INDEX

1. 本調査の背景と目的

2. 対象とするスマート農機について（調査のスコープ）
3. ヨーロッパ諸国、イスラエルのスマート農機の開発情勢
4. ハイブリッドカー等のリユースバッテリーを活用したスマート農機の受容性
5. スマート農機の普及戦略
6. 関係事業者の反応と今後の課題

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16

3. ヨーロッパ諸国、イスラエルのスマート農機の開発情勢 ー まとめ

世界的にスマート農機の開発は活発化してきており、諸外国の政府は主として研究開発を資金面で支援することにより流れを加速化させている

行政

現状

今後のトレンド（想定）⚫ 諸外国におけるスマート農機の普及促進に資する政策
は、農機メーカーの研究開発に対する資金支援が中心⚫ 普及促進のための施策の中心は、今後も当面は農機の研究開発への支援

イタリア (EU) ：農業向けの研究開発支援プログラムが機能
イスラエル：先端技術開発向けの基金より補助金を拠出

規制・補助

×

農機
メーカー

農
機

代
金

農業者

⚫ 農業者に対してスマート農機の導入を促すような直接的な施策（自動車で言うエコカー減税/補助金や排出ガス規制等）は実施されていない⚫ 一部海外で進む自動車の販売・利用に係る規制強化の動きが、農業分野に波及する可能性はある⚫ 諸外国において研究開発の盛んなスマート農機は、収穫作業の支援ロボット等であり、特にセンサー、アルゴ
リズム、マニュピレータ関連への注力が目立つ⚫ 主要な研究開発分野は、
今後も収穫作業の支援に主眼を置いた支援ロボット⚫ 果樹分野での研究開発主体は、多くが中小事業者⚫ ビジネスモデルについては、
サービス型を前提としつつ、
各種スマート農機の特性に合わせて、さらに多様化する可能性がある⚫ 海外における農機関連のビジネスモデルは、売り切り型（製品自体を売る）のではなく、サービス型（製品が生み出す付加価値を売る）が主流になりつつある

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17

スマート農機に関する政策

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18

3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標（EU：戦略目標）

EUにおける農業からのメタンやN2O等のGHG排出量は全体の10%を占める
削減のための戦略方向性も提示されているが、全体に占める石化燃料由来のCO2のシェアは少ないため、化学肥料の削減やその他領域によりフォーカスがあてられている
EU Agricultural GHG Emissions
1%

Industrial
processes

10%

Manuremanagement(CH4, N2O)

24%

Soil management (N2O)

Transport
Fuelcombustion

38%

26%
45%
29%
EU GHG
Emissions(2017)

Enteric
fermentation(CH4)

Agricultural
GHG
Emissions

Note: Fuel combustion excludes energy industries and transport.
Transport includes road, rail, water (domestic) and air (domestic
and international).
Source: European Commission

Carbon sinks

Energyindustries

15%

Others

Efficient production

Wastemanagement

3%
9%Agriculture

Agricultural Sector GHG Reduction Strategies
Reduce directemissions (CH4,N2O)

Reduce emissions fromlivestock and fertilisers via
appropriate farming practices

Reduce fossil fuelintensity

Reduce energy andagrochemical inputs inagricultural production

Reduce agricultural
production losses
and waste

Efficient production will
reduce GHG emissions

Provide carbon sinks“Capture” carbon organicallyin soil

Sustainableproduction of
biomass

Production of biomass for
replacing fossil carbon (e.g.
fuels, plastics, etc.)

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19

3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標（EU：戦略目標）「Green Deal」では、電力・輸送・建物業界からのCO2削減貢献が大きいと予想されている
農業関連では、Clean Energy 領域として、農業廃棄物の再利用が主要トピック◼ 欧州の「Green Deal」は、 「2050年気候中立目標（温室効果ガスの実質排出ゼロ）」を達成しつつ経済成長も実現する。

Green Deal Overview (1/3)
戦略概要

対応する産業

リサイクル・環境汚染との関連

Clean Energy• Prioritise energy efficiency and • Powerdevelop a power sector based• Industry
largely on renewable sources• Agriculture• Secure and affordable EUenergy supply• Fully integrated, interconnected
and digitalised EU energy
market• Create a more circular energy system by• Encouraging the reuse of waste heat from industrial sites
and data centres• Incentivising the use of agriculture residues to produce
sustainable biogas and biofuels•
Enable carbon capture, storage and use

Sustainable
Mobility• 90% reduction in greenhousegas emissions in transport* by
2050• Transport

•
•
•
•
•
•

Building andRenovating• Better energy performance ofbuildings• Construction• Design of buildings should be in line with the circular
economyEnding subsidies for fossil-fuels
Extending emissions trading to the maritime sector
Boost supply of sustainable alternative transport fuels
Stricter standards on car pollution
Reduce pollution in EU ports
Improve air quality near airports*Transport in Europe refers to road, rail, water and air. There is no CO2 policy that specifically targets agricultural machinery.

Source: European Commission

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3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標（EU：戦略目標）

持続可能な産業構築の中で、３Rの方針が掲げられている
それらの大方針にもとづき、EVバッテリーは重量ベースでの5割をリサイクルを目指すとしている
Green Deal Overview (2/3)
戦略概要

対応する産業

Sustainable
Industry• New industrial policy based on • Energythe circular economy
intensive• Industries must be helped toindustries suchmodernise and exploit
as steel andopportunities domesticallycementand globally.
• Resource• Stimulate the development
intense sectorsof new markets for climate
such as textiles,
neutral and circular products.
construction,
electronics,
plastics

リサイクル・環境汚染との関連• The decarbonisation and modernisation of energy-intensive
industries such as steel and cement.
• ‘Sustainable products’ policy that prioritises reducing andreusing materials before recycling them.
• All packaging in the EU is reusable or recyclable by 2030
• ‘Take-back’ schemes which will incentivise people to bringback their electronic devices for recycling.
• Digital sector for monitoring of air and water pollution as well
as how energy and natural resources are consumed

Battery Recycling in the EU
Batteries Directive

Strategic Action Plan on Batteries• EV batteries should not be disposed in landfill sites or byincineration.
• EV batteries should achieve a minimum recycling efficiency of
50% by mass.
• Extended Producer Responsibility: OEMs are responsible for
ensuring that battery is recycled (actual process can beoutsourced to third parties).

• Secure access to secondary raw materials through recycling
batteries• Promote sustainable battery value chain in a circular economy
context.
• Conduct further R&D on battery recycling• Analyse how to promote the second use of advanced batteries

Source: European Commission

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3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標（EU：戦略目標）

その他農業に関連する戦略方針では、環境汚染を最小化に焦点があてられている
Green Deal Overview (3/3)
戦略概要

Farm to Fork

• Access to healthy, affordable• Agriculture
and sustainable food• Tackle climate change• Protect the environment andpreserve biodiversity• Fair economic return in the foodchain
• Increase organic farming• Circular bio-based economy (e.g. biogas from agriculture
waste and residues)• Reduce the use and risk of chemical pesticides by 50% by
2030• Reduce fertiliser use by at least 20% by 2030

Biodiversity• Establish protected areas for atleast 30% of land and sea in
Europe• Restore degraded ecosystems
at land and sea across Europe• Agriculture• Forestry• Increasing organic farming and biodiversity-rich landscapefeatures on agricultural land
• Reducing the use and risk of pesticides by 50% by 2030

Eliminating
Pollution• Zero-pollution action plan toprevent pollution of air, waterand soil••••

Source: European Commission

対応する産業

Agriculture
Manufacturing
Heavy industry
Chemicals

リサイクル・環境汚染との関連• Prevent pollution of air, water and soil
• Reduce pollution from excess nutrients• Reduce particularly harmful pollution from micro-plastics andpharmaceuticals• Reduce pollution from large industrial installation• Improve prevention of industrial accidents• Develop more sustainable alternatives to dangerous
chemicals

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22

3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標（イタリア：戦略目標）

イタリアの農業研究戦略では、スマート農機の研究開発は主に労働力や農薬等の農業投入の最小化を目指している

Strategic Plan for Innovation and Research in the Agricultural, Food and Forestry Sector (2014-2020)
Strategic Areas for Research and Innovation

スマート農機開発事項

1. Sustainable increase in productivity, profitability
and resource efficiency in agro-ecosystems

Precision spraying of agropharmaceuticals

2. Climate change, biodiversity, soil functionality andother ecological and social services of agriculture

ICT systems that can optimise machine operations andreduce energy inputs

3. Coordination and integration of supply chain
processes and strengthening of the role of agriculture

Mechanisation/automation of pruning, thinning,
harvesting

4. Quality, typicality and safety of food and healthy
lifestyles

Organic farming machines (e.g. for sowing, mechanicalweeding, harvesting, monitoring, etc.)

