PyNCBIminer: A platform for assembling phylogenetic data sets via GenBank datamining. Journal of Systematics and Evolution. 63(4). 851–860.
4.
Liu, Nannan, Zhilan Wang, Xianyu Meng, et al.. (2025). Dietary non-forage fiber sources and starch levels: Effects on growth, meat fatty acid composition, and rumen bacterial community of fattening lambs. Animal Feed Science and Technology. 324. 116340–116340.
5.
Zhao, Pengshan, Hong Sun, Yujie Liu, et al.. (2023). Sand rice, a promising future crop for desert and marginal lands in northern China. 2(4). 260–265. 3 indexed citations
6.
Li, Xiaofeng, et al.. (2023). Tricotyledony in sand rice (Agriophyllum squarrosum). Genetic Resources and Crop Evolution. 71(1). 529–537. 3 indexed citations
7.
Zhao, Pengshan, et al.. (2022). Precipitation and local environment shape the geographic variation of seed size across natural populations of sand rice (Agriophyllum squarrosum). Journal of Experimental Botany. 73(16). 5682–5697. 6 indexed citations
8.
Абугалиева, Сауле, et al.. (2020). SSR-based evaluation of genetic diversity in populations of Agriophyllum squarrosum L. and Agriophyllum minus Fisch. & Mey. collected in South-East Kazakhstan. Vavilov Journal of Genetics and Breeding. 24(7). 697–704. 2 indexed citations
9.
Zhang, Ji‐Wei, et al.. (2018). Synteny-based mapping of causal point mutations relevant to sand rice (Agriophyllum squarrosum) trichomeless1 mutant by RNA-sequencing. Journal of Plant Physiology. 231. 86–95. 12 indexed citations
10.
Zhao, Pengshan, et al.. (2017). Transcriptional responses to phosphate starvation in Brachypodium distachyon roots. Plant Physiology and Biochemistry. 122. 113–120. 13 indexed citations
11.
Zhao, Pengshan, Ji‐Wei Zhang, Chaoju Qian, et al.. (2017). SNP Discovery and Genetic Variation of Candidate Genes Relevant to Heat Tolerance and Agronomic Traits in Natural Populations of Sand Rice (Agriophyllum squarrosum). Frontiers in Plant Science. 8. 536–536. 20 indexed citations
12.
Zhao, Pengshan, Lirong Wang, Xin Zhao, Guoxiong Chen, & Xiaofei Ma. (2017). A comparative transcriptomic analysis reveals the core genetic components of salt and osmotic stress responses in Braya humilis. PLoS ONE. 12(8). e0183778–e0183778. 3 indexed citations
13.
Zhao, Pengshan, Ji‐Wei Zhang, Xin Zhao, Guoxiong Chen, & Xiaofei Ma. (2016). Different Sets of Post-Embryonic Development Genes Are Conserved or Lost in Two Caryophyllales Species (Reaumuria soongorica and Agriophyllum squarrosum). PLoS ONE. 11(1). e0148034–e0148034. 5 indexed citations
14.
Wang, Lirong, et al.. (2016). Physiological adaptations to osmotic stress and characterization of a polyethylene glycol-responsive gene in Braya humilis. Acta Societatis Botanicorum Poloniae. 85(1). 4 indexed citations
15.
Zhao, Pengshan, Salvador Capella-Gutiérrez, Yong Shi, et al.. (2014). Transcriptomic analysis of a psammophyte food crop, sand rice (Agriophyllum squarrosum) and identification of candidate genes essential for sand dune adaptation. BMC Genomics. 15(1). 872–872. 29 indexed citations
16.
Zhao, Pengshan & Lu Jin. (2013). MAIGO2 is involved in gibberellic acid, sugar, and heat shock responses during germination and seedling development in Arabidopsis. Acta Physiologiae Plantarum. 36(2). 315–321. 6 indexed citations
17.
Shi, Yong, Yan Xia, Pengshan Zhao, et al.. (2013). Transcriptomic Analysis of a Tertiary Relict Plant, Extreme Xerophyte Reaumuria soongorica to Identify Genes Related to Drought Adaptation. PLoS ONE. 8(5). e63993–e63993. 56 indexed citations
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19.
20.
Zhao, Pengshan, Fei Liu, Zheng Guo-chang, & Heng Liu. (2010). Group 3 late embryogenesis abundant protein in Arabidopsis: structure, regulation, and function. Acta Physiologiae Plantarum. 33(4). 1063–1073. 15 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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