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Agricultural Robots and Drones 2017-2027: Technologies, Markets, Players
The future of farming; ultra precision farming; autonomous farming
Brand new for March 2017
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This report is focused on agricultural robots and drones. It analyses how robotic market and technology developments will change the business of agriculture, enabling ultra-precision farming and helping address key global challenges.
It develops a detailed roadmap of how robotic technology will enter into different aspects of agriculture, how it will change the way farming is done and transform its value chain, how it becomes the future of agrochemicals business and how it will modify the way we design agricultural machinery.
In particular, this report provides:
- Market forecasts: Granular ten-year segmented market forecasts for 14 categories including static milking robotics, mobile dairy farm robots, autosteer tractors, autonomous tractors, unmanned spraying drones, autonomous data mapping drones, robotic implements for de-weeding, autonomous de-weeding mobile robots, robotic fresh fruit harvesting, robotic strawberry harvesting, manned and unmanned robotic lettuce/vegetable thinning/harvesting and so on. Our market forecasts are also segmented by territory. All our assumptions and data points are clearly explained.
- Technology assessment: Detailed technology assessment covering all the key robotic/drone projects, prototypes and commercial products relevant to the agricultural sector. Detailed overview and assessment of key technological components such as vision sensors, LIDARs, novel end-effectors, and hyper/multi-spectral sensors. Technology roadmaps outlining how different equipment are increasingly becoming vision-enabled, intelligence and unmanned/autonomous.
- Application assessment: Detailed application assessment covering dairy farms, fresh fruit harvesting, organic farming, crop protection, data mapping, seeding, nurseries, and so on. For each application/sector, a detailed overview of the existing industry is given, the needs for and the challenges facing the robotic technology are analysed, the addressable market size is estimated by territory, and granular ten-year market projections are given.
- Company profiles: More than 20 interview-based full company profiles with detailed SWOT analysis, 40 company profiles without SWOT analysis, and the works of more than 76 companies/research groups listed and summarized.
Robotics in dairy farms will reach $8bn by 2023
Robotic and drones have already started to quietly transform many aspects of agriculture. Already, thousands of robotic milking parlours have been installed worldwide, creating a $1.9bn industry that is projected to grow to $8bn by 2023. Mobile robots are also already penetrating dairy farms, helping automate tasks such as feed pushing or manure cleaning.
Tractors become increasingly autonomous
Tractor guidance and autosteer technologies are also going mainstream thanks to improvements and cost reductions in RTK GPS technology. Indeed, more than 300k tractors equipped with autosteer or tractor guidance were sold in 2016, rising to more than 660k units per year by 2027.
Unmanned autonomous tractors have also been technologically demonstrated with large-scale market introduction largely delayed not by technical issues but by regulation, high sensor costs and the lack of farmers' trust. This will all change by 2022 when sales of unmanned or master-slave (e.g., follow me) tractors picks up.
Drones bring in increased data analytics into farming
Agriculture will be a major market for drones, reaching over $480m in 2027. Unmanned remote-controlled helicopters have already been spraying rice fields in Japan since early 1990s. Indeed, this is a maturing technology/sector with overall sales in Japan having plateaued. This market will benefit from a new injection of life as suppliers diversify into new territories and as low-cost light-weight sprayer drones enter the market.
The progress of drones is by no means limited to spraying. Their core function is to provide detailed aerial maps of farms, enabling farmers to take data-driven site-specific action. These light-weight low-cost drones are often loaded with small multi-spectral sensors, measuring key indicators about plant health, yields, water stress levels, nitrogen deficiency and so on.
This development will soon be entering into its growth years. This is because regulatory barriers for drone deployment are coming down and, more importantly, precision farming ecosystems is finally coming together meaning that farmers can act on what the data tells them. In time, the drone hardware will become commoditized and value will shift largely to data acquisition and analytics providers.
Source: IDTechEx
Robotics is the future of agrochemicals
Agricultural robotics is also rapidly progressing on the ground. Vision-enabled robotic implements have been in commercial use for some years in organic farming. These implements follow the crop rows, identify the weeds, and aid with mechanical hoeing. The next generation of these advanced robotic implements is also in its early phase of commercial deployment. Indeed, they are already thinning as much as 10% of California's lettuce fields.
