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The ontogenetic allometry of body morphology and chemical composition in dairy goat wethers

Published online by Cambridge University Press:  03 August 2017

R. A. M. Vieira ,
N. M. Rohem Júnior ,
R. S. Gomes ,
T. S. Oliveira ,
L. C. R. Bendia ,
F. H. V. Azevedo ,
D. L. Barbosa ,
L. S. Glória  and
M. T. Rodrigues
R. A. M. Vieira*
Affiliation:
Laboratório de Zootecnia, Centro de Ciências e Tecnologias Agropecuárias (CCTA), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF), Av. Alberto Lamego 2000, Campos dos Goytacazes, RJ, CEP 28013-602, Brazil
N. M. Rohem Júnior
Affiliation:
Animal Science Graduate Program, CCTA/UENF, Campos dos Goytacazes, RJ, CEP 28013-602, Brazil
R. S. Gomes
Affiliation:
Animal Science Graduate Program, CCTA/UENF, Campos dos Goytacazes, RJ, CEP 28013-602, Brazil
T. S. Oliveira
Affiliation:
Animal Science Graduate Program, CCTA/UENF, Campos dos Goytacazes, RJ, CEP 28013-602, Brazil
L. C. R. Bendia
Affiliation:
Animal Science Graduate Program, CCTA/UENF, Campos dos Goytacazes, RJ, CEP 28013-602, Brazil
F. H. V. Azevedo
Affiliation:
Animal Science Graduate Program, CCTA/UENF, Campos dos Goytacazes, RJ, CEP 28013-602, Brazil
D. L. Barbosa
Affiliation:
Animal Science Graduate Program, CCTA/UENF, Campos dos Goytacazes, RJ, CEP 28013-602, Brazil
L. S. Glória
Affiliation:
Laboratório de Zootecnia, Centro de Ciências e Tecnologias Agropecuárias (CCTA), Universidade Estadual do Norte Fluminense Darcy Ribeiro (UENF), Av. Alberto Lamego 2000, Campos dos Goytacazes, RJ, CEP 28013-602, Brazil
M. T. Rodrigues
Affiliation:
Departamento de Zootecnia, Centro de Ciências Agrárias, Universidade Federal de Viçosa, Viçosa, MG, CEP 36570-000, Brazil
*
†E-mail: [email protected]
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Abstract

We studied the ontogenetic growth of goat wethers (castrated male goats) of the Saanen and Swiss Alpine breeds based on a large range of intraspecific body mass (BM). The body parts and the chemical constituents of the empty body were described by the allometric function by using BM and the empty body mass (EBM) as the predictors for morphological traits and chemical composition, respectively. We fitted the allometric scaling function by applying the SAS NLMIXED procedure, but to evaluate assumptions regarding variances in morphological and compositional traits, we combined the scaling function with homoscedastic (MOD1), and the heteroscedastic exponential (MOD2) and power-of-the-mean (MOD3) variance functions. We also predicted the ontogenetic growth by using the traditional log-log transformation and back-transformed results into the arithmetic scale (MOD4). We obtained predictions from MOD4 in the arithmetic scale by a two-step process, and evaluated MOD1, MOD2 and MOD3 by a model selection framework, and compared MOD4 with MOD1, MOD2 and MOD3 based on goodness-of-fit measures. Based on information criteria for model selection, heterogeneous variance functions were more likely to describe 10 over 36 traits with a low level of model selection uncertainty. One trait was predicted by averaging the MOD1 and MOD2 variance functions; and nine traits were better described by averaging the MOD2 and MOD3 variance functions. The predictions for other 16 traits were averaged from MOD1, MOD2 and MOD3. However, MOD4 better described 11 traits according to the goodness-of-fit measures. Depending on the variable being analyzed, the body parts and the chemical amounts exhibited the three types of allometric behavior with respect to BM and EBM, that is, positive, negative and isometric ontogenetic growth. Reference BMs, that is, 20, 27, 35 and 45 kg, were used to compute the net protein and energy requirements based on the first derivative of the scaling function, and the results were presented in reference to the EBM and EBM0.75. Both the net protein and energy requirements scaled to EBM0.75 increased from 20 to 45 kg of BM.

