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Charmley Activity data collection livestock systems Nov 10 2014
1. Approaches to Activity data collection in
livestock systems
Ed Charmley, CSIRO Townsville
Hayley Norman, CSIRO Perth
ED.CHARMLEY@CSIRO.AU
2. 0
500
1000
1500
2000
2500
BEEF DAIRY PIGS BUFFALO CHICKENS SMALL
RUMINANTS
OTHER
PUOLTRY
Million tonnes CO2 -equiv
Total livestock emissions
• 7.1 gigatonnes CO2 -equiv
• 14.5% of global anthropogenic emissions
Global estimates of GHG emissions
Source: Tackling Climate Change through Livestock, FAO 2013
3. Global emissions intensity
0
100
200
300
400
500
Beef Dairy Small
ruminants
meat
Small
ruminants milk
Pork
Kg CO2 –equiv /kg protein
Source: Tackling Climate Change through Livestock, FAO 2013
4. Overview
1. Estimating animal numbers, weight, physiological state
2. Temporal/spatial distribution/scale
Seasonality
Selective grazing
3. Measurement techniques for benchmarking
Laser
4. Methane proxies
F-NIRS
Intake
5. Cost effective methods for benchmarking and mitigation
7. Problems
• How many animals?
• National and regional statistics
• Market information
• Processed feed consumption
• How large are the animals?
• Body weight
• Herd structure
• Body condition
• Physiological state
• Growing
• Mature
• Lactating
• gestating
8. Some thoughts on estimating animal numbers
• Census data is unreliable (snapshot in time)
• What are the alternatives?
• Catch and release methodology?
• Arial surveillance of animals?
• landscape condition
• Landscape condition = grazing pressure / pasture growth
• Pasture growth = land class x rainfall
24. NIRS method for international methane inventory
• Reference open circuit respiration chambers
• South America, Africa, Australia, SE Asia
• Faecal and feed samples associated with individual animal measurement collected, stored and
processed under standard methods
• Each feed/faeces sample set associated with individual animal methane emission (g/kg DMI)
• Standardised in country NIRS capability
• Does not require high level technical competency
• Machines linked into international network
• Centralized data processing
• All data into a global correlation
• Clustring of like samples to improve predictions.
• Centralized NIRS expertise (e.g. CSIRO, INRA, other)
• Wet chemistry to help with predictions
• NIRS for plant quality simultaneously.
• Can we predict CH4 from diet?
25. A CSIRO plan for Australia – extend to
international?
• That CSIRO, either independently or in collaboration with others, should develop a program of
research to develop a robust faecal NIR method for the estimation of livestock methane emissions
for Australia
• CSIRO have the equipment and technical capability at the Floreat Lab in Perth to undertake a
broad-scale analytical/NIR study of faeces and feeds collected from cattle and sheep studies
where methane production has been measured directly using open circuit respiration chambers.
• The dataset is increased by negotiating access to all samples and data generated under:
The Livestock Methane Research Cluster. Cluster members have already been discussing this
idea and are keen to take it further.
Negotiation with the National Livestock Methane Program to access samples generated as part
of that research program to further expand the database.
• The main components of the work would involve:
Collection of samples and associated data on intake and methane emission related to each
feed/faecal sample pair.
Processing and running samples through Spectrastar NIR equipment in Perth
Timeframe would be November 2014 to June 2015.
Approximate budget would be in the $40,000 to $50,000 range.
26. Thank you
Agriculture Flagship
Ed Charmley
Group Leader
t +61 7 4753 8586
e ed.charmley@csiro.au
w www.csiro.au
AGRICULTURE FLAGSHIP