Breakeven prices for recording of indicator traits to reduce the environmental impact of milk production.

A breeding scheme using genomic selection and an indicator trait for environmental impact (EI) was studied to find the most effective recording strategy in terms of annual monetary genetic gain and breakeven price for the recording of indicator traits. The breakeven price shows the investment space for developing a recording system for an indicator trait. The breeding goal consisted of three traits – milk production, functional trait and environmental impact – with economic values of €83, €82 and €-83, respectively. The first scenario included only breeding goal traits and no indicator traits (NoIT). The other scenarios included all three breeding goal traits and one indicator trait (IT) for EI. The indicator traits were recorded on a large scale (stayability after first lactation and stature), medium scale (live weight and greenhouse gases (GHG) measured in the breath of the cow during milking) or small scale (residual feed intake and total enteric methane measured in a respiration chamber). In the scenario with stayability, the genetic gain in EI was over 11% higher than it was in NoIT. The breakeven price of recording stayability was €8 per record. Stayability is easy to record in the national milk recording system, and its use as an indicator trait for EI would not generate any additional recording costs. Therefore, stayability would be a good indicator trait to use to mitigate EI. The highest genetic gain in EI (23% higher compared to NoIT) was achieved when the GHG measured in the breath of the cow was used as indicator trait. The breakeven price for this indicator trait was €29 per record in the reference population. Ideally the recording of a specific indicator trait for EI would take place when: (i) the genetic correlation between the IT and EI is high; and (ii) the number of phenotypic records for the indicator trait is high enough to achieve a moderately high reliability of direct genomic values.

[1]  L. Rydhmer,et al.  Differences in preferences for breeding traits between organic and conventional dairy producers in Sweden , 2014 .

[2]  A. C. Sørensen,et al.  Genomic selection using indicator traits to reduce the environmental impact of milk production. , 2013, Journal of dairy science.

[3]  M. Weisbjerg,et al.  Technical note: test of a low-cost and animal-friendly system for measuring methane emissions from dairy cows. , 2012, Journal of dairy science.

[4]  A. C. Sørensen,et al.  The value of cows in reference populations for genomic selection of new functional traits. , 2012, Animal : an international journal of animal bioscience.

[5]  J. Craigon,et al.  Variation among individual dairy cows in methane measurements made on farm during milking. , 2012, Journal of dairy science.

[6]  N. Nielsen,et al.  Methods for Measuring and Estimating Methane Emission from Ruminants , 2012, Animals : an open access journal from MDPI.

[7]  A. C. Sørensen,et al.  Genomic selection strategies in dairy cattle: Strong positive interaction between use of genotypic information and intensive use of young bulls on genetic gain. , 2012, Journal of animal breeding and genetics = Zeitschrift fur Tierzuchtung und Zuchtungsbiologie.

[8]  J. Lassen,et al.  Accuracy of noninvasive breath methane measurements using Fourier transform infrared methods on individual cows. , 2012, Journal of dairy science.

[9]  M P L Calus,et al.  Genetic parameters for predicted methane production and potential for reducing enteric emissions through genomic selection. , 2011, Journal of dairy science.

[10]  H. Gilbert,et al.  Attentes en matière d'élevage des acteurs de la sélection animale, des filières de l'agroalimentaire et des associations , 2011 .

[11]  Kristina Mohlin,et al.  Greenhouse gas taxes on animal food products: rationale, tax scheme and climate mitigation effects , 2011 .

[12]  G. Russell,et al.  The effect of improving cow productivity, fertility, and longevity on the global warming potential of dairy systems. , 2011, Journal of dairy science.

[13]  H. Janzen What place for livestock on a re-greening earth? , 2011 .

[14]  M. Denis,et al.  Strategies to reduce methane emissions from farmed ruminants grazing on pasture. , 2011, Veterinary journal.

[15]  L. Rydhmer,et al.  Culling reasons in organic and conventional dairy herds and genotype by environment interaction for longevity. , 2011, Journal of dairy science.

[16]  J. Dekkers Use of high-density marker genotyping for genetic improvement of livestock by genomic selection. , 2010 .

[17]  D. Moran,et al.  Developing breeding schemes to assist mitigation of greenhouse gas emissions. , 2010, Animal : an international journal of animal bioscience.

[18]  P. Smith,et al.  Mitigating climate change: the role of domestic livestock. , 2010, Animal : an international journal of animal bioscience.

[19]  David Gibbs,et al.  Genetic techniques for livestock breeding: Restructuring institutional relationships in agriculture , 2009 .

[20]  M. Goddard Genomic selection: prediction of accuracy and maximisation of long term response , 2009, Genetica.

[21]  A. Flint,et al.  Precision animal breeding , 2008, Philosophical Transactions of the Royal Society B: Biological Sciences.

[22]  J. Goopy,et al.  Cattle selected for lower residual feed intake have reduced daily methane production. , 2007, Journal of animal science.

[23]  P. Garnsworthy The environmental impact of fertility in dairy cows: a modelling approach to predict methane and ammonia emissions , 2004 .

[24]  A. Groen,et al.  Definition of animal breeding goals for sustainable production systems. , 2000, Journal of animal science.

[25]  B. Kennedy,et al.  Effect of selection on genetic parameters of correlated traits , 1990, Theoretical and Applied Genetics.

[26]  B. Guldbrandtsen,et al.  Genomic selection strategies in a small dairy cattle population evaluated for genetic gain and profit. , 2014, Journal of dairy science.

[27]  C. Morris,et al.  Genetics and livestock breeding in the UK: Co-constructing technologies and heterogeneous biosocial collectivities , 2014 .

[28]  L. Rydhmer,et al.  Farmers' views on the impact of breeding traits on profitability, animal welfare and environment , 2013 .

[29]  M. Calus,et al.  Reliability of direct genomic values for animals with different relationships within and to the reference population. , 2012, Journal of dairy science.

[30]  M. M. Wolf,et al.  Economic Analysis of the Impact of Cloning on Improving Dairy Herd Composition , 2010 .

[31]  H. Simianer,et al.  Economic evaluation of genomic breeding programs. , 2009, Journal of Dairy Science.

[32]  P. VanRaden,et al.  Genomic selection using low-density SNPs , 2008 .

[33]  R. Bacilieri,et al.  Simplified milk-recording protocols adapted to low-input environments with very small herd size. , 2008, Animal : an international journal of animal bioscience.