Keywords

bivariate allometrymodel averagingheteroscedasticitySaanenSwiss Alpine
Type
Research Article
Information
animal , Volume 12 , Issue 3 , March 2018 , pp. 538 - 553
Copyright
© The Animal Consortium 2017 

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References

Agricultural and Food Research Council - AFRC 1997. The nutrition of goats. Nutrition Abstracts and Reviews (Series B) 67, 765–830.Google Scholar
Al-Owaimer, A, Suliman, G, El-Waziry, A, Metwally, H and Abouheif, M 2013. Allometric growth patterns of body and carcass components in Ardhi goat. International Journal of Animal and Veterinary Advances 5, 183–189.Google Scholar
Almeida, AK, Resende, KT, Silva, SP, Soares, DC, Fernandes, MHMR and Teixeira, IAMA 2015. Protein requirements for growth in male and female Saanen goats. Revista Brasileira de Zootecnia 44, 397–404.CrossRefGoogle Scholar
Araujo, RP, Vieira, RAM, Rocha, NS, Abreu, MLC, Glória, LS, Rohem Júnior, NM and Fernandes, AM 2015. Long-term growth of body, body parts and composition of gain of dairy goat wethers. The Journal of Agricultural Science 153, 1321–1340.CrossRefGoogle Scholar
Bard, Y 1974. Nonlinear parameter estimation. Academic Press, Inc., New York, NY, USA.Google Scholar
Bonvillani, A, Peña, F, Gea, G, Gómez, G, Petryna, A and Perea, J 2010. Carcass characteristics of Criollo Cordobés kid goats under an extensive management system: effects of gender and liveweight at slaughter. Meat Science 86, 651–659.Google Scholar
Brody, S 1945. Bioenergetics and growth. With special reference to the efficiency complex in domestic animals. Reinhold Publishing Co., New York, NY, USA.Google Scholar
Burnham, KP and Anderson, DR 2004. Multimodel inference: understanding AIC and BIC in model selection. Sociological Methods & Research 33, 261–304.Google Scholar
Carmichael, AK, Kouakou, B, Gelaye, S, Kannan, G, Lee, JH and Terrill, TH 2012. Organ mass and composition in growing dairy goat wethers fed different levels of poultry fat and protein. Small Ruminant Research 104, 104–113.Google Scholar
Clauss, M, Schwarm, A, Ortmann, S, Streich, WJ and Hummel, J 2007. A case of non-scaling in mammalian physiology? Body size, digestive capacity, food intake, and ingesta passage in mammalian herbivores. Comparative Biochemistry and Physiology, Part A 148, 249–265.CrossRefGoogle ScholarPubMed
Colomer-Rocher, F, Kirton, AH, Mercer, GJK and Duganzich, DM 1992. Carcass composition of New Zealand Saanen goats slaughtered at different weights. Small Ruminant Research 7, 161–173.Google Scholar
Demment, MW and Van Soest, PJ 1985. A nutritional explanation for body-size patterns of ruminant and nonruminant herbivores. The American Naturalist 125, 641–672.Google Scholar
Ferreira, ACD, Yáñez, EA, Medeiros, AN, Resende, KT, Pereira Filho, JM, Fernandes, MHMR, Almeida, AK and Teixeira, IAMA 2015. Protein and energy requirements of castrated male Saanen goats. Small Ruminant Research 123, 88–94.CrossRefGoogle Scholar
Gill, JL 1981. Evolution of statistical design and analysis of experiments. Journal of Dairy Science 64, 1494–1519.CrossRefGoogle Scholar
Glazier, DS 2013. Log-transformation is useful for examining proportional relationships in allometric scaling. Journal of Theoretical Biology 334, 200–203.Google Scholar
