Dual energy X-ray absorptiometry is a valid tool for assessing in vivo body composition of broilers
Camila Angelica Gonçalves A C , Nilva Kazue Sakomura A C , Edney Pereira da Silva A , Silvana Martinez Baraldi Artoni A , Rafael Massami Suzuki A and Robert Mervyn Gous B CA Departamento de Zootecnia, UNESP – Universidade Estadual Paulista, Via de Acesso Professor Paulo Donato Castellane, s/n CEP: 14884-900, Jaboticabal, São Paulo, Brazil.
B BSchool of Agricultural, Earth and Environmental Sciences, University of KwaZulu-Natal,Carbis Road, 3201, Scottsville, Pietermaritzburg, South Africa.
C Corresponding author. Email: camilaangelicagoncalves@gmail.com; sakomura@fcav.unesp.br
Animal Production Science 59(5) 993-1000 https://doi.org/10.1071/AN17637
Submitted: 22 September 2017 Accepted: 4 April 2018 Published: 7 June 2018
Abstract
The use of non-invasive techniques to estimate body composition in animals in vivo conforms to the desire to improve the welfare of animals during research and also has the potential to advance scientific research. The purpose of the present study was to determine a predictive equation of the dual energy X-ray absorptiometry (DXA) method for broilers by comparing the measurement of body composition using DXA with that by chemical analysis. In total, 720 day-old Cobb500 broilers were distributed into a split-plot arrangement 3 (crude protein concentrations of diets) × 2 (genders) × 2 (methods of chemical body evaluation), with six replications of 20 birds each. To promote the modification of the body composition of broilers, diets varied in the crude protein concentration, which was 70%, 100% and 130% of the required. Two hundred and sixteen birds in different ages were evaluated by its bodyweight, lean, fat and ash contents. The data were submitted to ANOVA and it was demonstrated that the dietary crude protein levels applied allowed a greater variation of the body composition of the birds. Also, the results indicated that the DXA method did not predict fat mass, lean mass or bone mineral content as well as did chemical composition analysis, resulting in the need to develop regression equations for improving the in vivo prediction of these chemical components. The regression equations developed here enable the feather-free body composition of individual broilers to be directly estimated throughout growth using the DXA non-invasive technique.
Additional keywords: carcass deposition, fat deposition.
References
AOAC (2005) ‘Official methods of analysis of AOAC International.’ 18th edn. (Association of Analytical Communities: Gaithersburg, MD)Bazzocchi A, Ponti F, Albisinni U, Battista G, Guglielmi G (2016) DXA: technical aspects and application. European Journal of Radiology 85, 1481–1492.
| DXA: technical aspects and application.Crossref | GoogleScholarGoogle Scholar |
Brommage R (2003) Validation and calibration of DEXA body composition in mice. American Journal of Physiology. Endocrinology and Metabolism 285, E454–E459.
| Validation and calibration of DEXA body composition in mice.Crossref | GoogleScholarGoogle Scholar |
Buyse J, Swennen Q, Janssens G, Decuypere E, Geers R (2003) Evaluation of dual-energy X-ray absorptiometry to determine the in vivo body composition of broilers. Publication-european association for animal production 109, 477–480.
Danisman R, Gous R (2011) Effect of dietary protein on the allometric relationships between some carcass portions and body protein in three broiler strains. South African Journal of Animal Science 41, 194–208.
Emmans GC (1989) The growth of turkeys. In ‘Recent advances in turkey science. Poultry science symposium’. (Eds C Nixey, TC Grey) pp. 135–166. (Butterworths: London)
Hedrick H (1983) Methods of estimating live animal and carcass composition. Journal of Animal Science 57, 1316–1327.
Jebb SA, Garland SW, Jennings G, Elia M (1996) Dual-energy X-ray absorptiometry for the measurement of gross body composition in rats. British Journal of Nutrition 75, 803–809.
| Dual-energy X-ray absorptiometry for the measurement of gross body composition in rats.Crossref | GoogleScholarGoogle Scholar |
Johnson MS, Watts RJ, Hammer HS, Nagy TR, Watts SA (2017) Validation of dual‐energy X‐ray absorptiometry to predict body composition of channel catfish, Ictalurus punctatus. Journal of the World Aquaculture Society 48, 122–131.
| Validation of dual‐energy X‐ray absorptiometry to predict body composition of channel catfish, Ictalurus punctatus.Crossref | GoogleScholarGoogle Scholar |
Kohrt WM (1995) Body composition by DXA: tried and true? Medicine and Science in Sports and Exercise 27, 1349–1353.
| Body composition by DXA: tried and true?Crossref | GoogleScholarGoogle Scholar |
Lösel D, Kremer P, Albrecht E, Scholz AM (2010) Comparison of a GE Lunar DPX-IQ and a Norland XR-26 dual energy X-ray absorptiometry scanner for body composition measurements in pigs – in vivo. Archives Animal Breeding 53, 162–175.
| Comparison of a GE Lunar DPX-IQ and a Norland XR-26 dual energy X-ray absorptiometry scanner for body composition measurements in pigs – in vivo.Crossref | GoogleScholarGoogle Scholar |
Mitchell A, Rosebrough R, Conway J (1997) Body composition analysis of chickens by dual energy X-ray absorptiometry. Poultry Science 76, 1746–1752.
