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Nucleic acid-based approaches to investigate microbial-related cheese quality defects

Overview of attention for article published in Frontiers in Microbiology, January 2013
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Title
Nucleic acid-based approaches to investigate microbial-related cheese quality defects
Published in
Frontiers in Microbiology, January 2013
DOI 10.3389/fmicb.2013.00001
Pubmed ID
Authors

Daniel J. O'Sullivan, Linda Giblin, Paul L. H. McSweeney, Jeremiah J. Sheehan, Paul D. Cotter

Abstract

The microbial profile of cheese is a primary determinant of cheese quality. Microorganisms can contribute to aroma and taste defects, form biogenic amines, cause gas and secondary fermentation defects, and can contribute to cheese pinking and mineral deposition issues. These defects may be as a result of seasonality and the variability in the composition of the milk supplied, variations in cheese processing parameters, as well as the nature and number of the non-starter microorganisms which come from the milk or other environmental sources. Such defects can be responsible for production and product recall costs and thus represent a significant economic burden for the dairy industry worldwide. Traditional non-molecular approaches are often considered biased and have inherently slow turnaround times. Molecular techniques can provide early and rapid detection of defects that result from the presence of specific spoilage microbes and, ultimately, assist in enhancing cheese quality and reducing costs. Here we review the DNA-based methods that are available to detect/quantify spoilage bacteria, and relevant metabolic pathways in cheeses and, in the process, highlight how these strategies can be employed to improve cheese quality and reduce the associated economic burden on cheese processors.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 102 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 1 <1%
Italy 1 <1%
Canada 1 <1%
Unknown 99 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 18%
Student > Ph. D. Student 16 16%
Student > Master 10 10%
Student > Bachelor 7 7%
Other 7 7%
Other 17 17%
Unknown 27 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 43 42%
Biochemistry, Genetics and Molecular Biology 6 6%
Medicine and Dentistry 3 3%
Immunology and Microbiology 3 3%
Environmental Science 2 2%
Other 9 9%
Unknown 36 35%
Attention Score in Context

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 21 January 2013.
All research outputs
#20,178,948
of 22,693,205 outputs
Outputs from Frontiers in Microbiology
#22,097
of 24,504 outputs
Outputs of similar age
#248,696
of 280,672 outputs
Outputs of similar age from Frontiers in Microbiology
#264
of 407 outputs
Altmetric has tracked 22,693,205 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 24,504 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 280,672 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 407 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.