Evidence map›Paper›PMID 38820309›Full record

ArticlePloS one2024

Regression models from portable NIR spectra for predicting the carcass traits and meat quality of beef cattle.

Nathália Veloso Trópia, Rizielly Saraiva Reis Vilela, Flávia Adriane de Sales Silva, Dhones Rodrigues Andrade, Adailton Camêlo Costa, Fernando Alerrandro Andrade Cidrini, Jardeson de Souza Pinheiro, Pauliane Pucetti, Mario Luiz Chizzotti, Sebastião de Campos Valadares Filho

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Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

10 authors.

Nathália Veloso TrópiaDepartment of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.ORCID 0000-0002-2321-9254
Rizielly Saraiva Reis VilelaDepartment of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.
Flávia Adriane de Sales SilvaDepartment of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.
Dhones Rodrigues AndradeDepartment of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.
Adailton Camêlo CostaDepartment of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.
Fernando Alerrandro Andrade CidriniDepartment of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.
Jardeson de Souza PinheiroDepartment of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.
Pauliane PucettiDepartment of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.
Mario Luiz ChizzottiDepartment of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.
Sebastião de Campos Valadares FilhoDepartment of Animal Science, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.ORCID 0000-0003-4544-6316

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aims of this study were to predict carcass and meat traits, as well as the chemical composition of the 9th to 11th rib sections of beef cattle from portable NIR spectra. The 9th to 11th rib section was obtained from 60 Nellore bulls and cull cows. NIR spectra were acquired at: P1 -center of Longissimus muscle; and P2 -subcutaneous fat cap. The models accurately estimated (P ≥ 0.083) all carcass and meat quality traits, except those for predicting red (a*) and yellow (b*) intensity from P1, and 12th-rib fat from P2. However, precision was highly variable among the models; those for the prediction of carcass pHu, 12th rib fat, toughness from P1, and those for 12th rib fat, a* and b* from P2 presented high precision (R2 ≥ 0.65 or CCC ≥ 0.63), whereas all other models evaluated presented moderate to low precision (R2 ≤ 0.39). Models built from P1 and P2 accurately estimated (P ≥ 0.066) the chemical composition of the meat plus fat, bones and, meat plus fat plus bones, except those for predicting the ether extract (EE) and crude protein (CP) of bones and the EE of Meat plus bones fraction from P2. However, precision was highly variable among the models (-0.08 ≤ R2 ≤ 0.86) of the 9th and 11th rib section. Those models for the prediction of dry matter (DM) and EE of the bones from P1; of EE from P1; and of EE, mineral matter (MM), CP from P2 of meat plus fat plus bones presented high precision (R2 ≥ 0.76 or CCC ≥ 0.62), whereas all other models evaluated presented moderate to low precision (R2 ≤ 0.45). Thus, models built from portable NIR spectra acquired at different points of the 9th to 11th rib section were recommended for predicting carcass and muscle quality traits as well as for predicting the chemical composition of this section of beef cattle. However, it is noteworthy, that the small sample size was one of the limitations of this study.

Indexed as

Red MeatSpectroscopy, Near-InfraredAnimalsCattleFemaleMaleMeatMuscle, SkeletalRegression Analysis

Identifiers

PMID38820309
PMCPMC11142432

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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.