The Implications of Digital Agriculture and Big Data for Australian Agriculture

356 Pages·2017·14.22 MB·English

by  Australian Farm Institute

research report
Precision to Decision – Analysis of
the Economic Benefits and Strategies
for Delivery of Decision Agriculture
September 2017
© 2017 Australian Farm Institute
ISBN 978-1-921808-39-5
P2D_cover_A4b.indd 1 31-Aug-17 12:33:07 PM
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Perrett, E., Heath, R., Laurie, A. and L. Darragh, 2017. Precision to Decision- analysis of the economic benefit and
strategies for delivery of decision agriculture - Draft Final Report, Australian Farm Institute, Sydney, August.
Design and Production: Australian Farm Institute.
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Acknowledgements
The Australian Farm Institute acknowledges the significant contributions of the Centre for International Economics (CIE) to
this report.
The Australian Farm Institute also acknowledges the significant contributions of Prassack Advisors [Appendix 3] and
AgThentic [Appendix 5].

This project was funded by the Australian Government's Rural R&D for Profit programme.

Images: CAFNR, Murrumbidgee Irrigation, Valley Irrigation
Precision to Decision
– Analysis of the Economic Benefits
and Strategies for Delivery
of Decision Agriculture
September 2017
© 2017 Australian Farm Institute
ISBN 978-1-921808-39-5
ii
Table of Contents
1. Executive Summary 1
2. Introduction 5
Definitions and Glossary 5
What is Decision Agriculture? 5
Introduction 7
The Research Question / Context 7
Project Scope 8
Project Outputs 9
Report Structure 9
Background 11
Project Objective 13
Drivers of Decision Agriculture 13
The Age of Data and Analytics 15
The Digital Value Chain 20
Methodology
3. The Potential Economic Impact of Decision Agriculture 23
Background 23
Key Findings 24
Impact of Unconstrained Decision Agriculture to the Australian Economy 24
Sectoral Breakdown 25
Common Themes for Productivity and Profitability Improvement From Decision Agriculture 32
Summary 34
4. Business and Service Delivery Models for Decision Agriculture 35
Background and Context 35
Developing a Business Model 36
The ‘Lean’ and ‘Agile’ Approach to Business Development 38
Business Models Used to Profit from Big Data 40
Key Findings 43
The Current State of Digital Agriculture Product and Service Delivery for Australian Agriculture 43
Australian AgTech Snapshot – Current Digital Technology Developments by Sector 47
Rice 47
Grains 47
Cotton 48
Sugar 48
Horticulture (leafy greens, brassicas, carrots) 49
Red Meat (including beef, sheepmeat, and red meat processing) 49
Wool 51
Pork 52
Dairy 52
Eggs 53
Chicken Meat 53
Wine 54
Forest and Wood Products 54
September 2017 | Precision to Decision – Analysis of the Economic Benefits and Strategies for Delivery of Decision Agriculture
iii
Livestock Exports 55
Fisheries and Aquaculture 56
The Likely Development of Digital Agriculture in Australian Agriculture 57
An Assessment of the Business Environment for Decision Agriculture by Sector 63
5. The Impact of Current Constraints on Decision Agriculture 71
Availability of Appropriate Data 71
Data Analytics and Decision Support Tools 72
Connectivity Infrastructure 74
Trust and Legal Barriers 75
Value Proposition 77
Summary: The Impact of Current Constraints on the Realisation of Decision Agriculture 80
6. Conclusion and Recommendations 82