The end game however is to turn these implements into general-purpose autonomous weeding robots. This means that swarms of these small, light-weight robots will locate weeds and take site-specific precise action to eliminate them.
This has already starting to occur with numerous companies and groups developing and deploying a variety of weeding robots. Indeed, whilst most products are in prototype or semi-commercial trail phase, the first notable sales have also taken place aimed at small multi-crop vegetable farmers.
This has far reaching long-term consequences for the farming industry, particularly affecting suppliers of crop protection chemicals. This is because it changes the way we farm as farmers will no longer need to broadcast spray chemicals uniformly across the entire field. Instead, they will move even beyond variable-rate precision towards ultra-precision agriculture where the farm is managed on an individual plant basis and where each plant is given only the exact dose of chemicals that it requires.
This is only a long term development at this stage but it will impact the total consumption of crop protection chemicals. It can convert volume commodity agrochemical business into speciality chemical operations, and can force suppliers to re-invent themselves as providers of crop protection, whatever its form, and not just chemical suppliers.
Agricultural machinery transfigured?
The advent of agricultural robots will herald a change in the way agricultural machinery is envisaged. Today, bigger is better because the productivity of the skilled driver/operator is improved. Mobile robots could change this by taking the driver out of the equation.
Indeed, emerging mobile agricultural robots are likely to be slow, unmanned, light-weight and modular. Their slowness means that more attention is given to each plant, their lightness means no soil compaction, and their small size means potentially lower cost.
The latter point is critical if such mobile robots are ever to leave the drawing board because slower and small machines are inherently less productive therefore need to be lower cost, in some cases by as much as 24 times. This cost requirement alone will prevent uptake in the medium-term.
Today, most examples of such robots are only in the prototypes or early stage commercial trial phase but the direction of development is clear. The technological challenges will soon largely been solved and the industry will enter the phase of making and proving a commercial case, whether as an equipment or a service.
Farmers' conservatism will however turn this potentially revolutionary change into an evolutionary, incremental one.
Robotics finally succeed in fresh fruit harvesting?
Despite non-fresh fruit harvesting being largely mechanized, fresh fruit picking has remained mostly out of the reach of machines or robots. Picking is currently done using manual labour with machines at most playing the part of an aid that speeds up the manual work.
Progress here has been hampered by the stringent technical requirements. The vision system needs to detect fruits inside a complex canopy whilst the robotic arms needs to rapidly, economically and gently pick the fruit. The lack of CAD models has also prevented rapid iterations in product development. The absence of universal applicability has also put off large investments as each harvester is likely to work on a narrow segment.
This is however beginning to change, albeit slowly. A limited number of fresh strawberry harvesters are already being commercially trialled. Some versions require the farm layout to be changed and the strawberry to be trained to help the vision system identify a commercially-acceptable percentage of strawberries. Others are developing a more universal solution compatible with all varieties of strawberry farms. Market adoption will start from 2020/2021 onwards.
At the same time, fresh apple robotic harvesting has also reached the level of late stage prototyping. Here, novel low-cost end-effectors are being developed together with low-cost good enough robotic arms that will work in parallel. Market adoption will start from 2022/2023 onwards.
