52a Reunião Anual da Sociedade Brasileira de
Zootecnia
Zootecnia: Otimizando Recursos e Potencialidades
Belo Horizonte – MG, 19 a 23 de Julho de 2015
Uso de câmera de infravermelho para predizer peso, composição corporal e de carcaça em bovinos Nelore e
Angus¹
Gutierrez José de Freitas Assis2, Gustavo Reis Monteiro3, Marcio Machado Ladeira4, Rafael Aparecido Gomes3,
Karina Costa Busato3, José Rodolfo Reis Carvalho3, Mario Luiz Chizzotti5.
1
Parte da dissertação de mestrado do segundo autor.
Graduando em Zootecnia - UFV, Viçosa, Brasil. Bolsista de iniciação científica do CNPq, e-mail: [email protected]
3
Estudante de pós-graduação em Zootecnia - UFLA, Lavras, Brasil.
4
Professor Associado do Departamento de Zootecnia - UFLA, Lavras, Brasil.
5
Professor Adjunto do Departamento de Zootecnia - UFV, e-mail:[email protected]
2
Resumo: Objetivou-se com este trabalho, desenvolver e avaliar medidas biométricas obtidas por imagem de câmera
de infravermelho. Foram utilizados 35 tourinhos, sendo 17 da raça Nelore e 18 da raça Angus. As medidas obtidas
foram correlacionadas com variáveis relacionadas à composição corporal e de carcaça, assim como do peso
corporal (Pc) dos animais. As imagens foram obtidas no dia anterior ao abate e, a partir delas, foram calculadas as
seguintes medidas biométricas: altura (H), área do plano dorsal (APD), largura anterior (AW), Largura da costela
(RW) e largura posterior (PW). A PW e H apresentaram correlação positiva com o peso corporal. A APD
apresentou, nas duas raças, alta correlação com as variáveis de composição corporal e com o peso corporal (r =
0.90; 0.88, P<0.05). Foi desenvolvido um índice de composição corporal (BCI) a partir dos dados de Pc , H e APD.
Em ambas as raças, o BCI estimou satisfatoriamente a porcentagem de extrato etéreo na carcaça e nos animais da
raça Angus estimou, com maior precisão, os demais componentes corporais, em relação às estimativas baseadas
apenas no Pc. O desenvolvimento de um índice de composição corporal a partir de medidas biométricas tem grande
potencial para predição da composição da carcaça e ponto de abate. A APD mostrou-se eficiente na predição do
peso corporal de bovinos.
Palavras–chave: crescimento, carcaça, medidas biométricas, pecuária de precisão
Using Infrared camera to predict body weight and composition of carcass and body in Nellore and Angus
cattle¹
Abstract: The objective of this study was to develop and evaluate biometric measurements obtained by an infrared
camera. There were used 35 young bulls, 17 of Nellore and 18 of Angus breed. Measurements obtained from
images were correlated with variables related to body composition as well as with body weight (BW). The images
were taken the day before slaughter and, from them, the following biometric measurements were calculated: height
(H), dorsal plan area (DPA), anterior width (AW), rib width (RW) and posterior width (PW). The PW and H had a
positive correlation with BW. DPA presented, in both breeds, a high correlation with the body composition
variables as well as with BW(r = 0.90; 0.88, P<0.05). It was developed a body composition index (BCI) from
measurements of BW, H and DPA. In both breeds, the BCI was able to estimate the percentage of ether extract in
the carcass, and in Angus bulls, it estimated more accurately than BW the body composition. The development of a
body composition index from biometric measurements has huge potential to predict carcass composition as well as
slaughter point. The DPA was efficient in predicting cattle body weight.
Keywords: biometric measurements, carcass, growth, precision livestock farming
Introduction
Body and carcass composition have great nutritional and economic importance in beef cattle production
system. The estimation of body composition in live animals is crucial for the development of more efficient
production systems that use less resource and increase the accuracy of nutrient requirements prediction and to
support the decision of the optimal slaughter point to increase carcass quality (TEDESCHI; FOX; GUIROY, 2004).
Infrared images are non invasive and a cost effective way to monitor animal development. Therefore it was aimed
to evaluate and develop biometric measurements from infrared camera images that can predict body and carcass
composition.
Material e Methods
Thirty five young bulls, being 17 of Nellore and 18 of Aberdeen Angus breed were used. In the day before
slaughter, animals were conducted to a chute equipped with a infrared camera device adapted to collect images
from above de dorsal plan of the animals (PreciZoo, Viçosa, Brazil). This apparatus is composed of an infrared
laser projector and an infrared camera. A constant wave pattern is projected onto the subject and recorded by
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52a Reunião Anual da Sociedade Brasileira de
Zootecnia
Zootecnia: Otimizando Recursos e Potencialidades
Belo Horizonte – MG, 19 a 23 de Julho de 2015
infrared camera. The distance between the camera and the subject (depth) is obtained by a triangulation process.
This information is obtained by a standard splashed points created by the laser and captured by the infrared camera,
forming a color gradient image. From the generated image, it was assessed the anterior, rib and posterior width of
the animals, that were calculated by the difference of the pixel values points in x-axis, after calibration with a
standard objected previously recorded under the same conditions. An image of the scale without the presence of the
animal was also used to calibrate the sensor, and used to convert pixels of the images into mm.
