Visual evaluation of beef tenderness by using surface structural observations and its relationship to meat colour

Modika, K. Y.; Frylinck, L.; Moloto, K. W.; Strydom, P.E.; Heinze, PH; Webb, E.C.

doi:10.4314/sajas.v45i3.4

Cited by 11 publications

(7 citation statements)

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“…Also on day 3 variations in SL among different breeds were evident. These results contradict those reported by Modika et al [ 37 ] suggesting that meat tenderisation begins immediately after slaughter. The present results suggest that immediately after slaughter, there is a breed related enzymatic proteolytic system activation which can be associated with the muscle nanostructure degradation but not directly linked to tenderness since differences in tenderness related attributes such as SL were evident from day 3.…”

Section: Resultscontrasting

confidence: 99%

Effect of the muscle nanostructure changes during post-mortem aging on tenderness of different beef breeds

Soji

2021

Anim Biosci

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Objective: Tenderness is a very complex feature and the process of its formation is very complicated and not fully understood. Its diversification is one of the most important problems of beef production, as a result beef aging is widely used to improve tenderness as it is believed to provide a homogeneous product to consumers. While few studied have evaluated the muscle structure properties in relation to tenderness from early post-mortem, there little to no information available on how the muscle nanostructure of beef carcasses changes during post-mortem ageing to determine the appropriate aging time for acceptable tenderness. Methods: Muscle nanostructure (myofibril diameter (MYD), myofibril spacing (MYS), muscle fibre diameter (MFD), muscle fibre spacing (MFS) and sarcomere length (SL)), meat tenderness and cooking loss (CL) were measured on 20 A2 longissimus muscles of Bonsmara, Beefmaster, Hereford and Simbra at 45 mins , 1 , 3 and 7 days post-slaughter. Muscle nanostructure was measured using a scanning electron microscope, while tenderness was measured using Warner Bratzler Shear Force. Results: At 45 minutes post-slaughter, breed affected MYD and MYS only, while at 24 hrs it also affected MFD and MFS. On day 3 breed effected MFS and SL, while on day 7 breed effected tenderness only. As the muscles matured, both MYD and MYS decreased while CL increased and the muscles became tender. There was no uniformity on muscle texture features (surface structure, fibre separation, muscle contraction and relaxation) throughout the ageing period. Conclusion: Meat tenderness can be directly linked to breed related myofibril structure changes during aging in particular the myofibril diameter, spacing between myofibrils and their interaction; while the muscle fibre diameter, spacing between muscle fibres, sarcomere length and cooking loss explain the non-uniformity in beef tenderness.

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Section: Resultscontrasting

confidence: 99%

Effect of the muscle nanostructure changes during post-mortem aging on tenderness of different beef breeds

Soji

2021

Anim Biosci

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“…In addition, according to the results of the present study, the tenderness of the three cattle types on two different cuts (Senga: sirloin: 5.54 ± 1.90, chunk: 5.25 ± 2.47; Sheko: sirloin: 5.43 ± 2.76, chunk: 6.33 ± 2.28) was in agreement with the findings of [ 47 ], who showed that the muscles of Holstein Friesian bulls were 6.06 ± 0.199, 5.56 ± 0.199, 5.65 ± 0.199 and 5.97 ± 0.199, respectively. Another study reported [ 32 ] that beef muscle tenderness was 26.77 ± 2.202, which was not in line with the present study.…”

Section: Resultscontrasting

confidence: 96%

“…Similarly, Ref. [ 32 ] reported that the mean beef tenderness was 14.26 ± 3.9, which was greater than that in the present study. The difference in tenderness might not be due to the breed effect.…”

Section: Resultscontrasting

confidence: 68%

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Modeling of Ethiopian Beef Meat Marbling Score Using Image Processing for Rapid Meat Grading

Erena,

Belay,

Hailu

et al. 2024

J. Imaging

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Meat characterized by a high marbling value is typically anticipated to display enhanced sensory attributes. This study aimed to predict the marbling scores of rib-eye, steaks sourced from the Longissimus dorsi muscle of different cattle types, namely Boran, Senga, and Sheko, by employing digital image processing and machine-learning algorithms. Marbling was analyzed using digital image processing coupled with an extreme gradient boosting (GBoost) machine learning algorithm. Meat texture was assessed using a universal texture analyzer. Sensory characteristics of beef were evaluated through quantitative descriptive analysis with a trained panel of twenty. Using selected image features from digital image processing, the marbling score was predicted with R2 (prediction) = 0.83. Boran cattle had the highest fat content in sirloin and chuck cuts (12.68% and 12.40%, respectively), followed by Senga (11.59% and 11.56%) and Sheko (11.40% and 11.17%). Tenderness scores for sirloin and chuck cuts differed among the three breeds: Boran (7.06 ± 2.75 and 3.81 ± 2.24, respectively), Senga (5.54 ± 1.90 and 5.25 ± 2.47), and Sheko (5.43 ± 2.76 and 6.33 ± 2.28 Nmm). Sheko and Senga had similar sensory attributes. Marbling scores were higher in Boran (4.28 ± 1.43 and 3.68 ± 1.21) and Senga (2.88 ± 0.69 and 2.83 ± 0.98) compared to Sheko (2.73 ± 1.28 and 2.90 ± 1.52). The study achieved a remarkable milestone in developing a digital tool for predicting marbling scores of Ethiopian beef breeds. Furthermore, the relationship between quality attributes and beef marbling score has been verified. After further validation, the output of this research can be utilized in the meat industry and quality control authorities.

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“…Although consumer visual assessment provides a direct answer to the preferences of consumers, a benefit to using instrumental measurements of color is the possibility of comparing the quantitative values with those found in other studies. Color evaluation is an essential part of meat research (Modika et al., 2015) and important for understanding the quality and the value of beef (Holman et al., 2017). Yet, this task is limited by the lack of establishing objective instrumental thresholds to compare with subjective consumer‐based definitions of acceptable meat color.…”

Section: Effect Of Degree Of Doneness On the Sensory Properties Of Meatmentioning

confidence: 99%

Effects of increasing internal end‐point temperatures on physicochemical and sensory properties of meat: A review

Schwartz

Marais

Strydom

et al. 2022

Comp Rev Food Sci Food Safe

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Although many efforts have been made to improve and control the eating quality of meat, there is still high variability in palatability, which may ultimately result in customer dissatisfaction. Beef meat is especially intricate to study since consumers have specific preferences for degrees of doneness. The degrees of doneness in beef is known to affect its physicochemical properties and have a subsequent effect on palatability. Nevertheless, an in‐depth investigation into the exact changes that occur with increasing internal end‐point temperatures of meat is yet to be explored. With researchers implementing various cooking methods and cooking conditions (i.e., sample preparation and internal end‐point temperatures), the results of studies are often impossible to compare. This review provides an overview of the various benefits and drawbacks of the cooking methods commonly used at home, in commercial enterprises, and research on meat. Furthermore, the physicochemical changes in meat with increasing degrees of doneness are discussed in detail with considerations of the subsequent changes in the sensory properties of meat.

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Visual evaluation of beef tenderness by using surface structural observations and its relationship to meat colour

Cited by 11 publications

References 0 publications

Effect of the muscle nanostructure changes during post-mortem aging on tenderness of different beef breeds

Effect of the muscle nanostructure changes during post-mortem aging on tenderness of different beef breeds

Modeling of Ethiopian Beef Meat Marbling Score Using Image Processing for Rapid Meat Grading

Effects of increasing internal end‐point temperatures on physicochemical and sensory properties of meat: A review

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