09_Dairy farm profitability is enhanced by the application of quantitative genetics.
Submitting Institution
University of EdinburghUnit of Assessment
Biological SciencesSummary Impact Type
EnvironmentalResearch Subject Area(s)
Biological Sciences: Genetics
Summary of the impact
Impact on productivity, the economy and the environment: UK dairy
farmers can select the best animals for breeding using analysis of a wide
range of traits, leading to improved productivity, greater efficiency and
reduced environmental impact, because of UoE research creating a UK
Test Day Model (TDM) and an overall Profitable Lifetime Index
(PLI)
Beneficiaries: The principal beneficiary is the dairy
industry, specifically dairy farmers who are able to generate higher
profits. This has benefits for UK consumers and the economy by keeping
milk prices lower. The reduction in greenhouse gas emissions associated
with more efficient dairy farming practices has global benefits.
Significance and Reach: The genetic evaluation system enabled by
the PLI and TDM has resulted in a financial benefit to the UK dairy
industry of an estimated £440M over the period 2008-2013.
Attribution: The quantitative genetic research was led by Dr Sue
Brotherstone and Professor Bill Hill of the School of Biological Sciences,
UoE, with colleagues at Roslin Institute (UoE; UoA6) and SRUC (also
returned with UoE in UoA6) as described below.
Underpinning research
UoE has carried out much of the research and development underpinning
genetic evaluation systems for livestock in the UK. The research has been
a collaborative programme between researchers at the School of Biological
Sciences (UoE5; Brotherstone, Hill, White) and at the Roslin Institute and
SRUC (UoA6). The research which underpins this impact case study is the
underpinning quantitative genetics research led by Brotherstone, which has
provided the techniques and statistical models that have been applied to
provide productivity and profitability analyses for the UK dairy industry.
This research underpins effective genetic evaluation in livestock, which
requires a quantitative genetic statistical model in which phenotypic
variance is compartmentalised into environmental and genetic effects.
In 1998 Sue Brotherstone and Bill Hill established techniques for routine
genetic evaluations for dairy herd lifespan in the UK [1].
Brotherstone also showed for the first time how a random regression model
could be used to evaluate traits measured just once on an animal [2], for
example, udder composite and locomotion. This paved the
way for research into variance traits which are measured only once but
which change over time, such as energy balance and body condition.
Research by Brotherstone & White into an improved genetic evaluation
model for dairy cattle productivity (i.e. milk production levels)
published in 1999/2000 initially concentrated on milk yield and derived a
method of modelling the lactation curve for UK dairy cows [3]. Variance
components necessary for genetic evaluation were estimated for cows in
lactations 1 to 3. This allowed development of a test day, random
regression model for production traits which uses daily (`test day')
production data, providing the ability to account for environmental
effects on each test day and to model genetic variation in individual
lactation curves (i.e. a `Test Day Model' or TDM). Subsequent research
extended the work to the fat and protein content of milk using a
multivariate system, which involved the estimation of over 800 genetic and
environmental variance components. Brotherstone also developed methods of
accounting for both pregnancy [4] and heterogeneity of variance in the
model and derived a method of incorporating lactations 4 and 5 into the
evaluation system. This resulted in a UK-herd-specific TDM which delivers
more accurate genetic evaluations for production, allows genetic
evaluations for lactation persistency to be calculated and enables
lactations in progress to be easily incorporated into the system.
Further research by Brotherstone in collaboration with SRUC and the
Roslin Institute (genetics researchers Coffey, Woolliams, Wall, and
economist Stott) considered other indices that could be used to improve
genetic evaluation, demonstrating that there is wide genetic variation in
these traits and therefore scope for selection. She produced genetic
parameters for locomotion, which is used as a predictor of lameness [5]
and provided fertility parameters in collaboration with colleagues at SRUC
and Roslin [2, 6]. Stott provided the economic evaluations to convert
genetic indices to profitability measures.
