1. As tecnologias mais modernas
de tipificação de carcaças e
aplicação possível no Brasil
Bruno C. N. Cunha, M. Sc.

2. Histórico
Competições
de julgamento
de carcaças
1927 iniciou-se o
serviço oficial “USDA”
de classificação

3. Enviando os sinais corretos ao mercado
Todos comprados a preços similares / @

4. Analise de Video Imagem

5. Como funciona

6. CVS Dual Component System
Camera I
Camera II

7. Informações
! Medições de carcaças
! rea de olho de lombo
A
! spessura de gordura
E
! armoreio %
M
! Previsão de carne vendavel
! Yield grades (com décimos – 0,1)
! Previsão de cortes
! BeefCam® previsão de maciez
! Melhoria do “Quality Grade”

8. Câmera de carcaças quentes

11. YIELD PREDICTION

12. Carcaça quente - Equipamento em
funcionamento

14. Câmera de carcaças resfriadas

15. Carcaça resfriada - Equipamento
em funcionamento

18. Area de olho de lombo
Espessura de gordura

19. Melhorias no “On-Line Yield Grade”

20. Painel de melhoria da tipificação
14.1in.2
2.8 3.1
Source: Steiner et al. (NCBA/CSU, 2000)

21. USDA Yield Grades Melhorados:
Médias dos índices de Erro absolutos
.6 Belk et al. (1997)
CVS .52
.5 ViaScan
.40
.4 .34
.32
.3 .25 .24
.20 .21
.2 .14
.1
.0
HCW: Real Real Real Real Real
KPH: Real Nenhum Real Nenhum Grader
REA: Machine Machine Machine Machine Grader
PYG: Expert Expert Grader Grader Grader
Source: Steiner et al. (2000)

22. Maior % acerto no valor real
Até US$20 do valor real – tabela = 22% VIAscan = 78%
Source: Steiner et al. (2000)

23. Sistema INAC – estudo Vote et al. 2002.
(CSU, RMS, INIA e INAC).

24. Medições objetivas de composição
de carcaças
• Beef Classification
System ™ (BCS ™)
• Computer Vision
System ™ (CVS ™)

25. VIA Estudo de rendimentos de cortes
Passo 1 Passo 2
Passo 3 Passo 4

26. Prevendo Rendimento de Carne
vendável no Uruguai
Modelo CV - R2
INAC Fat Score 0.20
INAC Sex 0.25
USDA a PYG 0.51
USDA a PYG and REA 0.60
USDA a PYG, REA and HCW 0.61
USDA YG 0.54
Vote et al. (2002)

27. Prevendo Rendimento de carne
vendável BCS e CVS no Uruguai
R2
Modelo 10mm 5mm Tela CV
BCS 0.48 0.50 0.58 0.60
CVS 0.41 0.45 0.55 0.57
BCS and CVS 0.52 0.56 0.66 0.67
Vote et al. (2002)

29. CVS/BeefCAM
TM

33. BeefCam - Imagens
BeefCam Score = -0.3
BeefCam Score = -0.2
BeefCam Score = -0.1
Certified Tender
Certified Tender
Certified Tender
BeefCam Score = 0.0
BeefCam Score = 0.1
BeefCam Score = 0.2
Not-Certified Tender
Not-Certified Tender
Not-Certified Tender

35. Prototype BeefCAM Certification of
Beef Carcasses (N = 769)
% of Population % of Certified Cattle
Certified That Were Tough
All Carcasses 51.9 7.8 (92.2)
Upper 2/3 Choice 57.3 4.3 (95.7)
Lower 1/3 Choice 58.5 6.3 (93.7)
Select 37.5 16.5 (83.5)
Source: Wyle et al. (CSU/NCBA, 1999)

36. Prototype Accuracy Based On WBS Using
BeefCam Output Plus QG (N = 769)
Tough WBS Values, %
Carcasses
Product Line Certified, % Total Certified Rejected
All Carcasses 53.4 13.8y 5.6x 23.2z
Top Choice 78.0 7.9x 4.8x 18.9y
Low Choice 59.1 10.3xy 6.7x 15.4y
Select 19.8 24.7y 4.4x 23.8y
x, y, z Percentages within the row differ (P < .05).
Source: Wyle et al. (1999)

37. CSU WBS for TAMU BeefCam™ Validation Samples:
Nolan Ryan Tender Aged Natural Beef (N = 114; August 2001)
Sample Population Characteristics:
 8.6% of Select carcasses had WBS > 4.5 kg
2
 0.2% of Select carcasses had WBS > 5.0 kg
1
 8.8% of Choice carcasses had WBS > 4.5 kg
1
 2.5% of Choice carcasses had WBS > 5.0 kg
1

38. TAMU BeefCam™ Validation:
Nolan Ryan Tender Aged Natural Beef (N = 114; August 2001)
d,e,f,g,h,i BeefCam Scores differ (P < .05).
 There
“ were 50% fewer ribeye steaks with > 10 lb. Shear force from
USDA Select NRTAB-Accepted carcasses than from USDA Select
NRTAB-Rejected carcasses. USDA Select NRTAB-Accepted steaks
tended to perform similarly to USDA Choice ribeye steaks.”
 .
“ . . BeefCam does provide added assurance of acceptable tenderness
over using solely the USDA Quality Grading System.”
Source: Hale et al. (TAMU/NRTAB; 2001)

39. CVS BeefCAM no Uruguai
Identificação de cortes escuros
Corretamente Incorretamente
Classificação N Identificado (%) Identificado
Escuro 40 37 (92.5%) 3
Normal 305 282 (92.5%) 23
Vote et al. (2002)

40. Prevendo “Warner-Bratzler
Shear Force” (WBS) no Uruguai
Variaveis do Modelo WBS R2
INAC Fat Score 0.10
INAC Muscle Score 0.09
INAC Sex 0.07
INAC Dentition 0.04
USDA Maturity 0.18
USDA Marbling Score 0.20
CVS BeefCAM 0.20
Vote et al. (2002)

41. Segregando carcaças por maciez no
Uruguai
Identificando carcaças macias (N = 305)
Dark Cutters Removidas
Classification* N Mean WBS (SD) WBS > 4.5 kg
Tough 152 4.16 (1.39) 30.3%
Tender 152 3.29 (0.77) 6.5%
*The top 50% predicted most tender carcasses were classified as “Tender”
Vote et al. (2002)

42. Perguntas?