Literature DB >> 29331862

Preliminary investigation of the use of Raman spectroscopy to predict meat and eating quality traits of beef loins.

Stephanie M Fowler1, Heinar Schmidt2, Remy van de Ven3, David L Hopkins4.   

Abstract

A preliminary investigation was conducted to determine the potential for a handheld Raman spectroscopic device to predict sensory traits determined by an untrained consumer panel. Measurement of 45 beef loins (M. longissimus lumborum) was conducted using a 671nm handheld Raman spectroscopic device. Samples were then held frozen until testing by an untrained sensory panel. Sections were also excised to determine shear force values and other indicators of meat quality. Derived models suggest that the Raman spectroscopic device can predict juiciness and tenderness, with correlations between predicted and observed values (ρ) of 0.42 and 0.47, respectively. Spectra indicated that these predictions were characterised by the fatty acid concentration, the hydrophobicity of proteins and the orientation of collagen. However, future research is required to determine the repeatability and robustness of these models on a larger independent data set.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Carcase assessment; Optic technologies; Sensory traits

Mesh:

Substances:

Year:  2018        PMID: 29331862     DOI: 10.1016/j.meatsci.2018.01.002

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


  6 in total

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Journal:  Foods       Date:  2022-04-15

2.  Raman spectroscopy based characterization of cow, goat and buffalo fats.

Authors:  M Saleem; Ayyaz Amin; Muhammad Irfan
Journal:  J Food Sci Technol       Date:  2020-05-21       Impact factor: 2.701

Review 3.  Critical Review on the Utilization of Handheld and Portable Raman Spectrometry in Meat Science.

Authors:  Anel Beganović; Luzia Maria Hawthorne; Katrin Bach; Christian W Huck
Journal:  Foods       Date:  2019-02-01

4.  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 5.  A Review on Meat Quality Evaluation Methods Based on Non-Destructive Computer Vision and Artificial Intelligence Technologies.

Authors:  Yinyan Shi; Xiaochan Wang; Md Saidul Borhan; Jennifer Young; David Newman; Eric Berg; Xin Sun
Journal:  Food Sci Anim Resour       Date:  2021-07-01

6.  Online Prediction of Physico-Chemical Quality Attributes of Beef Using Visible-Near-Infrared Spectroscopy and Chemometrics.

Authors:  Amna Sahar; Paul Allen; Torres Sweeney; Jamie Cafferky; Gerard Downey; Andrew Cromie; Ruth M Hamill
Journal:  Foods       Date:  2019-10-23
  6 in total

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