The measurement of the dorsal plan area (DPA) was determined from a perpendicular line just above
animals shoulders. The software ImageJ (USA) was used to calculate the DPA from the collected infrared images,
cleaned from pixels not related to animal’s body. For calibration of area measurement tool it was used the distance
Arrow tool. The tolerance of the spectrum used in defining the selection area to be measured was 12 and the range
for all measurements was 202.5 pixels per meter, obtained through the chute length.
The day after the collection of images, all the animals were slaughtered. The gastrointestinal tract of each
animal was emptied, washed, weighed and together with all other body components, was used to determine the
empty body weight (EBW). Then, all non-carcass components were ground together and sampled. The carcass of
each animal was divided into two half-carcasses, which were weighed and then cooled in a cold chamber at 2 ° C
for 24 hours. The left half carcass, were dissected into separable muscle, bone and fat, that were weighed, and
subsequently grounded, to represent a carcass sample. The chemical composition of carcass and empty body was
then assessed accordinf to AOAC (1990) standard methods. Body crude protein (bCP) and ether extract (bEE) and
carcass crude protein (bCP) and ether extract (cEE) were the determined.
The Pearson’s correlations between biometric measurements and body and carcass variables were
evaluated using PROC CORR of SAS 9.1 (Statistical Analysis System Institute - SAS Institute, 2003). Then, linear
and stepwise regressions were applied to evaluate prediction equations using multiples biometric inputs, using
PROC GLM of SAS 9.1
Results and Discussion
In both breeds, the linear biometric measurements of AW, RW, PW and H showed no significant
correlations with any chemical composition variable in body or carcass (p> 0.10). Similar results were reported by
Ciryllo et al. (2003) who studied the relationship between hip height and length with carcass fat, kidney fat and
visceral fat and found no significant correlation with them.
Angus PW was correlated with BW, EBW and carcass weight (r = 0.64, 0.69 and 0.67, respectively). The
height was only correlated (r = 0.47) with BW in Angus. In Nelore, PW was also correlated with BW, EBW and
carcass weight (r = 0.51, 0.60 and 0.51). There was no correlation of height (p >0.05) with any variable in Nellore.
DPA showed high correlation with physical and chemical body composition. DPA in Angus breed had
significant correlation (p<0.05) with all characteristics studied, except for cCP and bCP, and was the best single
measurement among those studied. Nonetheless, In Nellore, correlations of DPA with the proportions of ether
extrat or protein in the body or carcass were not significant (P>0.05).
From correlation of multiple biometric measurements with body composition, it was designed a body
composition index: BCI = DPA0.75 × (1.86H × BW0.75)-1.
The BCI was positively correlated with all body and carcass variables (P<0.05) in both breeds. BCI
equations to predict fat content of carcass and body are presented in Table 1.
Table 1. Predicting body and carcass ether extract content (bEE and cEE) from body composition index (BCI) in
Nellore and Angus bulls.
Equations
n
R2
p-value
Angus
bEE= -56.47 + 2.126*BCI
18
0.77
<0.0001
cEE = -24.18 + 1.213* BCI
18
0.72
<0.0001
Nellore
bEE = 1.498 + 1.258 *BCI
17
0.61
0.0002
cEE = -7.773 + 1.100 *BCI
17
0.72
<0.0001
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52a Reunião Anual da Sociedade Brasileira de
Zootecnia
Zootecnia: Otimizando Recursos e Potencialidades
Belo Horizonte – MG, 19 a 23 de Julho de 2015
Additionally to estimate body composition, biometric measurements can be used to predict body weight,
replacing traditional scales in beef production systems. The DPA presented high correlation with BW in both
genetic groups studied. Therefore, equations to predict BW from images were developed (Table 2).
Table 2. Body weight (BW, kg) predictions from dorsal plane area (DPA, cm2) in Angus and Nellore bulls
Equation
n
R2
p-value
Angus :
BW = -195.02 +555,75* DPA
18
0.78
0.0017
Nellore:
BW = 25.05 + 332,37 * DPA
17
0.80
0.0001
Conclusions
Combined biometric measurements obtained from images were correlated with animal's body composition.
The use of an index of body composition has potential to be used to estimate carcass composition. The dorsal plane
area was efficient in predicting cattle body weight.
Acknowledgements
Authors thank the FAPEMIG and CNPq for having provided funds for this project.
References
Cyrillo, J.N.S.G. et al. Genetic changes to selection for yearling weight and correlated response on body
measurements in Nelore cattle. In: WORLD CONGRESS ON GENETIC APPLIED TO LIVESTOCK
PRODUCTION, 7. 2002, Montpellier. Proceedings... Montpellier: WCGALP, 2002. CD-ROM.
TEDESCHI, L. O.; FOX, D. G.; GUIROY, P. J. A decision support system to improve individual cattle
management: 1., a mechanistic, dynamic model for animal growth. Agricultural Systems, Essex, v. 79,
n. 2, p. 171-204, Feb. 2004.
STATISTICAL ANALYSIS SYSTEM INSTITUTE.User’s guide.Cary, 2003.129 p.
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