INS IGHT to AI in UK AgriTech - 2021 and beyond Make money work for you - Barclays
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INS IGHT to AI in UK AgriTech 2021 and beyond Make money work for you
AI in UK AgriTech — 2021 and beyond
Contents
03 Executive summary 32 UK AgriTech Trailblazers
Agrimetrics – The UK’s data marketplace
05 Introduction
33 UK AgriTech Trailblazers
06 Foreword Small Robot Company – A leading robotics innovator
07 UK Agriculture 34 UK AgriTech Trailblazers
The importance of tech in securing competitive advantage
Bedfordia Farms – Looking to take the next steps in data integration
16 UK AgriTech 35 UK AgriTech Trailblazers
How can we enable agriculture 4.0 in the UK?
Hands-Free Hectare – The future of farming?
31 UK AgriTech 36 What have we learned?
DroneAg – One of UK AgriTech’s drone pioneers
Summary and recommendations
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AI in UK AgriTech — 2021 and beyond
Executive summary
Smart Tech is fundamental to The UK can be at the forefront of Pinpoint the use case then build
securing UK Agriculture’s future innovation and implementation the tech
Leveraging technology effectively is critical in unlocking The UK boasts world-class technology and research Technologies offering immediately apparent solutions to
opportunities – whether productivity, profitability or capabilities, and is the global leader in the development of AI known issues – and that ‘fit’ with existing infrastructure,
sustainability-related – that will be critical in securing a enabled solutions. hardware or processes – are ‘easy wins’. AI-enabled sensor
robust future for UK Agriculture. tech is delivering critical data to farmers from devices
Organisations such as the Small Robot Company, the UK’s increasingly simple to implement, visualised in increasingly
While UK farmers are beginning to appreciate the many ways leading ag robotics firm, which has developed the world’s first simple and impactful ways, and it is no surprise to see
in which emerging technologies can deliver better outcomes weeding bot; Drone Ag, simplifying drone tech for the sector; increasingly widespread adoption.
– more efficient use of resources; more productive use of and the Hands Free Hectare project are pushing innovation
their time – there remain profound barriers that need cross- forward at pace. Other IoT or data solutions need to be matched more closely
industry collaborative solutions. to farmers’ needs, behaviours and – just as importantly – to
Solutions that can readily be integrated into core processes be adaptable to different environments. And furthermore,
Costs of adoption; return on investment; and fitness for can help to ensure farms such as Applegarth, which is to have clearly evident – and ideally demonstrable – return
purpose are all challenges that must be addressed – and can successfully leveraging a range of Precision Ag technologies, on investment. Small Robot Company is one developer that
be addressed – to put UK Ag on track for the next decade. will in future be the rule rather than the exception. is beginning to drive out positive examples in this respect.
Others should follow, ideally in collaboration with farmers to
ensure innovation is targeted effectively.
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AI in UK AgriTech — 2021 and beyond
Executive summary
Data will be at the core of tech Key steps to accelerate adoption
solutions in 2021 and beyond Knowledge sharing between farmers, leading industry bodies
and technologists is critical in ensuring that innovation is
The explosion of data in the last ten years and more is already
directed towards practical challenges; and that farmers are
arming farmers with key insights with which to optimise
made aware of the possibilities that technology can unlock.
process and outcomes. But the next wave of data innovation
Hands-Free Hectare is an exemplar in this respect.
must go further.
Support mechanisms such as the Countryside Productivity
With greater commonality in taxonomy and platforming
Small Grants programme must be fully funded on a long-
must come fully integrated datasets capable of feeding
term basis to ensure that farmers are not penalised for early
ML-enabled algorithms capable of unpicking complex
adoption of emerging tech.
interdependencies and pinpointing solutions.
Finally and perhaps most fundamentally, tech needs to
Bringing evidence, analysis, conclusions and
deliver practicable, workable broad-spectrum solutions
recommendations for solutions to life simply and visually
rather than disparate IoT components that are additive only
is the last piece of the puzzle, enabling farmers to make
within a very narrow scope and are often ill-suited to the
mission-critical decisions quickly and confidently. Providers
rigours of UK farms and climate.
such as Agrimetrics are beginning to bring this utopia to life,
but would acknowledge that much needs to happen to allow
the industry to transition to that point.
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AI in UK AgriTech — 2021 and beyond
Introduction
Total global agricultural At the vanguard of developments in this
context is the emergence of technologies
production has tripled in enabled by Artificial Intelligence (AI),
the last 60 years, outpacing Machine Learning (ML), Deep Learning
(DL), Robotics, the Internet of Things (IoT)
even the huge increase and Cloud Computing. These technologies,
– from 3B to more than already underpinning some of the most
7B – in the number of fundamental changes in agricultural working
practices seen in a century and more, will
mouths the industry must shape UK farms’ and farmers’ futures.
feed. Technology played Leveraging these technologies effectively
its part in our enhanced will separate the winners and losers,
domestically and internationally.
ability to feed ourselves, but
deforestation and intensive This report, which leverages both in-person
and quantitative data from samples of UK
farming played more. farmers, technologists and industry experts
conducted by our research partner Illuminas
Now, as UN1 estimates of the increases
in Summer and Autumn 2020, explores the
required to meet global demand in 2050
challenges facing UK farmers at a pivotal
range up to 150% of current production,
time for the industry. It discusses the pace of
and the agricultural sector is challenged to
change in the sector; examines some of the
build a more sustainable industry for the
most exciting developments in agricultural
next century, it is axiomatic that technology
technology in the UK today and tomorrow;
must play a leading role in our efforts to
and seeks to identify routes through
build better. We must be resourceful, and
which UK Farming can achieve sustainable
resource-conscious, to prosper in the
competitive advantage through unlocking
challenging times that face the sector in
some of the benefits of these technologies.
