Literature DB >> 22063693

Prediction of color, texture, and sensory characteristics of beef steaks by visible and near infrared reflectance spectroscopy. A feasibility study.

Yongliang Liu1, Brenda G Lyon, William R Windham, Carolina E Realini, T Dean D Pringle, Susan Duckett.   

Abstract

Color, instrumental texture, and sensory attributes of steaks from 24 beef carcasses at 2, 4, 8, 14, and 21 days post mortem were predicted by visible/near infrared (visible/NIR) reflectance spectroscopy in 400-1080 nm region. Predicting the Hunter a, b, and E* yielded the coefficient of determination (R(2)) in calibration to be 0.78-0.90, and R(2) was between 0.49 and 0.55 for tenderness, Hunter L, sensory chewiness and juiciness. The prediction R(2) for tenderness was in the range of 0.22-0.72 when the samples were segregated according to the aging days. Based on partial least square (PLS) model predicted tenderness, beef samples were classified into tender and tough classes with a correct classification of 83%. Soft independent modeling of class analogy of principal component analysis (SIMCA/PCA) model of measured tenderness showed great promise in the classification of tender and tough meats with over 96% success.

Entities:  

Year:  2003        PMID: 22063693     DOI: 10.1016/S0309-1740(02)00328-5

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


  6 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

Review 2.  Consumer Perception of Beef Quality and How to Control, Improve and Predict It? Focus on Eating Quality.

Authors:  Jingjing Liu; Marie-Pierre Ellies-Oury; Todor Stoyanchev; Jean-François Hocquette
Journal:  Foods       Date:  2022-06-13

3.  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

Review 4.  Predicting the Quality of Meat: Myth or Reality?

Authors:  Cécile Berri; Brigitte Picard; Bénédicte Lebret; Donato Andueza; Florence Lefèvre; Elisabeth Le Bihan-Duval; Stéphane Beauclercq; Pascal Chartrin; Antoine Vautier; Isabelle Legrand; Jean-François Hocquette
Journal:  Foods       Date:  2019-09-24

Review 5.  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

6.  Quality traits and fatty acid composition in meat of Hair Goat and Saanen  ×  Hair Goat (G1) crossbred kids fattened in different systems.

Authors:  Hacer Tüfekci; Mustafa Olfaz
Journal:  Arch Anim Breed       Date:  2021-07-19
  6 in total

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