5. Sustainable use of biological resources for energy
and industrial purposes

Precision irrigation – crop water sensors and irrigation
robots

6. Development and reorganisation of the knowledge
system for the agricultural, food and forestry sectors

Engines and agricultural machines that can use innovative
biofuels of various kinds

Source: MiPAAF

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3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標（イタリア：研究開発支援）

イタリアでは、「Rural Development Programme」の中に、「Operational Groups」が存在しており、農業関連の研究開発支援の補助金を拠出している◼ 国（例：National Research Programme）と地域（例：各大学の研究補助金）レベルの研究補助金が存在する。
◼ 「Rural Development Programme」は国と地域レベルでスマート農機を含めて多数のの農業研究開発プロジェクトを支援する。
Operational Groups概要
Name

Operational Groups (funded by the Rural Development Programme)

BudgetEUR 112 million across 352 projects, as of 2020

Project size

Average ~EUR 300,000

Focus

Innovation projects tackling specific issues and opportunities according to the needs of the agricultural andforestry sector. Innovations must be more ago resource efficient, productive, low emission, climate-friendly, andresilient and operate in harmony with the essential natural resources on which farming depends.

TargetMinimum of 2 entities, such as farmers, research institutions, businesses, consultants, etc.

Source: EIP AGRI

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24

3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標（イタリア：研究開発支援）（参考） 「Operational Group」にて選定、支援が行われたプロジェクト◼ イタリアのスマート農機開発は主に収量・品質の向上を目指している。対象作物は値段が高いオリーブとブドウである。
スマート農機 Operational Groups
Topic

Description

Targetcrop

Timeframe

BudgetObjective

Operating group for the
diffusion of autonomous
robots connected to DSS
for the sustainable andefficient management of
the vineyard (ROVITIS 4.0)

Rovitis 4.0 aims to demonstrate the feasibility of robotic
vineyard management through a system of robots, sensors
and software in order to minimise human labour. The projectwill field test 2 robot prototypes that will carry out treatments,
processing, mowing and data collection.

Vineyards

20182020

EUR 587
thousandLabourreduction,
pesticide
reduction,yield
improvement

Increased olive
productivity throughartificial pollination(OLIMPOLLIMONTAGNANI)

The project will compare 2 pollination methods – manualpollination by farmers and via programmed drones with flightroutes calibrated for each plant. If drone dispersion is effective,
it can be provided as a paid service to farmers in the future.

Olives20192021

EUR 363
thousandYield
improvement

Digital Viticulture in
Tuscany (DigiViT)This project will develop a drone prototype to collect ultra-highresolution images, which will be analysed by an operational
tool that can forecast yields and quality.

Vineyards

20192022

EUR 220
thousandYield
improvement

Precision agriculture:
reduction of theenvironmental impacts ofproduction systems

This project will develop a drone spraying system to combat
plant diseases. The drone will also be used to check the stateof the plant and perform precision fertilisation operations. The
field test will be carried out on olive trees.

Olives20192021

EUR 385
thousandYield
improvement,
pesticide/fertiliser
reduction

Source: EIP AGRI

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3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標（イタリア：研究開発支援）（参考） 「Operational Group」にて選定、支援が行われたプロジェクト
Name

Rovitis 4.0

Name

OLIMPOLLI MONTAGNANI

Developer

Giorgio Pantano Farm, Terre Grosse,
Confagricoltura Veneto, Energreen, CREA,
University of Maribor, CIRVE, CET Electronics

Developer

Country

Italy

CAICT SRL, CNR IBE, University of Siena, Tenuta
Montagnani, Mascagni Organic Farm, Olearia
Santella, Green Company Siena/Grosseto,
University of Florence, Aermatica 3D, Biotac

Target crop

Vineyards

Country

Italy

Function

Plant monitoring, spraying

Target crop

OlivesPower source

NA

Function

Pollination

StatusPrototype

Power source

Battery

Description• ROVITIS is an autonomous driving robot that cancollect data from vineyards and carry out
treatments based on the data. Precise treatment
can be carried out, thus optimizing resources,
minimizing environmental impact and reducing
labour.
• ROVITIS is intended to be a cost-effective
solution that can work for estates smaller than 20
hectares.

StatusPrototype

Description• A drone outfitted with special equipment is used
to distribute pollen to plants at the time when
flowers are most receptive to pollination.
• Assisted pollination is expected to increase yields
by up to 20-25%.
• This solution can be easily implemented by
farmers without changing their business structure.

Source: EIP AGRI

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26

3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標（イタリア：研究開発支援）（参考） 「Operational Group」にて選定、支援が行われたプロジェクト
Name

DigiViT

Name

Developer

CNR IBE, Ama Castle, Marchesi Mazzei SpA
Agricultural, Cennino Agricola, Sigma Ingegneria
srlPrecision agriculture: reduction of theenvironmental impact of production systems

Developer

Country

Italy

Adriatic Agricultural Consortium Cooperative
Society, ASSAM, Filippetti spa, Pegaso
Management srl, Green Company Marche, Marche
Polytechnic University

Target crop

Vineyards

Country

Italy

Function

Plant monitoring

Target crop

OlivesPower source

Battery

FunctionSpraying, plant monitoring

StatusPrototype

Power source

NA

Description• This project will develop a prototype drone that
can take very high-resolution images of vineyards
with its high-performance sensors.
• The images will be analysed by an operational
tool that will forecast yields and quality.

StatusPrototype

Description• This project will develop an aerial spraying system(drone) to fight against plant diseases.
• The drone will also be able to monitor the statusof the fruit and carry out fertiliser interventions.

Source: EIP AGRI

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27

3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標（イスラエル：戦略目標）

限られた資源や国土の中で食料需給率を高める必要があることから、イスラエルでは、
農業効率向上、汚染の削減、農地保全を目的にスマート農機の活用を進めている

持続可能農業戦略目標

スマート農機の位置づけ

Efficient use of resources andmaterials in agricultural activity

Efficient agricultural machines can reduce theamount of input required for (energy,
fertilisers, pesticides, labour, water)

Reduction of agriculture related
hazards and damage to theenvironment.

Precise and targeted spraying reduces the useof pesticides and fertilisers that damage theenvironment.

Preservation of agricultural land andsoil conservation

Source: United Nations

Light agricultural robots can reduce soil
compaction and prolong field lifespan.

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3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標（イスラエル：研究開発支援）

スマート農機への特定の資金スキームはなく、一般的な技術支援の枠組み内で個別プロジェク
ト毎に承認・支援が行われる◼ Israel Innovation Authorityは、研究から商業化までのプロジェクトに資金を提供する独立した公的機関である。
◼ ヨーロッパとは異なり、イスラエルにはスマート農機の研究開発に特化した特別な資金はないが、R&D FUNDやMAGNETプログラムな
どの有望な技術革新に対するR&D基金を利用することができる。
◼ さらに、イスラエルは自動的にHorizon 2020からの資金提供の対象となり、EU加盟国と同じ条件でプロジェクトに参加できる。
Israel Innovation Authority Funding Programmes
Description

Division

Programmes (non-exhaustive)

StartupThe Startup Division offers unique tools to support the early
developmental stages of technological initiatives at the pre-seed or initial
R&D stages, thus helping transform their ideas into reality while reachingsignificant funding milestones.

•
•
•
•

GrowthThe Growth Division operates incentive programmes that assist hi-techcompanies in the sales growth stage as well as mature hi-tech companies
that utilise growth channels based on technological innovation and/or
seek assistance in funding innovative research and development.

• Incentive Programmes for Innovation with Government
Entities• Generic R&D Incentive Programme for Large Companies• R&D Fund

Technological
Infrastructure

The Technological Infrastructure Division focuses on funding applied R&D
infrastructure, promoting applied research in academia, technology
transfer, Leveraging R&D for Dual Use Technologies, exchange ofknowledge and experience and developing of ground-breaking
innovation by an integrated group of researchers from academia andindustry.

• TELEM (The National Infrastructure Forum for Research andDevelopment)• Applied Support of Research Institutes• Promoting Applied Research in Academia - NOFAR, KAMIN• Technology Transfer - MAGNETON• Generic Technologies R&D Consortiums - MAGNET• Users' Association R&D Infrastructure

Source: Israel Innovation Authority

Incubators Incentive ProgrammeInnovation Labs Program - Incentive Programme
Tnufa (Ideation) Incentive Programme
Early Stage Companies Incentive Programme

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3-① スマート農機に関する政策 ー スマート農機開発に向けたロードマップや政策目標

欧州等の海外諸国ではスマート農機はまだ商業化の初期段階にあり、主に研究開発活動への補助が主要な支援施策として行われている。一方で、スマート農機に特定したプログラム等は存在せず、幅広く農業や一般技術支援の枠組みを活用した支援となっている。
Key strategy(Agriculture/Technology)

EU

Italy

IsraelFinancial Support
Agriculture-specific
R&D Support

General R&D Support• Horizon2020 research
themes for agricultural
digitalisation/robotics• Eurostars• COSME• “Strategic Plan for
Innovation andResearch in the
Agricultural, Food andForestry Sector“• Rural Development
Programme• National Research
Programme• Individual university
research grants• NA• Incentive Programmes
for Innovation with
Government Entities• Horizon2020
participation• Israel Innovation
Authority Funding
Programmes such as
R&D Fund, etc.