7. References 89
APPENDIX 1: CIE-REGIONS Food Procession Model 92
APPENDIX 2: The Economic Inpacts of Decision Agriculture by Sector 98
APPENDIX 3: A Review of the Australian AgTech Sector 225
APPENDIX 4: The Global Impact of Decision Agriculture 269
APPENDIX 5: A gTech Case Studies from the USA – Farmers Business Network,
Agrian, and Harvest Mark 319
Precision to Decision – Analysis of the Economic Benefits and Strategies for Delivery of Decision Agriculture | September 2017
iv
Abbreviations
Acronym Meaning
ABARES Australian Bureau of Agricultural and Resource and Economics Sciences
ABS Australian Bureau of Statistics
ACCC Australian Competition and Consumer Commission and Productivity Commission
ACFR Australian Centre for Field Robotics
AECL Australian Egg Corporation Limited
AFMA Australian Fisheries Management Authority
AGWA Australian Grape and Wine Authority
AMPC Australian Meat Processor Corporation
APL Australian Pork Limited
ARC Australian Research Council
AWI Australian Wool Innovation Limited
BCG Boston Consulting Group
CAD Computer Aided Design
CIE Centre for International Economics
CNST The Flinders Centre for Nanoscale Science and Technology
CRC(s) Cooperative Research Centre(s)
CRDC Cotton Research and Development Corporation
CSIRO The Commonwealth Scientific and Industrial Research Organisation
DA Dairy Australia Limited
DEPI Department of Environment and Primary Industries
DEXA Dual X-Ray Absorptiometry
DPI Department of Primary Industries
DPIPWE The Tasmanian Government Department of Primary Industries, Parks, Water and
Environment
DVC Data Value Chain
ESCAS Exporter Supply Chain Assurance System
FP Food Processing (model)
FRDC Fisheries Research and Development Corporation
FWPA Forest and Wood Products Australia
GDP Gross Domestic Production
GIS Geographical Information Systems
GNSS Global Navigation Satellite System
September 2017 | Precision to Decision – Analysis of the Economic Benefits and Strategies for Delivery of Decision Agriculture
v
Acronym Meaning
GPS Global Positioning System
GRDC Grains Research and Development Corporation
GVP Gross Value of Production
HD High Definition
HIA Horticulture Innovation Australia Limited
ICT Information and Communications Technology
IoT Internet of Things
IP Intellectual Property
LiveCorp Australian Livestock Export Corporation Limited
MIR Mid infrared
MLA Meat and Livestock Australia
NBN National Broadband Network
NZ New Zealand
OCM Objective carcase measurement
OHS Occupational health and safety
P2D The Accelerating Precision Agriculture to Decision Agriculture program
QA Quality Assurance
QDAFF Queensland Department of Agriculture, Forestry and Fisheries
QUT Queensland University of Technology
R&D/ RD&E Research and Development / Research Development and Extension
RAS/RAT Robotics and Automation Systems / Robotics and Automation Technologies
RDC(s) Rural Research and Development Corporation(s)
RIRDC Rural Industries Research and Development Corporation
RMIT Royal Melbourne Institute of Technology
SME Small and Medium Enterprise
SRA Sugar Research Australia Limited
UNE University of New England
US The United States of America
USO Universal Services Obligation
VRT Variable Rate Technology
WHS Workplace Health and Safety
Precision to Decision – Analysis of the Economic Benefits and Strategies for Delivery of Decision Agriculture | September 2017

