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Attention Score in Context
| Title |
Comparison of microbial communities from different Jinhua ham factories
|
|---|---|
| Published in |
AMB Express, February 2017
|
| DOI | 10.1186/s13568-017-0334-0 |
| Pubmed ID | |
| Authors |
Qingfeng Ge, Yubin Gu, Wangang Zhang, Yongqi Yin, Hai Yu, Mangang Wu, Zhijun Wang, Guanghong Zhou |
| Abstract |
Microbes in different aged workshops play important roles in the flavor formation of Jinhua ham. However, microbial diversity, community structure and age related changes in workshops are poorly understood. The microbial community structure and diversity in Jinhua ham produced in factories that have 5, 15, and 30 years of history in processing hams were compared using the pyrosequencing technique. Results showed that 571,703 high-quality sequences were obtained and located in 242 genera belonging to 18 phyla. Bacterial diversity and microbial community structure were significantly different with the years of workshops. Three-phase model to characterize the changes of ham microbial communities was proposed. Gas chromatography-mass spectrometry assays indicated that the hams produced in different aged workshops have great differences in number and relative contents of volatiles compounds. These results suggest that different aged factories could form special and well-balanced microbial diversity, which may contribute to the unique flavor characteristics in Jinhua ham. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 20% |
| Researcher | 3 | 15% |
| Professor | 2 | 10% |
| Lecturer > Senior Lecturer | 1 | 5% |
| Student > Doctoral Student | 1 | 5% |
| Other | 2 | 10% |
| Unknown | 7 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 35% |
| Immunology and Microbiology | 2 | 10% |
| Computer Science | 1 | 5% |
| Biochemistry, Genetics and Molecular Biology | 1 | 5% |
| Unknown | 9 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 14 February 2017.
All research outputs
#15,443,875
of 22,953,506 outputs
Outputs from AMB Express
#445
of 1,237 outputs
Outputs of similar age
#260,256
of 426,820 outputs
Outputs of similar age from AMB Express
#25
of 64 outputs
Altmetric has tracked 22,953,506 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,237 research outputs from this source. They receive a mean Attention Score of 2.8. This one is in the 40th percentile – i.e., 40% of its peers scored the same or lower than it.
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We're also able to compare this research output to 64 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.