• “Farm to Fork”

Non-Financial
Support• Development ofbroadband
infrastructure in ruralareas• Knowledge exchange
platforms such as AKIS
at EU/national level• Data sharing via Farm
Sustainability Data
Network etc.

• NA

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スマート農機の開発状況

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31

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー

ヨーロッパとイスラエルにおいて、果樹園芸のスマート農機は労働集約的な事業プロセスの代替を目指されており、特に収穫関連の開発がさかんに行われている
形態／事業プロセス
移動型ロ
ボット
＋
車両

作物育成

防除

収穫

汎用性
高い
BYELAB
UniBZ

汎用性
低い
ドローン

圃場・果樹整備

Mamut
Cambridge

VitiroverVitirover Solutions

VINBOT
Robotnik

MYCE_Vigne
WALL-YES55
HGMSWEEPER
Wageningen UR

FFRobot
FF Robotics

Octinion
RubionBACCHUS
AUTH

TED
Naio

大型
Spraying drone
Drone4Agri

小型

AGRO
AirBoard
eBee SQ
senseFly

Source: company websites, news articles

Skyx
Skyx

Tevel
Tevel Aerobotics Tech

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3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー

スマート農機は依然として人間のように適切は判断を行うことができないため、センサー、アルゴリズム、エンドエフェクターの速度と感度の向上に研究の焦点が当てられている◼ スマート農機は人の労働に匹敵する競争力を確保するために、より良い意思決定を行い、より速くより正確に動くことができる必要がある。
◼ スマート農機の人件費に対する費用対効果も改善する必要がある。
Field operation

Future research direction

Example H2020 project for technology

Increase planting accuracy (in position/depth/number of planted seeds)
Improve speed of planting operation
Develop algorithms that can decide on the best way to manage the plant
Improve dexterity of machines to carry out pruning quickly andaccurately without plant damage• A gardening robot for rose, hedge and topiary
trimming (TrimBot2020)• Rapid tree-planting through the use of remotesensing and unmanned vehicle planting
technologies for large scale reforestation(BioCarbon)

Field preparation(Seeding, pruning,
etc.)

•
•
•
•

Field scouting anddata collection(disease detection
and plant
monitoring)• Develop image databases for each disease to train the robots• Develop sensors that can work better in non-uniform lighting conditions• Develop better algorithms that can interpret large amounts of image dataand inconsistent lighting/intrusive backgrounds• Develop systems that can detect insects hidden in leaves• Precision Farming of Hazelnut Orchards(PANTEHON)• Intelligent decision from vineyard robots(VineScout)

Weeding andspraying• Increase speed and accuracy of weed detection• Increase performance by increasing working area and speed• Increase spraying speed and detection accuracy of plants that needspraying• Weeding robot for precision farming reducing
herbicide usage by 95% (Asterix)• RObotics for Microfarms (ROMI)

Harvesting• Improve speed of picking• Improve detection rate of ripe fruit• Reducing damage to plant and/or picked fruit• Sweet Pepper Harvesting Robot (SWEEPER)• The first high-performance robotic system for
automated harvesting of vegetables greenhouses(GRoW)

Source: Agricultural Robotics for Field Operations, news articles

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3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー

スマート農機におけるコスト削減の取組みは、複数のタスクを実行できる多目的ロボットの開発による実現が目指されている◼ 作物生産サイクル内では、ほとんどのフィールド作業は短期間に実行され、年に1〜2回しか実行されない。また、これらの期間は通常すべての栽培者で同じである。従って、ロボットを購入して共有することは現実的な選択肢ではない可能性がある。
◼ ロボットシステムは、複数のフィールド操作用に設計することにより、生産者にとってより手頃な価格にすることができる。フィールドで様々なタスクを実行するために異なった器具を装備できるロボットプラットフォームが開発された。

Robotic platformの事例
Bosch Deepfield Robotics （DEU）• Bosch develops BoniRob as
farming robot that can perform
various tasks with one unit.
• It can not only monitor crops as
measurement and health analysis,
but also fertilise, water and weedby exchanging modules.
• Price: N.A.

Saga Robotics（NOR）• Thorvald is an autonomous modular
robot that can be configured for mostagricultural environments. It canperform tasks such as picking fruits andvegetables, phenotyping, spraying, anddata collection.
• Price: N.A.

Clearpath Robotics（CAN）• Clearpath Robotics develops unmanned
robotic platforms that can be equippedwith different sensors, cameras andactuators to carry out different tasks.
• The Warthog robot is the base for FF
Robotics’ apple harvesting robot.
• Price: US$12-20k (Jackal robot; 20kg
payload)Autonomous Systems, Inc（USA）• The Forge Robotic Platform is designed
for use with over 100 attachments suchas mowers, blades and sprays.
• ASI works together with CNH Industrial(major European tractor company) tobring autonomous control to farmequipment.
• Price: N.A.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

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3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー

スマート農機の研究と促進には、官民様々な機関が参画している
主要なプレーヤーは汎用性の高いロボットに注力する傾向がある◼ スマート農機の研究と促進には、民間と公共の両方が参加している。主要なプレーヤーは、ロボットプラットフォームや幅広いアプリケーションを備えたスマート農機に注力する傾向がある。一方で、果樹園のロボットはよりタスク固有で、汎用性が低い傾向がある。

主要な研究開発機関（民間／公共）
Category

Name

Machinery
CNH Industrial
manufacturers

Research
institutes

Non profit
organisations

Description
CNH is a Dutch MNC that designs. Produces and sells agricultural equipment. Together with ASI, they aredeveloping autonomous tractors with the ability to seed, plant and till broad acre and row crops. CNH is also
exploring connected vehicles with Microsoft’s Azure cloud.

Bosch Deepfield Robotics

Bosch is a leading German engineering and technology company that has developed BoniRob, a robotic
platform that can be adapted for many agricultural applications, such as weeding and spraying.

John DeereJohn Deere is a leading agricultural machinery manufacturer. The MyJohnDeere platform is a centralised, online
platform that allows third parties to consolidate and manage farming data.

Wageningen University andResearch (UR)

Wageningen UR has more than 60 engineers and researchers working together with industrial partners on new
robotic systems for agri and food, specialising in artificial intelligence and sensing, learning and vision.

Fraunhofer Institute of
Manufacturing Engineeringand Automation IPA

Fraunhofer IPA develops and offers agricultural robotics solutions for undefined and dynamic environments,
ranging from navigation software for field swarm cooperation to machine vision and new small-scale robot
concepts.

Agricultural Research
Organisation

The Agricultural Research Organisation is the largest institute in Israel involved in agricultural research. Its mainfunctions are to assist the Israeli farmer in solving problems, to conduct research and development in promising
new agricultural fields and food sciences, and to plan, organise and implement agricultural research in Israel.

CEMA (European Agricultural
Machinery Association)

CEMA’s goal is to advance agricultural machinery and solutions for sustainable farming. The CEMA network
represents both large MNCS and European SMEs active in the sector.

EurAgEng (European Society
for Agricultural Engineers)

EurAgEng supports scientists and engineers working in the field of Agricultural and Biosystems Engineering inEurope. They promote collaboration between academic and industry research.

euRobotics aisbl

euRobotics aisbl is a non-profit association for all stakeholders in European robotics that aims to boost robotics
research, development and innovation and to foster a positive perception of robotics. euRobotics is currently
engaged in the preparation of the Horizon Europe programme (2021-2027).

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

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3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー

果樹園芸のスマート農機の開発目的は重要度順で労働力の削減、収量・品質の向上と農薬最小化による環境汚染の回避となっている。以下は、主要な機器の例。（1/2）◼ 果樹園芸専用のスマート農機は非常にコストがかかるため、ブドウ畑やイチゴなどの価値の高い作物や、非常に労働集約的な収穫に焦点を当てた開発が行われている。
Field operation
Name

Developer

Country

Field prep

BAKUS

VitiBot

FRx

MYCE_Vigne

WALL-YEFRx

Xf-Rovim

Polytechnic Universityof Valencia

ES

BYELAB

University of Bolzano

PANTHEON

Field
scouting

Weeding/
spraying

Main objective
HarvestTarget crop

Status*Power source

Yield

LabourEnvironment**x

Vineyards

C

Batteryxxx

Vineyards

C

Battery; solar
chargedxxx

Olive treesP

Gel battery

x

IT

x

Orchards

P

BatteryxRoma Tre University

ITx

Hazelnuts

P

Batteryx

Mamut

Cambridge
ConsultantsUKx

Orchards

P

NAx

VINBOT

Robotnik Automation
SLL

ES

x

Vineyards

P

Lithium battery

x

OUVA

Polariks

NLx

Vineyards

P

NA

x

VineScout

Polytechnic Universityof Valencia

ESx

Vineyards

P

Battery; solar
chargedxeBee SQ

senseFlyCHx

All cropsC

Batteryx

UX11AgDelairFRx

All cropsC

Batteryx

mdLiDAR

Microdrones GmbHDEx

All cropsC

Battery

x

Skyx

Skyx

IL

x

C

Battery

x

x

x

TED

Naio technologies

FR

C

Lithium batteryxx*P: Prototype; C: Commercial, PC: Pre-commercial
Source: company websites, news articlesxxx

