2014
DOI: 10.1111/ijfs.12720
|View full text |Cite
|
Sign up to set email alerts
|

Duplex PCR approach for the detection and quantification of donkey, horse and mule in raw and heat‐processed meat products

Abstract: Donkey-related products have been paid more attention for their high nutritional value to human beings. Due to donkey resource scarcity, coupled with gradually increasing market demand, adulterated donkey meat products with other low-cost animal meat, especially with the similar species horse and mule, are often found in market. Therefore, detection of species fraud in donkey meat products is important for consumer protection and food industries. In this study, a simple and highly specific duplex PCR method, b… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
4
1

Citation Types

0
14
1

Year Published

2015
2015
2020
2020

Publication Types

Select...
7
1

Relationship

0
8

Authors

Journals

citations
Cited by 26 publications
(15 citation statements)
references
References 31 publications
0
14
1
Order By: Relevance
“…The lowest percentage of donkey meat adulteration that could be detected by the real-time PCR method developed in this study was 0.001%, which was lower than 1% of detection limit reported by Chen et al [1] and same or lower than 0.001% and 0.01% of detection limits reported by Kesmen et al [19]. Therefore, this real-time PCR method can help to confirm the presence of donkey meat in highly processed meat products and provide accurate information on target meat species.…”
Section: Application Of the Real-time Pcr Assay To Meat Mixtures Treacontrasting
confidence: 76%
See 2 more Smart Citations
“…The lowest percentage of donkey meat adulteration that could be detected by the real-time PCR method developed in this study was 0.001%, which was lower than 1% of detection limit reported by Chen et al [1] and same or lower than 0.001% and 0.01% of detection limits reported by Kesmen et al [19]. Therefore, this real-time PCR method can help to confirm the presence of donkey meat in highly processed meat products and provide accurate information on target meat species.…”
Section: Application Of the Real-time Pcr Assay To Meat Mixtures Treacontrasting
confidence: 76%
“…Identification of animal species in meat products is important for preventing food adulteration and providing accurate information regarding meat species to consumers. Donkey meat products are highly nutritious; moreover, in many countries, including Korea, it is considerably more expensive than other meats owing to its low supply [1]. In Islamic countries, donkey meat consumption is prohibited on religious grounds [2].…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…The multiplex PCR method was applied to detect bovine, ovine and caprine meats in feedstuffs (Safdar and Junejo 2015) and to detect chicken, duck and goose in beef, mutton, pork or quail meat samples (Hou et al 2015). Conventional PCR techniques allow qualitative and speciesspecific detection in food and food ingredients (Rodriguez (Dalmasso et al 2004;Safdar et al 2014;Chen et al 2015). Real-time PCR has been widely used for the quantitative determination of animal species but it is not cost-effective for use to simply detect food fraud (Dooley et al 2004;Cheng et al 2014).…”
Section: Introductionmentioning
confidence: 99%
“…Molecular methodologies are especially useful in food authentication testing, thanks to the ubiquitous presence of DNA molecules in all biological tissues, and their stability under the production and processing operations applied along the food-chain (Asensio, Gonzá lez,genomic DNA provide a far more effective approach in authentication tests (Rahmati et al, 2016). Thus, Chen, Wei, Chen, Zhao, & Yang (2015) developed a duplex PCR assay for the identification of horse, donkey and mule species in raw and heat-processed meat products, based on the amplification of a fragment of the mitochondrial DNA. According to the authors, the target meat species could be detected at a level of 1%.…”
Section: Introductionmentioning
confidence: 99%