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SHACKELFORD ET AL.

Figure 4. Use of image analysis to identify carcasses that meet a proposed “ideal” longissimus area target (n = 66). T h e i d e a l l o n g i s s i m u s a r e a t a r g e t o f 7 1 t o 9 0 c m 2 w a s d e t e r m i n e d b y T a t u m ( 1 9 9 2 ) . F o r 8 9 % o f s a m p l e s , i m a g analysis correctly predicted whether the sample met the ideal longissimus area target. e

Of the numerous technologies that have been proposed for objectively evaluating beef carcass com- position, image analysis is believed to be the technol- ogy closest to commercial application (NLSMB, 1994).

Recent experiments have indicated that current image

analysis systems (R U S D A g r a d e r s ( R 2 = 2

= .55) are inferior to on-line .59) and off-line expert graders’

(R

2

=

.79)

assessments

of

carcass

cutability

(Belk

et

Brisket, boneless, deckle-off

120

46

54

59

Shoulder clod

114A

54

77

86

Chuck tender

116B

41

73

79

Cube steak

1100

23

48

59

Chuck roll

116A

74

75

76

Ribeye roll

112

51

78

72

Short ribs

123A

45

50

46

Flank steak

193

40

53

55

Tenderloin, side muscle off

190

34

66

72

Strip loin

180A

50

84

74

Top sirloin butt

184

51

78

80

Full knuckle

167A

34

65

78

Top round

168

30

78

82

Gooseneck round

171A

33

82

81

80% lean trimmings

54

83

91

Table 4. Percentage of total variation in cut weights accounted for by carcass weight alone or in combination with yield grade or image analysis

d a b c All s.c. fat and any accessible intermuscular fat was trimmed from Beef product specification code (NAMP, 1997). Cut weights were calculated using a two-variable model that incl calculated yield grade. Cut weights were calculated using a two-variable model that incl predicted retail product yield, which was predicted from image analysis

each cut.

uded hot carcass weight and

uded hot carcass weight and using Equation 15 (Table 3).

carcass

yield

image

NAMPb

weight

gradec

analysisd

Hot

Hot

carcass

carcass

Hot

+

+

Cuta

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