Vineyards**Environment: Agrochemical reduction, not CO2 reduction
Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

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3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー

果樹園芸のスマート農機の開発目的は重要度順で労働力の削減、収量・品質の向上と農薬最小化による環境汚染の回避となっている。以下は、主要な機器の例。（2/2）
NameDeveloper

Country

Field prep

Field operation
Field
Weeding/
scouting spraying

HarvestTarget crop

Status*Power source

VitiroverVitirover Solutions

FRx

Vineyards

C

AgriRobot

UKx

Orchards

P

NLx

Greenhouses

C

Agribot

Innovate Integra Ltd
Holland Green
MachineAgribot sp

Battery; solar
chargedNA

PL

x

Orchards

Spraying drone

Drone4Agro

NL

x

LV

x

S55

AGRO

AirBoard
Aristotle University of
BACCHUSThessaloniki
E-Series
Agrobot SL
Strawberry
Dogtoothharvesting robot Technologies
RubionOctinion
Raspberry
Fieldwork Robotics
harvesting robot
Cucumber
Wageningen UR
harvesting robot

x

x

x

x

NA

x

x

C

NA

x

All cropsC

Lithium batteryx

All cropsC

Lithium batteryxxVineyards

P

Lithium battery

ESxStrawberries

PC

Batteryx

UKx

Strawberries

P

NA

x

BE

x

Strawberries

C

NA

x

UK

x

Raspberries

P

Batteryx

NLx

Cucumbers

P

NA

x

P

Batteryx

PC

Battery

x

P

NA

x

P

Batteryx

GRx

SWEEPER

Wageningen UR

NLx

FFRobot

FF Robotics

IL

x

GRoW

MetoMotion
Tevel Aerobotics
Technologies

IL

x

IL

x

Tevel

*P: Prototype; C: Commercial, PC: Pre-commercial
Source: company websites, news articles

Main objective
EnvironYield
Labourment**

Sweet
peppers
ApplesGreenhouses
Apples,orangesx

x**Environment: Agrochemical reduction, not CO2 reduction
Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

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3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例
Name

BAKUS

Name

MYCE_Vigne

Developer

VitiBot

Developer

WALL-YECountry

FranceCountry

FranceTarget crop

Vineyards

Target crop

Vineyards

Function

Soil management, spraying

Function

Pruning, weeding, soil management

Power source

Battery

Power source

Battery (solar charged)

StatusCommercial; price unavailable

StatusCommercial; from EUR 15,000

Description• BAKUS is an autonomous electric robot that canbe fitted with interchangeable tools.
• Currently, the robot is able to loosen soil andspray. Other tools are being developed.
• BAKUS can work up to 10 hours on a single 2
hour quick charge.

Description• MYCE_Vigne is a solar-charged robot that can
prune, hoe and mow grapevines.
• The robot can prune 50-150 vines an hour(depending on type) for 24 hours.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

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3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例
Name

Xf-RovimName

BYELAB

Developer

Polytechnic University of Valencia, Institut Valencià
d'Investigacions Agràries (IVIA)

Developer

University of Bolzano

Country

Italy

Target crop

Orchards (e.g. apples), vineyards

Function

Plant monitoring

Power source

Battery

StatusPrototype

Description• BYELAB is an autonomous robot that can travel
within orchards with uneven terrain.
• It is a crop-monitoring mobile laboratory thatcan monitor different crop health indicatorssuch as vegetation thickness and flower density.
• Future work on the BYELAB will include
improving its abilities to measure plant health,detect plant diseases, navigate uneven terrain
and avoid obstacles.

Country

Spain

Target crop

Olive trees

Function

Disease detection

Power source

Gel battery

StatusPrototype (funded by Horizon 2020)

Description• Xf-Rovim is a small field robot for early detectionof Xylella fastidiosa disease in olive trees.
• The robot is remotely driven and fitted withdifferent sensing equipment to capture thermal,
spectral and structural information.
• It can inspect a field of 4 hectares without
interruptions in less than 6 hours.
• Although the robot is efficient in gathering data,
the data are yet to be analysed in an efficient way
to give accurate results on infection levels.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

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3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例
Name

PANTHEON

Name

Mamut

Developer

Roma Tre University, University Trier, Tuscia
University, Université libre de Bruxelles, Sigma
Consulting, Ferrero Trading

Developer

Cambridge Consultants

CountryUK

Target crop

Orchards

Function

Plant monitoring

Power source

NA

StatusPrototype

Description• Mamut is an autonomous robot that explores
crop fields, capturing data on health and yield at
the level of individual plants and on a massive
scale.
• By automating data capture, Mamut gives
growers regular, precise and actionable
information on their crops, enabling them topredict and optimise yields.

Country

Italy

Target crop

Hazelnuts

Function

Plant monitoring

Power source

Battery

StatusPrototype (funded by Horizon 2020)

Description• PANTHEON is an integrated system whereby alimited number of unmanned aerial and groundrobots move within the orchard to collect dataand perform typical farming operations.
• The information is collected on a plant-by-plantbasis. This will allow to dramatically increase thedetection of limiting factors for each individual
plant, such as lack of water or pests and diseases
affecting the plant health, and to reactaccordingly.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

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3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例
Name

VINBOT

Name

OUVA

Developer

Robotnik Automation SLL, Cooperativa Agricola deGranja CRL, Orgovanyi Gazdaszovetkzet Szovetket,
Bodegas Familiares de Rioja Provir etc.

Developer

Polariks

Country

Netherlands

Target crop

Vineyards

Function

Plant monitoringPowersourceNA

StatusPrototype

Description• OUVA is an autonomous rover equipped with ahyperspectral camera.
• OUVA can autonomously traverse vineyards tocollect data on canopy health and grape maturity.

Country

Spain

Target crop

Vineyards

Function

Plant monitoring

Power source

Lithium battery

StatusPrototype (funded by 7th European Framework

Description• VINBOT is an all-terrain autonomous mobile
robot with a set of sensors capable of capturing
and analysing vineyard images and 3D data.
• VINBOT is able to estimate the yield of vineyards
in kg/m2 based on the amount of leaves, grapes
and other phyto-data throughout the vineyard.
• Wineries and wine growers will be able to makeaccurate yield predictions to plan their wine
production and marketing.

Programme)

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

41

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例
Name

VineScoutNameeBee SQ

Developer

Polytechnic University of Valencia, WALL-YE Sarl,
Sundance Multiprocessor Technology Ltd,
University of Rioja, Symington Family Estates

Developer

senseFly

Country

Switzerland

Country

Spain

Target crop

All crops

Target crop

Vineyards

Function

Plant monitoring

Function

Plant monitoring

Power source

Battery

Power source

Battery (solar charged)

StatusStatusPrototype (funded by Horizon 2020)

Commercial; ~EUR 10,000, including 1 year
subscription to Pix4Dfields software

Description• VineScout is an autonomous robot that takes
high resolution images of the vines.
• The images are analysed to assess the needs andstatus of the vineyard so that the grower canmake decisions on irrigation, treatment andharvest.
• This research project has a strong focus oncommercialisation from the start. However, there
have been issues with durability and cost of therobot.

Description• senseFly provides drones that monitor crops
from the sky. Images are analysed to gain more
efficient crop insights and to more accuratelyplan and manage farm operations.
• Insights are provided from plant emergence topre-harvest yield prediction and drainage
planning for the next season.
• eBee SQ’s flights can be automated.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

42

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例

Name

TED

Name

Vitirover

Developer

Naio Technologies

Developer

Vitirover Solutions

Country

FranceCountry

FranceTarget crop

Vineyards

Target crop

Vineyards

Function

WeedingFunction

MowingPower source

Lithium battery

Power source

Battery (solar charged)

StatusCommercial

StatusDescription• TED is a fully electric autonomous mechanicalweeding robot for vineyards, reducing herbicideuse.
• The TED robot can cover up to 40 hectares andhas a speed of up to 4km/h.
• There are prototype tools in development fortrimming, spraying, etc.
• Naio Technologies also has the OZ and DINO
robots that can be used for vegetable crops.

Commercial; Robot-as-a-service model, priceunknown

Description• Vitirover is a small economical and ecologicalrobot that mows grass without the need forchemicals. Each robot is electric and runs onsolar energy.
• The Vitirover is deployed in fleets controlled by asingle operator. It is used to mow the grass in
between plants in vineyards and orchards.
• Going forward, Vitirover could be upgraded toinclude plant monitoring capability.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

43

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例
Name

AgriRobot

Name

S55

Developer

Innovate Integra Ltd, Loughborough University,
Jiangsu University, Nantong Guangyi Mechanical& Electrical Co Ltd

Developer

Holland Green MachineCountry

Netherlands

CountryUK

Target crop

Target crop

Orchards

Greenhouse crops such as tomatoes, cucumbers,
peppers, eggplants and flowers.