2020 and beyond.
1
Creating a Sustainable Food Future Final Report, July 2019
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AI in UK AgriTech — 2021 and beyond
Foreword
“Agriculture has for centuries evolved and
moved forward, the rate of change in the
second half of the last century begin to pick
Agri-tech is becoming
up pace and in the last decade, that change big business in
has gathered an unstoppable momentum.
farming. We’re seeing
The change global agriculture will witness more and more farms
in the coming decade I believe will be breath- improving productivity
taking. The drive towards greater farming
efficiency to ensure UK agriculture maintains and efficiency with
its position at the forefront of global tech.”
production for traceability, welfare and
quality, also driven by the UK farming target Mark Suthern
for achieving Net Zero by 2040 will
see rapid and exciting times ahead.
National Head of
This report highlights some of the great Agriculture, Barclays UK
innovation, the direction of travel and how
Agri-tech is being employed in real farm
situations to reach our goals as an industry
in the coming years.”
Mark Suthern
National Head of Agriculture
Barclays UK
Roxanne Martin
Eagle Lab AgriTech Industry Lead
Barclays UK
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AI in UK AgriTech — 2021 and beyond
UK Agriculture
The importance of tech in securing
competitive advantage
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AI in UK AgriTech — 2021 and beyond
The eye of the storm
As UK Agriculture looks to The issues impacting UK Agriculture
build a more sustainable
model going forward, it How are we going
faces a range of headwinds to continue to be
– geopolitical, (macro) profitable? That is the Tech investment Post Brexit
economic, regulatory driver for everything trade deal
– that will shape the that we do … I think
fortunes of the industry farms will operate in
for a generation and more. a very different way
The industry’s ability to over the coming years.
2040 Net Zero UK Agri-Business in Coronavirus
respond to these seismic The challenges are 2020 and beyond
shifts will require innovative going to be forced
thinking, and innovation in upon us. We are going
business practices. to have to change.”
Ian Rudge
Bedfordia Farms Sustainable Provisions of the
Agriculture Ag Bill 2021
Productivity growth
Source: Illuminas Research (2020)
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AI in UK AgriTech — 2021 and beyond
The eye of the storm
Meeting these challenges will require UK Farming to shift
from ‘vicious’ to ‘virtuous’ cyclical behaviours.
The Future of the EU-UK Relationship
88%
of UK farmers believe uncertainty around the trade deal/CAP provision is impacting significantly on
In order to survive in a highly volatile market and deal with
their businesses
the variation in yields, weakening condition of resources
and increased crop resistance, farmers have historically Impact of COVID
tended to adopt or persist with farming practices which
have maximised yields in the short term, but which have led,
however inadvertently, to grave depletion of natural resources 47% of UK farmers believe their businesses have been negatively impacted by the ongoing pandemic
in the long term.
The UK Agricultural Bill
79%
However, the priority amongst UK farmers today is to use
available inputs more effectively and efficiently. This is part of believe increasing environmental oversight and regulation is impacting significantly on their farm
a broader shift towards a virtuous cycle of lower costs, more
sustainable land use and – ultimately – greater productivity Productivity challenges
and profitability.
64%
of UK farmers are prioritising improving productivity, increasing output and/or farming smarter
going forward
Sustainability
82% of UK farmers believe improving the sustainability of farming and restoring soil health is fundamental
Climate change and 2040 Net Zero
90%
of UK farmers believe climate change and the NFU’s revised Paris target is impacting significantly on
their farm
Innovation and new farming methods
45%
of UK farmers have invested (30%), or are planning to invest (15%), in emerging tech to fuel
process innovation
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AI in UK AgriTech — 2021 and beyond
UK Farming must adapt quickly, putting technology
at the heart of its response
“We believe here that
53%
of UK farmers are prioritising increasing productivity and/or output/yield
the only way we are
going to be able to
produce enough food
to feed the UK – as
Farmers’
58%
are prioritising achieving material cost efficiencies
well as the wider world
– is to use science
strategic priorities and technology.”
48%
are prioritising farming smarter and more efficiently
Tony Bambridge
B & C Farming
51%
are prioritising reducing wastage/environmental impact and/or soil health
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UK Farming must adapt quickly, putting technology
at the heart of its response
Improved productivity is fundamental to the UK Farmers are beginning to appreciate the
UK industry’s longer-term competitiveness, pivotal role of technology in farming smarter
indeed to its financial sustainability, with and more productively.
11% “Our focus is on
UK Farming’s productivity lagging that of wasting less and not
Investment in systems and solutions to
EU competitors by sometimes considerable
enable greater productivity has to date
growing too much.
margins. Technology-related issues are often
posited as some of the most fundamental has been relatively limited, with only 11% Reducing waste is
in creating and maintaining the UK’s having prioritised in the past. But two in five the main thing. It’s
competitive disadvantage. farms plan to invest to unlock the greater
efficiencies in their operations. 40% expensive and by
• Educational/skills gaps; being more efficient
UK farmers recognise the fundamental
• Limited intra-industry sharing of
importance of farming smarter to longer-
(with your inputs) you
best practice;
term sustainability, both environmentally are able to cut a lot of
• Lagging other countries in data
generation and analysis and
and commercially. With only 36% of UK
it out.”
land croppable and estimates suggesting
modelling capabilities;
that high-intensity farming techniques have Have invested in AgriTech to achieve
• Disconnects between innovation strategy depleted our arable land of c. 50% of its increases in productivity
Patrick Allpress
and funding and farmers needs; organic content, action is imperative. Allpress Farms
• Slow deployment of connectivity Will invest in AgriTech to achieve
(FTTP; 5G). increases in productivity
54%
of UK farmers that are prioritising improved productivity believe tech
investment is fundamental to addressing this challenge
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Tech-enabled smarter farming has the potential to unlock
the advantages UK Farming desperately needs
More efficient resource allocation is critical
to manage costs, improve productivity,
59%
reduce environmental impact and –
ultimately – farm smarter. The Circular
Agriculture model at the heart of the
revolution transforming farming in the of UK farmers that are prioritising farming smarter believe tech investment can be material in achieving those goals
Netherlands recognises that productivity
centred on improved resource efficiency
will result in increased productivity with
concomitant environmental benefits.
