Prediction of tenderness in bovine longissimus thoracis et lumborum muscles using Raman spectroscopy
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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.
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.
참고문헌 (41)
- Hunt MR, "Consumer assessment of beef palatability from four beef muscles from USDA Choice and Select graded carcasses", Meat Sci, 98, pp.1~8 (2014)[DOI]
- Miller MF, "Consumer thresholds for establishing the value of beef tenderness", J Anim Sci, 79, pp.3062~3068 (2001)[DOI]
- Beattie RJ, "Preliminary investigation of the application of Raman spectroscopy to the prediction of the sensory quality of beef silverside", Meat Sci, 66, pp.903~913 (2004)[DOI]
- Ruiz De Huidobro F, "A comparison between two methods(Warner-Bratzler and texture profile analysis)for testing either raw meat or cooked meat", Meat Sci, 69, pp.527~536 (2005)[DOI]
- Jeremiah LE, "Assessment of the relationship between chemical components and palatability of major beef muscles and muscle groups", Meat Sci, 65, pp.1013~1019 (2003)[DOI]
- Aalhus JL, "Establishment of consumer thresholds for beef quality attributes", Can J Anim Sci, 84, pp.631~638 (2004)[DOI]
- Ozbekova Z, "Fluorescence spectroscopy for accurate and rapid prediction of meat composition", Indian J Anim Sci, 89, pp.786~790 (2019)
- Pu Y, "Optical detection of meat spoilage using fluorescence spectroscopy with selective excitation wavelength", Appl Spectrosc, 67, pp.210~213 (2013)[DOI]
- Damez JL, "Meat quality assessment using biophysical methods related to meat structure", Meat Sci, 80, pp.132~149 (2008)[DOI]
- De Biasio M, "Micro-raman spectroscopy for meat type detection", Proceedings the Next-Generation Spectroscopic Technologies VIII. SPIE 2015, 9482, pp.377~382 (2015)
- Herrero AM, "Raman spectroscopy a promising technique for quality assessment of meat and fish : a review", Food Chem, 107, pp.1642~1651 (2008)[DOI]
- Wang Q, "Rapid determination of pork sensory quality using Raman spectroscopy", Meat Sci, 91, pp.232~239 (2012)[DOI]
- Santos CC, "Predicting aged pork quality using a portable Raman device", Meat Sci, 145, pp.79~85 (2018)[DOI]
- Fowler SM, "Raman spectroscopy compared against traditional predictors of shear force in lamb m. longissimus lumborum", Meat Sci, 98, pp.652~656 (2014)[DOI]
- Fowler SM, "Prediction of intramuscular fat content and major fatty acid groups of lamb M. longissimus lumborum using Raman spectroscopy", Meat Sci, 110, pp.70~75 (2015)[DOI]
- Fowler SM, "Preliminary investigation of the use of Raman spectroscopy to predict meat and eating quality traits of beef loins", Meat Sci, 138, pp.53~58 (2018)[DOI]
- Bauer A, "Assessment of tenderness of aged bovine gluteus medius muscles using Raman spectroscopy", Meat Sci, 115, pp.27~33 (2016)[DOI]
- Cama-Moncunill R, "Prediction of Warner-Bratzler shear force, intramuscular fat, drip-loss and cook-loss in beef via Raman spectroscopy and chemometrics", Meat Sci, 167, pp.108157~ (2020)[DOI]
- Chen Q, "Non-destructive prediction of texture of frozen", thaw raw beef by Raman spectroscopy, 2020, pp.266, 109693~
- Fowler SM, "Predicting meat quality traits of ovine m. semimembranosus, both fresh and following freezing and thawing, using a hand held Raman spectroscopic device", Meat Sci, 108, pp.138~144 (2015)[DOI]
- AOAC, "Official methods of analysis", Association of Official Analytical Chemists, ~ (1992)
- Zamorano JM, "Contribution to improving the meat water holding capacity test by the filter paper press method. A comparison of three methods for measuring areas", Meat Sci, 46, pp.129~137 (1997)[DOI]
- AMSA, "Research guidelines for cookery, sensory evaluation and instrumental tenderness measurements of fresh meat" (2015), American Meat Science Asociation
- Ruiz de Huidobro F, "Changes in meat quality characteristics of bovine meat during the first 6 days post mortem", Meat Sci, 65, pp.1439~1446 (2003)[DOI]
- Szczesniak AS, "Objective measurements of food texture", J Food Sci, 28, pp.410~420 (1963)[DOI]
- Maria Sumampa Coria, "Feeding strategies alter gene expression of the calpain system and meat quality in the longissimus muscle of Braford steers", Animal Bioscience, 33(5), pp.753~762 (2020), 아세아·태평양축산학회[DOI]
- Shackelford SD, "Tenderness classification of beef : I. Evaluation of beef longissimus shear force at 1 or 2 days postmortem as a predictor of aged beef tenderness", J Anim Sci, 75, pp.2417~2422 (1997)[DOI]
- Di Rienzo JA, "InfoStat versión 2012", Grupo InfoStat, FCA, Universidad Nacional de Córdoba, ~ (2012)
- Candeloro P, "Raman database of amino acids solutions : a critical study of extended multiplicative signal correction", Analyst, 138, pp.7331~7340 (2013)[DOI]
- Ertbjerg P, "Muscle structure, sarcomere length and influences on meat quality : A review", Meat Sci, 132, pp.139~152 (2017)[DOI]
- Hopkins DL, "Explaining the variation in the shear force of lamb meat using sarcomere length, the rate of rigor onset and pH", Meat Sci, 88, pp.794~796 (2011)[DOI]
- Pouliot E, "Use of electrical stimulation and chilling to enhance meat tenderness of heavy lambs", Can J Anim Sci, 94, pp.627~637 (2014)[DOI]
- Hughes JM, "A structural approach to understanding the interactions between colour, water-holding capacity and tenderness", Meat Sci, 98, pp.520~532 (2014)[DOI]
- Realini CE, "Effect of pasture vs. concentrate feeding with or without antioxidants on carcass characteristics, fatty acid composition, and quality of Uruguayan beef", Meat Sci, 66, pp.567~577 (2004)
- Brito G, "Effect of different feeding systems(pasture and supplementation)on carcass and meat quality of Hereford and Braford steers in Uruguay", Proc 54th ICOMST, pp.1~3 (2008)
- Ueda Y, "Effects of intramuscular fat deposition on the beef traits of Japanese Black steers(Wagyu) : Original article", Anim Sci J, 78, pp.189~194 (2007)[DOI]
- Beattie RJ, "Preliminary investigations on the effects of ageing and cooking on the Raman spectra of porcine longissimus dorsi", Meat Sci, 80, pp.1205~1211 (2008)[DOI]
- Smith GC, "International perspective : Characterisation of United States Department of Agriculture and Meat Standards Australia systems for assessing beef quality", Aust J Exp Agric, 48, pp.1465~1480 (2008)[DOI]
- Velioglu HM, "Differentiation of fresh and frozen-thawed fish samples using Raman spectroscopy coupled with chemometric analysis", Food Chem, 172, pp.283~290 (2015)[DOI]
- Schmidt H, "Preliminary investigation on the relationship of Raman spectra of sheep meat with shear force and cooking loss", Meat Sci, 93, pp.138~143 (2013)[DOI]
- Nian Y, "Assessment of physico-chemical traits related to eating quality of young dairy bull beef at different ageing times using Raman spectroscopy and chemometrics", Food Res Int, 99, pp.778~789 (2017)[DOI]