FunctionSpraying

FunctionSpraying

Power source

NA

Power source

NA

StatusPrototype (funded by Innovate UK and Jiangsu
Province Science and Technology Department)

StatusCommercial; price unknown

Description

Description• The AgriRobot is a semi-autonomous agriculturalrobot capable of intelligently spraying orchard
crops using automatic navigation in a field byfollowing lanes rows between plants and trees.
• The AgriRobot can analyse the presence, size,
shape and density of the target trees to precisely
apply the necessary amount of pesticide whenneeded, leading to more efficient spraying.

• The S55 spray robot is a robot with batteries thatcan spray automatically. It uses a pipe rail system
to move through the greenhouse.
• The S55 can be adapted into the AIRMIXer,
Dosatron, foam disinfector and gutter cleaner
versions to achieve different functions.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

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3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例

Name

Agribot

Name

Spraying drone

Developer

Agripot sp

Developer

Drone4Agro

Country

PolandCountry

Netherlands

Target crop

Orchards

Target crop

All crops

FunctionSpraying

FunctionSpraying

Power source

NA

Power source

Lithium battery

StatusCommercial; price unknown

StatusCommercial; price unknown

Description• The Agribot is a small robot that autonomously
sprays orchards (water, fertiliser, herbicide or
pesticide).
• The Agribot can be used for orchards,
vineyards ,plantations, olive groves andvegetables.
• The Agribot travels at a maximum speed of
10km/h.

Description• The Drone4Agro drone can be used for different
applications such as spraying and fertilizing.
• The drone models can operate with a 5 – 100
litre payload.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

45

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例

Name

AGRO

Name

BACCHUSDeveloper

AirBoard

Developer

Aristotle University of Thessaloniki

Country

LatviaCountry

GreeceTarget crop

All crops

Target crop

Vineyards

FunctionSpraying

Function

HarvestingPower source

Lithium battery

Power source

Lithium battery

StatusCommercial; price unknown

StatusPrototype (funded by H2020)

Description• AirBoard AGRO is a Air Board fully autonomous
spraying designed for organic ingredients andchemical liquid substances.
• It offers customisable spray nozzles for pesticideand fertiliser overlay for vineyards, avocado,
wheat, corn, etc.

Description• BACCHUS is an autonomous robotic ecosystemutilizing mobile platforms and manipulators forintelligent and selective harvesting of grapes.
• In the future, the robot is expected to be able topredict grape yield, thin out small wine grapes
and detect and remove grapes infected withfungi.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

46

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例
Name

E-Series

Name

Strawberry harvesting robot

Developer

Agrobot SL

Developer

Dogtooth Technologies

Country

Spain

Country

United Kingdom

Target crop

Strawberries

Target crop

Strawberries

Function

Harvesting

Function

HarvestingPower source

Battery

Power source

NA

StatusPre-commercial; ~EUR 210,000 expected

StatusPrototype

Description• The E-Series is a pre-commercial electric robotic
harvester for gently harvesting strawberries.
• It uses colour and infrared depth sensors toassess fruit ripeness for picking. The robot isequipped with 24 independent robotic arms topick fruit,• The robot picks the strawberry from the stem anddoes not damage the fruit.

Description• Dogtooth’s autonomous strawberry harvesting
robot uses computer vision to identify ripe fruit
and machine learning to evolve efficient picking
strategies.
• After picking, the robot grades the fruit todetermine their size and quality and places them
directly into punnets.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

47

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例
Name

RubionName

Raspberry harvesting robot

Developer

Octinion

Developer

Country

Belgium

Fieldwork Robotics (University of Plymouth spinout), Bosch UK

Target crop

Strawberries

Country

United Kingdom

Function

Harvesting

Target crop

Raspberries

Power source

NA

Function

Harvesting

StatusCommercial; price unknown

Power source

Battery

Description• Rubion is an autonomous strawberry picking
robot that can pick strawberries gently like ahuman picker.
• Rubion can pick a strawberry every 4 seconds
and is able to pick 70-100% of ripe fruit,
depending on the variety.
• Octinion claims that its robot is the firstcommercial strawberry picking robot available.

StatusPrototype

Description• The raspberry harvesting robot uses sensors, 3D
cameras and machine learning to identify ripe
fruit.
• Currently, it takes the robot about a minute toharvest a fruit, with the eventual goal being
25,000 berries a day.
• The final version is expected to have 4 arms
working simultaneously.
• Separate field trials for this robot in China fortomatoes and cauliflower are underway.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

48

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例
Name

Cucumber Harvesting RobotName

SWEEPER

Developer

Wageningen University & Research

Developer

Country

Netherlands

Wageningen University & Research, Umea
Universitet, Proefstation Voor de Groenteleelt, Ben
Gurion University of the Negev, etc.

Target crop

Cucumbers

Country

Netherlands

Function

Harvesting

Target crop

Sweet peppers

Power source

Battery

Function

Harvesting

StatusPrototype

Power source

NA

Description• In 2001, Wageningen UR developed anautonomous harvest machine for cucumbers.
• The robot was able to successfully harvest 75%of the ripe cucumbers but took about a minuteto harvest each cucumber.

StatusPrototype (funded by Horizon 2020)

Description• SWEEPER is an automatic sweet pepper
harvesting robot that works in greenhouses.
• During trials, the robot was able to pick 18% ofripe fruit and took 24 seconds to pick each fruit.
• A fully automatic robotic sweet pepper harvesteris expected to be commercially viable in 5-10
years.
• SWEEPER’s technology and results are applicableto other fruit crops such as cucumbers, tomatoes,
grapes, apples, cardamom, banana and coconuts.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

49

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考） 果樹園芸のスマート農機事例
Name

FFRobot

Name

GRoW

Developer

FF Robotics

Developer

MetoMotion

Country

IsraelCountry

IsraelTarget cropApplesTarget crop

Function

Harvesting

Greenhouse crops such as tomatoes, eggplants,
cucumbers, peppers, etc.

Power source

Battery

Function

Harvesting

StatusPre-commercial; EUR 250-300k price expected

Power source

NA

Description• The FFRobot is an apple picker equipped with 12
robotic arms and picks fruit based on size andcolour. It can be adjusted based on the width ofthe orchard row.
• The robot requires one human supervisor.
• The machine has been shown to do only 3-5%
damage to the fruit, compared to 10-15% withhuman pickers.
• The machine is expected to cost US$300-500
thousand and could provide a return within 2 to 3
years.

StatusPrototype (funded by Horizon 2020)

Description• GRoW uses advanced 3D vision system andmachine vision algorithms to identify and locate
ripe fruit.
• GRoW’s error rate for tomatoes is less than 5%
and can harvest more than 720kg per hour. Its
ROI is expected to be about 3 years.
• In the future, GRoW will be able to do othergreenhouse tasks such as pruning, pollinating
and monitoring.

Source: company websites news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

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3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー

大手の農機メーカーが汎用性の高いロボットに集中するため、果樹園芸のスマート農機を開発する企業はほとんど中小企業である。
主要な果樹園芸スマート農機の研究開発機関（民間／公共）
Name

EstablishedCountry

Category

Projects/Products

Wageningen University
and Research (UR)1876

Netherlands

Research Institution• Cucumber picking robot• SWEEPER

Robotnik

2002

Spain

Manufacturer• BACCHUS• VINBOT

WALL-YE

2008

FranceManufacturer• MC_Vigne• VineScout

NaioTechnologies

2011

FranceManufacturer• TED• DINOsenseFly

2009

Switzerland

Manufacturer• eBeeSQ

Delair

2011

FranceManufacturer• UX11Ag

Saga Robotics

2016

NorwayManufacturer• Thorvald• BACCHUS

Robert Bosch GmbH1886

Germany

Manufacturer• BoniRob• Raspberry picking robot

Source: company websites, news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

51

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考）企業概要 － Wageningen University & Research（蘭）具体プロジェクト・製品事例

企業概要
Name

Wageningen University & Research

Founded

1876

Headquarters

Wageningen, Netherlands

Geographic
Coverage

NA

RevenueNA

Employees

12,819 students (2019-20)
5,928 undergraduates (2019-2020)
6,409 postgraduates (2019-2020)

Shareholders/NA
Investors
Websitehttps://www.wur.nl/

Description

Wageningen UR has more than 60 engineers
and researchers working together withindustrial partners on new robotic systems foragri and food, specialising in artificial
intelligence and sensing, learning and vision.