43%
of UK farmers that are prioritising farming smarter have invested in technologies to help them do so
Effective use of technology will be critical
to unlocking these benefits, and there
is recognition – albeit among only one-
half of UK Farmers – that tech can play
a central role in achieving efficiencies in
resource utilisation.
46%
of UK farmers that are prioritising farming smarter plan to invest in technologies to help them do so in the near future
52%
of UK farmers prioritising more efficient resource allocation believe tech investment is central to doing so
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Tech-enabled smarter farming has the potential to unlock
the advantages UK farming desperately needs
Circular agriculture urce optimisation One-third of farmers have claimed already
Reso to have made investments in technologies to
“We need to make our enable more efficient use of resources, with
farm sustainable for a further 40% planning to do so in 2021–23.
feed the next generation,
and the ones
after that.” 32%
Ian Rudge
Bedfordia Farmsg
produce
grow 40%
Evidence of the relationship between
technology and better and more sustainable
y
vit
Su
outcomes is irrefutable; and many UK
Have invested in AgriTech to enable
ti
st
uc
Farmers – although not all – appear to
smarter resource utilisation
a
od
ina
recycle recognize the importance of continuing
r
b
p
le
ed fa to invest, and to innovate. Technologists Will invest in AgriTech to enable
nc rm
ha ing looking to drive greater engagement within smarter resource utilisation
En the farming community must, it seems clear,
put sustainable impact on productivity at the
heart of their messages.
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There is an emerging core of tech-enabled UK farmers
that are building for the future
Leading the charge Planned investment in emerging agricultural technologies
Data from recent survey work shines a
light on a core group of UK farmers that
are looking to emerging AgriTech to build
more sustainable businesses and set the
foundations for commercial success; with
another 14% that are focusing instead on
embedding existing tech investment before
prioritising further investments. However,
55% have no plans to look to technology. Is
this group in danger of being left behind?
31%
of UK farmers plan to invest in new, emerging
14%
do not plan to invest in AgriTech but have
55%
have never invested in advanced AgriTech
technologies to ensure business success done so in the past to realise priorities and have no immediate plans to do so
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There is an emerging core of tech-enabled UK farmers
that are building for the future
Planned investment in emerging agricultural technologies
are more aggressive, more entrepreneurial are farms typically comfortable with the various “We need to make
farm businesses. applications of AI and emerging tech.
money, but we need
Often led by younger farmers, more comfortable These businesses are currently looking to embed to do it in the right
with technology and more likely to see tech as existing inventory/investments, and to realise ROI on way and in line with
offering a genuine competitive advantage if those, before committing to new investments.
leveraged effectively. legislation and public
sentiment. Whatever
technology can assist
AgriTech is part of Applegarth Farm’s DNA. A adherent of Central to the strategy of Bedfordia Farms is optimised
with that, we’re buying
vertical farming, 2021 will see the go-live of its 6,000 sq. ft productivity and resource management; and its tech strategy into it.”
aeroponic greenhouse programme, to add to the array of has been focused to that end. For 2021, it has prioritised
existing sensor and robotic technologies the farm deploys. its partnership with Agrimetrics to rationalise its array of Ian Rudge
different field, soil and yield mapping platforms to provide
Tech has enabled every phase of Applegarth’s growth to more coherent and consistent analysis rather than planning
Bedfordia Farms
date, and its commitment to ongoing investment is central to fresh investments.
its competitive strategy going forward.
Two businesses following different paths, but each in their own way leaders, illustrate
some of the opportunities that tech-oriented Agribusinesses are looking to unlock as
they align their businesses to compete in the next decade and beyond. The potential
of AI to be pivotal in doing so is only just beginning to be apparent.
Source: Illuminas Research (2020)
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UK AgriTech
How can we enable agriculture 4.0 in the UK?
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AI will transform UK agriculture forever
Farmers are only just beginning to recognise the transformative actions to take; or in the application and delivery of solutions at
potential of AI in its various applications, ranging across different source, AI is already changing the way farmers work. And yet we have
innovations in every component part of agricultural systems. Whether only begun to unlock its potential. Farms in future may as closely
in real time detection of developing issues; in rapid and accurate resemble open-air laboratories as they will the farms of today.
diagnosis of those issues; in determining the most appropriate
Detection Diagnosis Determination Delivery
UK AgriTech commands a set of baseline capabilities that is the challenges in bringing these technologies to life within a sector which
equal of any in the Netherlands, the US or other highly developed has been described as the least digitised in the world today. Is this
agricultural nations; and the Department of Trade has been active characterisation justified? And if so, what must be done to ensure UK
in promoting the nation’s Ag and AI, Robotics and Autonomous farmers are not left behind in the AI arms race?
