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Prediction of crude fat content of longissimus muscle of beef using the ratio of fat area calculated from computer image analysis: Comparison of regression equations for prediction using different input devices at different stations OAK
Kuchida, Keigo; Kono, S; Konishi, Kazuyuki; Van Vleck, L. D.; Suzuki, Mitsuyoshi; Miyoshi, Syunzou.
Crude fat content of longissimus (ribeye) muscle of beef cattle was predicted from a ratio of fat area (RFA) to area of ribeye muscle calculated from computer image analysis (CIA). Cross sections of 64 ribeyes taken from the 6-7(th) rib from cattle at experiment station A and cross sections of 94 ribeyes taken from the 6-7(th) rib from cattle at Experiment Station B were used in this study. Slices (1 to 1.5 cm in thickness) of just the Longissimus dorsi were homogenized and sampled for chemical estimation of crude fat content using petroleum ether. Crude fat content as determined from chemical analysis was used as the true estimate of fat content. A CCD (charge-coupled device) camera was used as the input device at Experiment Station A, and a single-lens...
Palavras-chave: Animal fat; Carcasses; Imagery.
Ano: 2000 URL: http://ir.obihiro.ac.jp/dspace/handle/10322/1027
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Prediction method of beef marbling standard number using parameters obtained from image analysis for beef ribeye OAK
KUCHIDA, Keigo; Tsuruta, Shogo; Van Vleck, L. D.; Suzuki, Mitsuyoshi; Miyoshi, Shunzo.
Factors affecting the difference between the Beef Marbling Standard (BMS) number assigned by examiners (BMSSUB) and the BMS number estimated from marbling percentage by image analysis (BMSFAT) were investigated. Pictures of ribeye area of 106 Japanese Black steers with BMSSUB were used. Marbling percentage in ribeye area,means and standard deviations of the area and of the form score for marbling particles classified into 5 levels (over 0.01,0.05,0.1,0.5,and 1.0 cm2),and standard deviations of marbling percentages in small areas which were obtained by dividing the ribeye 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...
Palavras-chave: Image analysis; BMS number; Japanese Black.
Ano: 1999 URL: http://ir.obihiro.ac.jp/dspace/handle/10322/952
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