Source: company websites, news articles

Cucumber picking robot• In 2001, Wageningen UR
developed an autonomous
harvest machine for cucumbers.
• The robot was able tosuccessfully harvest 75% of theripe cucumbers but took about aminute to harvest eachcucumber.
SWEEPER• SWEEPER is an automatic sweet
pepper harvesting robot that works
in greenhouses. A fully automatic
robotic sweet pepper harvester is
expected to be commercially viablein 5-10 years.
• SWEEPER’s technology and results
are applicable to other fruit crops
such as cucumbers, tomatoes, grapes,
apples, cardamom, banana andcoconuts.
Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

52

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考）企業概要 － Robotnik（西）具体プロジェクト・製品事例

企業概要
Name

Robotnik

Founded

2002

Headquarters

Barcelona, Spain

Geographic
Coverage

Offices in China, Singapore
Distributors present globally

RevenueNA

Employees

11-50

Shareholders/NA
Investors
Websitehttps://robotnik.eu/

Description

Robotnik designs, manufactures and markets
mobile robots and mobile manipulators.
Robotnik participates actively in European
research projects to develop robotic solutions
together with research institutions.

Source: company websites, news articles

BACCHUS• BACCHUS is an autonomous
robotic ecosystem utilizing
mobile platforms andmanipulators for intelligent andselective harvesting of grapes.
• In the future, the robot is
expected to be able to predict
grape yield, thin out small wine
grapes and detect and remove
grapes infected with fungi.
VINBOT• VINBOT is an all-terrain
autonomous mobile robot with aset of sensors capable ofcapturing and analysing vineyard
images and 3D data.
• VINBOT is able to estimate theyield of vineyards in kg/m2 basedon the amount of leaves, grapes
and other phyto-data throughout
the vineyard.
Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

53

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考）企業概要 － WALL-YE（仏）具体プロジェクト・製品事例

企業概要
Name

WALL-YE

Founded

2008

Headquarters

FranceGeographic
Coverage

NA

RevenueNA

Employees

NA

Shareholders/NA
Investors
Websitehttp://wall-ye.com/

Description

WALL-YE creates software and robots for
agriculture. Currently, in addition toparticipating in research, they have twocommercial robots, one for vineyards and theother for row crops.

Source: company websites, news articles

MYCE_VIGNE• MYCE_Vigne is a solarcharged robot that can prune,
hoe and mow grapevines.
• The robot can prune 50-150
vines an hour (depending ontype) for 24 hours.

VineScout• VineScout is an autonomous
robot that takes high resolution
images of vineyard vines.
• The images are analysed to assess
the needs and status of thevineyard so that the grower canmake decisions on irrigation,
treatment and harvest.

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

54

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考）企業概要 － Naio Technologies（仏）具体プロジェクト・製品事例

企業概要
Name

Naio Technologies

Founded

2011

Headquarters

Midi-Pyrenees, France

Geographic
Coverage

NA

Revenue

EUR 2 million (2017)

Employees

1-10

Shareholders/
JCS Consulting Group, Bpifrance, Capagro, etc.
Investors
Websitehttp://www.naio-technologies.com/

Description

Naio Technologies develops and markets
machines for agriculture and viticulture. Itfeatures electric tools for weeding, hoeing, andharvesting that help farmers collect andharvest their products.

Source: company websites, news articles

TED• TED is a fully electricautonomous mechanicalweeding robot for vineyards,
reducing herbicide use.
• The TED robot can cover up to
40 hectares and has a speed of
up to 4km/h.
• There are prototype tools indevelopment for trimming,
spraying, etc.
DINO
• Dino is a fully electricautonomous mechanical weedingrobot for raised vegetable beds
and rows.
• Dino can work for up to 8 hours
at a time and cover 5 hectares ina day.

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

55

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考）企業概要 － senseFly（スイス）
具体プロジェクト・製品事例

企業概要
Name

senseFly

Founded2009

Headquarters

Lausanne, Switzerland

Geographic
Coverage

USA, distribution available globally

RevenueNA

Employees

101-250

Shareholders/Parrot SA
Investors
Websitehttps://www.sensefly.com/

Description

SenseFly develops and produces aerial imagine
drones for professional applications. In 2012,
Parrot SA invested EUR 5 million in thecompany for a 57% stake.

Source: company websites, news articles

eBee SQ• The TED robot can cover up to 40 hectares and has a speedof up to 4kmsenseFly provides drones that monitor crops
from the sky. Images are analysed to gain more efficient crop
insights and to more accurately plan and manage farmoperations.
• Insights are provided from plant emergence to pre-harvest
yield prediction and drainage planning for the next season.
• eBee SQ’s flights can be automated.
• There are prototype tools in development for trimming,
spraying, etc.
• In 2017, a leading Basque winemaker employed senseFly
drone data to optimise its yield, resulting in a 17% increase inbottles.

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

56

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考）企業概要 － Delair SAS（仏）具体プロジェクト・製品事例

企業概要
Name

Delair SAS

Founded

2011

Headquarters

Toulouse, France

Geographic
CoverageFrance, USA, Singapore
Distribution available globally

Revenue

EUR 8.5 million (2018)

Employees

101-250

UX11Ag• Delair manufactures and sells professional drones for visual
intelligence for multiple industries, including agriculture.
• The UX11Ag is equipped with a high-end multispectral
camera for plant level measures.
• The Delair.ai platform helps to analyse the image data toprovide insights to the farmer. The insights can be loaded
onto the MyJohnDeere platform to inform tractor decisions.

Shareholders/Andromede, Intel capital, etc.
Investors
Websitehttp://delair.aero/

Description

Delair is a leading provider of end-to-end,visual intelligence solutions. The company’sofferings combine high performance UAV
hardware with delair.ai, the industry’s mostrobust platform.

Source: company websites, news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

57

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考）企業概要 － Saga Robotics（ノルウェー）
具体プロジェクト・製品事例

企業概要
Name

Saga Robotics

Founded

2016

Headquarters

As, Norway

Geographic
Coverage

NA

RevenueNA

Employees

11-50

Shareholders/ Rabobank Food & Agri Fund, Nysno, Cibus
Investors
Fund
Websitehttps://sagarobotics.com/

Description

Saga Robotics revolutionises the agricultural
sector by developing autonomous robots
capable of performing a wide variety ofagricultural operations at a lower price andwith higher quality than conventional systems.

Source: company websites, news articles

Thorvald• Thorvald is anautonomous modular
robot that can be
configured for mostagricultural environments.
It can perform tasks suchas picking fruits andvegetables, phenotyping,spraying, and datacollection.
BACCHUS• BACCHUS is an autonomous
robotic ecosystem utilizing
mobile platforms (Thorvald) andmanipulators for intelligent andselective harvesting of grapes.
• In the future, the robot is
expected to be able to predict
grape yield, thin out small wine
grapes and detect and remove
grapes infected with fungi.
Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

58

3-② スマート農機の開発状況 ー 主要な研究開発テーマ・プレイヤー（参考）企業概要 － Robert Bosch GmbH（独）具体プロジェクト・製品事例

企業概要
Name

Robert Bosch GmbHFounded

1886

Headquarters

Gerlingen, Germany

Geographic
Coverage

GlobalRevenue

EUR 78.5 billion (2018)

Employees

400,000 (2019)

Shareholders/
Robert Bosch Stiftung
Investors
Websitehttps://www.bosch.com/

Description

Bosch is a German multinational engineeringand technology company engaged in the
manufacture of electrical and electronic
products, automotive technology, power tools,
thermo technology, household appliances,
security systems and broadband networks, aswell as automation technology and packaging
technology.

Source: company websites, news articles

BoniRob• Bosch develops BoniRob as
farming robot can perform
various tasks with one unit.
• It can not only monitor crops
as measurement and healthanalysis, but also fertilise,water and weed by exchanging
modules.
Raspberry picking robot• The raspberry harvesting robot
uses sensors, 3D cameras andmachine learning to identify
ripe fruit.
• Currently, it takes the robot
about a minute to harvest afruit, with the eventual goal
being 25,000 berries per day.
• Bosch UK is collaborating withFieldwork Robotics to optimise
the robotic arms and develop
software in preparation for fullscale production.
Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

59

スマート農機関連のビジネスモデル

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60

3-③ スマート農機関連のビジネスモデル ー 主要なビジネスモデル

機器販売ではなく、成果やサービスで対価を得るようなビジネスモデルが実施されている◼ 農業機械がよりスマートになるにつれて、無人の農業機械の所有と維持のコストが複雑さを増している。投資収益率が不明な高価な
スマート農機に投資するよう農業者に説得するのは難しいと思われる。
◼ 従って、単に農業者に機器を販売する代わりに、ビジネスモデルは結果ベースになることが期待される。この場合、製造業者とサービスプロバイダーの収益は、農業者のために創出できる価値に直結される。
Business Models
モデル
Farmingas-aService

Assetsharing

Outcomebased
pricing

Ecosystem

ビジネススキーム
Manufacturer/
service provider

Manufacturer/
service provider

Manufacturer/
service provider

Service
Farmer$$ (based on output)

Hardware
$$

Asset
owner

Capacity
Farmer$$Advice + agri inputs

Farmer$$ (adjusted based on results)

IoT Platform
Manufacturer

Farmer$$ (future equipment sales)