Source IDTechEx
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| 1. | EXECUTIVE SUMMARY |
| 1.1. | What is this report about? |
| 1.2. | Growing population and growing demand for food |
| 1.3. | Major crop yields are plateauing |
| 1.4. | Employment in agriculture |
| 1.5. | Global evolution of employment in agriculture |
| 1.6. | Aging farmer population |
| 1.7. | Trends in minimum wages globally |
| 1.8. | Towards ultra precision agriculture via the variable rate technology route |
| 1.9. | Ultra Precision farming will cause upheaval in the farming value chain |
| 1.10. | Agricultural robotics and ultra precision agriculture will cause upheaval in agriculture's value chain |
| 1.11. | The battle of business models between RaaS and equipment sales |
| 1.12. | Transition towards to swarms of small, slow, cheap and unmanned robots |
| 1.13. | Market and technology readiness by agricultural activity |
| 1.14. | Technology progression towards driverless autonomous large-sized tractors |
| 1.15. | Technology progression towards autonomous, ultra precision de-weeding |
| 1.16. | Technology and progress progression roadmap for robotic fresh fruit harvesting |
| 1.17. | Ten-year market forecasts for all agricultural robots and drones segmented by type and/or function |
| 1.18. | Ten-year market forecasts for autonomous and mobile agricultural robots and drones segmented by type and/or function |
| 2. | AUTONOMOUS MOBILITY FOR LARGE TRACTORS |
| 2.1. | Number tractors sold globally |
| 2.2. | Value of crop production and average farm sizes per region |
| 2.3. | Overview of top agricultural equipment companies |
| 2.4. | Tractor Guidance and Autosteer Technology for Large Tractors |
| 2.5. | Auto steer for large tractors |
| 2.6. | Ten-year forecasts for autosteer tractors |
| 2.7. | Master-slave or follow-me large autonomous tractors |
| 2.8. | Fully autonomous driverless large tractors |
| 2.9. | Technology progression towards driverless autonomous large-sized tractors |
| 2.10. | Ten-year market forecasts for tractor guidance, autosteer and fully autonomous tractors/combines |
| 3. | AUTONOMOUS ROBOTIC AGRICULTURAL PLATFORMS |
| 3.1. | Autonomous small-sized agricultural robots |
| 3.2. | Autonomous agricultural robotic platforms |
| 3.3. | Ten-year market forecasts for autonomous robotic data scouts |
| 4. | ROBOTIC WEED KILLING |
| 4.1. | From manned, broadcast towards autonomous, ultra precision de-weeding |
| 4.2. | Crop protection chemical sales per top suppliers globally |
| 4.3. | Sales of top global and Chinese herbicide suppliers |
| 4.4. | Global herbicide consumption data |
| 4.5. | Glyphosate consumption and market globally |
| 4.6. | Regulations will impact the market for robotic weed killers? |
| 4.7. | Penetration of herbicides in different field crops |
| 4.8. | Growing challenge of herbicide-resistant weeds |
| 4.9. | Autonomous weed killing robots |
| 4.11. | Organic farming |
| 4.12. | Robotic mechanical weeding for organic farming |
| 4.13. | Technology progression towards autonomous, ultra precision de-weeding |
| 4.14. | Ten-year market forecast for robotic weeding by technology type |
| 5. | ROBOTIC VEGETABLE THINNING AND HARVESTING |
| 5.1. | Autonomous lettuce thinning robots |
| 5.3. | Automatic asparagus harvesting |
| 5.5. | Addressable market size for robotic lettuce thinning and weeding service provision |
| 5.6. | Ten-year market forecasts for robotic lettuce thinning and vegetable harvesting by technology and territory |
| 6. | ROBOTIC FRESH FRUIT PICKING |
| 6.1. | Field crop and non-fresh fruit harvesting is largely mechanized |
| 6.2. | Fresh fruit picking remains largely manual |
| 6.3. | Machining aiding humans in fresh fruit harvesting have not evolved in the past 50 years |
| 6.4. | Emerging robotic fresh fruit harvest assist technologies |
| 6.5. | Robot orchard data scouts and yield estimators |
| 6.6. | Emerging robotic fresh fruit harvest assist technologies |
