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Original Articles

Detection of rabbit and hare processed material in compound feeds by TaqMan real-time PCR

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Pages 771-779 | Received 21 Dec 2012, Accepted 07 Apr 2013, Published online: 06 Jun 2013
 

Abstract

Food and feed traceability has become a priority for governments due to consumer demand for comprehensive and integrated safety policies. In the present work, a TaqMan real-time PCR assay targeting the mitochondrial 12S rRNA gene was developed for specific detection of rabbit and hare material in animal feeds and pet foods. The technique is based on the use of three species-specific primer/probe detection systems targeting three 12S rRNA gene fragments: one from rabbit species, another one from hare species and a third fragment common to rabbit and hare (62, 102 and 75 bp length, respectively). A nuclear 18S rRNA PCR system, detecting a 77-bp amplicon, was used as positive amplification control. Assay performance and sensitivity were assessed through the analysis of a batch of laboratory-scale feeds treated at 133°C at 3 bar for 20 min to reproduce feed processing conditions dictated by European regulations. Successful detection of highly degraded rabbit and hare material was achieved at the lowest target concentration assayed (0.1%). Furthermore, the method was applied to 96 processed commercial pet food products to determine whether correct labelling had been used at the market level. The reported real-time PCR technique detected the presence of rabbit tissues in 80 of the 96 samples analysed (83.3%), indicating a possible labelling fraud in some pet foods. The real-time PCR method reported may be a useful tool for traceability purposes within the framework of feed control.

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Corrigendum

Acknowledgements

This work was supported by the Programa de Vigilancia Sanitaria 2009/AGR/1489 of the Comunidad de Madrid (Spain) and by a project (AGL2010/15279) from the Ministerio de Ciencia e Innovación (Spain). Nicolette Pegels is recipient of a fellowship from the Ministerio de Educación (Spain). Inés López-Calleja is recipient of a Juan de la Cierva grant from the Ministerio de Ciencia e Innovación (Spain).

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