Skip to main content Accessibility help
×
Home

Genetic parameters of sow feed efficiency during lactation and its underlying traits in a Duroc population

  • M. Piles (a1), J. Martí (a1), J. Reixach (a2) and J. P. Sánchez (a1)

Abstract

As a result of the genetic selection for prolificacy and the improvements in the environment and farms management, litter size has increased in the last few years so that energy requirements of the lactating sow are greater. In addition, selection for feed efficiency of growing pigs is also conducted in maternal lines, and this has led to a decrease in appetite and feed intake that is extended to the lactation period, so the females are not able to obtain the necessary energy and nutrients for milk production and they mobilize their energetic reserves. When this mobilization is excessive, reproductive and health problems occur which ends up in an early sow culling. In this context, it has been suggested to improve feed efficiency at lactation through genetic selection. The aim of this study is to know, in a Duroc population, the genetic determinism of sow feed efficiency during lactation and traits involved in its definition, as well as genetic and environmental associations between them. The studied traits are daily lactation feed intake (dLFI), daily sow weight balance (dSWB), backfat thickness balance (BFTB), daily litter weight gain (dLWG), sow residual feed intake (RFI) and sow restricted residual feed intake (RRFI) during lactation. Data corresponded to 851 parities from 581 Duroc sows. A Bayesian analysis was performed using Gibbs sampling. A four-trait repeatability animal model was implemented including the systematic factors of batch and parity order, the standardized covariates of sow weight (SWf) and litter weight (LWs) at farrowing for all traits and lactation length for BFTB. The posterior mean (posterior SD) of heritabilities were: 0.09 (0.03) for dLFI, 0.37 (0.07) for dSWB, 0.09 (0.03) for BFTB, 0.22 (0.05) for dLWG, 0.04 (0.02) for RFI and null for RRFI. The genetic correlation between dLFI and dSWB was high and positive (0.74 (0.11)) and null between dLFI and BFTB. Genetic correlation was favourable between RFI and dLFI and BFTB (0.71 (0.16) and −0.69 (0.18)), respectively. The other genetic correlations were not statistically different from zero. The phenotypic correlations were low and positive between dLFI and dSWB (0.27 (0.03), dSWB and BFTB (0.25 (0.04)), and between dLFI and dLWG (0.16 (0.03)). Therefore, in the population under study, the improvement of the lactation feed efficiency would be possible either using RFI, which would not have unfavourable correlated effects, or through an index including its component traits.