| 6.7. | Robotic fresh apple harvesting |
| 6.8. | Robotic fresh citrus harvesting |
| 6.9. | Fresh fruit harvesting robots |
| 6.10. | Technology and progress progression roadmap for robotic fresh fruit harvesting |
| 6.11. | Addressable market size for robotic fresh apple-picking service provision |
| 6.12. | Ten-year market forecasts for robotic fresh citrus/apple harvesting by territory |
| 6.13. | Robotic fresh strawberry harvesting |
| 6.14. | Addressable market size for robotic fresh strawberry-picking service provision |
| 6.15. | Ten-year market forecasts for robotic fresh strawberry harvesting by territory |
| 7. | VINE PRUNING ROBOTS |
| 7.1. | Autonomous robotic vineyard scouts and pruners |
| 8. | GREENHOUSES AND NURSERIES |
| 8.1. | Autonomous robotics for greenhouses and nurseries |
| 9. | ROBOTIC SEEDERS |
| 9.1. | Variable rate technology for precision seed planting |
| 9.2. | Robotic seed planting |
| 10. | ROBOTIC DAIRY FARMING |
| 10.1. | Global trends and averages for diary farm sizes |
| 10.2. | Global number and distribution of dairy cows by territory |
| 10.3. | Global country-specific addressable markets for robotic milking machines and feed pushers |
| 10.4. | Robotic milking parlours |
| 10.6. | Autonomous robotic feed pushers |
| 10.7. | Alternatives to autonomous robotic feed pushers |
| 10.8. | Autonomous robotic shepherds |
| 10.9. | Autonomous manure cleaning robots |
| 10.10. | Ten-year market forecasts for robotic milking systems by country |
| 10.11. | Ten-year market forecasts for automatic feed pusher and other mobile robotics in dairy farming |
| 11. | AERIAL DATA COLLECTIONS |
| 11.1. | Satellite vs. plane vs drone mapping and scouting |
| 11.2. | Benefits of using aerial imaging in farming |
| 11.3. | Unmanned drones in rice field pest control in Japan |
| 11.4. | Unmanned drones and helicopters for field spraying |
| 11.5. | Unmanned agriculture drones on the market |
| 11.6. | Comparing different agricultural drones on the market |
| 11.7. | Regulation barriers coming down? |
| 11.8. | Agricultural drones: the emerging value chain |
| 11.9. | Core company information on key agricultural drone companies |
| 11.10. | Ten-year market forecasts for agricultural drones |
| 12. | KEY ENABLING COMPONENTS |
| 13. | GRIPPER TECHNOLOGY |
| 13.1. | Suction-based end effector technologies for fresh fruit harvesting |
| 13.2. | Simple and effective robotic end effectors for fruit harvesting |
| 13.3. | Soft robotics based end effector technologies for fresh fruit handling |
| 13.4. | Robotic end effector technologies for fresh fruit harvesting |
| 13.5. | Dexterous robotic hands for agricultural robotics |
| 13.6. | Examples of dexterous robotic hands |
| 14. | NAVIGATIONAL TECHNOLOGIES (RTK, LIDAR, LASERS AND OTHERS) |
| 14.1. | RTK systems: operation, performance and value chain |
| 14.2. | Lidar- basic operation principles |
| 14.3. | Review of LIDARs on the market or in development |
| 14.4. | Performance comparison of different LIDARs on the market or in development |
| 14.5. | Assessing suitability of different LIDAR for agricultural robotic applications |
| 14.6. | Hyperspectral image sensors |
| 14.7. | Hyperspectral imaging and precision agriculture |
| 14.8. | Hyperspectral imaging in other applications |
| 14.9. | Hyperspectral imaging sensors on the market |
| 14.10. | Common multi-spectral sensors used with agricultural drones |
| 14.11. | GeoVantage |
| 15. | MARKET FORECAST, BUSINESS LANDSCAPE, COMPANY POSITIONING, AND COMPANY PROFILE |
| 15.1. | Ten-year market forecasts for all agricultural robots and drones segmented by type and/or function |
| 15.3. | Ten-year market forecasts for autonomous and mobile agricultural robots and drones segmented by type and/or function |
| 15.4. | Ten-year market forecasts for tractor guidance, autosteer and fully autonomous tractors/combines |
| 15.5. | Ten-year market forecasts for autonomous robotic data scouts |
