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Prediction of physical characteristics of the lamb carcass using in vivo bioimpedance analysis

Published online by Cambridge University Press:  27 November 2018

A. B. Moro Open the ORCID record for A. B. Moro [Opens in a new window] ,
C. C. Pires ,
L. P. da Silva ,
A. M. Menegon ,
R. S. Venturini ,
A. A. Martins ,
R. de O. Mello  and
D. B. Galvani
A. B. Moro*
Affiliation:
Department of Animal Science, Universidade Federal de Santa Maria, Avenida Roraima, 1000, Cidade Universitária, Bairro Camobi, Santa Maria, RS 97105-900, Brazil
C. C. Pires
Affiliation:
Department of Animal Science, Universidade Federal de Santa Maria, Avenida Roraima, 1000, Cidade Universitária, Bairro Camobi, Santa Maria, RS 97105-900, Brazil
L. P. da Silva
Affiliation:
Department of Animal Science, Universidade Federal de Santa Maria, Avenida Roraima, 1000, Cidade Universitária, Bairro Camobi, Santa Maria, RS 97105-900, Brazil
A. M. Menegon
Affiliation:
Department of Animal Science, Universidade Federal de Santa Maria, Avenida Roraima, 1000, Cidade Universitária, Bairro Camobi, Santa Maria, RS 97105-900, Brazil
R. S. Venturini
Affiliation:
Instituto Federal de Educação, Ciência e Tecnologia Farroupilha, Campus of Santo Augusto, Rua Fábio João Andolhe, 1100, Bairro Floresta, Santo Augusto, RS 98590-000, Brazil
A. A. Martins
Affiliation:
Department of Animal Science, Universidade Federal de Santa Maria, Avenida Roraima, 1000, Cidade Universitária, Bairro Camobi, Santa Maria, RS 97105-900, Brazil
R. de O. Mello
Affiliation:
Department of Food Science and Technology, Universidade Federal de Santa Maria, Avenida Roraima, 1000, Cidade Universitária, Bairro Camobi, Santa Maria, RS 97105-900, Brazil
D. B. Galvani
Affiliation:
Embrapa Caprinos e Ovinos, Rodovia Sobral/Groaíras, km 4, Zona Rural, Sobral, CE 62010-970, Brazil
*
†E-mail: andersondazoo@gmail.com
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Abstract

The increase of sheep meat competitiveness in international markets can be attributed to the rise of the quantity and the improvement of the quality of the edible portion of sheep carcasses. Usually, carcass yield is established after the slaughter of the animals. Yet, when carcass yield is determined in vivo, it can be both a costly and subjective method. This study proposes models for predicting the physical characteristics of lamb carcass using bioimpedance analysis (BIA) in live animals. Thirty-one Texel × Ile de France crossbreed ram lambs were slaughtered at 20, 26, 32 or 38 kg of BW. Before the slaughter, values of resistance (Rs) and reactance (Xc) were collected using a single-frequency BIA equipment (Model RJL Quantum II Bioelectrical Body Composition Analyzer). Then, BIA main variables such as body bioelectrical volume (V), phase angle (PA), resistive density (RsD) and reactive density (XcD) were calculated. After slaughter, cold carcass weight (CCW), cold carcass yield (CCY), subcutaneous fat thickness (SFT), soft tissue weight (STW) and soft tissue yield (STY) were also measured. Multiple regression analyses were carried out using the physical characteristics as dependent variables and the bioimpedance values as independent variables. Predictive performance of the models was assessed using leave-one-out cross-validation. The prediction model of CCW was obtained using the V, PA and RsD (R2 = 0.97), STW through the V, RsD and XcD (R2 = 0.97), CCY by Rs, Z and XcD (R2 = 0.69), STY by V and XcD (R2 = 0.67), and SFT only for XcD (R2 = 0.84). The results indicated that BIA has the potential to predict carcass characteristics of lambs at different body masses.

Keywords

sheepcarcass traitssoft tissue yieldbody compositionimpedance
Type
Research Article
Information
animal , Volume 13 , Issue 8 , August 2019 , pp. 1744 - 1749
Copyright
© The Animal Consortium 2018 