Gokdal, O 2013. Growth, slaughter and carcass characteristics of Alpine x Hair goat, Saanen x Hair goat and Hair goat male kids fed with concentrate in addition to grazing on rangeland. Small Ruminant Research 109, 69–75.Google Scholar
Gould, SJ 1966. Allometry and size in ontogeny and phylogeny. Biological Reviews 41, 587–640.Google Scholar
Hooper, AP and Welch, JG 1983. Chewing efficiency and body size of kid goats. Journal of Dairy Science 66, 2551–2556.Google Scholar
Hui, D and Jackson, RB 2007. Uncertainty in allometric exponent estimation: a case study in scaling metabolic rate with body mass. Journal of Theoretical Biology 249, 168–177.CrossRefGoogle ScholarPubMed
Huxley, JS and Teissier, G 1936. Terminology of relative growth. Nature 137, 780–781.Google Scholar
Kleiber, M 1975. The fire of life. An introduction to animal energetics. Robert E. Krieger Publishing Co., Inc., New York, NY, USA.Google Scholar
Lawrence, TLJ and Fowler, VR 2002. Growth of farm animals. CABI, Wallingford, UK.Google Scholar
Lin, LI-K 1989. A concordance correlation coefficient to evaluate reproducibility. Biometrics 45, 255–268.Google Scholar
Luo, J, Goetsch, AL, Nsahlai, IV, Johnson, ZB, Sahlu, T, Moore, JE, Ferrell, CL, Galyean, ML and Owens, FN 2004. Maintenance energy requirements of goats: predictions based on observations of heat and recovered energy. Small Ruminant Research 53, 221–230.Google Scholar
Mahgoub, O, Kadim, IT, Al-Saqry, NM and Al-Busaidi, RM 2004. Effects of body weight and sex on carcass tissue distribution in goats. Meat Science 67, 577–585.Google Scholar
Mascaro, J, Litton, CM, Hughes, RF, Uowolo, A and Schnitzer, SA 2014. Is logarithmic transformation necessary in allometry? Ten, one-hundred, one-thousand-times yes. Biological Journal of the Linnean Society 111, 230–233.Google Scholar
Morand-Fehr, P 1981. Growth. In Goat production (ed. C Gall), pp. 253–283. Academic Press Inc, London, UK.Google Scholar
Owens, FN, Dubeski, P and Hanson, CF 1993. Factors that alter the growth and development of ruminants. Journal of Animal Science 71, 3138–3150.Google Scholar
Packard, GC 2013. Is logarithmic transformation necessary in allometry? Biological Journal of the Linnean Society 109, 476–486.Google Scholar
Packard, GC, Birchard, GF and Boardman, TJ 2011. Fitting statistical models in bivariate allometry. Biological Reviews 86, 549–563.Google Scholar
Sahlu, T, Goetsch, AL, Luo, J, Nsahlai, IV, Moore, JE, Galyean, ML, Owens, FN, Ferrell, CL and Johnson, ZB 2004. Nutrient requirements of goats: developed equations, other considerations and future research to improve them. Small Ruminant Research 53, 191–219.Google Scholar
Spiess, A-N and Neumeyer, N 2010. R2 as an inadequate measure for nonlinear models in pharmacological and biochemical research: a Monte Carlo approach. BMC Pharmacology 10, 1–11.Google Scholar
Underwood, EJ and Suttle, NF 1999. The mineral nutrition of livestock. CABI, Wallingford, UK.Google Scholar
von Bertalanffy, L 1957. Quantitative laws in metabolism and growth. The Quarterly Review of Biology 32, 217–231.Google Scholar
Vonesh, EF 2012. Generalized linear and nonlinear models for correlated data: theory and applications using SAS® . SAS Institute Inc, Cary, NC, USA.Google Scholar
Yáñez, EA, Resende, KT, Ferreira, ACD, Pereira Filho, JM, Medeiros, AN and Teixeira, IAMA 2009. Relative development of tissues, commercial meat cuts and live weight components in Saanen goats. Revista Brasileira de Zootecnia 38, 366–373.Google Scholar