| 15.6. | Ten-year market forecast for robotic weeding by technology type |
| 15.7. | Ten-year market forecasts for robotic lettuce thinning and vegetable harvesting by technology and territory |
| 15.8. | Ten-year market forecasts for robotic fresh citrus/apple harvesting by territory |
| 15.9. | Ten-year market forecasts for robotic fresh strawberry harvesting by territory |
| 15.10. | Ten-year market forecasts for robotic milking systems by country |
| 15.11. | Ten-year market forecasts for automatic feed pusher and other mobile robotics in dairy farming |
| 15.12. | Ten-year market forecasts for agricultural drones |
| 16. | INTERVIEW-BASED COMPANY PROFILES |
| 16.1. | Agrobot |
| 16.2. | Blue River Technology |
| 16.3. | DeepField Robotics |
| 16.4. | F. Poulsen Engineering ApS |
| 16.5. | Fresh Fruit Robotics |
| 16.6. | Harvest CROO Robotics |
| 16.7. | Ibex Automation |
| 16.8. | miRobot |
| 16.9. | Naio Technologies |
| 16.10. | Nippon Signal |
| 16.11. | Parrot |
| 16.12. | Precision Hawk |
| 16.13. | Quanergy |
| 16.14. | Robotic Solutions |
| 16.15. | Shadow Robotics |
| 16.16. | Soft Robotics Inc |
| 16.17. | Stream Technologies |
| 16.18. | SwarmFarm Robotics |
| 16.19. | Tillet and Hague |
| 16.20. | Velodyne LiDAR |
| 17. | COMPANY PROFILES |
| 17.1. | 3D Robotics |
| 17.2. | AGCO |
| 17.3. | AgEagle |
| 17.4. | AgJunction Inc |
| 17.5. | Agribotix |
| 17.6. | Airinov |
| 17.7. | Autonomous Tractor Cooperation |
| 17.8. | Beijing UniStrong Science and Technology (BUST) |
| 17.9. | Case IH |
| 17.10. | Dogtooth Technologies |
| 17.11. | Empire Robotics |
| 17.12. | Farmbot |
| 17.13. | Festo |
| 17.14. | Gamaya |
| 17.15. | GrabIT |
| 17.16. | Harvest Automation |
| 17.17. | Headwall |
| 17.18. | HerdDog |
| 17.19. | HETO |
| 17.20. | HiPhen |
| 17.21. | Hortau |
| 17.22. | John Deere |
| 17.23. | Kinzes Autonomous Harvest System |
| 17.24. | Kubota Corp |
| 17.25. | L'Avion Jaune |
| 17.26. | LeddarTech |
| 17.27. | Lely |
| 17.28. | LemnaTec |
| 17.29. | Magnificant |
| 17.30. | Mavrx |
| 17.31. | McRobotic |
| 17.32. | MicaSense |
| 17.33. | Motorleaf |
| 17.34. | NavCom |
| 17.35. | Near Earth Autonomy |
| 17.36. | Novariant |
| 17.37. | Orbital Insight |
| 17.38. | Pix4D |
| 17.39. | Prospera |
| 17.40. | Qubit Systems |
| 17.41. | Robotics Plus |
| 17.42. | Robotnik |
| 17.43. | Scanse |
| 17.44. | senseFly |
| 17.45. | Sentra |
| 17.46. | SkySquirrel |
| 17.47. | SpeIR |
| 17.48. | Trimble |
| 17.49. | UAV-IQ Precision Agriculture |
| 17.50. | Urban Crops |
| 17.51. | URSULA Agriculture |
| 17.52. | VineRangers |
| 17.53. | Yanmar |
| 17.54. | Yara |
| 18. | COMPANIES COVERED IN THE REPORT |
| 18.1. | Aarhus University |
| 18.2. | Abundant Robotic Inc |
| 18.3. | Adigo |
| 18.4. | Aerial Technology Limited |
| 18.5. | Agricultural Solutions Ltd |
| 18.6. | Ai-Solution |
| 18.7. | Amazonen-Werke |
| 18.8. | Australian Centre of Field Robotics |
| 18.9. | Autonomous Tractor Corporation |
| 18.10. | BASF |
| 18.11. | Bayer |
| 18.12. | BeauMatic Robotics |
| 18.13. | Bosch |
| 18.14. | C. Write & Son Ltd |
| 18.15. | Carnegie Mellow University |
| 18.16. | Cerescon |
| 18.17. | CNH Industrial (Case IH and New Holland) |
| 18.18. | Conpleks Innovation (Kongskilde Vibro Crop Robotti) |
| 18.19. | Cork University |
| 18.20. | DBR Conveyor Concepts |
| 18.21. | Delair-tech |
| 18.22. | DeLaval |
| 18.23. | DEMCON |
| 18.24. | Deutz Fahr |
| 18.25. | DJI |
| 18.26. | Dorhout R&D |
| 18.27. | Dow |
| 18.28. | DroneDeploy |
| 18.29. | DuPont |
| 18.30. | ecoRobotix |
| 18.31. | Energid |
| 18.32. | Ferrari Costruzioni Meccaniche |
| 18.33. | Festo |
| 18.34. | FMTC |
| 18.35. | Frankin Robotics |
| 18.36. | Fuji Heavy Industries |
| 18.37. | Gardford Machinery |
| 18.38. | Geiger Lund |
| 18.39. | GeoVantage |
| 18.40. | Hexacon |
| 18.41. | HoneyComb |
| 18.42. | Industrial Technology Centre of Nagasaki |
| 18.43. | JCB |
| 18.44. | JOZ |
| 18.45. | Kinov |
| 18.46. | Kinze Autonomy |
