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ARS Home » Plains Area » Clay Center, Nebraska » U.S. Meat Animal Research Center » Genetics and Animal Breeding » Research » Publications at this Location » Publication #96587
Title: A METHOD FOR PREDICTING BEEF MARBLING STANDARD USING PARAMETERS OBTAINED FROM IMAGE ANALYSIS OF BEEF RIB-EYES

Author
item KUCHIDA, K. - UNIV. OF NEBRASKA-LINCOLN
item TSURUTA, T. - UNIV. OF NEBRASKA-LINCOLN
item Van Vleck, Lloyd
item SUZUKI, M. - UNIV. OF NEBRASKA-LINCOLN
item MIYOSHI, S. - UNIV. OF NEBRASKA-LINCOLN

Submitted to: Official Journal of Japanese Society of Zootechnical Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/15/1999
Publication Date: N/A
Citation: N/A

Interpretive Summary: The assignment of a marbling score to the cross-section of the rib-eye of beef cattle in Japan requires a special examiner to assign a subjective score. The purpose of this project was to find a way to use computer analysis of a picture of the cross-section of the rib eye to assign objectively a comparable beef marbling score. The analysis of the computer rimage can provide characteristics such as fraction of the area that shows fat marbling, the rib-eye area, the uniformity of the marbling particles, and shape scores of the marbling particles. These additional characteristics were used in a study of pictures of rib-eye cross-sections of 106 Japanese Black steers to assign objective beef marbling standard numbers that were in close agreement with numbers assigned by trained examiners of the Wagyu Registry Association. The information from image analysis and rib-eye area resulted in over 90% of samples having computer predicted scores within plus/minus one (on a 12 point scale) of the scores assigned by the trained examiner.

Technical Abstract: Factors affecting the difference between the Beef Marbling Standard (BMS) number assigned by examiners (BMSSUB) in Japan and the BMS number estimated from marbling percentage by image analysis (BMSFAT) were investigated. Pictures of rib-eye area of 106 Japanese Black steers were BMSSUB were used. Marbling percentage in rib-eye area, means and standard deviations of the area and of the form score for marbling particles classified into 5 size levels (over 0.01, 0.05, 0.1, 0.5, and 1.0 cm squared), and standard deviations of marbling percentages in small areas which were obtained by dividing the rib-eye into 4, 9, 25, and 100 partitions were calculated by image analysis. Multiple regression equations with the difference between BMSSUB and BMSFAT as the dependent variable were obtained by a stepwise method starting with 25 independent covariates which were image analysis traits and rib-eye area. The number of independent covariates used in the final equation was limited to three. The range of the differences between BMSFAT and BMSSUB was from -3 to +4 and the percentage of differences within scores of plus/minus one was 67.0%, while the range of the difference between BMSSUB and the BMS number which was calculated from a multiple regression equation was from -2 to +2 and the percentage of differences within scores of plus/minus 1 was 91.5%. These results show that the BMS number can be predicted with high accuracy from parameters obtained by image analysis.