Copyright

Corresponding author

References

Hide All
Bergsma, R, Kanis, E, Verstegen, MWA and Knol, EF 2008. Genetic parameters and predicted selection results for maternal traits related to lactation efficiency in sows. Journal of Animal Science 86, 10671080.
Bergsma, R, Kanis, E, Verstegen, MWA, van der Peet-Schwering, CMC and Knol, EF 2009. Lactation efficiency as a result of body composition dynamics and feed intake in sows. Livestock Science 125, 208222.
Cai, W, Casey, DS and Dekkers, JC 2008. Selection response and genetic parameters for residual feed intake in Yorkshire swine. Journal of Animal Science 86, 287298. doi: 10.2527/jas.2007-0396
Clowes, EJ, Aherne, FX, Foxcroft, GR and Baracos, VE 2003. Selective protein loss in lactating sows is associated with reduced litter growth and ovarian function. Journal of Animal Science 81, 753764.
Dourmad, JY 1991. Effect of feeding level in the gilt during pregnancy on voluntary feed intake during lactation and changes in body composition during gestation and lactation. Livestock Production Science 27, 309319.
Drouilhet, L, Achard, CS, Zemb, O, Molette, C, Gidenne, T, Larzul, C, Ruesche, J, Tircazes, A, Segura, M, Bouchez, T, Theau-Clement, M, Joly, T, Balmisse, E, Garreau, H and Gilbert, H 2016. Direct and correlated responses to selection in two lines of rabbits selected for feed efficiency under ad libitum and restricted feeding: I. Production traits and gut microbiota characteristics. Journal of Animal Science 94, 3848. doi: 10.2527/jas.2015-9402
Eissen, JJ, Kanis, E and Kemp, B 2000. Sow factors affecting voluntary feed intake during lactation. Livestock Production Science 64, 147165.
Gilbert, H, Bidanel, JP, Billon, Y, Lagant, H, Guillouet, P, Sellier, P, Noblet, J and Hermesch, S 2012. Correlated responses in sow appetite, residual feed intake, body composition, and reproduction after divergent selection for residual feed intake in the growing pig. Journal of Animal Science 90, 10971108.
Gilbert, H, Bidanel, JP, Gruand, J, Caritez, JC, Billon, Y, Guillouet, P, Lagant, H, Noblet, J and Sellier, P 2007. Genetic parameters for residual feed intake in growing pigs, with emphasis on genetic relationships with carcass and meat quality traits. Journal of Animal Science 85, 31823188. doi: 10.2527/jas.2006-590
Grandinson, K, Rydhmer, L, Strandberg, E and Solanes, FX 2005. Genetic analysis of body condition in the sow during lactation, and its relation to piglet survival and growth. Animal Science 80, 3340.
Kennedy, BW, Vanderwerf, JHJ and Meuwissen, THE 1993. Genetic and statistical properties of residual feed-intake. Journal of Animal Science 71, 32393250.
Kim, SW, Hurley, WL, Kan, IK and Easter, RA 2000. Growth of nursing pigs related to the characteristics of nursed mammary glands. Journal of Animal Science 78, 13131318.
Kim, SW, Osaka, I, Hurley, WL and Easter, RA 1999. Mammary gland growth as influenced by litter size in lactating sows: impact on lysine requirement1. Journal of Animal Science 77, 33163321.
Lundgren, H, Fikse, WF, Grandinson, K, Lundeheim, N, Canario, L, Vangen, O, Olsen, D and Rydhmer, L 2014. Genetic parameters for feed intake, litter weight, body condition and rebreeding success in primiparous Norwegian Landrace sows. Animal 8, 175183.
Misztal, I, Tsuruta, S, Strabel, T, Auvray, B, Druet, T and Lee, DH 2002. BLUPF90 and related programs (BGF90). In Proceedings of the 7th World Congress on Genetics Applied to Livestock Production, 19–23 August 2002, Montpellier, France, pp. 12.
Noblet, J, Close, WH, Heavens, RP and Brown, D 1985. Studies on the energy metabolism of the pregnant sow. 1. Uterus and mammary tissue development. British Journal of Nutrition 53, 251265.
Noblet, J, Dourmad, JY and Etienne, M 1990. Energy utilization in pregnant and lactating sows: modeling of energy requirements. Journal of Animal Science 68, 562572.
Noguera, JL, Varona, L, Babot, D and Estany, J 2002. Multivariate analysis of litter size for multiple parities with production traits in pigs: I. Bayesian variance component estimation. Journal of Animal Science 80, 25402547. doi: 10.1093/ansci/80.10.2540
Piles, M, Garcia, M, Rafel, O, Ramon, J and Baselga, M 2006. Genetics of litter size in three maternal lines of rabbits: repeatability versus multiple-trait models. Journal of Animal Science 84, 23092315.
Piles, M and Sánchez, JP 2019. Use of group records of feed intake to select for feed efficiency in rabbit. Journal of Animal Breeding and Genetics, 00, 110. 10.1111/jbg.12395
Sánchez, JP, Ragab, M, Quintanilla, R, Rothschild, MF and Piles, M 2017. Genetic parameters and expected responses to selection for components of feed efficiency in a Duroc pig line. Genetics Selection Evolution 49, 86.
Schinckel, AP, Schwab, CR, Duttlinger, VM and Einstein, ME 2010. Analyses of feed and energy intakes during lactation for three breeds of sows. The Professional Animal Scientist 26, 3550.
Shirali, M, Varley, PF and Jensen, J 2018. Bayesian estimation of direct and correlated responses to selection on linear or ratio expressions of feed efficiency in pigs. Genetics Selection Evolution 50, 33.
Silalahi, P, Tribout, T, Prunier, A, Billon, Y, Gogue, J and Bidanel, JP 2016. Estimation of the effects of selection on French Large White reproductive performance using frozen semen. Journal of Animal Science 94, 36553662.
Smith, BJ 2007. boa: An R package for MCMC output convergence assessment and posterior inference. Journal of Statistical Software 21, 137.
Strathe, AB, Mark, T, Nielsen, B, Do, ND, Kadarmideen, HN, Jensen, J 2014. Deriving genomic breeding values for residual feed intake from covariance functions pf random regression models. In Proceedings of the 10th World Congress of Genetics Applied to Livestock Production, 17–22 August 2014, Vancouver, BC, Canada.
Thekkoot, DM, Kemp, RA, Rothschild, MF, Plastow, GS and Dekkers, JC 2016. Estimation of genetic parameters for traits associated with reproduction, lactation, and efficiency in sows. Journal of Animal Science 94, 45164529.
Wetten, M, Ødegård, J, Vangen, O and Meuwissen, THE 2012. Simultaneous estimation of daily weight and feed intake curves for growing pigs by random regression. Animal 6, 433439.
Whittemore, CT and Morgan, CA 1990. Model components for the determination of energy and protein requirements for breeding sows: a review. Livestock Production Science 26, 137.
Young, JM, Bergsma, R, Knol, EF, Patience, JF and Dekkers, JC 2016. Effect of selection for residual feed intake during the grow/finish phase of production on sow reproductive performance and lactation efficiency. Journal of Animal Science 94, 41204132.

Keywords

Type Description Title
WORD
Supplementary materials

Piles et al. supplementary material
Piles et al. supplementary material

 Word (18 KB)
18 KB

Genetic parameters of sow feed efficiency during lactation and its underlying traits in a Duroc population

  • M. Piles (a1), J. Martí (a1), J. Reixach (a2) and J. P. Sánchez (a1)

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed