Genomic breeding schemes with large cow reference populations will give room for more line division within dairy cattle breeding and therefore also for organic breeding lines. The reason is that different economic values between organic and conventional production systems are expected in the future and the existence of genotype by environment interaction will presumably be even more recognized. Therefore, correlations between organic and conventional breeding goals are expected to be significantly lower than one. This in combination with increased future “break even” correlations opens up for specific organic breeding lines

Hjortø, Line

Kargo, Morten

Slagboom, Margot

Thomasen, Jørn Rind

Wallenbeck, Anna

Organic Eprints

Proceedings of the World Congress on Genetics Applied to Livestock Production, 11.536Organic dairy breeding lines? – Possibilities and RequirementsM. Kargo1,2, J. R. Thomasen3, A. Wallenbeck4,,L. Hjortø1& M. Slagboom1,41Aarhus University, Blichers Allé 20, 8830 Tjele, Denmarkmorten.kargo@mbg.au.dk (Corresponding author)2 SEGES Cattle, Agro Food Park 15, 8200 Aarhus N, Denmark3VikingGenetics, Ebeltoftvej 16, 8960 Assentoft, Denmark4 Swedish University of Agricultural Sciences, Ulls väg 26, 756 51 Uppsala, SwedenSummaryGenomic breeding schemes with large cow reference populations will give room for more linedivision within dairy cattle breeding and therefore also for organic breeding lines. The reason isthat different economic values between organic and conventional production systems areexpected in the future and the existence of genotype by environment interaction will presumablybe even more recognized. Therefore, correlations between organic and conventional breedinggoals are expected to be significantly lower than one. This in combination with increased future“break even” correlations opens up for specific organic breeding lines.Keywords: breeding strategy, breeding goal, organic dairy farmingIntroductionOrganic farming is expected to be an important part of future animal production. However, untilnow, improvements in the efficiency of organic dairy production have mainly occurred throughbetter management, feeding and production strategies, using the same dairy cattle breeds andbreeding material as in conventional production systems. In the pre-genomic era, there have beenmany good arguments for doing this. Genetic progress was strongly dependent on a substantialnumber of tested young bulls per year, which required many daughters sired by young bulls.Therefore, quite large populations were required to provide enough genetic progress. Now, in thegenomic era, progeny testing is no longer essential to achieve good rates of genetic progress, andtherefore there is an opportunity to use smaller populations or lines of populations. This has animpact on the opportunity to establish organic breeding lines. The possibilities and requirementsfor establishing organic breeding lines will be explored and discussed in this paper.Why organic breeding lines?The idea behind organic production, as well as the restrictions set by both national andinternational regulations for organic production, may result in: 1) different breeding goals fororganic dairy cattle as described by Slagboom et al., (2018); 2) genotype by environmentinteractions (G by E) between conventional and organic production systems, and 3) the need toinclude new traits in the organic breeding goal, which have little or no value in the conventionalproduction systems. Depending on the differences between breeding goal traits and the extent ofthe G by E, the optimal solution will be customized indices for organic farmers or establishingreal organic breeding lines.The main reason for absence of organic breeding lines is most likely that the so-called “breakeven” correlation was too low for separation in lines in most breeding schemes in the pre-genomic era. The “break even” correlation is the correlation, where it is beneficial to divide thepopulation in lines when the actual correlation between breeding goals in two lines is lower thanthe “break even” correlation. A correlation higher than approximately 0.8 has been shown tocause loss of genetic gain when dividing populations with less than a million cows in lines(Smith and Banos, 1991; Mulder and Bijma, 2006). Where populations are small, the “breakeven” correlation will be lower. However, this assumption was when progeny testing of bullswas the overall driver of genetic gain as shown in Figure 1.Figure 1 Illustration of the driving forces for obtaining genetic gain in dairy breeding programsbefore genomic selection. The accuracy of bull EBVs depend on the balance between thenumber of registered cows and the number of progeny tested bulls, and the selection intensity ofbulls to be selected, depend on the number of progeny tested bulls.In the future, the number of genotyped cows with phenotypes will be the overall driver ofgenetic gain as illustrated in Figure 2. So, dependent on: 1) the level of genotyping within thepopulation, 2) the traits of importance in the breeding goal (low or high heritability traits), and3) the possibilities for sharing reference populations with other lines or populations, it will bepossible to obtain genetic gain at an acceptable level in small and medium sized populations. Inlarger populations the use of cows in the reference population opens up for having different lineswith different breeding goals, as illustrated in Figure 2. Therefore, the “break even” correlationbetween breeding goals is likely higher in breeding schemes using genomic selection. Thismeans that the correlation between an organic and conventional breeding goal does not need tobe as low as in the pre-genomic era before line division is advisable.Figure 2 Illustration of the driving forces for obtaining genetic gain in genomic dairy breedingprograms. The accuracy of GEBVs depends on the number of cows in the reference populations,and the selection intensity of the selected bulls depends on the number of genotyped bull calves..Economic valuesAs described, mainly two factors affect the “break even” correlation. Firstly, the economicvalues in the breeding goal for the possible lines and secondly the presence of biological G by E.The breeding goal defines which traits are to be improved and how much weight is given to eachtrait (Groen et al. 1997). In dairy cattle breeding, the