| 18.47. | Kongskilde Industries A/S (Kongskilde Vibro Crop Robotti) |
| 18.48. | KU Leuven |
| 18.49. | Lockheed Martin |
| 18.50. | Mahindra Group |
| 18.51. | Monosem |
| 18.52. | Monsanto |
| 18.53. | Nurfam |
| 18.54. | Pneubotics |
| 18.55. | Precision Planting LLC |
| 18.56. | Pulse Electronics |
| 18.57. | Queensland University of Technology(Agbot I and Agbot II) |
| 18.58. | Resonon |
| 18.59. | RoboPeak |
| 18.60. | Rowbot |
| 18.61. | SAC Milking |
| 18.62. | SAPOS |
| 18.63. | Schunk |
| 18.64. | SICK |
| 18.65. | Strauss Verpackungsmaschinen GmbH |
| 18.66. | Sumitomo Chemical |
| 18.67. | Syngenta |
| 18.68. | Topcon |
| 18.69. | University of Illinois |
| 18.70. | University of New South Wales |
| 18.71. | Vision Robots Corp |
| 18.72. | Wageningen University |
| 18.73. | Wall-Ye |
| 18.74. | Wasserbauer |
| 18.75. | Yamaha |
| TABLES AND FIGURES INCLUDE: | |
| Evolution of agricultural machinery from manual hoes through to robots | |
| Population growth between 1950 and 2050 segmented by development stage | |
| Income growth of developed and developing countries between 2005 and 2050 | |
| Expansion in global arable land between 1961 to 2050 in million ha | |
| Grain yield improvements by territory for wheat, maize and rice between 1950 to 2012 | |
| Share of labour force working in agriculture between 1300 to 2000 for England, Netherlands, Italy France and Poland | |
| Output per unit of labour in agriculture between 1961 to 2001 by country | |
| Global map of agricultural employment for 1980s, 1990s, 2000s, and 2010s | |
| Average age of principal farm operator in the USA between 192 to 2120 | |
| Average age of different farmer groups in Australia | |
| Correlation between minimum wage and GPD per person at PPP | |
| Minimum wage level in $/hr by country | |
| Real hourly wage for non-supervisory hired farm works in the US between 1990 and 2012 | |
| Technology roadmap showing progression from constant rate technology, to variable rate technology and now ultra-precision technology | |
| Existing and emerging value chain of agriculture showing how robotic technologies shift value away from traditional players | |
| Assessing the pros and cons of RaaS vs. equipment sale model | |
| Evolution of agriculture machinery from heavy, fast, large to light, slow and small | |
| Soil compaction depth as a function of year caused by increased vehicle weight | |
| Table showing that new robots need to be 24 times cheaper than traditional tractor models | |
| Market and technology readiness chart placing different agricultural robotic technology on levels ranging from proof-of-concept to fully maturity | |
| Market and technology readiness chart placing different agricultural robotic companies on levels ranging from proof-of-concept to fully maturity | |
| Technology roadmap showings technology progression from manned tractor to tractor guidance to manned autosteer to master-slave and to fully autonomous tractors | |
| Technology roadmap showing progress from manned aerial vehicles towards fully autonomous ultra-precision weeding | |
| Technology roadmap showings the progression of robotic technology in fresh fruit harvesting | |
| Ten-year market forecasts segmented by 14 agricultural robotics categories | |
| Number of tractors sold globally between 2010 and 2014 by country | |
| Number of tractors sold in the USA and Canada by horse power level between 2006 and 2015 | |
| Total value of crop production in $bn between 2009 and 2016 fir EU, USA, Brazil, CIS, China and India | |
| Table showing the number and average size of farms in USA, EU, Brazil, CIS, China and India | |
| Revenues in $bn of leading tractor suppliers including Yanmar, Deutz Fahr, Mihandra, AGCO, John Deere, Kubota Tractor Corp., CNN Industrial and so on | |
| 5- or 10-year annual sales for Kubota, John Deere, AGCO, Mihandra, CNH Industrial, Deutz Fahr and so on | |
| RTK GPS-enabled auto-steer technology | |