Systems research as world-class. However, there remain many
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Advanced AI-enabled systems are beginning to make
their way out of the labs and into the fields
There is an increasingly broad
range of technologies becoming Detection Diagnosis Determination Delivery
available which offer the potential Using techniques Advanced data Harnessing the power Automated solutions
fundamentally to transform the such as image analytics, using of AI to determine the such as advanced
farms of today into the farms of processing, soil nutrient a range of inputs from on most appropriate solutions robotics, able to undertake
the future. monitoring and crop and and off-farm data resources, to complex problems and – in complex and precise tasks
animal health scanning to providing real-time diagnoses the future – allowing farmers that until now have required
There are however a range of detect problems often invisible of complex problems. to outsource decisions to tak manual intervention.
challenges in harnessing the to the naked eye. action.
power of AI in the agricultural Analytics solutions from The UK’s leading ag robotics
sector, some of which are, research Next-gen sensor tech from GlasData and Diometer Research at CHAP using ML firm, Small Robot Company,
confirms, impeding broader firms such as Arable are multi- offering seamless integration to build a thinking machine has developed a robot capable
adoption and preventing the functional and can seamlessly of data from different providers capable of recommending of plant-by-plant care and the
sector from accessing some of integrate with ML-enabled and platforms. optimal biological world’s first weeding bot.
the competitive advantages it so decision-making systems. treatments strategies.
Telemetric tools able to Ongoing development of
desperately needs. Drone Automation, in enable the location and John Innes Centre developing a Autonomous Agri Vehicles by
development at DroneAg, baseline problem diagnoses for low-cost solution for automated HandsFree Hectare Project in
will offer full automation of equipment and livestock. seed imaging and ML-based the UK and Bear Flag Robotics
collection, analysis, and remote phenotypic analysis of and others in the US.
transfer of data to farmers in crop germination.
The Ceres AgriTech venture
real time.
ML-driven neural networks from to improve outdoor robotic
Leading industrial Drone GlasData able to understand capabilities in terms of: speed
developer American Robotics is the interrelationships between of performance; accuracy and
bringing automated Drone and soil, climatic, biological reliability of image processing;
IoT Sensor platforms to market, and other inputs to provide haptics to enable soft-
offering full integration of aerial recommendations for harvesting capabilities; ability to
imaging data and in-field sensor yield optimization. perform in a range of conditions
biometrics. on-farm.
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AI-based tech has yet to achieve widespread adoption
AI-enabled AgriTech remains some way from seeing wide-scale Barriers remain profound, with cost (perceived or actual, depending on Without measures to protect
implementation on UK farms, as evidenced below. experience) the most significant factors. Data from Defra’s Farm Business farmers from very considerable
Income Survey indicates that, across sector, profitability declined between swings in costs, only a minority
Current adoption of AI-enabled AgriTech 8.5%-17%* to FYE2019, with YoY changes over the last 15 years ranging of highly profitable – or highly
from +40% to -36%. Farm profitability is more than usually subject to geared – farms are likely to
volatility, and reducing the sector’s exposure to swings in input costs and, continue to support investment in
where possible, to output yields, is a priority for industry lobbyists and emerging tech.
21% Sensors (EW) trade bodies.
Against this backdrop, many
Barriers to adoption of AI-enabled AgriTech farmers consider themselves
16% Sensors (Crop health) as simply incapable of making
the very significant investments
Capex costs too high 56%
required to unlock the benefits
9% Drones of AI; many others – including
Total costs too high 49% 36% of adopters in our survey
– are uncertain as to whether
9% Data analytics Maintenance costs
35%
that investment can, or will
high/uncertain be, recouped. The onus is on
technologists and providers to
RoI is uncertain 35%
4% Field robots (Collection) bring the benefits to life and
to ensure that propositions are
available that meet the needs and
Doubts over material benefits 31%
the budgets of UK farmers.
0% Field robots (Monitoring)
Tech is unfit for purpose in
26%
current form
8% Autonomous sprayers Prefer to rely on own
17%
judgement/intuition
0% Autonomous vehicles Negative feedback from peers 14%
Source: Illuminas Research (2020) Source: Illuminas Research (2020) Previous | 19 | Next pageAI in UK AgriTech — 2021 and beyond
The benefits of AI-enabled tech are considerable, but There are a range of issues around
which all parties need to converge
to ensure that the benefits of
the barriers are – for many farmers – no less profound Ai-enabled AgriTech can be
fully realised.
Detection Diagnosis Determination Delivery
• Precision Agriculture (enabling resource • Greater oversight of farming activity and • Widest possible set of inputs • Automation of time and labour-intensive
and cost efficiencies and gains in yield status of fields, crops, etc. • Ability to understand and identify farming tasks
/ output) • Digitisation of inputs, outputs, and/ complex causal relationships • ‘Always on’ source of labour
Benefits
• ‘Always on’ crop, plant, soil and/or animal or financials • Replaces intuition with evidence- • Increased productivity, efficiency
health monitoring capability • Evidence-based, rather than intuition- based solutions and output
• Greater, and more efficient, based, decision-making • Integrating problem identification to • Frees up time to concentrate on business
farm coverage solutions implementation management/strategy
• Greater availability of ‘all in one’ • Availability of platforms able to automate In development In development
solutions comprising predictive data collection irrespective of device • Potential ‘accelerators’ include • Potential ‘accelerators’ include:
capabilities (Sensors) type/app/provider
– Consolidation of disparate – Greater investment in R&D to enable
• Launch of fully automated systems • Simple, smart and easy platform UX data sources the development of tools able to
Enablers
and legislation enabling their • Analytical tools which can identify the deploy outside of lab conditions
– Agreement of industry benchmarks
adoption (Drones) impact of farming activity on output/
– Cross-team working groups (end- – Cross-team working groups to
• Detection capabilities superior to the yield, resource usage and profitability develop fit for purpose soft harvesting
users; technologists; institutions) to
naked eye executions
direct innovation to most directly
applicable areas – Greater availability of ‘Farming as a
Service’ propositions
• Lack of ‘all in one’ solutions able to • Limited platform interconnectivity/cross- • Insufficient data inputs (range of • Insufficient data
predict issues compatibility variables/quality of data/time series • No commonly agreed data taxonomy/
• Incompatibility with existing on-site • Limited integration with existing on- datasets) benchmarks
data platforms farm tech • No commonly agreed data taxonomy • Outputs based on ‘partial picture’ data
Barriers
• Time/labour required to manage (Drones) • Poor platform UX / benchmarks lack face validity
• Human ability to detect issues by • Face validity of data • Outputs based on ‘partial picture’ data
‘walking the fields’ and solutions require lack face validity
• Outputs describe the ’state of play’ rather
human intervention than inform ‘direction of travel’
• Requires farmers to be ‘in the office’
rather than out on farm
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Use of sensors and drone tech for problem detection
is growing, but challenges remain
The benefits of sensor and drone
technologies are increasingly widely
recognised but adoption remains relatively
narrow at present, and there are tech and
commercial challenges to overcome to
broaden adoption of technologies which are
key enablers of Precision Agriculture.
