Danying Xing

548 total citations
24 papers, 403 citations indexed

About

Danying Xing is a scholar working on Plant Science, Genetics and Soil Science. According to data from OpenAlex, Danying Xing has authored 24 papers receiving a total of 403 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Plant Science, 9 papers in Genetics and 3 papers in Soil Science. Recurrent topics in Danying Xing's work include Rice Cultivation and Yield Improvement (13 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers) and GABA and Rice Research (6 papers). Danying Xing is often cited by papers focused on Rice Cultivation and Yield Improvement (13 papers), Genetic Mapping and Diversity in Plants and Animals (9 papers) and GABA and Rice Research (6 papers). Danying Xing collaborates with scholars based in China, Philippines and France. Danying Xing's co-authors include Jianlong Xu, Xianjin Qiu, Yunlong Pang, Yajun Zhu, Shaobing Peng, Congcong Shen, Zhihua Yuan, Guoyou Ye, Yunbo Zhang and Xiuqin Zhao and has published in prestigious journals such as PLoS ONE, Theoretical and Applied Genetics and Sustainability.

In The Last Decade

Danying Xing

24 papers receiving 394 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Danying Xing China 11 364 152 37 28 28 24 403
Janete Mariza Adamski Brazil 9 376 1.0× 83 0.5× 13 0.4× 105 3.8× 23 0.8× 16 427
Rosario Jimenez Philippines 6 339 0.9× 55 0.4× 29 0.8× 41 1.5× 44 1.6× 7 392
Zunxin Wang China 10 280 0.8× 43 0.3× 54 1.5× 75 2.7× 17 0.6× 14 317
Prafulla K. Behera India 9 339 0.9× 43 0.3× 10 0.3× 26 0.9× 26 0.9× 25 402
Hua Duan China 7 324 0.9× 30 0.2× 38 1.0× 27 1.0× 56 2.0× 8 368
Chandrapal Vishwakarma India 7 249 0.7× 33 0.2× 33 0.9× 30 1.1× 13 0.5× 13 289
Natalija Kravić Serbia 9 217 0.6× 63 0.4× 18 0.5× 25 0.9× 18 0.6× 53 266
Hanjing Sha China 8 343 0.9× 48 0.3× 10 0.3× 57 2.0× 21 0.8× 17 375
Rory Hayden United Kingdom 9 522 1.4× 47 0.3× 45 1.2× 89 3.2× 66 2.4× 14 588
Cemal Yücel Türkiye 5 449 1.2× 52 0.3× 74 2.0× 26 0.9× 147 5.3× 6 483

Countries citing papers authored by Danying Xing

Since Specialization
Citations

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

Fields of papers citing papers by Danying Xing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danying Xing

This figure shows the co-authorship network connecting the top 25 collaborators of Danying Xing. A scholar is included among the top collaborators of Danying Xing 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 Danying Xing. Danying Xing 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.
Hu, Fengqin, et al.. (2023). Selenium and Nitrogen Fertilizer Management Improves Potato Root Function, Photosynthesis, Yield and Selenium Enrichment. Sustainability. 15(7). 6060–6060. 10 indexed citations
2.
Wang, Wenxi, Fan Zhang, Dapu Liu, et al.. (2022). Distribution characteristics of selenium, cadmium and arsenic in rice grains and their genetic dissection by genome-wide association study. Frontiers in Genetics. 13. 1007896–1007896. 6 indexed citations
3.
4.
Li, Xiaoxiao, Jing Cao, Jianliang Huang, Danying Xing, & Shaobing Peng. (2021). Effects of topsoil removal on nitrogen uptake, biomass accumulation, and yield formation in puddled-transplanted rice. Field Crops Research. 265. 108130–108130. 14 indexed citations
5.
Qiu, Xianjin, et al.. (2020). Genome-wide association mapping for grain shape in rice accessions.. International Journal of Agriculture and Biology. 23(3). 582–588. 2 indexed citations
6.
7.
Zhang, Jian, Hui Hu, Danying Xing, et al.. (2018). Identification of QTLs for yield-related traits using two sets of introgression lines with a common donor parent in rice.. International Journal of Agriculture and Biology. 20(1). 15–24. 4 indexed citations
8.
Qiu, Xianjin, Kai Chen, Yajun Zhu, et al.. (2017). Examining two sets of introgression lines reveals background-independent and stably expressed QTL that improve grain appearance quality in rice (Oryza sativa L.). Theoretical and Applied Genetics. 130(5). 951–967. 31 indexed citations
9.
Shen, Congcong, et al.. (2017). Identification and Evaluation of Blast Resistance for Resequenced Rice Core Collections. ACTA AGRONOMICA SINICA. 43(6). 795–795. 2 indexed citations
10.
Wang, Meng, et al.. (2016). Effects of combined application of selenium, nitrogen, phosphorus and potassium fertilizers on growth and selenium absorption in rice at vegetative period. 47(12). 2046. 1 indexed citations
11.
Liu, Huan, Yajun Zhu, Xianjin Qiu, et al.. (2016). QTL underlying iron and zinc toxicity tolerances at seedling stage revealed by two sets of reciprocal introgression populations of rice ( Oryza sativa L.). The Crop Journal. 4(4). 280–289. 17 indexed citations
12.
Qiu, Xianjin, Yunlong Pang, Zhihua Yuan, et al.. (2015). Genome-Wide Association Study of Grain Appearance and Milling Quality in a Worldwide Collection of Indica Rice Germplasm. PLoS ONE. 10(12). e0145577–e0145577. 60 indexed citations
13.
Chen, Kai, et al.. (2015). Genetic Dissection of Grain Chalkiness in Indica Mini-core Germplasm Using Genome-wide Association Method. ACTA AGRONOMICA SINICA. 41(7). 1007–1016. 1 indexed citations
14.
Qiu, Xianjin, Zhihua Yuan, Huan Liu, et al.. (2015). Identification of salt tolerance‐improving quantitative trait loci alleles from a salt‐susceptible rice breeding line by introgression breeding. Plant Breeding. 134(6). 653–660. 21 indexed citations
15.
Xing, Danying, et al.. (2013). Density and Reserved Leaf Number of Tobacco to be Replanted in Cold Waterlogged Paddy Field. Advance Journal of Food Science and Technology. 5(4). 436–439. 1 indexed citations
16.
Li, Pengfei, et al.. (2013). Effect of Direct Sowing Rates on Mid-season 'Rice Feng-liang-you-xiang-1'. Advance Journal of Food Science and Technology. 5(4). 422–424. 6 indexed citations
17.
Zhang, Yanxia, et al.. (2013). EFFECTS OF DENSITY ON MAIN AGRONOMIC TRAITS AND YIELD OF AUTUMN SOWING POTATO IN JIANGHAN PLAIN. 22(12). 1653–1656. 1 indexed citations
18.
Zhang, Yunbo, Qiyuan Tang, Shaobing Peng, et al.. (2012). Water Use Efficiency and Physiological Response of Rice Cultivars under Alternate Wetting and Drying Conditions. The Scientific World JOURNAL. 2012. 1–10. 45 indexed citations
19.
Peng, Shaobing, Cougui Cao, P. S. Virk, et al.. (2011). Agronomic performance of rice breeding lines selected based on plant traits or grain yield. Field Crops Research. 121(1). 168–174. 24 indexed citations
20.
Xing, Danying. (2009). Optimum Application Rates of Basal Fertilizer of Late-season Rice with Zero-tillage and Direct Sowing. Hubei nongye kexue. 1 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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