IoT Applications in the Agricultural Industry - 3rd Edition

Table of Contents

Table of Contents

List of Figures

Executive Summary

1. The Agricultural Sector

• 1.1. Agricultural production
  • 1.1.1. Agricultural land use
  • 1.1.2. Irrigated area and irrigation methods
  • 1.1.3. Employment in agriculture
  • 1.1.4. Forestry
  • 1.1.5. The food and agribusiness value chain
• 1.2. Agricultural commodities
• 1.3. Demand for agricultural commodities
  • 1.3.1. Population growth and economic development
  • 1.3.2. Consumption of agricultural products
• 1.4. Agricultural operations
  • 1.4.1. Farm income and capital expenditures
  • 1.4.2. Mixed crop-livestock farming
  • 1.4.3. Crop farming
  • 1.4.4. Livestock farming
• 1.5. Agricultural equipment

2. Smart Farming Technologies and Solutions

• 2.1. Smart farming infrastructure
  • 2.1.1. Farm equipment segment
  • 2.1.2. Field segment
  • 2.1.3. Livestock segment
  • 2.1.4. Drone segment
  • 2.1.5. Satellite segment
  • 2.1.6. Network segment
  • 2.1.7. Backoffice segment
• 2.2. Machinery management
  • 2.2.1. Vehicle diagnostics and maintenance planning
• 2.3. Precision agriculture
  • 2.3.1. Guidance and automated steering
  • 2.3.2. Yield monitoring and mapping
  • 2.3.3. Precision seeding
  • 2.3.4. Precision fertilising
  • 2.3.5. Precision spraying
• 2.4. Remote sensing
  • 2.4.1. Aerial imagery
• 2.5. Remote monitoring and control
  • 2.5.1. Environmental monitoring
  • 2.5.2. Pest monitoring
  • 2.5.3. Water management
• 2.6. Precision livestock farming
  • 2.6.1. Pig management
  • 2.6.2. Poultry management
  • 2.6.3. Beef cattle management
  • 2.6.4. Dairy herd management
• 2.7. Data management and predictive analysis
• 2.8. Business models and strategies

3. Market Forecasts and Trends

• 3.1. Market analysis
  • 3.1.1. Installed base and unit shipments
  • 3.1.2. Regional markets
  • 3.1.3. Wireless technologies
  • 3.1.4. Precision agriculture
  • 3.1.5. In-field monitoring and control
  • 3.1.6. Dairy herd management
• 3.2. Market drivers and barriers
  • 3.2.1. Macroeconomic environment
  • 3.2.2. Regulatory environment
  • 3.2.3. Competitive environment
  • 3.2.4. Technology environment
• 3.3. Value chain analysis
  • 3.3.1. Input industry players
  • 3.3.2. Farm equipment industry players
  • 3.3.3. Precision farming industry players
  • 3.3.4. Dairy equipment industry players
  • 3.3.5. Telecom industry players
  • 3.3.6. M&A activity along the smart farming value chain
• 3.4. Market trends
  • 3.4.1. The emerging digital ecosystem requires a shift towards collaboration
  • 3.4.2. Larger herds drive the adoption of precision livestock farming technologies
  • 3.4.3. IoT start-ups attract significant venture capital investments
  • 3.4.4. System integration and interoperability are high on the agenda
  • 3.4.5. Dealerships remain as gateways to customers
  • 3.4.6. OEMs likely to extend free telematics subscription periods
  • 3.4.7. Freemium strategies will intensify competition between software vendors
  • 3.4.8. Autonomy will play a significant role in agricultural operations

4. OEM Products and Strategies

• 4.1. AGCO
• 4.2. ARGO Tractors
• 4.3. CLAAS Group
• 4.4. CNH Industrial
• 4.5. Deere & Company
• 4.6. Komatsu
• 4.7. Krone
• 4.8. Kubota
• 4.9. Mahindra & Mahindra
• 4.10. Ponsse
• 4.11. Rottne
• 4.12. SDF
• 4.13. Tigercat
• 4.14. Vermeer