Although the benefits can be significant,
with faster detection of emerging issues
and greater precision in solutions offering
often significant delta improvements in
Awareness 75% 77%
resource utilisation, many farmers remain
unconvinced that the tech is fit for purpose,
or that it can in fact provide time, labour or
Currently use,
65% 57%
cost savings.
or would consider
Currently use 27% 9%
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Use of sensors and drone tech for problem detection “Thanks to the Yara
is growing, but challenges remain N-Sensor we are seeing
areas of the field which are
struggling and need input,
so with a better sprayer
we’re making better use
Benefits Always on Precision Process efficiencies Smarter farming
of the product having
• Detection tech • Detect issues (pests, • Greater, and more • Generates time
generates data which disease, poor growth, efficient, coverage of series plots which made the decision to use it
enables users to etc.) and to deploy any given farm’s land enable farmers to based on the data.”
remotely monitor the solutions (fertilisers, area than ‘walking understand impact
health of crops/plants, herbicides, etc.) the fields’ of farming activity JJ Ibbett
soils and/or animals precisely on growth rates and
in real-time and Bedfordia Farms
• Reductions in resource identify activities
24/7/365 usage and waste, cost with greatest positive
efficiencies, and gains impact on yield (e.g.
in yield/output varietals; rotations;
treatments; etc.)
Barriers Deployment costs Return on investment Lack of predictive
capability
Technical issues
• Complexity/diversity • Little evidence exists • Require human
of farm businesses of the link between • The value-add of operation and training “We got a Drone and to a
require multitude of investment and insights derived is degree it helped but you
• Limited battery life and
sensors (limited multi- material gains in limited to confirmation risk of motor failure still have to interpret the
function availability) output/yield; and of issues – which pictures. Our agronomist
• Legislative implications
• Sophisticated drones that which does is not farmers can detect by
of drones unclear looked at the problematic
(multi-spectral/ compelling ‘walking the fields’ –
rather than revelation • Time/labour intensive ones and said ‘I’ll go and
thermal imaging;
of future ones to operate have a look’. He may as
thermal and/or hyper-
spectral sensors; well have done that in the
image processing first place!”
capabilities) can cost
tens of thousands Tony Bambridge
of pounds
B & C Farming
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There are a range of different solutions that can There are a range of issues to address
which, if addressed, can be potentially
transformative in driving broader and
enable greater deployment of detection tech deeper adoption.
Challenges Solutions Benefits Impact on uptake
Core • Multifunction detection devices, such as integrated • More consistent UX across different functions • Potentially considerable if
functionality crop/plant and soil health sensors and drones • Simplified procurement process pricing model and tariffs are
• ‘All in one’ devices able to monitor crop/plant growth, sufficiently compelling
• Time/labour efficiency (obviates the need for farmers to ‘walk
soil moisture, pests and disease, etc. the fields’)
• Sensitivity of detection beyond the human eye/farmer’s • Ability to operate in rural areas with low broadband speeds
own experience
• Automated production of comprehensive data sets which are
• Telemetric functionality for auto measurement and easy-to-use and manage
transmission of data between device platforms.
Device inter- • Devices which use standardised data architecture and • Automated data entry into a centralised platform • Potentially value-additive
operability taxonomy • Integrated data analysis provided platform UX engages
• Develop an ‘open source’ culture to enable technologists • Time/labour efficiency (avoids manual entry/management of
to add value and disrupt the monopolisation of larger multi platforms)
firms’ propriety software
Platform • Platform able to predict issues based on the health • Optimisation of resource utilisation • Potentially game-changing if
integration profile of any given crop/plant, soil and/or animal • Reduction in waste insights can be validated
• Ability to diagnose underlying causes of issues • Increased yield/output
• Ability to recommend potential actions to address issues • Improved profitability
Cost • Multifunction detection devices (as above) to reduce • Increased cost-efficiency • Potentially considerable if
cost per function • Reduced inventory pricing model and associated
tariffs are sufficiently affordable
Skills/ • Drones capable of autonomous/driverless operation • Obviates the need for farmers to acquire skills in Drone operation • Potentially value-additive
educational gaps (including automation) • Time/labour efficiencies (obviates the need for farmers to ‘walk
• Provision of clear and up-to-date legal/regulatory the fields’)
guidelines on their use (Drones) • Clarifies legal/regulatory implications of their implementation
Cross-industry collaboration will be essential in addressing these challenges. Barclays aims to promote cross-industry collaboration with the launch of the Eagle Lab Farm in University of Lincoln, helping to build an established ecosystem of
AgriTech businesses dedicated to working with like- minded partners, and thereby creating a more sustainable farming industry for generations to come.
