DNA-Based Traceability of Meat

Shackell, G. H.; Dodds, K. G.

doi:10.1007/978-0-387-79382-5_3

Cited by 3 publications

(3 citation statements)

References 65 publications

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“…These characteristics are the breadth of information (amount of collection and transmitted information), the depth of the traceability (the degree of tracing forward and backward), and the precision of the information (accuracy). providing information that allows genetic improvement of production animals; validating that improvement by verifying of pedigree; verifying the origin of meat; protecting the brand of niche market meats; identifying and enabling selection for meat quality detecting fraud (Shackell and Dodds 2008). Skoglund and Dejmek (2007) proposed a concept called 'fuzzy traceability' to improve the handling of batch identities in continuous production of liquid food.…”

Section: Development and Implementation Of Tsmentioning

confidence: 99%

Critical Success Factors for Implementing Traceability Systems in Chinese Food Enterprises

Miao

Liu²,

Duan

et al. 2011

2011 International Conference on Management and Service Science

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i CRITICAL SUCCESS FACTORS FOR IMPLEMENTING TRACEABILITY SYSTEMS IN CHINESE FOOD ENTERPRISES MEIYIN MIAO ABSTRACTFood safety has always been the focus of worldwide attention. Chinese government has promulgated a series of initiatives, laws and regulations to implement the traceability systems since 2004. However, the implementation of traceability system (TS) in China faces many challenges which are creating major barriers to the traceability system implementation success. This research aims to identify critical success factors (CSF) for implementing TS in Chinese food enterprises. More specifically, the study attempts to develop a set of criteria of TS implementation success from theoretical and practical point of views and identify and propose a framework of critical success factors for TS implementation success.To achieve the research objectives, this research adopted both qualitative and quantitative approaches.

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Section: Development and Implementation Of Tsmentioning

confidence: 99%

Critical Success Factors for Implementing Traceability Systems in Chinese Food Enterprises

Miao

Liu²,

Duan

et al. 2011

2011 International Conference on Management and Service Science

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“…Most meat in a ground beef batch comes from off-cuts or trimmings. These raw materials are usually blended during processing as it would be entirely impractical and uneconomic to process, label or tag each component separately [49] . Because different animals exhibit wide variation in meat and fat content, the quantity and quality of trimmings varies considerably among animals.…”

Section: Discussionmentioning

confidence: 99%

“…Our results recognize the complexity of tracking and tracing ground meat batches based on the trimmings since more than 1000 animals could be included in a single grind batch. Grinding operations are the last phase before the market or end-users in the meat supply chain [49] . The existing meat traceability systems are primarily documented in regards to the primal cuts [54] and have inadequate tracing of the mixed trimmings.…”

Section: Discussionmentioning

confidence: 99%

Estimating Animal Abundance in Ground Beef Batches Assayed with Molecular Markers

Simila²,

Platz³

et al. 2012

PLoS ONE

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Estimating animal abundance in industrial scale batches of ground meat is important for mapping meat products through the manufacturing process and for effectively tracing the finished product during a food safety recall. The processing of ground beef involves a potentially large number of animals from diverse sources in a single product batch, which produces a high heterogeneity in capture probability. In order to estimate animal abundance through DNA profiling of ground beef constituents, two parameter-based statistical models were developed for incidence data. Simulations were applied to evaluate the maximum likelihood estimate (MLE) of a joint likelihood function from multiple surveys, showing superiority in the presence of high capture heterogeneity with small sample sizes, or comparable estimation in the presence of low capture heterogeneity with a large sample size when compared to other existing models. Our model employs the full information on the pattern of the capture-recapture frequencies from multiple samples. We applied the proposed models to estimate animal abundance in six manufacturing beef batches, genotyped using 30 single nucleotide polymorphism (SNP) markers, from a large scale beef grinding facility. Results show that between 411∼1367 animals were present in six manufacturing beef batches. These estimates are informative as a reference for improving recall processes and tracing finished meat products back to source.

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