Environmental variation and breed sensitivity for growth rate and backfat depth in pigs
L. Li A B and S. Hermesch AA Animal Genetics and Breeding Unit (a joint venture of NSW Department of Primary Industries and the University of New England), University of New England, Armidale, NSW 2351, Australia.
B Corresponding author. Email: lli4@une.edu.au
Animal Production Science 56(1) 61-69 https://doi.org/10.1071/AN14066
Submitted: 3 February 2014 Accepted: 29 September 2014 Published: 15 January 2015
Abstract
This study investigated the magnitude of environmental variation and compared the environmental sensitivity of Large White, Landrace and Duroc pigs based on reaction norms analyses for lifetime average daily gain (ADG) and backfat depth (BF). Data comprised 265 165 records collected between 2000 and 2010 on pigs from nine herds in Australia. Four environmental descriptors [the phenotypic mean and three least-squares means of contemporary groups (CG) of linear mixed models fitting fixed effects only or fitting sire or animal as additional random effects] were compared in order to quantify the environmental variation based on herd-by-birth month (HBM) and herd-by-birth week (HBW) CG for ADG and BF. Similar levels of variation were found for environmental descriptors based on HBM or HBW CG definitions for both traits but the accuracy of estimates for environmental descriptors was higher for HBM than HBW. The standard deviations of environmental descriptors were 31 (35) g/day for ADG and 1.0 (1.1) mm for BF based on the animal model fitting HBM (HBW), which are similar to the genetic standard deviations usually observed for these traits. Most of this variation in environmental conditions was also observed within years and within herds. Landrace had the highest ADG and Large White had the lowest BF across the environmental range. Significant breed-by-environment interaction was found for ADG but not for BF. Duroc was least sensitive and Large White was most sensitive indicating that the leaner breed was less able to perform consistently across the observed range of environmental conditions in this study.
Additional keywords: average daily gain, genotype–environment interactions, linear regression, reaction norms.
References
Bergsma R, Hermesch S (2012) Exploring breeding opportunities for reduced thermal sensitivity of feed intake in the lactating sow. Journal of Animal Science 90, 85–98.| Exploring breeding opportunities for reduced thermal sensitivity of feed intake in the lactating sow.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XnvFOjtQ%3D%3D&md5=6806e0c1bd8835984a5876be6f3a60f0CAS | 21788430PubMed |
Bradshaw AD (1965) Evolutionary significance of phenotypic plasticity in plants. Advances in Genetics 13, 115–155.
| Evolutionary significance of phenotypic plasticity in plants.Crossref | GoogleScholarGoogle Scholar |
Bryant JR, Lopez-Villalobos N, Pryce JE, Holmes CW, Johnson DL, Garrick DJ (2007) Environmental sensitivity in New Zealand dairy cattle. Journal of Dairy Science 90, 1538–1547.
| Environmental sensitivity in New Zealand dairy cattle.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXitlWmsr0%3D&md5=889588126222f12115720b5c6744da92CAS | 17297127PubMed |
Calus MPL, Bijma P, Veerkamp RF (2004) Effects of data structure on the estimation of covariance functions to describe genotype by environment interactions in a reaction. Genetics, Selection, Evolution. 36, 489–507.
| Effects of data structure on the estimation of covariance functions to describe genotype by environment interactions in a reaction.Crossref | GoogleScholarGoogle Scholar |
Fikse WF, Rekaya R, Weigel KA (2003) Genotype x environment interaction for milk production in Guernsey cattle. Journal of Dairy Science 86, 1821–1827.
| Genotype x environment interaction for milk production in Guernsey cattle.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXjslGisbw%3D&md5=7900f282ffd96b355b5c0369705dc597CAS | 12778593PubMed |
Gilmour AR, Gogel B, Cullis B, Thompson R, Butler D (2009) ‘ASReml user guide release 3.0.’ (VSN International Ltd: Hemel Hempstead, UK)
Haskell MJ, Brotherstone S, Lawrence AB, White IMS (2007) Characterization of the dairy farm environment in great Britain and the effect of the farm environment on cow life span. Journal of Dairy Science 90, 5316–5323.
| Characterization of the dairy farm environment in great Britain and the effect of the farm environment on cow life span.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD2sXht1Kru7rI&md5=ff7d608624a0ffa74cf614173337cbfcCAS | 17954772PubMed |
Hermesch S, Huisman AE, Luxford BG, Graser HU (2006) Analysis of genotype by feeding level interaction in pigs applying reaction norm models. In ‘Proceedings of the 8th world congress on genetics applied to livestock production. Belo Horizonte, Minas Gerais, Brazil, 13–18 August, 2006’. Communication no. 06–03. (Instituto Prociência: Brazil)
Huquet B, Leclerc H, Ducrocq V (2012) Characterization of French dairy farm environments from herd-test-day profiles. Journal of Dairy Science 95, 4085–4098.
| Characterization of French dairy farm environments from herd-test-day profiles.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC38XoslGqsr4%3D&md5=607a2cbf8414526c465773796706fcc3CAS | 22720965PubMed |
Hyun Y, Ellis M, Riskowski G, Johnson R (1998) Growth performance of pigs subjected to multiple concurrent environmental stressors. Journal of Animal Science 76, 721–727.
