Integrated Sustainable Aquaculture Production
Transcript of Integrated Sustainable Aquaculture Production
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2015/HLPD-FSBE/007 Session: 3
Integrated Sustainable Aquaculture Production
Purpose: Information Submitted by: ABAC New Zealand
High Level Policy Dialogue on Food Security and Blue Economy
Iloilo, Philippines4-6 October 2015
APEC HIGH LEVEL POLICY DIALOGUE ON FOOD SECURITY AND BLUE ECONOMY
Session 2: Fish loss reduction for increased fish production
Fish Loss Reduction and Value Added Seafood Products (sharing of best practice from ABAC /
Australian CSIRO / Australian Aquaculture Industry)
Connected Oysters and the Internet of Things ‐ Presented by ABAC PPFS Co‐Chair Mr Tony Nowell
on behalf of ABAC Australia and the Australian CSIRO
EXECUTIVE SUMMARY
Integrated sustainable aquaculture production and Sense – T ‐ Aquaculture optimisation through
the use of sensing technology – aims to transform the productivity, profitability and sustainability of
Australian and global aquaculture industries via integrated, whole of system collaborative research.
This work is enabled by Sense‐T, which is helping to build an economy‐wide sensor network and data
resource, creating a digital view of Tasmania and giving industry, governments and communities the
tools to solve practical problems and make better decisions.
Sense‐T is a shared resource to help people improve efficiency and productivity, and to develop new
approaches to economic, environmental and social sustainability. These can be tested in Tasmania
and applied across Australia and the world.
Based at the University of Tasmania, Sense‐T is a partnership between the University, CSIRO and the
Tasmanian Government, and is also funded by the Australian Government.
Three Pacific oyster growing areas across Tasmania (Pittwater, Moulting Bay and Duck Bay) will be
fitted with a network of biosensors on individual oysters for research on the connection between
variables such as oyster heart‐rate and production, as well as environmental sensors.
The data collected on the health of oysters and on‐farm conditions will inform real‐time decision‐
making on production and help the industry to become more competitive, efficient and sustainable.
Supporting documents and media:
PowerPoint Presentation: Integrated sustainable aquaculture production and Sense – T.pptx
Video (1): The Internet of Everything – Connected Oysters.mp4
Video (2): Sense‐T‐Explainer_revisedLogos_720p.mp4
Video (3): Sense‐T edit (computer playback version).wmv
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Integrated sustainable aquaculture productionNigel Preston: Development of Aquaculture Science Platforms 11‐02‐2015
Goal
Transform the productivity, profitability and sustainability of Australian and global aquaculture industries via integrated, whole of system collaborative research
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Research focus, targets and deliverables
Disease control
Genome selection
Novel aquafeeds
Whole system
TARGETS
Salmon sex control
Novel fish feeds
Elite salmonprawn and mollusc breeds
Whole genome access – salmon prawns oysters
Fully integrated whole of system production
technology
On‐farm sensor
technology
Prawndisease
therapeutics(RNAi)
Prawn feed (NovacqTM)
Atlantic salmondisease
therapeutics
Improved catfish breeds & systems
DELIVERABLES
RESEARCH FOCUS
2015 2016 2017 2018 2019 2020
Sensor technology, system models and decision support
Disease detection and prevention technology
Nutrition nutrigenomics and aquafeed technology
Applied selective breeding genetics and genomics
Fishmeal
Feeds• Sustainable feeds
Markets
Broodstock
Processing
An integrated approach
Energy
Breeds
Health Environment & Biosecurity
Sensing technology
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Sensor arrays
Remote sensorsEnvironmental monitoring
Sentinel fish
Nutrients
Nutrients
Whole of system modelling and monitoring of prawn farms and adjacent environments
Sediment
Sediment
Aeration
Nutrients
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CSIRO.
Broad scale (whole coastline) spatial analysis
Decision Support/Situational Awareness for aquaculture management = “Farm model”
Data Analyses/ML
Apps/ Visualisation/Decisions
BOM
Sensors
Ecosystem modelsRiver flow
Management
NETWORKS STORAGE ANALYSES USE
Monitoring Production
Climate models
Past and Present data = Predictions for management
RETRIEVAL
DATA
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AGRICULTURE FLAGSHIP
Breeding Higher Value Food Crops
Crop Improvement
Productive & Adaptive Livestock Systems
Integrated Agricultural Systems
Sustainable Ag Soil & Landscapes
Ag & Food Security
Breakthrough Genetic Breeding Technologies
Production
Physiology, sensing modelling, predictionpotential decision support systems
Breeds
Genetics, genomics, health & welfare
Raw materials Feed technology nutrigenomics
Feeds
Integrated Sustainable Aquaculture Production
Salmon farming whole system integration
Marine pathogen monitoring
Quarantine disease research facilities
BIOSECURITY and AAHL FOOD & NUTRITION
Human health and nutrition food safety
Biosensors, wireless networks and systems
DIGITAL PRODUCTIVITY
OCEANS & ATMOSPHERE
Climate and fine scale modelling & predictions
LAND & WATER
Systems modelling
• Salmon and oysters ‐ early warning of stress
• Prawns ‐ bio‐economics, licence to operate
• Abalone ‐ improving production systems
• Macq‐Sense concept – major opportunity for 5‐10 year focus on ‘digitising’ Macquarie Harbour salmon, tourism, hydro, mining
Digital aquaculture potential deliverables
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Recruit Project Leader (CSOF 5)
OCE Northern aquaculture
Digital aquaculture activities, capability & deliverables
2015 2016 2017 2018 2019 2020
POC on‐farm sensor
technologyfor oysters and salmon
Strategic biosensor project
Prawn “APSIM” and bio‐economic
models
Rural R&D biosensor proposal
Co investment from industry and regulators
Implement on‐farm sensor
technologyfor oysters and salmon
Digitised Macquarie harbour and integrated
whole of system production technology
DELIVERABLES
ACTIVITIES
Sarah Andrewartha
Postdoctoral Fellow
@DrSarz
John McCulloch
Senior Engineer
AQUACULTURE OPTIMISATION
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Monitoring oysters is challenging
Real-time oyster physiology on-farm
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Tem
pera
ture
(o
C)
8
12
16
20
24
28
Water temperature
29-Dec-14 05-Jan-15 12-Jan-15 19-Jan-15 26-Jan-15 02-Feb-15
Hea
rt r
ate
(b
eats
per
min
ute)
0
15
30
45
Heart rate
B
Time (seconds)
00 10 20 30
He
art
sig
na
l
54 beats per minute
Time (seconds)
00 10 20 30
30 beats per minute
17oC 25oC
He
art
sig
na
l
CSIRO Sensor cloud
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Date
22/12/14 29/12/14 05/01/15 12/01/15 19/01/15 26/01/15 02/02/15
Gap
e si
gn
al
Can we predict growth from gape?
Growth?
Phase 2: Can sentinels inform production?
Pittwater
Duck River St Helens
Sensors Field Work Lab Work
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Tasmanian Shellfish Quality Assurance Program
TSQAP
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Acknowledgements
University of TasmaniaPeter FrappellBrian Taylor
CSIROJohn McCullochNick ElliottAndrew HellicarDaniel HugoChris Sharman
Greg Timms
Barilla Bay Justin Goc
TSQAPAlison TurnbullKate WilsonMegan BurgoyneJason Whitehead