Source: NRI

概要

スマート農機実用段

利用者は、製品の代わりに提供される実際の成果・便益に対して対価を支払う。
例えば、農業者は機械を用いた土地の広さに基づいて代金を支払う形態

適用可能

商業ベース

高額な機器の場合、シェアリングを通じて余った稼働キャパシティを売り戻し、危機の稼働率を最大化する方法も採りうる。（機器の市場浸透を高める効果も期待される）

適用可能
（現在は一
般的な農機
のみ）

パイロット

製品・サービス提供者が、利用者にアドバイスや農業情報を提供し、収穫量等のパフォーマンスを保証する形式（したがって最終的な収益は、パフォーマンスに基づき確定する）

適用可能
（現在は種
子・化学業
界のみ）

パイロット

製品提供者が、利用者に追加費用なしでIoTプ
ラットフォームを提供することにより、利用者を自社のエコシステムに囲い込み、将来的な製品販売を促進する。

適用可能

商業ベース

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

61

3-③ スマート農機関連のビジネスモデル ー 主要なビジネスモデル（事例①： Farming-as-a-Service）

Farming-as-a-Serviceモデルでは、顧客は製品そのものではなく、製品により提供されたサービスに対して支払いを行う◼ Small Robot Company（英国）は、畑作物を自律的に植え付け、監視し、処理できる小さなロボットを扱う。ロボットを購入する代わりに、農業者はロボットが農場をデジタル化して作業するための料金を1ヘクタールごとに支払う。これにより、農業者にとって、新しいテクノロジーを採用するコストとリスクが軽減される。

Farming-as-a-Service business model

Pros and cons of business model

Pros• The Small Robot Company has 2 autonomous robots – Tom
and Dick, as well as Wilma, the AI behind the robots.
• Instead of selling the robots directly to farmers, the farmers
pays a per-hectare fee for the robots to take care of their crop.

• Low risk for farmers as they do not have tocommit to expensive equipment with unknown
benefit and obsolescence. Farmers can easily opt
out if the robot is not right for their operations.
• Start-up companies can bring their product tomarket early without having to perfect thedesign until it can be reliability operated without
expert intervention.
• Farmers are already used to paying for output –fruit pickers are paid for the amount they harvest,
not by the number of hours worked.

Cons

TOM: Crop monitoring and mapping• This business model is not as effective for highly
specific robots that do tasks that only need to bedone once a year for a short period of time andby all farmers at the same time.
• Unlike software, robots are physical machines, so
their range and deployment are limited bygeographical location. There has to be sufficient
farm density and enough operators in the area.

Robots$Small Robot
Company

Source: Small Robot Company$/hectare covered

Farmer

DICK: Mechanical weeding

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

62

3-③ スマート農機関連のビジネスモデル ー 主要なビジネスモデル（事例②： Asset sharing business model）

Asset sharingモデルでは、農機の”遊び”時間にシェアリングサービスを提供し、農機の稼働率の最大化を目指している◼ Mermix（ギリシャ）は、機器の所有者がマシンの余剰容量を収益化するための「Uber for 農業機械」プラットフォームを運営している。パイロットは2016年に実施され、EUの第7次フレームワークプログラムから資金提供を受けた。
Asset sharing business model

Pros and cons of business model

Spare equipment
capacity$
Payment

Pros• Equipment owners are able to monetise theirexcess capacity.
• Farmer are able to use expensive machinery thatthey may otherwise not have access to.

Cons• The model works best if there is sufficientequipment and farm density within a small area,
as it is neither efficient not feasible to transportheavy equipment over long distances.
• Since many farming activities in the same area aredependent on climate and are carried out at thesame time, equipment may not be available atthe right time as the owner is using it.

Farm equipment$
Payment

MermixPremium app
version$Equipment
owner

Subscription fee(EUR100/year)

Farmer• Mermix is a platform that allows farmer to monetise the sparecapacity of their machinery, or an “Uber for farm machinery”. The
owners set the price for use of their machinery, from which Mermix
will take a cut.
• In addition, the Mermix app has a premium version, which provides
additional service beyond equipment matching, such as cost andcrop reports. This subscription service costs EUR 100 annually.
• The pilot for Mermix ran in 2016 and was funded by the EU 7th
Framework Programme. There have been no updates since 2017.
Source: Mermix

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

63

3-③ スマート農機関連のビジネスモデル ー 主要なビジネスモデル（事例③：Outcome-based pricing）

Outcome-based pricing モデルでは、製造業者とサービスプロバイダーは、顧客にアドバイス
および農業資材を提供し、収穫実績に基づいて対価を得る◼ バイエル（ドイツ）は、米国で成果ベースの価格モデルを試行している。このモデルでは、増分歩留まりのシェアと引き換えに、作物の歩留まりパフォーマンスを保証します。保証された結果に満たない場合、バイエルは農業投入物のコストの一部を払い戻す。このビジネスモデルは現在パイロットにすぎないが、今後5年以内に商用化される可能性がある。

Outcome-based pricing business model
Before harvest$

After harvest

Pros• This business model reduces the production risk
for farmers as the downside is shared with Bayer.
• It also encourages farmers to try new products
as the Bayer covers some of the risk.
• For Bayer, the advice they gives is a direct sales
channel through which they can push theirproducts.

Cons• Bayer has to have high confidence that its data
analysis and advice will lead to positive
outcomes, as it is sharing the risk with the farmer.
• There are many factors in farming beyond seeds
and chemical inputs (e.g. weather, irrigation). It is
hard to determine the farmer’s baseline and theextent to which Bayer’s advice is responsible forthe increase or decrease in yield.
• Performance metrics and fair pricing are hard todetermine, especially since there is notransparency into Bayer’s data algorithms andpricing models.

SeedAdvisor, FieldView+ analytics and advice
Subscription fee
Seeds, chemical inputs

Bayer

Pros and cons of business model$

Farmer

Payment for inputs(Less-than-expected yield)$% refund on input price(More-than-expected yield)

Bayer

$

Farmer% of incremental harvest• In 2019, Bayer ran a pilot in the USA for outcome-based pricing. Bayerprovides farming advice through its digital apps, based on the farmers
data, and guarantees a certain yield if their advice is followed.
• If the farmer takes Bayer’s advice and produces a better-than-predicted
yield, the upside is shared with Bayer. If not, Bayer will refund a portionof the input price.
• The pilot is currently only for seeds, but will be extended to chemical
products in the future. This model may be implemented within the next
5 years.
Source: Bayer, news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

64

3-③ スマート農機関連のビジネスモデル ー 主要なビジネスモデル（事例③：Outcome-based pricing）（参考）バイエルは種子と農薬の主要生産者である◼ バイエルはドイツの多国籍企業であり、製薬、消費者の健康、作物科学をカバーする世界最大の製薬会社の1つである。彼らの作物科学部門は、殺菌剤、除草剤、殺虫剤、種子を製造、販売しています。

企業概要

Crop Science Products

Name

Bayer AG

Herbicides

Roundup™, Adengo™, Alion™, Corvus™

Founded1863

Fungicides

Fox™, Luna™, Nativo™, Serenade™, Xpro™

CEO

Werner Baumann

Insecticides

BioAct™, Confidor™, Movento™, Sivanto™

HQ

Leverkusen, Germany

Seeds

Dekalb™, Asgrow™, Seminis™, DeRuiters™

Geographic
coverage

GlobalEnvironmental
Science

Ficam™, Maxforce™, Esplanade™, K-Othrine™,
Fludora™ Fusion# of
Employees

104,000 (2019)

Digital Agriculture

Climate FieldView™

LatestRevenue

Total: EUR 43.5 billion (2019)
Crop science: EUR 19.8 billion (2019)

Climate FieldView

Owners /Investors• Norges Bank Investment Management(3.0% shareholding)• The Vanguard Group (3.0%
shareholding)Description

Bayer is a Germany MNC and one of thelargest pharmaceutical companies in theworld, covering pharmaceutical, consumer
health and crop science.

Source: Bayer, Climate FieldView

Climate FieldView is a platform thatallows farmers to collect, store andview their field data in one digitalplatform that they can access fromanywhere. Farmers can visualises
and analyse crop performance withfield data maps so they can build
customised plans for each field andoptimise their inputs.
Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

65

3-③ スマート農機関連のビジネスモデル ー 主要なビジネスモデル（事例④：Ecosystem business model）

Ecosystem business モデルでは、IoTプラットフォームを顧客に無償提供しつつ、農業資材やサービス提供、オペレーションへのレコメンデーションを提供している◼ John Deere（米国）は、機器の購入者がMyJohnDeereプラットフォームを無料で使用できるようにする。このプラットフォームは、機器、天気、作物などのデータを所有者、オペレーター、ディーラー、コンサルタントなどと結び付ける。このプラットフォームを通じて、サードパーティの開発者はアプリケーションを提供することができる。John Deereはプラットフォームの使用料を請求しないことで、将来のハードウェア販売を促進するために顧客をエコシステムに閉じ込める戦略を取っている。

Ecosystem business model

Pros and cons of business model

Pros• By providing the platform at no additional cost to its
customers, John Deere hopes to lock its customers
into its ecosystem to drive future hardware sales.
• The data from farmers that John Deere gathers can bemonetised in the future (with the right privacy
protections).
• Smaller players are unable to offer a similar
platform for free as they will not be able to recoverdevelopment costs.
• John Deere is able to build direct relationships with
end-customers and understand how they interact
with John Deere’s products.
• John Deere is able to leverage the data to provide
additional services such as predictive maintenance.

