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A Multiplex PCR Method for the Identification of Commercially Important Salmon and Trout Species ( <i>Oncorhynchus</i> and <i>Salmo</i> ) in North America

2010· article· en· W2112419249 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Food Science · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicIdentification and Quantification in Food
Canadian institutionsUniversity of Guelph
FundersU.S. Food and Drug AdministrationOntario Centre of Innovation
KeywordsSalmoOncorhynchusFisheryTroutMultiplex polymerase chain reactionRainbow troutBiologyIdentification (biology)Fish <Actinopterygii>ZoologyMultiplexEcologyPolymerase chain reactionGeneticsGene

Abstract

fetched live from OpenAlex

UNLABELLED: The purpose of this study was to develop a species-specific multiplex polymerase chain reaction (PCR) method that allows for the detection of salmon species substitution on the commercial market. Species-specific primers and TaqMan® probes were developed based on a comprehensive collection of mitochondrial 5' cytochrome c oxidase subunit I (COI) deoxyribonucleic acid (DNA) "barcode" sequences. Primers and probes were combined into multiplex assays and tested for specificity against 112 reference samples representing 25 species. Sensitivity and linearity tests were conducted using 10-fold serial dilutions of target DNA (single-species samples) and DNA admixtures containing the target species at levels of 10%, 1.0%, and 0.1% mixed with a secondary species. The specificity tests showed positive signals for the target DNA in both real-time and conventional PCR systems. Nonspecific amplification in both systems was minimal; however, false positives were detected at low levels (1.2% to 8.3%) in conventional PCR. Detection levels were similar for admixtures and single-species samples based on a 30 PCR cycle cut-off, with limits of 0.25 to 2.5 ng (1% to 10%) in conventional PCR and 0.05 to 5.0 ng (0.1% to 10%) in real-time PCR. A small-scale test with food samples showed promising results, with species identification possible even in heavily processed food items. Overall, this study presents a rapid, specific, and sensitive method for salmon species identification that can be applied to mixed-species and heavily processed samples in either conventional or real-time PCR formats. PRACTICAL APPLICATION: This study provides a newly developed method for salmon and trout species identification that will assist both industry and regulatory agencies in the detection and prevention of species substitution. This multiplex PCR method allows for rapid, high-throughput species identification even in heavily processed and mixed-species samples. An inter-laboratory study is currently being carried out to assess the ability of this method to identify species in a variety of commercial salmon and trout products.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.244
Threshold uncertainty score0.225

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.298
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it