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Conservation of water for washing beef heads at harvest
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Conservation of water for washing beef heads at harvest
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R. E. DeOtte
,
K. S. Spivey
,
H. O. Galloway
,
T. E. Lawrence
The objective of this research was to develop methods to conserve water necessary to cleanse beef heads prior to USDA–FSIS inspection. This was to be accomplished by establishing a baseline for the minimum amount of water necessary to adequately wash a head and application of
image analysis
to provide an objective measure of head cleaning. Twenty-one beef heads were manually washed during the harvest process. An average 18.75L (2.49 SD) and a maximum of 23.88L were required to cleanse the heads to USDA–FSIS standards. Digital images were captured before and after manual washing then evaluated for percentage red saturation using commercially available
image analysis
software. A decaying exponential curve extracted from these data indicated that as wash water increased beyond 20L the impact on red saturation decreased. At 4σ from the mean of 18.75L, red saturation is 16.0 percent, at which
logistic regression analysis
indicates 99.994 percent of heads would be accepted for inspection, or less than 1 head in 15,000 would be rejected. Reducing to 3σ would increase red saturation to 27.6 percent, for which 99.730 percent of heads likely would be accepted (less than 1 in 370 would be rejected).
Journal:
Meat Science - MEAT SCI
, vol. 84, no. 3, pp. 371-376, 2010
DOI:
10.1016/j.meatsci.2009.09.004
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References
(7)
Estimation of the Water Requirement for Beef Production in the United States112
(
Citations: 5
)
J. L. Beckett
,
J. W. Oltjen
Published in 2010.
DUAL-COMPONENT VIDEO IMAGE ANALYSIS SYSTEM (VIASCANTM) AS A PREDICTOR OF BEEF RED MEAT YIELD PERCENTAGE AND FOR AUGMENTING APPLICATION OF USDA YIELD GRADES
(
Citations: 15
)
R. C. Cannell
,
J. D. Tatum
,
K. E. Belk
,
J. W. Wise
,
R. P. Clayton
,
G. C. Smith
Computer image analysis for measuring lean and fatty areas in cross-sectioned dry-cured hams1
(
Citations: 4
)
P. Carnier
,
L. Gallo
,
C. Romani
,
E. Sturaro
,
V. Bondesan
Published in 2010.
Video image analysis in the Australian meat industry – precision and accuracy of predicting lean meat yield in lamb carcasses
(
Citations: 14
)
D. L. Hopkins
,
E. Safari
,
J. M. Thompson
,
C. R. Smith
Journal:
Meat Science - MEAT SCI
, vol. 67, no. 2, pp. 269-274, 2004
Evaluation of the E+V video image analysis system as a predictor of pork carcass meat yield1
(
Citations: 4
)
E. K. McClure
,
J. A. Scanga
,
K. E. Belk
,
G. C. Smith