Evidence map›Paper›PMID 38487278›Full record

ArticleJournal of food science and technology2024

Identification of individual goat animals by means of near infrared spectroscopy and chemometrics analysis of commercial meat cuts.

D Cozzolino, S Zhang, A Khole, Z Yang, P Ingle, M Beya, P F van Jaarsveld, D Bureš, L C Hoffman

Abstract read
In one paragraph

Article in Journal of food science and technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Assessment of Tail-Cutting in Frozen Albacore (Foods (Basel, Switzerland) · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

D CozzolinoCentre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Queensland Alliance for Agriculture and Food Innovation (QAAFI), Brisbane, QLD 4072 Australia.
S ZhangCentre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Queensland Alliance for Agriculture and Food Innovation (QAAFI), Brisbane, QLD 4072 Australia.
A KholeCentre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Queensland Alliance for Agriculture and Food Innovation (QAAFI), Brisbane, QLD 4072 Australia.
Z YangCentre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Queensland Alliance for Agriculture and Food Innovation (QAAFI), Brisbane, QLD 4072 Australia.
P IngleCentre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Queensland Alliance for Agriculture and Food Innovation (QAAFI), Brisbane, QLD 4072 Australia.
M BeyaCentre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Queensland Alliance for Agriculture and Food Innovation (QAAFI), Brisbane, QLD 4072 Australia.
P F van JaarsveldCentre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Queensland Alliance for Agriculture and Food Innovation (QAAFI), Brisbane, QLD 4072 Australia.
D BurešInstitute of Animal Science, 104 00 Přátelství 815, 104 00 Prague, Czech Republic.
L C HoffmanCentre for Nutrition and Food Sciences (CNAFS), The University of Queensland, Queensland Alliance for Agriculture and Food Innovation (QAAFI), Brisbane, QLD 4072 Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although the identification of animal species and muscles have been reported previously, no studies have been found on the use of NIR spectroscopy to identify individual animals from the analysis of commercial meat cuts. The aim of this study was to evaluate the use of a portable near infrared (NIR) instrument combined with classical chemometrics methods [principal component analysis (PCA) and partial least squares discriminant analysis PLS-DA)] to identify the origin of individual goat animals using the spectral signature of their commercial cut. Samples were collected from several carcasses (6 commercial cuts x 24 animals) sourced from a commercial abattoir in Queensland (Australia). The NIR spectra of the samples were collected using a portable NIR instrument in the wavelength range between 950 and 1600 nm. Overall, the PLS-DA models correctly classify 82% and 79% of the individual goat samples using either the goat rack or loin cut samples, respectively. The study demonstrated that NIR spectroscopy was able to identify individual goat animals based on the spectra properties of some of the commercial cut samples analysed (e.g. loin and rack). These results showed the potential of this technique to identify individual animals as an alternative to other laboratory methods and techniques commonly used in meat traceability.

Indexed as

ChemometricsCommercial cutGoatNIRProvenanceTraceability

Identifiers

PMID38487278
PMCPMC10933230

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.