| Body composition analysis of chickens by dual energy X-ray absorptiometry.Crossref | GoogleScholarGoogle Scholar |
Mitchell A, Scholz A, Pursel V, Evock-Clover C (1998a) Composition analysis of pork carcasses by dual-energy X-ray absorptiometry. Journal of Animal Science 76, 2104–2114.
| Composition analysis of pork carcasses by dual-energy X-ray absorptiometry.Crossref | GoogleScholarGoogle Scholar |
Mitchell AD, Scholz AM, Conway JM (1998b) Body composition analysis of small pigs by dual-energy X-ray absorptiometry. Journal of Animal Science 76, 2392–2398.
| Body composition analysis of small pigs by dual-energy X-ray absorptiometry.Crossref | GoogleScholarGoogle Scholar |
Mitchell A, Rosebrough R, Taicher G, Kovner I (2011) In vivo measurement of body composition of chickens using quantitative magnetic resonance 1. Poultry Science 90, 1712–1719.
| In vivo measurement of body composition of chickens using quantitative magnetic resonance 1.Crossref | GoogleScholarGoogle Scholar |
Pietrobelli A, Formica C, Wang Z, Heymsfield SB (1996) Dual-energy X-ray absorptiometry body composition model: review of physical concepts. American Journal of Physiology. Endocrinology and Metabolism 271, E941–E951.
| Dual-energy X-ray absorptiometry body composition model: review of physical concepts.Crossref | GoogleScholarGoogle Scholar |
Pietrobelli A, Wang Z, Formica C, Heymsfield SB (1998) Dual-energy X-ray absorptiometry: fat estimation errors due to variation in soft tissue hydration. American Journal of Physiology. Endocrinology and Metabolism 274, E808–E816.
| Dual-energy X-ray absorptiometry: fat estimation errors due to variation in soft tissue hydration.Crossref | GoogleScholarGoogle Scholar |
Rostagno HS, Albino LFT, Donzele JL, Gomes PC, Oliveira RF, Lopes DC, Ferreira AS, Barreto SLT, Euclides RF (2011) ‘Tabelas Brasileiras para aves e suínos: composição de alimentos e exigências nutricionais.’ (UFV, DZO: Viçosa, MG, Brazil)
Salas C, Ekmay R, England J, Cerrate S, Coon C (2012) Determination of chicken body composition measured by dual energy X-ray absorptiometry. International Journal of Poultry Science 11, 462–468.
| Determination of chicken body composition measured by dual energy X-ray absorptiometry.Crossref | GoogleScholarGoogle Scholar |
Scholz AM, Mitchell AD, Förster M, Pursel VG (2007) Two-site evaluation of the relationship between in vivo and carcass dual energy X-ray absorptiometry (DXA) in pigs. Livestock Science 110, 1–11.
| Two-site evaluation of the relationship between in vivo and carcass dual energy X-ray absorptiometry (DXA) in pigs.Crossref | GoogleScholarGoogle Scholar |
Schreiweis M, Orban J, Ledur M, Moody D, Hester P (2005) Validation of dual-energy X-ray absorptiometry in live White Leghorns. Poultry Science 84, 91–99.
| Validation of dual-energy X-ray absorptiometry in live White Leghorns.Crossref | GoogleScholarGoogle Scholar |
Speakman JR, Booles D, Butterwick R (2001) Validation of dual energy X-ray absorptiometry (DXA) by comparison with chemical analysis of dogs and cats. International Journal of Obesity 25, 439–447.
| Validation of dual energy X-ray absorptiometry (DXA) by comparison with chemical analysis of dogs and cats.Crossref | GoogleScholarGoogle Scholar |
Suster D, Leury B, Ostrowska E, Butler K, Kerton D, Wark J, Dunshea F (2003) Accuracy of dual energy X-ray absorptiometry (DXA), weight and P2 back fat to predict whole body and carcass composition in pigs within and across experiments. Livestock Production Science 84, 231–242.
| Accuracy of dual energy X-ray absorptiometry (DXA), weight and P2 back fat to predict whole body and carcass composition in pigs within and across experiments.Crossref | GoogleScholarGoogle Scholar |
Suster D, Leury B, Hofmeyr C, D’souza D, Dunshea F (2004) The accuracy of dual energy X-ray absorptiometry (DXA), weight, and P2 back fat to predict half-carcass and primal-cut composition in pigs within and across research experiments. Australian Journal of Agricultural Research 55, 973–982.
| The accuracy of dual energy X-ray absorptiometry (DXA), weight, and P2 back fat to predict half-carcass and primal-cut composition in pigs within and across research experiments.Crossref | GoogleScholarGoogle Scholar |
Swennen Q, Janssens G, Geers R, Decuypere E, Buyse J (2004) Validation of dual-energy x-ray absorptiometry for determining in vivo body composition of chickens. Poultry Science 83, 1348–1357.
| Validation of dual-energy x-ray absorptiometry for determining in vivo body composition of chickens.Crossref | GoogleScholarGoogle Scholar |
Williams JE, Wells JC, Wilson CM, Haroun D, Lucas A, Fewtrell MS (2006) Evaluation of Lunar Prodigy dual-energy X-ray absorptiometry for assessing body composition in healthy persons and patients by comparison with the criterion 4-component model. The American Journal of Clinical Nutrition 83, 1047–1054.
| Evaluation of Lunar Prodigy dual-energy X-ray absorptiometry for assessing body composition in healthy persons and patients by comparison with the criterion 4-component model.Crossref | GoogleScholarGoogle Scholar |