Literature DB >> 24976561

Use of near infrared spectroscopy for estimating meat chemical composition, quality traits and fatty acid content from cattle fed sunflower or flaxseed.

N Prieto1, O López-Campos2, J L Aalhus3, M E R Dugan3, M Juárez3, B Uttaro3.   

Abstract

This study tested the ability of near infrared reflectance spectroscopy (NIRS) to predict meat chemical composition, quality traits and fatty acid (FA) composition from 63 steers fed sunflower or flaxseed in combination with high forage diets. NIRS calibrations, tested by cross-validation, were successful for predicting crude protein, moisture and fat content with coefficients of determination (R(2)) (RMSECV, g·100g(-1) wet matter) of 0.85 (0.48), 0.90 (0.60) and 0.86 (1.08), respectively, but were not reliable for meat quality attributes. This technology accurately predicted saturated, monounsaturated and branched FA and conjugated linoleic acid content (R(2): 0.83-0.97; RMSECV: 0.04-1.15mg·g(-1) tissue) and might be suitable for screening purposes in meat based on the content of FAs beneficial to human health such as rumenic and vaccenic acids. Further research applying NIRS to estimate meat quality attributes will require the use on-line of a fibre-optic probe on intact samples.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Fatty acid; Flaxseed; Meat quality; NIRS; Sunflower

Mesh:

Substances:

Year:  2014        PMID: 24976561     DOI: 10.1016/j.meatsci.2014.06.005

Source DB:  PubMed          Journal:  Meat Sci        ISSN: 0309-1740            Impact factor:   5.209


  8 in total

1.  Prediction of meat quality traits in Nelore cattle by near-infrared reflectance spectroscopy.

Authors:  Ana Fabrícia Braga Magalhães; Gustavo Henrique de Almeida Teixeira; Ana Cristina Herrera Ríos; Danielly Beraldo Dos Santos Silva; Lúcio Flávio Macedo Mota; Maria Malane Magalhães Muniz; Camilo de Lelis Medeiros de Morais; Kássio Michell Gomes de Lima; Luis Carlos Cunha Júnior; Fernando Baldi; Roberto Carvalheiro; Henrique Nunes de Oliveira; Luis Artur Loyola Chardulo; Lucia Galvão de Albuquerque
Journal:  J Anim Sci       Date:  2018-09-29       Impact factor: 3.159

2.  Differentiation of Livestock Internal Organs Using Visible and Short-Wave Infrared Hyperspectral Imaging Sensors.

Authors:  Cassius E O Coombs; Brendan E Allman; Edward J Morton; Marina Gimeno; Neil Horadagoda; Garth Tarr; Luciano A González
Journal:  Sensors (Basel)       Date:  2022-04-27       Impact factor: 3.847

3.  Using near-infrared spectroscopy to determine intramuscular fat and fatty acids of beef applying different prediction approaches.

Authors:  Wilson Barragán-Hernández; Liliana Mahecha-Ledesma; William Burgos-Paz; Martha Olivera-Angel; Joaquín Angulo-Arizala
Journal:  J Anim Sci       Date:  2020-11-01       Impact factor: 3.159

4.  The scope for manipulating the polyunsaturated fatty acid content of beef: a review.

Authors:  Payam Vahmani; Cletos Mapiye; Nuria Prieto; David C Rolland; Tim A McAllister; Jennifer L Aalhus; Michael E R Dugan
Journal:  J Anim Sci Biotechnol       Date:  2015-06-24

5.  Near-Infrared Spectroscopy as a Beef Quality Tool to Predict Consumer Acceptance.

Authors:  Wilson Barragán-Hernández; Liliana Mahecha-Ledesma; Joaquín Angulo-Arizala; Martha Olivera-Angel
Journal:  Foods       Date:  2020-07-24

6.  Rapid Identification of Rainbow Trout Adulteration in Atlantic Salmon by Raman Spectroscopy Combined with Machine Learning.

Authors:  Zeling Chen; Ting Wu; Cheng Xiang; Xiaoyan Xu; Xingguo Tian
Journal:  Molecules       Date:  2019-08-06       Impact factor: 4.411

Review 7.  Infrared Spectrometry as a High-Throughput Phenotyping Technology to Predict Complex Traits in Livestock Systems.

Authors:  Tiago Bresolin; João R R Dórea
Journal:  Front Genet       Date:  2020-08-20       Impact factor: 4.599

Review 8.  Historical Evolution and Food Control Achievements of Near Infrared Spectroscopy, Electronic Nose, and Electronic Tongue-Critical Overview.

Authors:  Balkis Aouadi; John-Lewis Zinia Zaukuu; Flora Vitális; Zsanett Bodor; Orsolya Fehér; Zoltan Gillay; George Bazar; Zoltan Kovacs
Journal:  Sensors (Basel)       Date:  2020-09-24       Impact factor: 3.576

  8 in total

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