Hostname: page-component-76fb5796d-25wd4 Total loading time: 0 Render date: 2024-04-26T02:24:05.763Z Has data issue: false hasContentIssue false
  • English
  • Français

Growth of total fat and lean and of primal cuts is affected by the sex type

Published online by Cambridge University Press:  10 February 2017

A. Carabús ,
R. D. Sainz ,
J. W. Oltjen ,
M. Gispert  and
M. Font-i-Furnols
A. Carabús
Affiliation:
Department of Product Quality, IRTA, Finca Camps i Armet, 17121 Monells, Catalonia, Spain
R. D. Sainz
Affiliation:
Department of Animal Science, University of California, Davis, CA 95616, USA
J. W. Oltjen
Affiliation:
Department of Animal Science, University of California, Davis, CA 95616, USA
M. Gispert
Affiliation:
Department of Product Quality, IRTA, Finca Camps i Armet, 17121 Monells, Catalonia, Spain
M. Font-i-Furnols*
Affiliation:
Department of Product Quality, IRTA, Finca Camps i Armet, 17121 Monells, Catalonia, Spain
*
†E-mail: maria.font@irta.cat
Get access

Abstract

Knowledge of tissue and cuts growth depending on the sex could be used to improve performance and efficiency. Computed tomography (CT) is a non-invasive technology that enables the study of the body composition of live animals during growth. The aims of the present study were (1) to evaluate variation in the body composition of four sex types (SEX) of pigs (castrated males (CM), immunocastrated males (IM), entire males (EM) and females (FE)) at the live weight of 30, 70, 100 and 120 kg, assessed using CT; (2) to model the growth of the main tissues and cuts; and (3) to predict the mature BW (MBW) of the four SEX and establish the relationships between the growth models and the MBW. There were significant phenotypic differences in the allometric growth of fat and lean among SEX. For the lean tissue, FE and EM showed higher values of the b coefficient than CM and IM (1.07 and 1.07 v. 1.00 and 1.02, respectively) all of them close to unity, indicating a proportional growth rate similar to live weight and that this tissue developed faster in FE and EM than in CM and IM. However, these differences were not related to differences in estimated MBW. There were significant differences in estimated MBW among SEX, being higher in IM and EM than in CM and FE (303 and 247 v. 219 and 216 kg), however, the MBW may have been overestimated, especially for the IM. The poorer accuracy of the MBW estimate for the IM could be due to a maximum live weight of 120 kg in the experiment, or to the fact that this particular SEX presented two clear behaviours, being more similar to EM from birth to the second injection of the vaccine (130 days) and comparable with CM from that point to the final BW.