5. Aftermarket Solution Providers

• 5.1. Precision farming
  • 5.1.1. Ag Leader Technology
  • 5.1.2. Agjunction
  • 5.1.3. DICKEY-john
  • 5.1.4. Farmers Edge
  • 5.1.5. Hexagon
  • 5.1.6. Lacos
  • 5.1.7. Raven Industries
  • 5.1.8. Topcon Positioning Systems
  • 5.1.9. Trimble
  • 5.1.10. UniStrong
  • 5.1.11. Yara
• 5.2. Agricultural drones
  • 5.2.1. AgEagle
  • 5.2.2. Aonic
  • 5.2.3. DJi
  • 5.2.4. Draganfly
  • 5.2.5. Hylio
  • 5.2.6. Jiyi
  • 5.2.7. Sentera
  • 5.2.8. TTA
  • 5.2.9. Wingtra
  • 5.2.10. XAG
• 5.3. Environmental and pest monitoring
  • 5.3.1. Campbell Scientific
  • 5.3.2. Davis Instruments
  • 5.3.3. Fieldin
  • 5.3.4. Prointegra
  • 5.3.5. Pessl Instruments
  • 5.3.6. Semios
  • 5.3.7. Sencrop
  • 5.3.8. Trapview
  • 5.3.9. Weenat
• 5.4. Water management
  • 5.4.1. Arable Labs
  • 5.4.2. AquaSpy
  • 5.4.3. CropX
  • 5.4.4. EarthScout
  • 5.4.5. Hortau
  • 5.4.6. Libelium
  • 5.4.7. Lindsay Corporation
  • 5.4.8. Netafim
  • 5.4.9. Pycno
  • 5.4.10. Rivulis
  • 5.4.11. Valmont Industries
• 5.5. Dairy herd management
  • 5.5.1. Afimilk
  • 5.5.2. BouMatic
  • 5.5.3. CowManager
  • 5.5.4. Dairymaster
  • 5.5.5. Datamars
  • 5.5.6. DeLaval
  • 5.5.7. Farmnote
  • 5.5.8. Fullwood JOZ
  • 5.5.9. GEA Group
  • 5.5.10. Lely
  • 5.5.11. Merck
  • 5.5.12. Moocall
  • 5.5.13. Nedap
  • 5.5.14. Stellapps
  • 5.5.15. Zoetis
• 5.6. Agricultural software
  • 5.6.1. 365FarmNet
  • 5.6.2. Agrivi
  • 5.6.3. BASF
  • 5.6.4. Bushel
  • 5.6.5. The Climate Corporation (Bayer)
  • 5.6.6. Conservis
  • 5.6.7. Corteva Agriscience
  • 5.6.8. Cropin
  • 5.6.9. DKE-Data
  • 5.6.10. Farmers Business Network
  • 5.6.11. Isagri
  • 5.6.12. Proagrica
  • 5.6.13. Syngenta
  • 5.6.14. Telus Agriculture & Consumer Goods
• List of Acronyms and Abbreviations