| Number of GNSS receivers in used agriculture between 2006 and 2023 segmented by tractor guidance, automatic steering, VRT and asset management | |
| Market value (in $m) for GNSS receivers used in agriculture between 2006 and 2023 segmented by tractor guidance, automatic steering, VRT and asset management | |
| Unit price ($/unit) of GNSS receivers used in agriculture between 2006 and 2023 segmented by tractor guidance, automatic steering, VRT and asset management | |
| Master-slave autonomous tractors by Yanmar, Fendt, Case IT, John Deere and Kinze Autonomy | |
| Fully autonomous tractors by Yanmar, Kubota Corp., and Autonomous Tractor Corp. | |
| Technology roadmap showings technology progression from manned tractor to tractor guidance to manned autosteer to master-slave and to fully autonomous tractors | |
| Ten-year market forcasts for tractor guidance, autosteer and fully autonomous tractors/combines | |
| Agbot II by QUT | |
| Kongskilde Vibro Crop Robotti by by Kongskilde Industries A/S and Conpleks Innovation. | |
| Astrix autonomous agricultural robot by Adigo | |
| Horibit autonomous agricultural robot by Aarhus University | |
| Ladybird autonomous agricultural robot by Australian Centre of Field Studies | |
| Autonomous tractors by the The Robot Fleers for Highly Effective Agriculture and Forestry Management project | |
| ATRV-2 | |
| Autonomous agricultural robot KU Leuven and FMTC | |
| Autonomous agricultural robot by Rowbot for cornfields | |
| Ten-year market forecasts for autonomous robotic data scouts | |
| Technology evolution from manual hoeing to large-scale broadcast spraying to unmanned drone spraying to manned weeding with high precision and finally to autonomous weeding with ultra-high precision | |
| Crop protection revenues for top ten global agrochemical suppliers including Monsanto, Sumitomo Chemical, Agricultural Solutions Ltd, DuPont, Bayer, Syngenta, BASF, DOW, Nufran | |
| Crop protection revenues for top 20 Chinease suppliers including Zheijang Wynca Chemical Industrial Group, Zhejiam Jinfanda BioChemical, Nutrichem, Sichuan Leshan Fuhua Tonga Agrochemical and so on | |
| 2014 and 2015 herbicide sales for Monsanto, Sumitomo Chemical, Agricultural Solutions Ltd, DuPont, Bayer, Syngenta, BASF, DOW, Nufran | |
| Revenue map of Top ten Chinese producers of glyphosate | |
| Historical data on global herbicide consumption in tonnes between 2004 and 2014 segmented by country | |
| Glyphosate global consumption in agricultural and non-agricultural activities between 1994 and 2014 in Kg | |
| Market size for glyphosate in $bn between 2004 and 20014 | |
| Historical growth in adoption of GE-HE seeds for major field crops such as soybeans, cotton, and corn | |
| Increase in the number of herbicide-resistant weed species between 1950 and today | |
| Total area in acres covered with herbicide-resistant weeds in the US between 1998 and 2014 | |
| Geographical spread of herbicide-resistant weeds in the US by state | |
| Autonomous robotic weeder | |
| Development of organic land in million ha | |
| Distribution of organic land between different uses | |
| Robotic weeding implements for organic farming | |
| Ten-year market forecast for robotic weeding by technology type | |
| Autonomous asparagus harvesting robots | |
| Autonomous lettuce thinning robots | |
| Ten-year market forecasts for robotic lettuce thinning and vegetable harvesting by technology and territory | |
| Non-fresh fruit harvesting machines | |
| Machines aiding manual fresh fruit harvesting | |
| Robotic bin follower | |
| Robotic orchard data scouts | |
| Emerging robotic fresh fruit harvest assist technologies | |
| Robotic fresh apple harvesting | |
| Robotic fresh citrus harvesting | |
| Fresh fruit harvesting robots | |
| Addressable market size for robotic fresh apple-picking service provision | |
| Ten-year market forecasts for robotic fresh citrus/apple harvesting by territory | |
| Robotic fresh strawberry harvesting | |