Keywords

Computed tomographyimmunocastrationmature weightpigs
Type
Research Article
Information
animal , Volume 11 , Issue 8 , August 2017 , pp. 1321 - 1329
Copyright
© The Animal Consortium 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Bardera, A, Martίnez, R, Boada, I, Font-i-Furnols, M and Gispert, M 2012. VisualPork towards the simulation of a virtual butcher. In Proceedings of the First Annual Farm Animal Imaging Conference on Carcass Evaluation, Meat Quality, Software and Traceability, 25–26 September, Dublin, Ireland, 97pp.Google Scholar
Batorek, N, Čandek-Potokar, M, Bonneau, M and Van Milgen, J 2012. Meta-analysis of the effect of immunocastration on production performance, reproductive organs and boar taint compounds in pigs. Animal 6, 1330–1338.CrossRefGoogle ScholarPubMed
Boada, I, Spinola, J, Rodriguez, J, Martínez, R and Font-i-Furnols, M 2009. VisualPork towards the simulation of a Virtual Butcher. In Proceedings of the 2nd Workshop on the Use of Computed Tomography (CT) in Pig Carcass Classification. Other CT applications: Live Animals and Meat Technology, 16–17 April, Monells, Catalunya.Google Scholar
Carabús, A, Gispert, M, Brun, A, Rodríguez, P and Font-i-Furnols, M 2014. In vivo computed tomography evaluation of the composition of the carcass and various cuts of growing pigs of three commercial crossbreeds. Livestock Production Science 170, 191–192.Google Scholar
Carabús, A, Sainz, RD, Oltjen, JW, Gispert, M and Font-i-Furnols, M 2015. Predicting fat, lean and the weight of primal cuts of pigs of different genotypes and sexes using computed tomography. Journal of Animal Science 93, 1–10.CrossRefGoogle ScholarPubMed
D’Souza, DN and Mullan, BP 2002. The effect of genotype, sex, and management strategy on the eating quality of pork. Meat Science 60, 95–101.Google Scholar
Dunshea, FR, Colantoni, C, Howard, K, McCauley, I, Jackson, P, Long, KA, Lopaticki, S, Nugent, EA, Simons, JA, Walker, J and Hennessy, DP 2001. Vaccinations of boars with GnRH vaccine (Improvac) eliminates boar taint and increases growth performance. Journal of Animal Science 79, 2524–2535.CrossRefGoogle ScholarPubMed
Fàbrega, E, Velarde, A, Cros, J, Gispert, M, Suárez, P, Tibau, J and Soler, J 2010. Effect of vaccination against gonadotrophin-releasing hormone, using Improvac®, on growth performance, body composition, behaviour and acute phase proteins. Livestock Science 132, 53–59.CrossRefGoogle Scholar
Ferguson, NS, Gous, RM and Emmans, CG 1994. Preferred components for the construction of a new simulation model of growth, feed intake and nutrient requirements of growing pigs. South African Journal of Animal Science 24, 10–17.Google Scholar
Fisher, AV, Green, DM, Whittemore, CT, Wood, JD and Schofield, CP 2003. Growth of carcass components and its relation with conformation in pigs of three types. Meat Science 65, 639–650.Google Scholar
Font-i-Furnols, M, Carabús, A, Pomar, C and Gispert, M 2014. Estimation of carcass and cuts composition from computed tomography images of growing live pigs of different genotypes. Animal 9, 166–178.Google Scholar
Gispert, M, Oliver, MA, Velarde, A, Suarez, P, Perez, J and Font i Furnols, M 2010. Carcass and meat quality characteristics of immunocastrated male, surgically castrated male, entire male and female pigs. Meat Science 85, 664–670.Google Scholar
Gompertz, B 1825. On the nature of the function expressive of the law of human mortality and on a new method of determining the value of contingencies. Philosophical Transactions of the Royal Society of London 115, 513–585.Google Scholar
Gould, SJ 1971. Geometric similarity in allometric growth: a contribution to the problem of scaling in the evolution of size. The American Naturalist 105, 113–136.CrossRefGoogle Scholar
Huxley, JS 1932. Problems of relative growth. Methuen, Co. Ltd, London, UK.Google Scholar
Huxley, JS 1950. Relative growth and form transformation. Proceedings of the Royal Society of London 137 (B), 465–469.Google ScholarPubMed
Ibáñez-Escriche, N and Blasco, A 2011. Modifying growth curve parameters by multitrait genomic selection. Journal of Animal Science 89, 661–668.Google Scholar
Jaros, P, Burgi, E, Stärk, KDC, Claurs, R, Hennessy, D and Thun, R 2005. Effect of active immunisation against GnRH on androstenone concentration, growth performance and carcass quality in intact male pigs. Livestock Production Science 92, 31–38.CrossRefGoogle Scholar
Knap, PW 2000. Variation in maintenance requirements of growing pigs in relation to body composition. A simulation study. PhD thesis, Wageningen University, The Netherlands.Google Scholar
Kolstad, K 2001. Fat deposition and distribution measured by computer tomography in three genetic groups of pigs. Livestock Production Science 67, 281–292.Google Scholar
Kyriazakis, I and Emmans, GC 1991. Diet selection in pigs: dietary choices made by growing pigs following a period of underfeeding with protein. Animal Production 52, 337–346.Google Scholar
Latorre, MA, Lázaro, R, Gracia, MI, Nieto, M and Mateos, GG 2003. Effect of sex and terminal sire genotype on performance, carcass characteristics, and meat quality of pigs slaughtered at 117 kg body weight. Meat Science 65, 1369–1377.CrossRefGoogle ScholarPubMed
McLaren, DG, McKeith, FM and Novakofski, J 1988. Prediction of carcass characteristics at market weight from serial real-time ultrasound measures of backfat and loin eye area in the growing pigs. Journal of Animal Science 67, 1657–1667.Google Scholar
SAS 2001. Statistical Analysis Software, version 9.3. © SAS Institute Inc., SAS Campus Drive, Cary, North Carolina 27513, USA.Google Scholar
Schinckel, AP, Mahan, DC, Wiseman, TG and Einstein, E 2008. Growth of protein, moisture, lipid, and ash of two genetic lines of barrows and gilts from twenty to one hundred and twenty-five kilograms of body weight. Journal of Animal Science 86, 460–471.Google Scholar
Strathe, AB, Danfer, A and Sorensen, H 2009. A new mathematical model for combining growth and energy intake in animals. The case of the growing pig. Journal of Theoretical Biology 261, 165–175.Google Scholar
Vincek, D, Sabo, K, Kusec, G, Kralik, G, Durkin, I and Scitovski, R 2012. Modeling of pig growth by S-function - least absolute deviation approach for parameter estimation. Archiv fur Tierzucht 55, 364–374.Google Scholar
Wellock, IJ, Emmans, GC and Kyriazakis, I 2004. Describing and predicting potential growth in the pig. Journal of Animal Science 78, 379–388.CrossRefGoogle Scholar
Supplementary material: File

Carabús supplementary material

Tables S1-S2

Download Carabús supplementary material(File)
File 21.7 KB