Jones RM, Crump RE, Hermesch S (2011) Group characteristics influence growth rate and backfat of commercially raised grower pigs. Animal Production Science 51, 191–197.
| Group characteristics influence growth rate and backfat of commercially raised grower pigs.Crossref | GoogleScholarGoogle Scholar |
Knap PW, Su G (2008) Genotype by environment interaction for litter size in pigs as quantified by reaction norms analysis. Animal 2, 1742–1747.
| Genotype by environment interaction for litter size in pigs as quantified by reaction norms analysis.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC38vptFemsQ%3D%3D&md5=aac506a8edba6b4060ed36508d983fffCAS | 22444079PubMed |
Kolmodin R, Strandberg E, Madsen P, Jensen J, Jorjani H (2002) Genotype by environment interaction in Nordic dairy cattle studied using reaction norms. Acta Agriculturae Scandinavica, Section A – Animal Science 52, 11–24.
Lewis CRG, Bunter KL (2011) Effects of seasonality and ambient temperature on genetic parameters for production and reproductive traits in pigs. Animal Production Science 51, 615–626.
| Effects of seasonality and ambient temperature on genetic parameters for production and reproductive traits in pigs.Crossref | GoogleScholarGoogle Scholar |
Li L, Hermesch S (2013) Genotype by environment interactions for average daily gain using multiple-trait analyses in Australian pigs. In ‘The 20th conference of the Association for the Advancement of Animal Breeding and Genetics. Napier, New Zealand. Volume 20’. (Ed. NL Villalobos) pp. 323–326. (Association for the Advancement of Animal Breeding and Genetics: Available at http://www.aaabg.org/aaabghome/AAABG20papers/li20323.pdf [Verified 2 December 2014]
Mattar M, Silva LOC, Alencar MM, Cardoso FF (2011) Genotype x environment interaction for long-yearling weight in Canchim cattle quantified by reaction norm analysis. Journal of Animal Science 89, 2349–2355.
| Genotype x environment interaction for long-yearling weight in Canchim cattle quantified by reaction norm analysis.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BC3MXps1yqu74%3D&md5=dbda7d8f63af43f6094ffca55f36521cCAS | 21421832PubMed |
Pollott GE, Greeff JC (2004) Genotype x environment interactions and genetic parameters for fecal egg count and production traits of Merino sheep. Journal of Animal Science 82, 2840–2851.
Potter ML, Tokach LM, Dritz SS, Henry SC, DeRouchey JM, Tokach MD, Goodband RD, Nelssen JL, Rowland RRR, Hesse RA, Oberst R, Anderson J, Hays M (2012) Genetic line influences pig growth rate responses to vaccination for porcine circovirus type 2. Journal of Swine Health and Production 20, 34–43.
Schinckel AP, Richert BT, Frank JW, Kendall DC (1999) Genetic by environmental interactions for pig growth. Purdue University 1999 Swine Day Report. Available at http://www.ansc.purdue.edu/swine/swineday/sday99/13.pdf [Verified 3 November 2014]
Strandberg E (2006) Analysis of genotype by environment interaction using random regression models. In ‘Proceedings of the 8th world congress on genetics applied to livestock production. Belo Horizonte, Minas Gerais, Brazil’. 13–18 August 2006. Communication no. 25–05. (Instituto Prociência: Brazil)
Strandberg E, Brotherstone S, Wall E, Coffey MP (2009) Genotype by environment interaction for first-lactation female fertility traits in UK dairy cattle. Journal of Dairy Science 92, 3437–3446.
| Genotype by environment interaction for first-lactation female fertility traits in UK dairy cattle.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD1MXnslGjurg%3D&md5=7b027a4296576db511c12793ac21222dCAS | 19528622PubMed |
Zwald NR, Weigel KA, Fikse WF, Rekaya R (2003) Identification of factors that cause genotype by environment interaction between herds of Holstein cattle in seventeen countries. Journal of Dairy Science 86, 1009–1018.
| Identification of factors that cause genotype by environment interaction between herds of Holstein cattle in seventeen countries.Crossref | GoogleScholarGoogle Scholar | 1:CAS:528:DC%2BD3sXitFyqur8%3D&md5=253dc91f60c3bf05a61988bf9f0cbefaCAS | 12703638PubMed |
