Literature DB >> 22063930

Prediction of technological and organoleptic properties of beef Longissimus thoracis from near-infrared reflectance and transmission spectra.

B Leroy1, S Lambotte, O Dotreppe, H Lecocq, L Istasse, A Clinquart.   

Abstract

Technological and organoleptic properties of beef cuts were predicted by near-infrared (NIR) spectroscopy. Spectra were collected on 189 beef Longissimus thoracis muscle samples using, transmission (NIRT) and reflectance with a probe. Quality assessment and NIR recordings were performed on sliced loin after 2 and 8 days ageing. Partial least squares regression yielded determination coefficients of cross-validation (R(2)(cv)) of 0.12-0.25 for the prediction of Warner-Bratzler Peak Shear Force in reflectance and 0.15-0.41 in transmission. Higher R(2)(cv) were obtained for L* parameter (0.83-0.85), a* (0.39-0.49) and b* (0.73-0.75) with reflectance. Predictions of drip loss and cooking loss were less accurate with a R(2)(cv) range of 0.38 to 0.54 and 0.25 to 0.47, respectively. The NIR spectra collected on fresh meat show good potential to predict CIE L* and b* parameters in reflectance mode.

Entities:  

Year:  2004        PMID: 22063930     DOI: 10.1016/S0309-1740(03)00002-0

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.  Rapid Determination of the Oil and Moisture Contents in Camellia gauchowensis Chang and Camellia semiserrata Chi Seeds Kernels by Near-infrared Reflectance Spectroscopy.

Authors:  Yingzhong Zhang; Liangbo Zhang; Jing Wang; Xuxiao Tang; Hong Wu; Minghuai Wang; Wu Zeng; Qihui Mo; Yongquan Li; Jianwei Li; Yijuan Huang; Baohua Xu; Mengyu Zhang
Journal:  Molecules       Date:  2018-09-12       Impact factor: 4.411

Review 3.  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

4.  Prediction of meat quality traits in the abattoir using portable near-infrared spectrometers: heritability of predicted traits and genetic correlations with laboratory-measured traits.

Authors:  Simone Savoia; Andrea Albera; Alberto Brugiapaglia; Liliana Di Stasio; Alessio Cecchinato; Giovanni Bittante
Journal:  J Anim Sci Biotechnol       Date:  2021-03-12

5.  Determination of Moisture and Protein Content in Living Mealworm Larvae (Tenebrio molitor L.) Using Near-Infrared Reflectance Spectroscopy (NIRS).

Authors:  Nina Kröncke; Rainer Benning
Journal:  Insects       Date:  2022-06-20       Impact factor: 3.139

6.  Phenotypic and genetic variation of ultraviolet-visible-infrared spectral wavelengths of bovine meat.

Authors:  Giovanni Bittante; Simone Savoia; Alessio Cecchinato; Sara Pegolo; Andrea Albera
Journal:  Sci Rep       Date:  2021-07-06       Impact factor: 4.379

7.  Postmortem Aging of Beef with a Special Reference to the Dry Aging.

Authors:  Muhammad I Khan; Samooel Jung; Ki Chang Nam; Cheorun Jo
Journal:  Korean J Food Sci Anim Resour       Date:  2016-04-30       Impact factor: 2.622

Review 8.  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

  8 in total

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