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There are a number of challenges to address
before farmers adopt a ‘data-first’ approach
There is at present no fully AI-enabled
analytics platform live in the UK, and what
minimal adoption of data solutions is evident
at present is limited to relatively simpler,
piecemeal solutions.
There are a number of potentially compelling
benefits to more effective AI-based data
tools, but feedback from experts and
technologists would suggest the industry is
some way from being capable of delivering
fully operational solutions.
Awareness 57%
Currently use,
or would consider 53%
Currently use 9%
Previous | 24 | Next pageAI in UK AgriTech — 2021 and beyond
There are a number of challenges to address
before farmers adopt a ‘data-first’ approach
“John Deere’s platform
(JD Link) has enabled us
to make more informed
Benefits Digitisation of core farming Enhanced monitoring and
tracking capabilities
Evidence-based
decision making decisions about how to
• Enable farms to have a
digital record of inputs, • Data analytic and • Ability to make decisions cultivate a field based on
outputs and financials visualization tools enable based on ‘hard’ data the data on it, rather than
• Enables farm managers the farm to understand rather than solely farmers’ just based on a 5-minute
to better monitor and the status of their fields, own experience/intuition kick-around.”
manage core operations crops/plants, soils, and/ (e.g. when/where and
or animals what treatments; when/
• Integration with JJ Ibbett
• Enables historical/point in where to plough, sow and
procurement and Bedfordia Farms
time comparisons harvest; fields, areas and/
auditing processes
or animals to keep in/take
out of production; etc.)
Barriers Lack of commercially
available solutions
Limited value-add Poor user experiences Cultural
• Very limited evidence • No availability of unified • Farmers are neither
• No ML-driven insight and of the impact of data platform architectures agronomists nor
decision-recommendation on decision-making at able to work with multiple data scientists “What we need is to see
platform is yet present, with manifold data inputs from different • Difficult to meld data and the data brought together,
(widely) available frustrations over volume devices, data sources, etc. intuition or experience and any gaps filled, to
of data collected vs. value • Amount of data to analyse • Significant upskilling enable us to identify
of data generated (“data overload”) across the industry the decisions that are
• Validity of data, data is required increasing – or decreasing
errors, gaps, etc.
– the yield potential.”
JJ Ibbett
Bedfordia Farms
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There are a number of potential solutions to drive The industry needs to move much more
quickly to agree standards for data integration
before material progress may be made.
greater engagement with data solutions
Challenges Solutions Benefits Impact on uptake
Core • Smart tools to enable farm managers to generate • Provision of directional outputs, with visibility of the • Potentially game-changing if data
functionality simple, visually engaging, charts and which enable the rationale for direction(s) proposed driven decisions lead to material gains
cross analysis of inputs, outputs and/or financials • Measurable impact of changes to farming practices on in productivity and profitability
• Ability to automate the categorisation of data sets and productivity and – ultimately – profitability • A simple and light touch approach
to select/filter analyses • Avoid ‘data overload’ to diagnostic and predictive analysis
• Algorithms to be based on agreed that complements farmers’ existing
• To establish norms in crop/livestock health and
benchmarks parameters experience and intuition
development, etc.
• Ability to target variables known to be deterministic • Build more robust algorithms and produce more
• Integration with ‘big data’ (national, regional and farm- consistent outputs through cross-industry partnerships
based datasets)
Device inter- • Devices based upon a single standardised data • Datasets with sufficient depth and breadth of data points • Potentially value-additive provided
operability architecture and taxonomy to be additive platform UX engages
• Automation of data entry into a centralised platform
• Time/labour efficiency
• Reduced errors
Platform • Centralised platform able to integrate inputs from • Ability for data outputs to be fed back to devices to enable • Potentially transformative in terms of
integration different providers autonomation of activity accuracy, transparency and efficiency
• Smart platforms able to automate all data input and • Data at the core of analysis and implementation, ensuring of process
gap-fill based on norms trackability across processes
Cost • Centralised platform (single cost) • Single licensing cost • Potentially transformative assuming
• Direct incentivisation of data sharing user experience is positive
(Agrimetrics model)
Skills/ • Cost-effective remote education training programmes • Upskilling UK Agriculture in tech best practice, increasing • Fundamental to break down barriers
educational gaps • Case studies/testimonials awareness and familiarity with solutions
The adoption of a unified data taxonomy, architecture and language are fundamental to unlocking the potential in data to revolutionise UK Farming. Barclays believe that only by working together towards a unified language can the industry
maximise the potential from data applications in future.
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Automation may be potentially game-changing
but technology is insufficiently developed
Automation is capable of unlocking
potentially significant advantages as UK
Agriculture looks to compete internationally
while facing labour shortages at home.
It is likely to be 2023 and beyond before the
beneficial impact of greater automation
is felt, absent regulatory reform and
significantly expedited development cycles.
There are currently many barriers to address.