All research cited here was undertaken by UoE: Led by Dr Sue
Brotherstone, Senior Research Fellow in the School of Biological Sciences
(1982-retired 2011) with substantial contributions from Professor Bill
Hill, School of Biological Sciences (1965-2002; now Senior Honorary
Professorial Fellow), PDRA Ian White (1996-retired 2012), Dr Huw Jones
(Biosciences KTN) contributed to paper [2]. Other UoE collaborators at
SRUC and Roslin Institute are named above; SRUC led the work in paper [6].
References to the research
1. Brotherstone, S., Veerkamp, R.F. and Hill, W.G. (1998). Predicting
breeding values for herd life of Holstein-Friesian dairy cattle from
lifespan and type. Animal Science 67, 405-411. doi: http://dx.doi.org/10.1017/S135772980003280X.
18 Scopus citations at 21/10/2013.
2. Jones, H.E., White, I.M.S. and Brotherstone, S. (1999). Genetic
evaluation of Holstein Friesian sires for daughter condition-score changes
using a random regression model. Animal Science 68,
467-475. Web of Knowledge Accession Number: WOS:000080023800015. 52
Scopus citations at 21/10/2013.
3. Brotherstone, S., White, I.M.S. and Meyer, K. (2000). Genetic
modelling of daily milk yield using orthogonal polynomials and parametric
curves. Animal Science 70, 407-415. Web of Knowledge Accession
Number: WOS:000087576100005. 77 Scopus citations at 19/09/2013.
4. Brotherstone, S., Thompson, R. and White, I.M.S. (2004). Effects of
pregnancy on daily milk yield of Holstein-Friesian dairy cattle. Livestock
Production Science 87, 265-269. doi:
10.1016/j.livprodsci.2003.07.014. 12 Scopus citations at 21/10/2013.
5. Stott, AW, Coffey, MP and Brotherstone, S (2005) Including lameness
and mastitis in a profit index for dairy cattle. Animal Science 80, 41-52.
doi: http://dx.doi.org/10.1079/ASC40520041.
19 Scopus citations at 21/10/2013.
6. Wall, E, Brotherstone, S, Woolliams, JA, Banos, G and Coffey, MP
(2003) Genetic evaluation of fertility using direct and correlated traits.
Journal of Dairy Science. 86, 4093-4102. PubMed ID: 14740850. 94
Scopus citations at 21/10/2013.
Details of the impact
Improvements in livestock production are the result of selection
practised by breeders who aim to select and breed from the "best"
individuals. Before selection decisions can be made, an accurate genetic
evaluation of the animal must take place. In the dairy cattle industry,
genetic evaluations take place three times per year and the results are
used by breeding companies and by farmers to improve the genetic merit of
the national herd.
The techniques established by UoE researchers for routine genetic
evaluations for dairy herd lifespan in the UK [1] allowed farmers for the
first time to select for both longevity and milk production. The inclusion
of breeding values for lifespan gives improved selection decision; before
this, dairy farmers selected only for high production, which had negative
impacts on cow health and welfare and thus on profitability.
This innovation was the first stage in development of the Profitable
Lifetime Index (PLI), a widely-used tool provided by DairyCo (a
levy-funded, not-for-profit organisation working on behalf of Britain's
dairy farmers) which is proven to relate to actual profitability on the
farm. The PLI is made up of the traits most strongly linked to
profitability and identifies bulls that pass these traits onto their
daughters. Since its introduction the PLI has been updated a number of
times building on the original production and lifespan parameters which
were produced in collaboration between Brotherstone and Hill providing the
genetic parameters and SRUC colleagues providing the economic analyses
[1-4]. Updating has incorporated lameness [5] and fertility [6]. The
traits now included in the PLI are production (milk yield, fat and protein
composition of milk), lifespan, type traits (udder conformation and
locomotion), fertility, and somatic cell counts [a,b]. The UoE research by
Brotherstone described above has provided the underlying parameters and
genetic indices for production traits (through the UK Test Day Model)
[3,4] and has contributed substantially to the lifespan [1,2], fertility
[2,6], and the locomotion type traits [5] that are used in genetic
evaluation to derive the PLI for UK dairy cattle.
