Huaming Mao

1.2k total citations
44 papers, 597 citations indexed

About

Huaming Mao is a scholar working on Agronomy and Crop Science, Molecular Biology and Genetics. According to data from OpenAlex, Huaming Mao has authored 44 papers receiving a total of 597 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Agronomy and Crop Science, 13 papers in Molecular Biology and 13 papers in Genetics. Recurrent topics in Huaming Mao's work include Ruminant Nutrition and Digestive Physiology (11 papers), Genetic and phenotypic traits in livestock (10 papers) and Effects of Environmental Stressors on Livestock (6 papers). Huaming Mao is often cited by papers focused on Ruminant Nutrition and Digestive Physiology (11 papers), Genetic and phenotypic traits in livestock (10 papers) and Effects of Environmental Stressors on Livestock (6 papers). Huaming Mao collaborates with scholars based in China, Thailand and India. Huaming Mao's co-authors include Weidong Deng, Xiaoning Tang, Shuli Yang, Bin Zhang, Lihong Tang, Xiaoning Tang, Chuanbin Liu, Lin Li, Jing Leng and Zhengxiang Shi and has published in prestigious journals such as Journal of Agricultural and Food Chemistry, Gene and Applied Surface Science.

In The Last Decade

Huaming Mao

41 papers receiving 582 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Huaming Mao China 15 173 131 110 108 96 44 597
Ling Pan China 18 269 1.6× 77 0.6× 50 0.5× 53 0.5× 40 0.4× 45 857
Maximilian Cohen United States 9 40 0.2× 301 2.3× 96 0.9× 92 0.9× 93 1.0× 12 578
Lucile Martin France 21 180 1.0× 63 0.5× 169 1.5× 195 1.8× 123 1.3× 41 1.2k
Larry L. Berger United States 16 71 0.4× 252 1.9× 70 0.6× 164 1.5× 166 1.7× 34 747
T Vijaya Kumar India 14 89 0.5× 67 0.5× 55 0.5× 159 1.5× 64 0.7× 78 600
Joshua C McCann United States 17 271 1.6× 594 4.5× 81 0.7× 189 1.8× 172 1.8× 57 1.0k
Shengguo Zhao China 19 360 2.1× 231 1.8× 51 0.5× 341 3.2× 269 2.8× 101 1.1k
Gloria Panella Italy 11 111 0.6× 176 1.3× 34 0.3× 126 1.2× 254 2.6× 14 660
A.B.Z. Zuki Malaysia 15 148 0.9× 64 0.5× 41 0.4× 66 0.6× 164 1.7× 50 831
Yanling Huang China 19 358 2.1× 24 0.2× 132 1.2× 52 0.5× 85 0.9× 79 1.1k

Countries citing papers authored by Huaming Mao

Since Specialization
Citations

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

Fields of papers citing papers by Huaming Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Huaming Mao