Awareness 76% 58%
Currently use,
or would consider 44% 39%
Currently use 5% 0%
Previous | 27 | Next pageAI in UK AgriTech — 2021 and beyond
Automation may be potentially game-changing “Before the robots each
but technology is insufficiently developed cow averaged 9k litres per
year. Now, with the robots,
we’re getting 10.7k litres
per cow, per year. We’ve
Benefits Automation Productivity gains Greater flexibility Always-on labour increased our yield almost
20% with the same
• Labour savings offer • Process automation • Relieving farmers from • With the industry
number of cows, feed,
the potential to be driving increased time/labour intensive facing potentially very
and acreage.”
transformational output/yield (in tasks, and thereby significant labour
principle or in providing greater shortages post Brexit,
Will Griffiths
practice), for example flexibility in task robots provide a
Blaencorse Farm
robotic milking management 24/7/365 alternative
machines enabling • Allows farmers to to domestic or
cows to be milked move from ‘working overseas workers
more frequently, in’ their businesses
increasing output to ‘working on’ their
and providing businesses “Today’s robots can only
demonstrable ROI
deal with controlled
environments such as
Barriers Deployment costs Operability Cultural Legal glasshouses where the
payback is over ten years.
• Capital expenditure is • Robotics very often • Shift away from the • Autonomous vehicles
They’re going to cost
often considerable for optimised for vertical farm as a centre of are currently illegal
you, what, £20k pa? I
larger solutions (e.g. farming environments local employment and in the UK and the
don’t know. Against a
Robotic Milkers) and but incapable of community ongoing consultation,
person it’s not worth it at
beyond many farmers’ operating in rough • Significant assuming min. six
the moment.”
available tech budgets terrain or adverse training/upskilling months’ delays
• Cost of Field Robots is climatic conditions requirements for COVID, is
Patrick Allpress
often net-neutral vs. • Very often incapable unlikely to publish
Allpress Farms
human labour, with of performing tasks recommendations
productivity gains with the accuracy or before 2022
often marginal delicacy of human
sight and touch
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IoT can power fundamental changes There are considerable gaps in operational capabilities of technologies
currently available. For those businesses starting afresh with vertical farming
environments, the benefits are more immediately attainable. But for the
to working practices if optimised majority of mature businesses, the technology is at present not fit for purpose.
Challenges Solutions Benefits Impact on uptake
Core functionality • Robots able to reliably conduct crop/plant and soil care and/or • Solving for the sector’s productivity issues • Potentially revolutionary
harvesting tasks • Offsetting labour shortages exacerbated by Brexit but is more likely to
• Robots able to operate/adapt to different terrains and and COVID be evolutionary
weather conditions • Ability to operate in rural areas with low
• Integrated vehicle fleets for automated tasks (e.g. harvesting) broadband speeds
• Telemetric functionality for automatic measurement and • Automated production of comprehensive data
transmission of data sets which are easy-to-use and manage
• Ability for devices to interact/train one another (device-to-device • Optimisation of machine capabilities
learning)
Device inter- • Single operating ‘language’ to allow intra-device communication in • Seamless integration with data analytics and • Potentially value-
operability real time other devices additive assuming can be
• Time/labour efficiency (avoids management of delivered SIMPLY
multiple platforms)
Platform • Integration of data outputs and agents, enabling automated • Increased yield/output • Potentially game-changing
integration diagnosis and delivery of solution with minimal or no manual • Improved profitability
intervention
Cost • Provision of robotics in agriculture as a service • Reduced capex/opex requirements • Potentially value-additive
• Ability to ‘bolt on’ robotics onto existing machinery/equipment
Skills/ • Basic robot maintenance • Reduced maintenance costs • Potentially value-additive
educational gaps • Provision of clear and up-to-date legal/regulatory guidelines on • Clarity regarding legal responsibility
their use
It is critical that to take meaningful steps forward in productivity and competitiveness, UK farming has access to the right tech and tools. Barclays wants to be able to support the farming industry through the de-mystification of tech by ensuring
that technology is solving everyday problems the industry faces, starting with the problems and working backwards towards the solutions.
Previous | 29 | Next pageAI in UK AgriTech — 2021 and beyond
UK AgriTech
Trailblazers
Previous | 30 | Next pageAI in UK AgriTech — 2021 and beyond
One of the UK’s leading Agri-tech
drone solutions providers
Background What Value Is Drone Ag Adding?
“We’ve learned a lot over the last five
DroneAg is a firm of farmers, agronomists and drone techs building The core principles of the app, which mirror those of Drone Ag more years. We assumed when we began
drone-enabled solutions from its base on a 6000-acre farm in generally, might almost serve as a ‘ready reckoner’ of the principles to that a farmer wouldn’t be bothered
Northumberland. The firm was formed in 2015 when its founder Jack which technologists should subscribe: by a price point of £25k for a Drone
Wrangham, from a farming background, wanted to apply his skills System because he spends £80k
• Simple to implement • Affordable
and experience from his time managing an aerial media company on a Tractor. But we learnt that’s
• Simple to use • Help get the most from existing tech
utilising drone tech, to the challenge of unlocking the benefits of not how it works. A farmer doesn’t
drone technology for UK farmers. • Fully automated • Integrated with other data sources know what to do with a drone, but
• Proven to identify problems he knows exactly what to do with
What Challenges Is Drone Ag Addressing? a tractor.”
The app recently won gold at the LAMMA 2020 Innovation Awards
The company began life by manufacturing custom-made Drone (which recognise and give exposure to some of the best advances in Jack Wrangham
Systems but soon thereafter pivoted to design and implementation agricultural manufacturing). Founder, Drone Ag
– including training provision – for agricultural drones, after realising
DroneAg is the UK’s only pure play provider of Drones for the
how often farmers that had made initial investments in drone tech
Agricultural sector and one of the few technology providers whose
subsequently allowed them to go largely unused, often because of
core personnel are all steeped in agriculture from birth, giving them
training needs or under-appreciation of the benefits.
baseline knowledge that they augment by staying close to their target
The insight gained from interactions from farmers, and the client groups, via Trade events, at one of their training courses, or
frustrations they expressed with expensive tech from they were on-farm itself.
unable to extract (sufficient) value, inspired ‘Skippy Scout’, an AI-
The firm’s mantra of ‘Do More In Less Time’ empowers its core
enabled mobile app able to deploy almost any existing Drone on-farm
client groups – smaller, younger, resource challenged businesses –
into an easy to use, automated agricultural detection tool.
with tools that would otherwise be beyond their budgets and their
experience to access. The propositions are fully integrated with
existing processes and provide farmers the insights to make the right
decisions quickly.
