Does Instrument Grading Spot More Yield Grade 4-5 Carcasses?

A project led through Ohio State Beef extension aims to scrutinise just how reliable video image analysis is in carcass grading.
calendar icon 22 October 2013
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Findings by Steiner et al. (2003) confirmed that video image analysis is highly accurate when compared with USDA official measurements and had an correlation of 0.92 for assessment of variables used in calculation of USDA yield grading. Similar findings were reported by Shackelford et al. (2003), in which video image analysis technology explained more of the variation (90 vs. 73 per cent) in calculated yield grading than USDA on-line graders. Therefore, video image analysis technology was subsequently approved for use in the assessment of yield grading through augmentation and calculation of USDA yield grading parameters. Notice in table 1 the trend in number of Yield Grade 4s and 5s are increasing.

Data reported in the 1995 and 2005 National Beef Quality Audits support an increase in s.c. fat depth (.47 to .51 inch), and percentage of carcasses grading Yield Grade 4 (7.06 to 10.81 per cent) and 5 (0.83 to 2.17 per cent). This current study involved approximately 5000 carcass evaluated by video image analysis technology and USDA on-line graders.

Results and Discussion

Yield grade distribution (n = 5002) for USDA stamped yield grading 1, 2, 3, 4, and 5 was 12.24, 35.23, 41.68, 9.36, and 1.50%, respectively (Table 1). The distribution of video image analysis calculated yield grading 1, 2, 3, 4, and 5 was 10.78, 33.99, 39.86, 13.29, and 2.08%, respectively.

Table 1. USDA yield grades by period of time
1995 to 1999 12.2% 48.0% 38.0% 1.6% 0.12%
2000 to 2004 10.0 43.5 41.9 4.1 0.48
2005 to 2010 10.0 38.3 41.6 8.9 1.27

Calculated percentages among each evaluation method support a slight distribution shift whereby numerically fewer carcasses were classified as yield grading 1, 2, and 3 by video image analysis assessment. However, no significant differences (P > 0.48) were found between the 2 evaluation methods for USDA yield grading classifications 1, 2, or 3. For the yield grading 4 and 5 classifications, results indicated fewer (P < 0.02; 3.93 per cent yield grading 4, 0.58 per cent yield grading 5) carcasses assessed into those categories by USDA graders.

Table 2. Distribution of USDA Yield Grades by video image analysis or on-line USDA Grader (5002 carcasses)
Video Image Analysis 10.78% 33.99% 39.86% 13.29% 2.08%
USDA Grader 12.24 35.23 41.68 9.36 1.50

For producers, understanding and mitigating differences between subjective and objective evaluation methods could be an aid in marketing cattle. If cattle are sold based on a formula, this investigation has indicated that classification of carcasses using Video image analysis-calculated Yield Grade will in turn lead to a shift in the distributions of Yield Grade within each pen marketed where trends indicated fewer yield grading 1 and more yield grading 5 carcasses will be observed.

Literature Cited

Shackelford, S. D., T. L. Wheeler, and M. Koohmaraie. 2003. On-line prediction of yield grade, longissimus muscle area, preliminary yield grade, adjusted preliminary yield grade, and marbling score using the MARC beef carcass image analysis system. J. Anim. Sci. 81:150-155.

Steiner, R., D. J. Vote, K. E. Belk, J. A. Scanga, J. W. Wise, J. D. Tatum, and G. C. Smith. 2003. Accuracy and repeatability of beef carcass longissimus muscle area measurements. J. Anim. Sci. 81:1980-1988.

October 2013

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