The UK TDM provides the Production component of the PLI [b],
which accounts for around 45% of the weighting given to the different
traits included in the PLI. The UK TDM has dramatically improved genetic
evaluations for milk and its components by allowing data to be adjusted
for herd management and environmental effects that change over time, and
by accounting for genetic differences in the shape of the lactation curve.
The UK moved to this model for the calculation of genetic indexes for
production in 2005 and the impact has been felt throughout the assessment
period [b]. Milk yields have increased as a result of improved selection
utilising TDM assessment: 15% higher per cow per annum in 2011/12 compared
to 2003/4; the increase in milk yield in Holsteins from 1980 to 2012 is
approaching 60%, with improved genetic selection estimated to have
accounted for around half of this improvement [b,c] The multivariate
system for assessing the fat and protein content of milk allows the
identification of the best cattle to breed depending on the type of milk
the offspring would produce. So, cheesemakers desire cows bred to produce
milk with a high fat and protein content whereas milk producers desire
cows bred to produce high volumes of milk with less emphasis on content.
Improved genetic analysis for milk production using the TDM therefore also
increases the efficiency and profitability of specialist producers.
Genetic evaluation systems are vital for the efficiency and
competitiveness of the UK livestock industry. The benefits from genetic
progress in livestock populations are well documented. For example Moran et
al. [d] showed that animal genetic improvement is expected to
deliver public good rates of return between 11% and 18%, far in excess of
the recommended Treasury rate of return for public investment (3.5%).
Total benefit from dairy cattle genetic improvement in the UK from 1980 to
2009 has been calculated as £2.42 Billion; the introduction of the new TDM
in 2005 and improved PLI as a result of UoE research suggest such economic
improvements would be sustained or accelerated, equating to £440M over the
REF period [e].
The benefits of genetic evaluation also extend into environmental impact.
Jones et al [f] showed that past selection on production traits in
UK livestock has resulted in a decrease in the livestock population
through higher productivity per cow, and hence an average 1.4% per year
reduction in greenhouse gas production per unit of food produced. In
addition, increased longevity and improved fertility through better
breeding selection reduces the number of replacement females which need to
be reared (e.g. a 2% fall in the size of the national herd was recorded
between 2010/11 and 2011/12 [c]), and thus results in reduced greenhouse
gas emissions. Data on emissions for more recent periods than the Jones et
al. evaluation are not available but this environmental benefit will
have continued during the impact census period.
Sources to corroborate the impact
The Tiny URLs provide a link to archived web content, which should be
accessed if the original web content is no longer available.
a) Head of Genetics Group, DairyCo, can corroborate the importance of TDM
and PLI to the industry and the impact of UoE research.
b) DairyCo documentation on Test Day Model and use of genetic indices:
http://www.dairyco.org.uk/resources-library/technical-information/breeding-genetics/breeding-briefs/
or http://tinyurl.com/nkv4p2r
c) DairyCo Average Milk Yield Statistics (2012): http://www.dairyco.org.uk/resources-library/market-information/farming-data/average-milk-yield/
or http://tinyurl.com/nmkzsky.
d) Corroboration of quoted economic value of genetic improvement tools:
Moran, D., Barnes, A. and McVittie, A. 2007. The rationale for Defra
investment in R&D underpinning the genetic improvement of crops and
animals (IF0101). Final report to DEFRA.
e) Corroboration of quoted profitability benefits to UK dairy industry:
Amer, P.R., Wall, E., Nuhs, J., Winters, M. and Coffey, M.P. 2011. Sources
of benefits from genetic improvement in the UK dairy industry and their
impacts on producers and consumers. Interbull Bulletin No 43, Stavanger,
Norway.
f) Corroboration of quoted environmental benefit through reduced
greenhouse gas emissions: Jones, H.E., Warkup, CC., Williams, A. and
Audsley, E. 2008. The effect of genetic improvement on emission from
livestock systems. In Proceedings of the European Association of Animal
Production, 24-27 August 2008, Vilnius, Lithuania, Session 5.6, p28. DEFRA
report on this project is available.