This figure shows the co-authorship network connecting the top 25 collaborators of Huaming Mao. A scholar is included among the top collaborators of Huaming Mao 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 Huaming Mao. Huaming Mao 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.
Tang, Xiaoning, et al.. (2024). Construction of ZnO/Cu2O composites for enhanced antibacterial activity and analysis of antibacterial mechanism. Inorganic Chemistry Communications. 162. 112182–112182. 10 indexed citations
2.
3.
Yang, Shuli, et al.. (2024). Multiomics of yaks reveals significant contribution of microbiome into host metabolism. npj Biofilms and Microbiomes. 10(1). 133–133. 4 indexed citations
4.
Yang, Jian‐Fa, Xinyan Xie, Junrong Chen, et al.. (2022). Prevalence and multilocus genotyping of Giardia duodenalis in Holstein cattle in Yunnan, China. Frontiers in Veterinary Science. 9. 949462–949462. 13 indexed citations
5.
Mao, Huaming, et al.. (2021). The use of metabolomics to reveal differences in functional substances of milk whey of dairy buffaloes raised at different altitudes. Food & Function. 12(12). 5440–5450. 11 indexed citations
6.
Li, Lin, et al.. (2020). Impacts of drainage beds covered with sand and wood shavings on the comfort behaviour of dairy buffalo in a temperate climate. Irish Veterinary Journal. 73(1). 4–4. 1 indexed citations
7.
Li, Yang, Gao Song-wei, Bin Zhang, Huaming Mao, & Xiaoning Tang. (2020). Electrospun Ag-Doped SnO2 Hollow Nanofibers with High Antibacterial Activity. Electronic Materials Letters. 16(3). 195–206. 18 indexed citations
8.
Zhang, Guangrong, et al.. (2020). Exploration of the effects of altitude change on bacteria and fungi in the rumen of yak (Bos grunniens). Archives of Microbiology. 203(2). 835–846. 26 indexed citations
9.
Zhang, Guangrong, et al.. (2020). Host and altitude factors affect rumen bacteria in cattle. Brazilian Journal of Microbiology. 51(4). 1573–1583. 13 indexed citations
10.
Li, Lin, et al.. (2018). Metabolomics Reveals that Crossbred Dairy Buffaloes Are More Thermotolerant than Holstein Cows under Chronic Heat Stress. Journal of Agricultural and Food Chemistry. 66(49). 12889–12897. 66 indexed citations
11.
Wang, Jia‐Bin, Chunhua Ma, Wen-Yuan Hu, et al.. (2018). Relationship between Peak Milk Yield and Udder Parameters of Dehong Crossbred Dairy Buffaloes. Iranian journal of applied animal science. 8(1). 25–32. 2 indexed citations
12.
Li, Qing, Youwen Wang, Jing Leng, et al.. (2017). Effects of age on slaughter performance and meat quality of Binlangjang male buffalo. Saudi Journal of Biological Sciences. 25(2). 248–252. 22 indexed citations
13.
Xi, Dongmei, Qing Liu, Jianhong Guo, et al.. (2011). Genetic variability of the coding region for the prion protein gene (PRNP) in gayal (Bos frontalis). Molecular Biology Reports. 39(2). 2011–2020. 10 indexed citations
14.
Miao, Yongwang, Gui-Sheng Wu, Lei Wang, et al.. (2010). The role of MC1R gene in buffalo coat color. Science China Life Sciences. 53(2). 267–272. 25 indexed citations
15.
Wang, Yongqi, et al.. (2009). Hybrid origin of Yunnan gayal revealed by mtDNA and SRY gene sequence variation.. Zhongguo Nongye Daxue xuebao. 14(1). 31–37.
16.
Li, Wen, Yongmei He, Guoxing Wu, et al.. (2009). Molecular cloning, sequence characteristics analysisand tissue expression profiles of three novel genes<i>RhoB, RhoF</i> and <i>RhoH</i> from the Black-boned sheep(<i>Ovis aries</i>). Journal of Animal and Feed Sciences. 18(2). 271–282. 4 indexed citations
17.
Deng, Weidong, et al.. (2007). Phylogenetic Analysis of 16S rDNA Sequences Manifest Rumen Bacterial Diversity in Gayals (Bos frontalis) Fed Fresh Bamboo Leaves and Twigs (Sinarumdinaria). Asian-Australasian Journal of Animal Sciences. 20(7). 1057–1066. 20 indexed citations
18.
Xi, Dongmei, et al.. (2007). Comparison of Gayal (Bos frontalis) and Yunnan Yellow Cattle (Bos taurus): In vitro Dry Matter Digestibility and Gas Production for a Range of Forages. Asian-Australasian Journal of Animal Sciences. 20(8). 1208–1214. 19 indexed citations
19.
Mao, Huaming. (2007). Effect of Different Varieties and Harvesting Times on the Corn Yield and Nutrition. Acta Agrestia Sinica. 1 indexed citations
20.
Mao, Huaming, et al.. (2005). Studies on the specific characteristics of Yunnan black-bone sheep. Yunnan Nongye Daxue xuebao. 2 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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