| Addressable market size for robotic fresh strawberry-picking service provision | |
| Ten-year market forecasts for robotic fresh strawberry harvesting by territory | |
| Autonomous robotic vineyard scouts and pruners | |
| Autonomous robotics for greenhouses and nurseries | |
| Schematic showing the concept of VRT for seed planting | |
| Robotic seed planting | |
| Map of average dairy farm sizes worldwide | |
| Average size and number of dairy farms in the US between 1970 and 2007 | |
| Global number and distribution of dairy cows by country | |
| Addressable market for robotic milking machines by country | |
| Addressable market for robotic feed pushers by country | |
| Lely's robotic milking machine | |
| Robotic milking machines | |
| Autonomous robotic feed pushers | |
| Robotic manure cleaning | |
| Alternatives to autonomous robotic feed pushers | |
| Autonomous robotic shepherds | |
| Ten-year market forecasts for robotic milking systems by country | |
| Ten-year market forecasts for automatic feed pusher and other mobile robotics in dairy farming | |
| Table comparing the resolution, image acquisition cost, image processing cost and minimum order size for satellite imaging | |
| Annual sales of unmanned spraying helicopters in Japan | |
| Area of rice paddies in Japan sprayed by unmanned helicopters between in Ha | |
| Unmanned drones and helicopters for field spraying | |
| Unmanned agriculture drones on the market | |
| Table comparing different agricultural drones on the market on the basis of price, type, autonomy, cruise speed, flight time and so on | |
| Agricultural drones: the emerging value chain | |
| Core company information on key agricultural drone companies | |
| Ten-year market forecasts for agricultural drones | |
| Suction-based end effectors by Vision Robotics | |
| Suction-based end effectors by Abundant Robotics | |
| Other novel end-effectors in development | |
| Soft robotic grippers by Soft Robotics, Festo, Empire Robotic, Pneubotics | |
| Dexterous robotic by Shadow Robotics, Schunk, Allegro, Willow Garage and so on | |
| Value chain of RTK GPS Technology from signal service provides to receiver manufacturers to device vendors to tractor companies | |
| Performance levels of DGPS, OmniStar XP/HP and RTK technologies | |
| Basic operational mechanism of LIDAR | |
| LIDAR examples | |
| Table comparing the performance of different LIDARs on the market or in development | |
| Table assessing suitability of different LIDAR for agricultural robotic applications | |
| Hyperspectral imaging and precision agriculture | |
| Hyperspectral imaging sensors on the market | |
| Common multi-spectral sensors used with agricultural drones | |
| Ten-year market forecasts for all agricultural robots and drones segmented by type and/or function | |
| Ten-year market forecasts for agricultural robots and drones segmented by type and/or function | |
| Ten-year market forecasts for autonomous and mobile agricultural robots and drones segmented by type and/or function | |
| Ten-year market forecasts for tractor guidance, autosteer and fully autonomous tractors/combines | |
| Ten-year market forecasts for autonomous robotic data scouts | |
| Ten-year market forecast for robotic weeding by technology type | |
| Ten-year market forecasts for robotic lettuce thinning and vegetable harvesting by technology and territory | |
| Ten-year market forecasts for robotic fresh citrus/apple harvesting by territory | |
| Ten-year market forecasts for robotic fresh strawberry harvesting by territory | |
| Ten-year market forecasts for robotic milking systems by country | |
| Ten-year market forecasts for automatic feed pusher and other mobile robotics in dairy farming | |
| Ten-year market forecasts for agricultural drones |
A complex market reaching $10bn as early as 2022
Report Statistics
| Slides | 163 |
|---|---|
| Companies | 140+ |
| Forecasts to | 2027 |
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