THE PREDICTION OF FAT PERCENTAGE IN THE <i>LONGISSIMUS DORSI</i> MUSCLE IN FED BEEF USING NUCLEAR MAGNETIC RESONANCE

García, Lyda G.; Lawrence, T.E.; Montgomery, T. H.; Parker, David B.; Brown, Michael S.

doi:10.1111/j.1745-4573.2006.00057.x

Cited by 6 publications

(10 citation statements)

References 3 publications

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“…Moore et al (2010) also reported an increase in fat percentage variance as marbling score increased and that both expert panel graders and camera grading precision decreased as marbling score increased. Garcia et al (2006) found similar results of variation in fat percentage using the CEM.…”

Section: Prediction Equations For Fat Determination Methodssupporting

confidence: 67%

“…Compared with Moore et al (2010), means for ether-extractable fat in this study were numerically greater for SLAB, MD, and SL and less for MT and SM. Garcia et al (2006) reported the same relative relationships using microwave drying and NMR with the CEM SMART Trac for determining percentage of fat within LM. Means for CEM fat were numerically less for all marbling levels in this study compared with Garcia et al (2006), which may be due to sample size differences.…”

Section: Crude Fatmentioning

confidence: 87%

“…Garcia et al (2006) reported the same relative relationships using microwave drying and NMR with the CEM SMART Trac for determining percentage of fat within LM. Means for CEM fat were numerically less for all marbling levels in this study compared with Garcia et al (2006), which may be due to sample size differences. Overall, greater marbling scores were expected to result in greater fat percentages because Means within a column lacking a common subscript letter differ (P < 0.05).…”

Section: Crude Fatmentioning

confidence: 87%

See 2 more Smart Citations

Prediction of fat percentage within marbling score on beef longissimus muscle using 3 different fat determination methods1

Dow

Wiegand

Ellersieck

et al. 2011

Journal of Animal Science

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Consumers are concerned with fat consumption from meat products, and the ability to determine fat has changed with recent technological advances. The objective of this study was to predict fat percentage within marbling scores and compare 3 fat analysis procedures. Steaks (n = 119) were selected by USDA grading system using an E + V Vision Grading camera at a commercial beef plant during 1 d. Two samples per carcass were cut from the 13th rib, both sides, and transported to the University of Missouri meat laboratory. The sample from the right side of the carcass was allotted to Warner-Bratzler shear force, and the sample from the left side, which was graded by the camera, was allotted to fat extraction. Warner-Bratzler shear force samples were cut into 2.54-cm steaks and aged for 14 d. Steaks allotted to fat extraction were trimmed of all external fat and twice ground using 8- and 4-mm grinding plates. The finely ground beef was then split into its allotted fat-extraction methods. The 3 methods used in fat extraction were 2:1 chloroform/methanol (Folch), ether-extractable fat (ether), and microwave drying and nuclear magnetic resonance (CEM). Warner-Bratzler shear force values were not different between marbling scores (P > 0.05). Regardless of fat extraction method, fat percentage increased as marbling score increased (P < 0.05). All regression equations for fat percentage, regardless of extraction method, were linear. Prediction equation for fat percentage using CEM was -3.46 + 0.016 (marbling score), R(2) of 0.824 (P < 0.0001). Prediction equation for fat percentage using ether was -3.08 + 0.017 (marbling score), R(2) of 0.859 (P < 0.0001). Prediction equation for fat percentage using Folch was -3.42 + 0.019 (marbling score), R(2) of 0.816 (P < 0.0001). When the CEM, Folch, and ether methods were compared, CEM and Folch regression lines had different slopes (P < 0.05). The slope of the regression line for ether was not different (P > 0.05) from CEM or Folch. Overall, ether is the most accurate method based on the R(2) value, but CEM is environmentally safe and the fastest method for determining total crude fat percentage.

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Section: Prediction Equations For Fat Determination Methodssupporting

confidence: 67%

Section: Crude Fatmentioning

confidence: 87%

Section: Crude Fatmentioning

confidence: 87%

See 1 more Smart Citation

Prediction of fat percentage within marbling score on beef longissimus muscle using 3 different fat determination methods1

Dow

Wiegand

Ellersieck

et al. 2011

Journal of Animal Science

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show abstract

“…In the same context of non-destructive evaluation, few works have been identified in the literature [13,14]. This could be due to the nature of the problem which is both recent and complex.…”

Section: Introductionmentioning

confidence: 99%

Visible and near-infrared light transmission: A hybrid imaging method for non-destructive meat quality evaluation

Ziadi

Maldague

Saucier

et al. 2012

Infrared Physics & Technology

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“…The range of the volumetric marbling of the meat samples is estimated at 9 to 27 % of the volumetric meat sample. Garcia et al [11] predicted the percentage of intramuscular fat in beef Longissimus dorsi muscle classified as "Prime" with respect to the U.S Department of Agriculture (USDA) grading system [11], which is equivalent to AAA grade in Canada. In this study, the predicted minimum and maximum values of marbling ranged between 7.09 and 18.32%, which demonstrates that our estimation is in accordance with the recognized grading system.…”

Section: Resultsmentioning

confidence: 99%

Image analysis in computer vision: A high level means for Non-Destructive evaluation of the marbling in the beef meat

Ziadi¹,

Maldague²,

Saucier³

2010

Proceedings of the 2010 International Conference on Quantitative InfraRed Thermography

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Evaluation of meat quality by computer vision has been an ambitious area of research in recent years. Marbling (intramuscular fat tissue) in beef meat is one of the most important criteria for quality in meat grading systems. Chemical analysis, a destructive and expensive method, is the most frequently used for quantitative evaluation of marbling in beef meat. In this paper, a new Non-Destructive approach using computer vision is proposed as a possible alternative to the traditional chemical method. It is demonstrated that using near-infrared light in transmission mode, it is possible to detect not only the visible fat on the meat surface but also under the surface. Hence, in combining the analysis of the two sides of a meat sample, it is possible to estimate the overall percentage of marbling in this meat sample. The result of this new study showed that the proposed method is a valuable technique, thereby demonstrating the potential of implementing this approach in a vision system to quantify meat quality objectively.

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THE PREDICTION OF FAT PERCENTAGE IN THE LONGISSIMUS DORSI MUSCLE IN FED BEEF USING NUCLEAR MAGNETIC RESONANCE

Cited by 6 publications

References 3 publications

Prediction of fat percentage within marbling score on beef longissimus muscle using 3 different fat determination methods1

Prediction of fat percentage within marbling score on beef longissimus muscle using 3 different fat determination methods1

Visible and near-infrared light transmission: A hybrid imaging method for non-destructive meat quality evaluation

Image analysis in computer vision: A high level means for Non-Destructive evaluation of the marbling in the beef meat

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