A Review of Potential New Methods of On-Line Pork Carcass Evaluation

Forrest, J. C.; Kuei, C. H.; Orcutt, M. W.; Schinckel, A. P.; Stouffer, J. R.; Judge, M. D.

doi:10.2527/jas1989.6782164x

Cited by 60 publications

(31 citation statements)

References 4 publications

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“…Several studies have indicated that electromagnetic scanning (EMS) is capable of accurately determining the lean content of beef (Gwartney et al, 1992) and pork (Forrest et al, 1989) primals, quarters, and carcasses. Gwartney et al (1992) presented a coefficient of determination (CD) of 91.0 and residual standard deviation (RSD) of 1.1 kg for predicting hindquarter lean content by scanning hindquarters.…”

Section: The Effects Of Orientation and Storage Time On The Predictiomentioning

confidence: 99%

The effects of orientation and storage time on the prediction of beef rib composition using electromagnetic scanning

Gwartney

Meseck

Calkins

1995

Journal of Animal Science

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Section: The Effects Of Orientation and Storage Time On The Predictiomentioning

confidence: 99%

The effects of orientation and storage time on the prediction of beef rib composition using electromagnetic scanning

Gwartney

Meseck

Calkins

1995

Journal of Animal Science

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“…Electromagnetic scanning has been shown to be effective in predicting the amount of lean in pork carcasses (Forrest et al, 1989). Limited work has been conducted with beef carcasses or cuts.…”

Section: Resultsmentioning

confidence: 99%

Electromagnetic scanning of beef quarters to predict carcass and primal lean content

Lin

et al. 1994

Journal of Animal Science

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ABSTRACT:To study the use of electromagnetic scanning in prediction of lean content in beef carcasses and cuts, 100 beef cattle (60 steers and 40 heifers), representing a broad range in external fat thickness (. 1 to 2.9 cm) and live weight (414 to 742 kg), were selected. Chilled right sides were divided into streamlined (foreshank, brisket, and ventral plate removed) forequarters ( F Q ) and full hindquarters ( H Q ) and scanned. Primal rounds, loins, ribs, and chucks were fabricated from the right side, scanned, and physically separated into lean, fat, and bone. Prediction equations for dissected lean content and percentage of lean included the peak of the electromagnetic scan response curve (obtained from scanning the HQ or FQ), length, temperature and weight of the scanned cut, and fat thickness at the 12th rib. Using the coefficient of determination, root mean square error, and Mallows' Cp statistic, the best model for each dependent variable (weight and percentage of lean) that included up to five independent variables was selected. Prediction equations for the HQ or FQ of steers accounted for 84 to 93% of the variation in lean weight of beef sides and quarters and 71 to 93% of primals. Sixty-one to 75% of the variation in percentage of lean in sides and quarters and 48 to 65% of primals was also explained. Similar results were obtained for heifer carcasses. Predicting percentage of lean in any scanned cut, rather than weight of lean, accounted for less of the variation. Weight and fat thickness contributed significantly when predicting percentage of lean. These data indicate that electromagnetic scanning is capable of objectively measuring lean content in beef quarters and primals.

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“…A similar result was found by Terry et at. (1989) whilst Forrest et at. (1989) showed that there was little difference between the measurements on warm and chilled pig carcasses.…”

Section: Methods Of Instrumental Grading Of Pig Carcassesmentioning

confidence: 99%

Robotics in Meat, Fish and Poultry Processing

Khodabandehloo¹

1993

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A Review of Potential New Methods of On-Line Pork Carcass Evaluation

Cited by 60 publications

References 4 publications

The effects of orientation and storage time on the prediction of beef rib composition using electromagnetic scanning

The effects of orientation and storage time on the prediction of beef rib composition using electromagnetic scanning

Electromagnetic scanning of beef quarters to predict carcass and primal lean content

Robotics in Meat, Fish and Poultry Processing

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