Author
Listed:
- Xin-Sheng Hu
- Janika Simila
- Sindey Schueler Platz
- Stephen S Moore
- Graham Plastow
- Ciaran N Meghen
Abstract
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.
Suggested Citation
Xin-Sheng Hu & Janika Simila & Sindey Schueler Platz & Stephen S Moore & Graham Plastow & Ciaran N Meghen, 2012.
"Estimating Animal Abundance in Ground Beef Batches Assayed with Molecular Markers,"
PLOS ONE, Public Library of Science, vol. 7(3), pages 1-12, March.
Handle:
RePEc:plo:pone00:0034191
DOI: 10.1371/journal.pone.0034191
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