weighting factors are often EV based onmodelling. The EV are marginal EV, meaning the EV of one unit improvement of the trait –keeping the remaining traits constant. Therefore the EV, are functions of the productioncircumstances, depending on differences in productions systems and differences in economiccircumstances, e.g. prices of output (milk and meat) and input (primarily feed prices). Thiscreates different EV for different traits in conventional and organic production systems (Kargo etal., 2015). These EV are based on economic models which for some traits, e.g. traits related towelfare and robustness can be difficult to derive. In such cases, one can choose to assign thesetraits with so-called non-market values (Nielsen et al., 2005). Furthermore, the EV can beadjusted based on farmer preferences, which can be incorporated into the model to calculate EV(Slagboom et al., 2016, Slagboom et al., 2017) or they can be adjusted in accordance withprinciples for production, e.g. the principles for organic production as shown by Slagboom et al.,2018.G by E interactionLooking at Interbull correlations (Interbull, 2017) between countries there is no doubt that G byE exist. Even for simply measured traits like production traits there are correlations below 0.8between the primarily confinement production systems in West European countries and the grassbased production system in New Zealand with minimal feeding of concentrates. This suggeststhat there may also be G by E between organic grass based productions systems and more indoorbased systems with high amount of concentrate and high quality silage in feeding. There are,however, quite few and inconsistent estimates for G by E within literature. In Sweden, G by Ebetween organic and conventional dairy farms were found for fertility traits in second lactationonly, and no G by E were found for production traits (Sundberg et al., 2010). In the Netherlands,moderate G by E were found for milk production traits (Nauta et al., 2006). The reason for thesemany nonsignificant and inconsistent estimates may be due to a low number of registrations inthese analyses and in some cases difficulties in assigning the different herds to the rightproductions classes. Our expectation are, however that dairy cattle breeding in the future will befaced with more diversified production systems, some very intensive and some more extensivesystems, and therefore also faced with the existence of G by E.ConclusionWe have argued that in the future we will have different EV for conventional and organic dairyproduction systems, and that there is a high probability for the existence of G by E betweenconventional and organic production systems. The “break even” correlation, measuring how lowcorrelation between breeding goals must before line division is advisable, will go up in genomicbreeding schemes with large cow reference populations. All this is in favor of specific lines.Before arguing for organic breeding lines, the correlations between the two environments musttherefore be estimated. Furthermore, breeding scheme simulations must be carried out toinvestigate whether it is economically sound to set up different lines, meaning that the extragains achieved will be able to pay for the extra costs of running two or more breeding linesinstead of one. On top of this the requirements are sound phenotypic registrations and enoughgenomic tests for females to create reference populations within each production system. Inconclusion we expect that organic breeding lines or lines fitting other specific productioncircumstances will be created in the future.List of referencesBuch, L.H., A.C. Sørensen, J. Lassen, P. Berg, L.G. Christensen, and M.K. Sørensen. 2009.Factors affecting the exchange of genetic material between Nordic and us Hholsteinpopulations. J. Dairy Sci.. 92:4023–4034..Groen, A. F., T. Steine, J. J. Colleau, J. Pedersen, J. Pribyl, and N. Reinsch. 1997. Economicvalues in dairy cattle breeding, with special reference to functional traits. Report of anEAAP-working group. Livest. Prod. Sci. 49:1–21.Interbull, 2017. http://www.interbull.org/ib/maceev_archiveKargo, M., J.F. Ettema, L. Hjortø, J. Pedersen, and S. Østergaard. 2015. Derivation of economicvalues for breeding goal traits in conventional and organic dairy production. Pages 403–403in Book of Abstracts of the 66th Annual Meeting of the European Association for AnimalProduction. Wageningen Academic Publishers, The Netherlands.Mulder, H.A., and P. Bijma. 2006. Benefits of cooperation between breeding programs in thepresence of genotype by environment interaction. J. Dairy Sci.. 89:1727–1739.Nauta, W.J., R.F. Veerkamp, E.W. Brascamp, and H. Bovenhuis. 2006. Genotype byenvironment interaction for milk production traits between organic and conventional dairycattle production in the Netherlands. J. Dairy Sci. 89:2729–2737.Nielsen, H. M. Amer, P.R. and Byrne, T.J. (2014) Approaches to formulating practical breedingobjectives for animal production systems. Acta Agriculturae Scandinavica, 64, pp. 2-12.Nielsen, H. M., Christensen, L. G., and Groen, A. F. (2005). Derivation of sustainable breedinggoals for dairy cattle using selection index theory. J. Dairy Sci.. 88: 1882-1890.Slagboom, M., 2018. Breeding Goals for Organic Dairy Farming in Denmark Based on thePrinciples of Organic Agriculture. WCGALP, New ZealandSlagboom, M., M. Kargo, D. Edwards, A.C. Sørensen, J.R. Thomasen, and L. Hjortø. 2016.Organic dairy farmers put more emphasis on production traits than conventional farmers. J.Dairy Sci.. 99: 9845–9856Slagboom, M., M. Kargo, D. Edwards, A.C. Sørensen, J.R. Thomasen, and L. Hjortø. 2017.Herd characteristics influence farmers’ preferences for trait improvements in danish red anddanish jersey cows. Acta Agric. Scand. Sect. A — Anim. Sci. 66: 177-182Smith, C., and G. Banos. 1991. Selection within and across populations in livestockimprovement. J. Anim. Sci.. 69:2387–2394.Sundberg, T., L. Rydhmer, W.F. Fikse, B. Berglund, and E. Strandberg. 2010. Genotype byenvironment interaction of Swedish dairy cows in organic and conventional productionsystems. Acta Agric. Scand. Sect. A - Anim. Sci., 60:65–73.

Organic dairy breeding lines? – Possibilities and Requirements

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Organic dairy breeding lines? – Possibilities and Requirements

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