towards identifying novel phenotypes in climate adapted livestock production
TRANSCRIPT
Leading the way in Agriculture and Rural Research, Education and Consulting
Towards Identifying Novel Livestock Phenotypes
in Different Feed and Production Systems
Mizeck Chagunda
SRUC
Acknowledgements
• SRUC Dairy Research Centre
Team
• Peter Lovendahl : University of Aarhus
• Liveness Banda: Lilongwe, Malawi
• Nic Friggens: Agri Paris Tech/INRA
• Stephen Ross: SUDT: Singapore
• Dave Ross, Eileen Wall &
Malcolm Mitchell: SRUC
• Laura Randall: University of Nottingham
• Reuben Newsome: University of
Nottingham
• Dave Roberts: SRUC
• Jan Philipsson & SLU for invitation
Outline
• Feed and Production Systems
• Novel Phenotypes
• Some examples: – Reproduction
– Feed utilisation efficiency and environmental impact
– Cow Health
• Implications and Application
The Langhill Herd
2 Feeding Systems
Home-grown grazing & ration grown on farm (7000 kg milk/cow/year,
36 % of DM)
By-products ration based on co-products (11000 kg milk/cow/year,
50% DM)
2 Genetic Lines
Control
Select
SRUC Dairy Centre
Long running G x E experiment
200 cows
BPS, BPC, HGS, HGC
Recording and Goal
• Both traditional and advanced technologies for large scale measurements of phenotypes
• Measure both normal and difficult to measure traits
• Goal: improved resource efficiency; reduced environmental impact; improved animal health while producing high quality product.
Consistency across groups
• Staff
• Housing
• 3 x daily milking
• Health and fertility
• Young stock rearing
• S and C managed together
• Replacement policy - 3 lactations
• Same conserved forages offered within group
• Data as a commodity
Smallholder Dairy Systems
Why Phenotypes?
• Observable characteristics
• Phenotype is King (Mike Coffey)
Source: Council for Responsible Genetics
Why Phenotypes?
Why Novel Phenotypes?
• Traditional and conventional phenotypes have served us well, however…
• The Times They are Changin’ (Bob Dylan, 1964)
• Global challenges of Food Security and Climate Change
• Require animals that can adapt to… and practices that can mitigate climate change
Traits
Reproduction
Feed Utilisation Efficiency
and Environmental Impact
Health
Cow Activity
• Pedometers
• Neck collars
Reproduction cycles
• Gold standard for reproductive activity is progesterone
• The normal cycles are usually easier to identify
• The start of cycling or lack of it is the problem
• Impossible in heifers (using milk)
Friggens & Chagunda, 2006
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P4
Days after calving
Need for automation
• Difficult with manual sampling
• Need for specialised equipment/techniques (e.g. ELISA, RIA, Herd Navigator, etc)
Friggens & Chagunda, 2006
Profiles from Activity Meters
Lovendahl & Chagunda, 2011
Activity
Days to first high activity episode
Breed Parity N Median SD
Red Dane 1 86 35 18
2 69 26 27
3 42 25 22
Holstein 1 90 36 30
2 53 40 30
3 31 39 32
Jersey 1 50 37 32
2 43 30 22
3 22 41 33
Milk recording data obtained using automatic milking units (Robots) 267
lactations; 111298 milkings
Lovendahl, Chagunda, et al 2010
Average daily activity in different genetic and
feeding systems
Variable Production system
BPC BPS HGC HGS
Milk yield (litres/day) 30.5 36.8 24.5 26.1
BEC (MJ/day) 4902 4356 4284 3938
No of steps/day 1336 1324 1644 1612
Motion index/day 50.3 49.0 62.1 61.3
Standing duration (hrs) 12.90 12.61 13.54 13.63
Feeding duration (h/d) 4.39 4.83 5.05 5.13
Banda, et al. 2016
Overall motion index two feed types
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Mo
tio
n in
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Time (days)
Dairy mash
Maize bran
Banda, et al. 2016
Water Intake vs Cow Activity
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Wat
er In
take
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d A
ctiv
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Days to Oestrus
Activity
Water Intake
Any Genetic Component to it?
Genetic and Phenotypic variance, ACTIVITY
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Variance
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S_Total
Animal=P+G
S_Perm
S_Gene
Residual
T
H2
Løvendahl and Chagunda, 2006
Implications
• The cow indicates when ready to be served
• Continuous data flow and hence applicable in
both large scale and smallholder systems
• Potential to be used as a bench mark to
Artificial Insemination (AI) and fertility
Enteric Methane
Respiration calorimetric chambers
Breath Measurement in Livestock
• Breath analysis is steadily gaining ground in
livestock production.
• Examples – Lassen et al. 2012
– Ross et al 2012
– Garnsworthy, 2012
– Laser Methane Detector (Chagunda et al, 2009; 2011; 2013; 2015)
• Providing a platform for cow-side methods
Laser Methane Detector
• Based on infrared absorption
spectroscopy
• Using a semiconductor laser as
a collimated excitation source
• Employs second harmonic
detection of wavelength
modulation spectroscopy to
establish methane concentration
Non-contact and non-invasive
• Amenable to animal
welfare
• Safe for operator and
animal
• Able to take measurements
without disturbing the
animals
Recording Duration
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cow1814
Breath Eructation
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cow1953
ppm
ppm
Time, s
Relationship between measurements
y = 0.6983x + 114.95
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Laser Methane Detector (ppm)
Meta
bolic
Cham
ber
(ppm
)
Chagunda, M.G.G and Yan T. 2011..
Any Genetic Component?
• (Predicted) methane
heritable and varies
– Chr 2 (chr signif only)
• International
development of
genomic predictions for
novel traits from
resource populations
Laser methane
h2 = 0.06-0.13
rg ~ 0.6 (highest)
Pickering, Chagunda et al, 2015
Implications
• Methane contributes to climate change
• Enteric methane reflects feed energy loss
• Implications on Feed Conversation efficiency
• Feed energy loss is money lost and GHG
increased
Body Energy Content
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Bo
dy e
nerg
y c
on
ten
t (M
J)
Time (weeks)
BPC BPS
HGC HGS
Body Condition Score and Lameness
• BCS was found to be significantly associated with lameness
• BCS minimum target threshold of ≥2 for control of severe lameness Randal, Green, Chagunda et al. 2015
Health Indicators in Milk
• Disease are traditionally categorical traits
• But disease is a creeping phenomenon
• Continuous indicators in milk
Chagunda et al. 2006
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Time from calving
mic
ro m
oles
/min
; and
L
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Time from Calving
Out
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k
Mastitis risk profile
Chagunda et al. 2006
What have we learnt so far
• Importance of setting up robust recording
systems
• New Phenotypes will help us improve efficiency
• Partnerships are very important (e.g. across
country genetic valuations)
• Cows are always communicating
…thank you for your attention
If Phenotype is King…
…then Recording System is the Prince