Hostname: page-component-586b7cd67f-2plfb Total loading time: 0 Render date: 2024-11-30T16:01:24.248Z Has data issue: false hasContentIssue false

Economic weights of maternal and direct traits of pigs calculated by applying gene flow methods

Published online by Cambridge University Press:  23 October 2018

M. Wolfová
Affiliation:
Institute of Animal Science, Přátelství 815, 10400 Prague Uhříněves, Czech Republic
E. Krupa*
Affiliation:
Institute of Animal Science, Přátelství 815, 10400 Prague Uhříněves, Czech Republic
Z. Krupová
Affiliation:
Institute of Animal Science, Přátelství 815, 10400 Prague Uhříněves, Czech Republic
E. Žáková
Affiliation:
Institute of Animal Science, Přátelství 815, 10400 Prague Uhříněves, Czech Republic
*
Get access

Abstract

Multiple trait selection indexes in pig breeding programmes should take into account the population structure and time delay between parent selection and expressions of traits in all production levels next to the trait impacts on economic efficiency of production systems. Gene flow procedures could be used for the correct evaluation of maternal and direct traits of pig breeds involved in breeding or crossbreeding systems. Therefore, the aim of this study was to expand a previously developed bioeconomic model and computer program to calculate the marginal economic values by including a gene flow procedure to calculate the economic weights for maternal and direct traits in pig breeds. The new program was then applied to the three-way crossbreeding system of the Czech National Programme for Pig Breeding. Using this program, the marginal economic values of traits for dam breeds Czech Large White in the dam position and Czech Landrace in the sire position, and for the sire breed Pietrain were weighted by the number of discounted gene expressions of selected parents of each breed summarised within all links of the crossbreeding system during the 8-year investment period. Economic weights calculated in this way were compared with the approximate economic weights calculated previously without a gene flow procedure. Taking into account the time delay between parent selection and trait expression (using discounting with half-year discount rates of 2% or 5%) and including more than one generation of parent progeny had little impact on the relative economic importance of maternal and direct traits of breeds involved in the evaluated three-way crossbreeding system. These results indicated that this gene-flow method could be foregone when estimating the relative economic weights of traits in pig crossbreeding systems applying artificial insemination at all production levels.

Type
Research Article
Copyright
© The Animal Consortium 2018 

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

Amer, PR 1999. Economic accounting of numbers of expressions and delays in sheep genetic improvement. New Zealand Journal of Agricultural Research 42, 325336.Google Scholar
Amer, PR, Ludemann, CI and Hermesch, S 2014. Economic weights for maternal traits of sows, including sow longevity. Journal of Animal Science 92, 53455357.10.2527/jas.2014-7943Google Scholar
Berry, DP, Madalena, FE, Cromie, AR and Amer, PR 2006. Cumulative discounted expressions of dairy and beef traits in cattle production systems. Livestock Science 99, 159174.Google Scholar
Bouwman, AC, Bergsma, R, Duijvesteijn, N and Bijma, P 2014. Maternal and social genetic effects on average daily gain of piglets from birth until weaning. Journal of Animal Science 88, 28832892.Google Scholar
Danell, Ö, Rönningen, K, Ström, H, Andersson, K and Sundgren, P-E 1976. An extension of the discounted gene flow method with example in pig breeding. Acta Agriculturae Scandinavica 26, 203210.Google Scholar
Dube, B, Mulugeta, SD and Dzama, K 2013. Integrating economic parameters into genetic selection for Large White pigs. Animal 7, 12311238.10.1017/S1751731113000530Google Scholar
Elsen, JM and Mocquot, JC 1974. Méthode de prevision de l’evolution du niveau génétique d’une population soumise à une operation de selection et dont les generations se chevauchent. INRA Bulletin Technique du Département de Génétique Animale 17, 3054.Google Scholar
Hermesch, S, Ludemann, CI and Amer, PR 2014. Economic weights for performance and survival traits of growing pigs. Journal of Animal Science 92, 53585366.Google Scholar
Houška, L, Wolfová, M and Fiedler, J 2004. Economic weights for production and reproduction traits of pigs in the Czech Republic. Livestock Production Science 85, 12091221.10.1016/S0301-6226(03)00128-3Google Scholar
Kearney, JF, Amer, PR and Villanueva, B 2005. Cumulative discounted expressions of sire genotypes for the complex vertebral malformation and β-casein loci in commercial dairy herds. Journal of Dairy Science 88, 44264433.Google Scholar
Krupa, E, Krupová, Z, Wolfová, M and Žáková, E 2017. Estimation of economic values for traits of pig breeds in different breeding systems: II. Model application to a three-way crossing system. Livestock Science 205, 7078.10.1016/j.livsci.2017.09.018Google Scholar
Lundgren, H, Canario, L, Grandinson, K, Lundeheim, N, Zumbach, B, Vangen, O and Rydhmer, L 2010. Genetic analysis of reproductive performance in Landrace sows and its correlation to piglet growth. Livestock Science 128, 173178.Google Scholar
McClintock, AE and Cunningham, EP 1974. Selection in dual-purpose cattle populations defining the breeding objective. Animal Production 18, 237247.Google Scholar
Roehe, R, Shrestha, NP, Mekkawy, W, Baxter, EM, Knap, PW, Smurthwaite, KM, Jarvis, S, Lawrence, AB and Edwards, SA. 2010. Genetic parameters of piglet survival and birth weight from a two-generation crossbreeding experiment under outdoor conditions designed to disentangle direct and maternal effects. Journal of Animal Science 88, 12761285.Google Scholar
Quinton, VM, Wilton, JW, Robinson, JA and Mathur, PK 2006. Economic weights for sow productivity traits in nucleus pig populations. Livestock Science 99, 6977.Google Scholar
Wierzbicki, H, Peura, J, Filistowicz, A and Przysiecki, P 2007. Economic weights for litter size and fur coat traits of arctic fox in Poland. Journal of Animal and Feed Science 16, 140152.Google Scholar
Wolfová, M and Nitter, G 2004. Relative economic weights of maternal versus direct traits in breeding schemes. Livestock Production Science 88, 117127.Google Scholar
Wolfová, M, Wolf, J, Krupa, E, Krupová, Z and Žáková, E 2016. User’s manual for the program package ECOWEIGHT (C programs for calculating economic weights in livestock), version 8.0.0. Part 5B: Program GFPIG for gene flow in pigs, version 1.0.0. Retrieved on 6 March 2018 from https://www.researchgate.net/publication/323496792.Google Scholar
Wolfová, M, Wolf, J, Krupová, Z, Krupa, E and Žáková, E 2017. Estimation of economic values for traits of pig breeds in different breeding systems: I. Model development. Livestock Science 205, 7987.Google Scholar
Wünsch, U, Nitter, G and Schüller, L 1999. Genetic and economic evaluation of genetic improvement schemes in pigs. I. Methodology with an application to a three-way crossbreeding scheme. Archives of Animal Breeding 42, 571582.10.5194/aab-42-571-1999Google Scholar
Supplementary material: File

Wolfová et al. supplementary material

Wolfová et al. supplementary material 1

Download Wolfová et al. supplementary material(File)
File 34.3 KB