List of Figures

• Figure 1.1: Area and yield trend for wheat, rice, soybean and corn (World 2022)
• Figure 1.2: Moving 10-year average growth in crop yield (World 2022)
• Figure 1.3: Land use and agricultural land (World 2021)
• Figure 1.4: Top ten countries by planted area (World 2021)
• Figure 1.5: Employment in agriculture (2021)
• Figure 1.6: The agribusiness value chain
• Figure 1.7: Major crop production statistics (World 2022)
• Figure 1.8: Leading producers of major crops (World 2022)
• Figure 1.9: Meat and milk production statistics (World 2022)
• Figure 1.10: Live animal stock (World 2021)
• Figure 1.11: Agricultural commodity prices (2000-2023)
• Figure 1.12: Population in billion (World)
• Figure 1.13: Use of cereal grains (World 2022)
• Figure 1.14: Examples of agricultural equipment
• Figure 1.15: Example of central-pivot irrigation equipment
• Figure 2.1: Smart farming infrastructure overview
• Figure 2.2: ISOBUS connector
• Figure 2.3: Real-Time Kinematic correction service with drones
• Figure 2.4: Example of smart farming backoffice segment
• Figure 2.5: Example of a yield monitor
• Figure 2.6: Example of a yield map
• Figure 2.7: Example of a tractor-mounted crop sensor
• Figure 2.8: Example of a crop spraying drone
• Figure 2.9: Example of an in-field weather station
• Figure 2.10: Examples of monitored variables in precision livestock farming
• Figure 2.11: Examples of AMS and AMR milking robots
• Figure 2.12: Wearable devices for cattle monitoring
• Figure 3.1: Unit shipments and installed base by segment (World 2022-2027)
• Figure 3.2: Unit shipments and installed base by region (World 2022-2027)
• Figure 3.3: Unit shipments and installed base by technology (World 2022-2027)
• Figure 3.4: Precision agriculture market value (World 2022-2027)
• Figure 3.5: Agricultural drones market value (World 2022-2027)
• Figure 3.6: Livestock activity monitoring solutions market value (World 2022-2027)
• Figure 3.7: AgGateway's ADAPT framework
• Figure 3.8: Revenues of top providers of crop protection chemicals and seeds
• Figure 3.9: Financial data for farm equipment companies active in precision agriculture
• Figure 3.10: Financial data for precision technology companies
• Figure 3.11: Financial data for top providers of dairy equipment
• Figure 3.12: Top 10 mobile operators by IoT connections (World Q4-2022)
• Figure 3.13: M&A activity among companies active in smart farming (2020-2021)
• Figure 3.14: M&A activity among companies active in smart farming (2021-2023)
• Figure 3.15: Total funding in FMS, sensing and IoT start-ups (2015-2022)
• Figure 4.1: Precision Planting - Panorama data app
• Figure 4.2: CLAAS Group's CEMIS 1200 display
• Figure 4.3: AGXTEND's NirXact hardware
• Figure 4.4: The John Deere connectivity family
• Figure 4.5: John Deere Precision Forestry including JDLink
• Figure 4.6: Kubota Precision Farming products
• Figure 4.7: Overview of SDF Smart Farming Solutions
• Figure 4.8: Tigercat telematics - RemoteLog and LogOn
• Figure 4.9: Vermeer Telematics interface
• Figure 5.1: Ag Leader Technology's InCommand 1200
• Figure 5.2: Hexagon's HxGN AgrOn Core Box
• Figure 5.3: Raven Industries' Slingshot Field Hub 2.1
• Figure 5.4: Topcon Positioning Systems' CL-55 cloud connectivity device
• Figure 5.5: Trimble's R750 Modular GNSS Receiver
• Figure 5.6: Hemisphere GNSS' Atlas correction service
• Figure 5.7: Yara's N-Sensor ALS 2
• Figure 5.8: AgEagle's eBee Ag Drone for aerial imagery
• Figure 5.9: DJI's Agras T40 crop spraying drone
• Figure 5.10: Hylio's crop spraying drone
• Figure 5.11: Sentera's PHX fixed-wing drone for aerial imagery
• Figure 5.12: TTA's M6E-G300 crop spraying drone
• Figure 5.13: The WingtraOne Gen II VTOL drone for aerial imagery
• Figure 5.14: XAG's P Series crop spraying drone
• Figure 5.15: Davis Instruments' Vantage Pro2 GroWeather Sensor Suite
• Figure 5.16: Pessl Instruments' iMETOS 3.3 weather station
• Figure 5.17: Semois' remote monitoring platform
• Figure 5.18: Sencrop's Raincrop connected weather station
• Figure 5.19: Trapview's insect trap for pest monitoring and control
• Figure 5.20: The Arable Mark 3 sensor system
• Figure 5.21: CropX's farm management system
• Figure 5.22: Libelium One IoT gateway
• Figure 5.23: The Zimmatic 712C control panel
• Figure 5.24: Netafim's irrigation operating system GrowSphere
• Figure 5.25: Pycno's soil moisture sensors network
• Figure 5.26: Valley 365 platform modules
• Figure 5.27: Afimilk's AfiAct II leg-mounted monitoring solution
• Figure 5.28: CowManager's herd management system
• Figure 5.29: The DeLaval Plus farm management system
• Figure 5.30: GEA Group's CowScout collar
• Figure 5.31: Moocall's tail-mounted Calving Sensor
• Figure 5.32: The 365Active solution
• Figure 5.33: Xarvio Connect's workflow
• Figure 5.34: DKE-Data's Agrirouter