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Permanent link (DOI): https://doi.org/10.7939/R3HH6C930
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Estimating animal abundance in ground beef batches assayed with molecular markers Open Access
- Author or creator
Hu, X. S.
Platz, S. S.
Moore, S. S.
Meghen, C. N.
- Additional contributors
simulation and modeling
- Type of item
- Journal Article (Published)
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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- Attribution 4.0 International
- Citation for previous publication
Hu, X.S., Simila, J., Platz, S.S., Moore, S.S., Plastow, G., Meghen, C.N. (2012). Estimating animal abundance in ground beef batches assayed with molecular markers. PloS ONE, 7(3), e34191. doi:10.1371/journal.pone.0034191
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