SECTION 1: Executive Summary 1
Executive Summary
Digital technologies have the potential to fundamentally transform the way food and fibre is
produced, traded and consumed.
A new wave of technologies is enabling farm operators to manage farms with a much higher
degree of precision than has been feasible in the past, and when combined with the power of
modern computers and big data analytics, is driving the development of sophisticated
decision-support tools that allow businesses to make better data-driven decisions.
The overall objective of this research is to develop a business case and clear value
proposition for Australian producers, agribusinesses, RDCs, and governments about the
potential benefits of decision agriculture.
This is the first project to be supported by all fifteen rural Research and Development
Corporations (RDCs), whose levy-paying members reflect the diversity of food and fibre
production in Australia. In doing so, it takes a whole-of-agriculture approach to the adoption
of digital agriculture technologies and systems, and explores opportunities for improved
cross-sectoral industry research collaboration. Recommendations from this report are
intended to guide ongoing investments and coordinated action in areas that are likely to
address current constraints and accelerate the shift from precision agriculture to decision
agriculture.
This report presents results on research covering two broad areas.
Firstly, an analysis of the potential benefit to the Australian economy from the
implementation of decision agriculture. This research was conducted with support from the
Centre for International Economics (CIE). Findings from this report provide an overview of
the potential value to the Australian economy of a 'fully-enabled' decision agriculture. By
quantifying the 'size of the prize' and analysing the impact of constraints, this project provides
a high-level and strategic overview of the broad opportunities for government and industry to
invest in digital agriculture.
Secondly, an analysis of the various aspects that will impact the delivery of those benefits to
farmers are reported including likely business models for the delivery of decision agriculture
products and services. This includes a review of international developments in decision
agriculture and an analysis of their implications for the Australian agricultural industry. Input
from AgThentic and US-based consultancy firm Prassack Advisors helped inform this
review.
Currently there is a gap in knowledge about the potential economic costs and benefits of
digital agriculture, and their impacts on the Australian economy. This report estimates that
the unconstrained implementation of decision agriculture would result in a lift in the gross
value of agrifood production of $19.1 billion (a 25% increase on 2014-15 levels). In addition,
the benefits of unconstrained decision agriculture would have major flow-on effects to other
Precision to Decision – Analysis of the Economic Benefits and Strategies for Delivery of Decision Agriculture | September 2017
2 SECTION 1: Executive Summary
parts of the economy and delivery an overall increase of $24.3 billion to national gross
domestic product (GDP) (a 1.5% increase on 2014-15 levels).
The benefits and drivers of decision agriculture vary by sector, but there are consistent
messages about the value of digital agriculture applications such as remote sensing and
automation, objective measurement, variable rate management, and improving regulatory
compliance. The common challenges and opportunities facing many agricultural sectors
reinforce the need for cross-sectoral collaboration in areas that will facilitate the development
of decision agriculture.
This project is primarily focused on how technology and data impacts on-farm decision-
making. However, many of the biggest changes associated with decision agriculture will
occur at other points in the value chain. There are a number of 'push and pull' factors
influencing how farmers, processors, retailers and other businesses utilise data and
technology to improve decision-making and business profitability. The structure of the value
chain, including the size of businesses and the level of business integration between
production and retail stages, has a significant effect on the potential for decision agriculture.
The combination of several technological, social and business trends is changing the way
businesses in all sectors of the economy operate. We are witnessing the rise of digital
entrepreneurs and the proliferation of start-ups, driven in part by changes to the financial
sector (e.g. private equity trends). This is leading to digital disruption and the rise of new
players who are challenging traditional business models (think Uber in the taxi industry or
Airbnb in the hotel industry). The ubiquity of digital technology is leading to the emergence
of new business models in agriculture and the development of an AgTech1 sector.
Currently, the development and uptake of digital agriculture technologies has been
underwhelming compared to the associated hype. The Australian market for decision
agriculture products and services is in its relative infancy compared to the scale and pace of
developments occurring in other parts of the world, notably the United States and Israel.
However, the transformation of the Australian agriculture sector into a smart, high-tech
industry is showing strong signs of interest and growth. Increasingly, investors and
technology developers not traditionally associated with agriculture are recognising the
opportunities associated with decision agriculture. As a consequence, the
Australian AgTech market is rapidly expanding, with new business models emerging and
successful Australian start-ups positioning themselves to benefit from global market
opportunities.
The likely emergence of decision agriculture business and service delivery models varies by
sector and is shaped by several factors including the market size, potential international
technological spillover, and the digital maturity of the sector. Together these factors suggest
the potential economic impact of digital agriculture, the specific challenges facing the sector,
and readiness of producers to adopt new technology.

1 The term decision agriculture is used throughout this report to describe a specific set of digital technologies
and the purpose of their use. In the investment community, the technologies that are involved in decision
agriculture are often described as AgTech.

September 2017 | Precision to Decision – Analysis of the Economic Benefits and Strategies for Delivery of Decision Agriculture