Prediction of Tenderness in Bovine Longissimus Thoracis Et Lumborum Muscles Using Raman Spectroscopy

Overview

Journal Anim Biosci

Specialty Veterinary Medicine

Date 2023 Mar 14

PMID 36915932

Authors

Maria Sumampa Coria

Maria Sofia Castano Ledesma

Jorge Raul Gomez Rojas

Gabriela Grigioni

Gustavo Adolfo Palma

Claudio Dario Borsarelli

Affiliations

Soon will be listed here.

Abstract

Objective: This study was conducted to evaluate Raman spectroscopy technique as a noninvasive tool to predict meat quality traits on Braford longissimus thoracis et lumborum muscle.

Methods: Thirty samples of muscle from Braford steers were analyzed by classical meat quality techniques and by Raman spectroscopy with 785 nm laser excitation. Water holding capacity (WHC), intramuscular fat content (IMF), cooking loss (CL), and texture profile analysis recording hardness, cohesiveness, and chewiness were determined, along with fiber diameter and sarcomere length by scanning electron microscopy. Warner-Bratzler shear force (WBSF) analysis was used to differentiate tender and tough meat groups.

Results: Higher values of cohesiveness and CL, together with lower values of WHC, IMF, and shorter sarcomere were obtained for tender meat samples than for the tougher ones. Raman spectra analysis allows tender and tough sample differentiation. The correlation between the quality attributes predicted by Raman and the physical measurements resulted in values of R2 = 0.69 for hardness and 0,58 for WBSF. Pearson's correlation coefficient of hardness (r = 0.84) and WBSF (r = 0.79) parameters with the phenylalanine Raman signal at 1,003 cm-1, suggests that the content of this amino acid could explain the differences between samples.

Conclusion: Raman spectroscopy with 785 nm laser excitation is a suitable and accurate technique to identify beef with different quality attributes.

Citing Articles

Acoustic Characterization Study of Beef Loins Using Ultrasonic Transducers.

Jimenez A, Rufo M, Paniagua J, Gonzalez-Mohino A, Antequera T, Perez-Palacios T Sensors (Basel). 2023; 23(23).

PMID: 38067937 PMC: 10708575. DOI: 10.3390/s23239564.

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