Cons• Customers have not been as easily sold into the data
features as expected, and John Deere has had to
improve customer service and education efforts inorder to encourage platform adoption.
• John Deere’s software licensing terms have
prevented farmers from making DIY repairs to theirown equipment, which is costly for the farmer in both
repairs and time, resulting in illegal software hacking.

Connected equipment (tractor, harvester, etc.)$ Payment for equipment
Data

John Deere

Development

MyJohnDeere

Analytics

FarmerIntegration$
3rd party apps

Payment for 3rd party services, if applicable• John Deere launched their MyJohnDeere platform in 2012, whichconnects data from equipment, weather, crops etc. with owners,
operators, dealers, consultants etc. The platform helps farmers tomanage their fleet more effectively.
• The platform allows 3rd party developers to connect and provide
applications. John Deere does not appear to be charging for this.
• MyJohnDeere is free for consumers who purchase John Deere
equipment. The strategy is to lock customers into their ecosystem
to drive future hardware sales.
Source: John Deere, news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

66

3-③ スマート農機関連のビジネスモデル ー 主要なビジネスモデル（事例④：Ecosystem business model）（参考）John Deereは農業機械の企業概要と提供機器◼ John Deereは、農業、建設、林業機械を製造するアメリカの多国籍企業であるDeere & Companyのブランド名である。
Agricultural Machinery

企業概要
Name

Deere & Company

Founded1837

CEOJohn C. May

HQ

Moline, Illinois, USA

Geographic
coverage

Global# of
Employees

73.500 (2019)

LatestRevenue

Total: US$39.26 billion (2019)
Agri: US$23.67 billion (2019)

Owners /Investors• Cascade Investment LLC (10.1%
shareholding)• The Vanguard Group (7.1%
shareholding)Description

John Deere is the brand name of Deere &Company, an American MNC that
manufactures agricultural, construction
and forestry machinery.

Source: John Deere

Crop Harvesting

•
•
•
•

Combines
Front-end equipment
Sugar cane
CottonTurf & Utility

•
•
•
•

Utility vehicles
Riding lawn equipment
Commercial mowing
Walk-behind mowers

Hay and Forage

•
•
•
•

Self-propelled forage harvesters
Heads
BalersMowingCrop Care• Seeding• Tillage• Application equipment

Tractors

•
•
•
•

Large
MediumUtility
Loaders

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

67

3-③ スマート農機関連のビジネスモデル ー 主要なビジネスモデル（事例④：Ecosystem business model）

エコシステムが作れる企業は大手に限られているが、中小企業はそのエコシステムを活用して自社の製品を販売することができる◼ Delair（フランス）は空中マッピングのドローンとソフトウェアを提供する会社である。空中地図は直接に「MyJohnDeere] に転送し、種苗や農薬散布等を自動化することができるので、「MyJohnDeere」のエコシステムユーザは他社より、Delairの製品を利用することが想定されている。
Delair business model

Pros and cons of business model

Pros• The product has access to the large customer
base of the existing digital ecosystem.
• The product gains credibility if access to theecosystem requires prior approval from theecosystem operator.
• Synergies between the product and otherservices in the ecosystem can unlock additional
value for users.

Cons• The product may be seen as exclusionary tousers who are not part of the ecosystem.
• Over-reliance on any single ecosystem exposes
the company to the risks of the ecosystem’sowner.

Drone + software$
Delair

Payment for hardware/software

Mapped data

MyJohnDeere

FarmerTractor operation insights• Delair is a French company that provides high performancedrones and accompanying software. Images taken by Delair’s
drones can be managed and analysed via Delair’s software.
• Also, the aerial maps from the software can be seamlesslytransferred to the MyJohnDeere ecosystem and used toautomate field tasks such as planting and herbicide/fertiliser
application according to field variability.
• Existing MyJohnDeere users are likely to prefer Delair’s drones
and software ahead of other non-integrated competitors as it
works with an ecosystem that they are already familiar with.
Source: Delair, news articles

Delair UX11Ag drone

Aerial map example on
MyJohnDeere forvariable application offarm input (e.g. more
fertiliser on the redareas, etc.)

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

683-③ スマート農機関連のビジネスモデル ー 主要なビジネスモデル（事例④：Ecosystem business model）

スマート農機は自国での普及率はまだ低いため、海外に展開した企業がない。
ドローンの海外展開のみが進んでいる。畑のマッピングに使われている。(1/2)
Agricultural Drone Mapping Case (South Africa)

Peanut Field Mapping in South Africa•
The farmer used senseFly’s eBee Ag drone to map thehealthy and unhealthy peanut plants in his field.
•
It only took 8 minutes to capture the images and 20
minutes to process the data.
•
From further investigation, it was found that parts of the
field were waterlogged, while other parts were being
eaten by hungry animals.
•
The farmer was able to take immediate action on these
problems.
Source: senseFly, news articles

Agricultural Drone Mapping Case (Asia/Africa)

Rubber and Oil Palm Plantation Mapping in Asia andAfrica• The SIAT group uses Delair’s DT18 AG drones to survey
75,000 hectares of rubber and oil palm plantations in
Asia and Africa.
• The images are used to map the health of the crop inorder to improve yield quality and quantity.
• Using Delair’s drone, the company managed to reduce its
aerial data acquisition costs by 50%.
Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

69

3-③ スマート農機関連のビジネスモデル ー 主要なビジネスモデル（事例④：Ecosystem business model）

スマート農機は自国での普及率はまだ低いため、海外に展開した企業がない。
ドローンの海外展開のみが進んでいる。畑のマッピングに使われている。(2/2)
Agricultural Drone Mapping Case (Asia/Africa)

Rubber and Oil Palm Plantation Mapping in Asia
and Africa• The SIAT group uses Delair’s DT18 AG drones tosurvey 75,000 hectares of rubber and oil palm
plantations in Asia and Africa.
• The images are used to map the health of thecrop in order to improve yield quality andquantity.
• Using Delair’s drone, the company managed toreduce its aerial data acquisition costs by 50%.

Source: Delair, news articles

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

70

3-③ スマート農機関連のビジネスモデル ー 主要なビジネスモデル（事例④：Ecosystem business model）（参考）MyJohnDeereのプラットフォーム概要
MyJohnDeereの概要
センサーから得られる情報• 機械の稼動情報• 土壌の含水率、栄養分の組成など

5秒ごとにクラウドへ送信

プラットフォーム“My John Deere”

農業者
My John Deereが提供する情報• 農地の成熟度• 機械の使用状況• 業務状況

GPSと土壌情報から農地に関する情報提供

Source: John Deere

アイドル、移動、収穫中等の機械の使用状況

ジョブスケジューリングや機械の稼動実績

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

71

3-③ スマート農機関連のビジネスモデル ー ビジネスモデルの普及に関わる課題

技術レベルの更なる向上、業界標準の欠如、曖昧な法律、自律機械の信頼性向上、などがスマート農機とその関連ビジネスモデルの普及における阻害要因とされている
1

技術水準• スマート農業ロボットのセンサー、アクチュエーター、パターン認識、意思決定技術は、現段階において人間の労働力と同等レベ
ルとは言えず、同じコストで利用することもできない

2

産業標準化

3
規制

4

信頼性・受容性• 資機材の分野では統一された基準・規格がないため、メーカーが満たさなければならない各国の要件は多数にわたる。
将来的にはロボットの性能・技術の進歩を比較するためのターム、システムの性能測定方法等の標準化が必要となる。
• 車両と管理ソフトウェア間の通信には、オープンデータ標準が必要であり、全てではないにせよ、ほとんどのメーカーが標準規格に加入すると予想されている。

• 自動走行を採用する前に、おもに自動走行する機械とその製造事業者の責任に関する法律や規制を定義する必要がある。
すでに制定されている責任法に加え、保険会社にとっては適切な保険パッケージを開発・提供する必要がある。
• 自律システムによって生成されるデータについては、そのデータが誰の所有物となるかが問題となっており、現時点で未解決の状態である。

• 農機の利用者（オペレーター）は、信頼できるシステムを求めている。
ある調査によれば無人トラクター、農作物収穫ロボット、UAVを現時点で導入しない理由として、①信頼できない、②（背景となる）農業知識が不足している、③社会的認知の低下、などが挙げられており、第一に信頼性が着目されている。
• 例えば、小規模な農業地域では、自動化技術が必要であることを農業者が納得することは難しいと考えられる。多くの場合、農業者は自動化技術を望んでおらず（贅沢で派手なものであるとみなされている）、さらには伝統的な農業への挑戦・脅威として捉えられている。

Source: Scouting the Autonomous Agricultural Machinery Market

Copyright（C） Nomura Research Institute, Ltd. All rights reserved.

72