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References

Altmann, M, Pliquett, U, Suess, R and Borell, E von 2005. Prediction of carcass composition by impedance spectroscopy in lambs of similar weight. Meat Science 70, 319–327.Google Scholar
Avril, DH, Lallo, C, Mlambo, V and Bourne, G 2013. The application of bioelectrical impedance analysis in live tropical hair sheep as a predictor of body composition upon slaughter. Tropical Animal Health and Production 45, 1803–1808.Google Scholar
Berg, EP and Marchello, MJ 1994. Bioelectrical impedance analysis for the prediction of fat-free mass in lambs and lamb carcasses. Journal of Animal Science 72, 322–329.Google Scholar
Berg, EP, Neary, MK, Forrest, JC, Thomas, DL and Kauffman, RG 1996. Assessment of lamb carcass composition from live animal measurement of bioelectrical impedance or ultrasonic tissue depths. Journal of Animal Science 74, 2672–2678.Google Scholar
Cadavez, VAP and Henningsen, A 2012. The use of seemingly unrelated regression to predict the carcass composition of lambs. Meat Science 92, 548–553.Google Scholar
Gardner, GE, Williams, A, Ball, AJ, Jacob, RH, Refshauge, G, Hocking Edwards, J, Behrendt, R and Pethick, DW 2015. Carcase weight and dressing percentage are increased using Australian Sheep Breeding Values for increased weight and muscling and reduced fat depth. Meat Science 99, 89–98.Google Scholar
Grill, L, Ringdorfer, F, Baumung, R and Fuerst-Waltl, B 2015. Evaluation of ultrasound scanning to predict carcass composition of Austrian meat sheep. Small Ruminant Research 123, 260–268.Google Scholar
Jenkins, TG, Leymaster, KA and Turlington, LM 1988. Estimation of fat-free soft tissue in lamb carcasses by use of carcass and resistive impedance measurements. Journal of Animal Science 66, 2174–2179.Google Scholar
Johansen, J, Aastveit, AH, Egelandsdal, B, Kvaal, K and Røe, M 2006. Validation of the EUROP system for lamb classification in Norway; repeatability and accuracy of visual assessment and prediction of lamb carcass composition. Meat Science 74, 497–509.Google Scholar
Kempster, AJ 1981. Fat partition and distribution in the carcasses of cattle, sheep and pigs: a review. Meat Science 5, 83–98.10.1016/0309-1740(81)90007-3Google Scholar
Kenyon, PR, Maloney, SK and Blache, D 2014. Review of sheep body condition score in relation to production characteristics. New Zealand Journal of Agricultural Research 57, 38–64.Google Scholar
Lambe, NR, Navajas, EA, Schofield, CP, Fisher, AV, Simm, G, Roehe, R and Bünger, L 2008. The use of various live animal measurements to predict carcass and meat quality in two divergent lamb breeds. Meat Science 80, 1138–1149.Google Scholar
Lukaski, HC 2013. Evolution of bioimpedance: a circuitous journey from estimation of physiological function to assessment of body composition and a return to clinical research. European Journal of Clinical Nutrition 67, S2–S9.Google Scholar
Lukaski, HC, Johnson, PE, Bolonchuk, WW and Lykken, GI 1985. Assessment of fat-free mass using bioelectrical impedance measurements of the human body. American Journal of Clinical Nutrition 41, 810–817.Google Scholar
Norman, K, Stobäus, N, Pirlich, M and Bosy-Westphal, A 2012. Bioelectrical phase angle and impedance vector analysis - clinical relevance and applicability of impedance parameters. Clinical Nutrition 31, 854–861.Google Scholar
Owens, FN, Dubeski, P and Hansont, CF 1993. Factors that alter the growth and development of ruminants. Journal of Animal Science 71, 3138–3150.Google Scholar
Ricardo, HA, Fernandes, ARM, Mendes, LCN, Oliveira, MAG, Protes, VM, Scatena, EM, Roça, RO, Athayde, NB, Girão, LVC and Alves, LGC 2015. Carcass traits and meat quality differences between a traditional and an intensive production model of market lambs in Brazil: preliminary investigation. Small Ruminant Research 130, 141–145.Google Scholar
Sarubbi, F, Baculo, R and Iannuzzi, L 2008. Bioelectrical impedance analysis for the prediction of hot carcass weight in buffalo calf. Italian Journal of Animal Science 7, 513–523.Google Scholar
Shackelford, SD, Leymaster, KA, Wheeler, TL and Koohmaraie, M 2012. Effects of breed of sire on carcass composition and sensory traits of lamb. Journal of Animal Science 90, 4131–4139.Google Scholar
Sinanoglou, VJ, Batrinou, A, Mantis, F, Bizelis, I and Miniadis-Meimaroglou, S 2013. Lipid quality indices: differentiation of suckling lamb and kid breeds reared by traditional sheep farming. Small Ruminant Research 113, 1–10.Google Scholar
Swantek, PM, Crenshaw, JD, Marchello, MJ and Lukaski, HC 1992. Bioelectrical impedance: a nondestructive method to determine fat-free mass of live market swine and pork carcasses. Journal of Animal Science 70, 169–177.Google Scholar
Tedeschi, LO 2006. Assessment of the adequacy of mathematical models. Agricultural Systems 89, 225–247.Google Scholar
Wood, JD, MacFie, HJH, Pomeroy, RW and Twinn, DJ 1980. Carcass composition in four sheep breeds: the importance of type of breed and stage of maturity. Animal Production 30, 135–152.Google Scholar
Zollinger, BL, Farrow, RL, Lawrence, TE and Latman, NS 2010. Prediction of beef carcass salable yield and trimmable fat using bioelectrical impedance analysis. Meat Science 84, 449–454.Google Scholar