↓ Skip to main content

Molecular assay to fraud identification of meat products

Overview of attention for article published in Journal of Food Science and Technology, July 2011
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

blogs
1 blog
twitter
3 tweeters

Citations

dimensions_citation
66 Dimensions

Readers on

mendeley
116 Mendeley
Title
Molecular assay to fraud identification of meat products
Published in
Journal of Food Science and Technology, July 2011
DOI 10.1007/s13197-011-0456-3
Pubmed ID
Authors

Abbas Doosti, Payam Ghasemi Dehkordi, Ebrahim Rahimi

Abstract

Detection of species fraud in meat products is important for consumer protection and food industries. A molecular technique such as PCR method for detection of beef, sheep, pork, chicken, donkey, and horse meats in food products was established. The purpose of this study was to identification of fraud and adulteration in industrial meat products by PCR-RFLP assay in Iran. In present study, 224 meat products include 68 sausages, 48 frankfurters, 55 hamburgers, 33 hams and 20 cold cut meats were collected from different companies and food markets in Iran. Genomic DNA was extracted and PCR was performed for gene amplification of meat species using specific oligonucleotid primers. Raw meat samples are served as the positive control. For differentiation between donkey's and horse's meat, the mitochondrial DNA segment (cytochrome-b gene) was amplified and products were digested with AluI restriction enzyme. Results showed that 6 of 68 fermented sausages (8.82%), 4 of 48 frankfurters (8.33%), 4 of 55 hamburgers (7.27%), 2 of 33 hams (6.6%), and 1 of 20 cold cut meat (5%) were found to contain Haram (unlawful or prohibited) meat. These results indicate that 7.58% of the total samples were not containing Halal (lawful or permitted) meat and have another meat. These findings showed that molecular methods such as PCR and PCR-RFLP are potentially reliable techniques for detection of meat type in meat products for Halal authentication.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 116 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 <1%
Spain 1 <1%
Thailand 1 <1%
Malaysia 1 <1%
Unknown 112 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 22%
Student > Bachelor 18 16%
Unspecified 15 13%
Student > Ph. D. Student 14 12%
Researcher 14 12%
Other 29 25%
Readers by discipline Count As %
Agricultural and Biological Sciences 34 29%
Biochemistry, Genetics and Molecular Biology 25 22%
Unspecified 20 17%
Chemistry 13 11%
Business, Management and Accounting 5 4%
Other 19 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 24 April 2015.
All research outputs
#1,338,940
of 13,279,412 outputs
Outputs from Journal of Food Science and Technology
#55
of 829 outputs
Outputs of similar age
#25,539
of 240,353 outputs
Outputs of similar age from Journal of Food Science and Technology
#5
of 16 outputs
Altmetric has tracked 13,279,412 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 829 research outputs from this source. They receive a mean Attention Score of 4.3. This one has done particularly well, scoring higher than 93% of its peers.
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 240,353 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 16 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.