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The UK’s Agri-Food data marketplace
Who are they? Some of the key areas Agrimetrics are targeting include: • AI and linked-data technologies pre-linking and
harmonising data from multiple sources, saving man
Agrimetrics is one of four centres for agricultural innovation • Crop Analytics – algo-enabled predictive analytics weeks or months in data transformation.
seeded by Innovate UK, drawing on the expertise of providing estimates of yield, risk and supply chain
founding partners NIAB, SRUC, Rothamsted Research forecasting; and tools for crop health management, such Agrimetrics strives to ensure that their data simplifies,
and The University of Reading. A graduate of Microsoft’s as optimising water usage and preventing crop lodging. rather than complicates, the decisions agribusinesses
prestigious ‘AI for Earth’ accelerator, its goal is to help make, providing only the most relevant data in the simplest
• Harvest Forecasting: AI-driven predictive modelling that possible way to demystify the often very complex world of
build more productive and sustainable food systems by
can predict the optimal window for harvesting of time AI‑enabled analytics.
improving access to food, farming, and environmental data
sensitive perishable crops.
– and by making it easier and more affordable for agrifood
Looking forward, Agrimetrics is focused on removing
organisations to derive insights and ultimately commercial
• Sustainability analytics, such as natural capital barriers – whether privacy or compensation-related – to
value from that data.
accounting, bringing data views together not simply to ensure data owners and users all benefit from this new data
enable regulatory compliance but to help data-hungry ecosystem and to enable the data-driven knowledge sharing
Collaboration is the cornerstone of the Agrimetric
organisations manage resources more cost-effectively that Agrimetrics believe is key to securing a profitable future
philosophy, and of its open architecture aggregation
and identify potential competitive advantages. for UK farming.
proposition, The Agri-Food Data Marketplace, which allows
agrifood organisations and reseachers to access relevant
In short, Agrimetrics is enabling organsiations to move
ancillary data points to enrich analyses; to share data
towards what it firmly believes is the future of farming – a
securely; and to monetise that data.
sector powered by data, an information business.
“Don’t tell a farmer ‘you need to
What Challenges Is Agrimetrics What Value Is Agrimetrics Adding?
adopt AI’. Ask them what challenges
their business faces, and is there a
Addressing? tool that can help? AI is just one tool
The Agrimetrics platform, Data Marketplace, is something
in the box.”
Poor access to data, or lack of expertise or budget to unlock entirely new in UK agriculture, and promises to break down
its value, are major barriers to innovation in the agricultural some of the most fundamental barriers to deeper integration Professor Richard Tiffin
sector, Agrimetrics’s Marketplace and underlying linked-data of data into agrifood processes: Chief Scientific Officer
technologies are enabling solutions providers to address
these challenges and thereby to drive efficiencies and • Open architecture allowing users access to breadth and
improve performance and sustainability across the whole depth of data in one place, easily searchable, through
food chain. one simple interface.
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The Small Robot Company: The UK’s leading
agricultural robotics firm
Background All managed through a simple user interface that visualises
the challenges for farmers and allows them to be in control
Small Robot Company (SRC) aims to revolutionise UK farming of the solutions without requiring significant upskilling in
analytics or bioscience. An Integrated
to make food production sustainable. Inspired by work of
Network of
Simon Blackmore in the National Centre for Precision Farming
Autonomous Robots
at Harper Adams and his vision a new way of farming, What Challenges Is SRC Addressing? controlled by a
founders Ben and Sam were inspired to begin work on
centralised AI-enabled
Farming as a Service, embodied in and powered by AI and FaaS is helping farmers in:
Platform
cutting-edge robotics technologies.
• Reducing the environmental cost of farming through
Aware of the often sceptical attitudes with respect to new more efficient use of inputs, whilst – at the same time -
technology, and the pain those on the ‘bleeding edge’ maximising outputs.
often experience, nevertheless consultation with farmers Tom lives on the farm
highlighted opportunities for early stage tech adoption • Reducing costs, including inventory and maintenance
trundling about, constantly
if it could be derisked financially and operationally. That overheads, offering technology with few of its inherent
checking the crop
opportunity is made real in SRC’s ‘Farming-as-a-Service’ commercial risks.
(FaaS) model.
FaaS is putting Precision Agriculture at farmers’ fingertips, Wilma lives in Tom’s
allowing them to pay for outputs rather than inputs, and kennel and turns Tom’s
What Challenges Is SRC Addressing? although in its infancy in deployment, services such as info into instructions
automated weed identification, early (non-chemical) for Dick and Harry
Fundamentally to challenge existing – longer-tern
intervention and weeding are proving extremely popular
unsustainable – norms of farming, putting AI at the heart of
with those farmerssolutions. These conversations remain an
an integrated scanning, processing and execution loop that
ongoing workstream within the business, rather than a ‘one- Harry is called out to Dick is called out to
monitors crops, solves problems and implements solutions.
off’ at the point of product design. plant the crop with feed the crop, zap
Small thinking machines replacing large dumb technology.
Putting the emphasis on accuracy rather than vspeed. no ploughing, and the weeds and spray
record the location of the nasties
every plant
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