China Smart Agriculture and Autonomous Agricultural Machinery Market Report, 2022
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Research on smart agriculture and autonomous agricultural machinery: top-level design, agricultural digitization and automation present a potential market

Amid the pandemic, the conflict between Russia and Ukraine has directly led to a reduction in global food production, which will exacerbate the global instability. Since 2022, the FAO (Food and Agriculture Organization) Food Price Index (FFPI) of has been soaring.

The No.1 central document, which is issued by China's central authorities in 2022, pointed out, "We must firmly hold the bottom lines of guaranteeing China's grain security and ensuring there will be no large-scale return to poverty." It also called for greater efforts in the construction of digital villages, development of smart agriculture, as well as integrated application of information technology, agricultural machinery and agronomy. The outline of the "14th Five-Year Plan" mentioned that it is necessary to accelerate the development of smart agriculture and promote the digital transformation of agricultural production, operation and management services. The government’s work report in 2022 stipulated "the development of digital villages" for the first time, signaling an important way to realize the modernization of agriculture and rural areas.

The CAGR of China's smart agriculture market size exceeds 14.1%, and agricultural digitalization generates a potential market

It is estimated that by 2025, the total output value of smart agriculture in the world will reach USD68.389 billion. In Asia-Pacific, the fastest growing region, smart agriculture mainly includes precision agriculture in fields, smart animal husbandry, smart fishery, and smart greenhouses; main technologies include remote sensing and sensor systems, agricultural big data and cloud service technology, intelligent agricultural equipment (UAVs, robots).

According to UN projections on population and hunger, the global population will increase by 2 billion by 2050, and agricultural productivity will need to increase by 60% to provide adequate food. Artificial intelligence and machine learning are likely to be at the core of new technologies to help close the gap in anticipated food needs for an additional 2 billion people worldwide by 2050. Global spending on connected smart farming technologies and systems, including artificial intelligence and machine learning, will grow significantly in the future.


In China, the increasing demand for modern agricultural machinery and the continuous R&D and application of new technologies will promote the sustained and rapid growth of the smart agriculture market. Driven by stimuli such as the national rural revitalization strategy and the national digital agriculture strategy, a potential agriculture market appeals to giants like Alibaba,, Baidu, and Tencent that have deployed smart agriculture to promote the construction of smart agriculture in China.

Smart agriculture is the starting point of rural revitalization. The encouragement and benefits at the macro level have spurred a large number of technology companies to smart agriculture, covering all sectors ranging from production to marketing. More and more technology start-ups bring a lot of capital while flocking into smart agriculture construction.



In the future, smart agriculture will see rapid growth under the influence of favorable policies, application of innovative technologies and capital support.

Smart agriculture is widely used at the micro level, with the top-level design in the planning and design stage

When it comes to smart agriculture, agricultural planting is in the spotlight. The main technologies involved herein include intelligent water and fertilizer integration, agricultural IoT monitoring, satellite remote sensing/meteorology/UAV-based aerial surveys with remote sensing, plant protection UAVs, autonomous agricultural machinery, and plant chemical factories. However, smart agriculture is far more than just agricultural planting where application cases are ubiquitous.

Smart agriculture covers the entire industrial chain of agricultural production, distribution and marketing, mainly including four application scenarios: digital agriculture (data platform services), plant protection UAVs, precision agriculture, and autonomous agricultural machinery. It is widely used in agricultural planting and animal husbandry. Wherein, data platform services and plant protection UAVs account for 75% of the total.


In China, there are many smart agriculture projects, and UAVs and autonomous agricultural machinery have developed rapidly. Chinese products can compete with foreign counterparts. The development potential of UAVs and autonomous agricultural machinery is enormous. However, China is still planning smart agriculture with the ongoing top-level design:

20120114.gifThe construction of big data platforms is relatively late: the Big Data Center of the Ministry of Agriculture and Rural Affairs of China (MARA) was established in 2021. The top-level design of China's agricultural and rural big data system construction has entered the stage of practical operation; by contrast, foreign agricultural big data platforms have developed for more than ten years, for example, the United States started building agricultural informatization in the 1950s, and supported smart agriculture through the establishment of agricultural informatization systems and agricultural databases with the state as the entity.

20120114.gifThe top-level design of digital villages is being planned: since 2021, domestic local governments and Internet companies have launched their own top-level design for digital villages, such as 2021 Pukou’s suburban digital villages, Tencent’s top-level design for digital villages, the overall architecture of Alibaba Cloud Big Data Center, Tencent's digital village system architecture, China Unicom's overall digital village architecture, and Huawei's overall business architecture for digital agriculture and rural areas. The top-level design has not yet been implemented. Mostly, the projects about autonomous planting, breeding and regional big data analysis platforms have been performed.

20120114.gifThe UAV market is highly concentrated: 160,000 agricultural UAVs existed in China in 2021 with a year-on-year increase of 60%, and they served over 1.4 billion mu of land. DJI and XAG occupy more than 90% market share.

20120114.gifThe pattern of autonomous agricultural machinery industry is unsettled: China’s best-selling autonomous agricultural machinery systems in 2021 included those from Heilongjiang Huida Technology Development Co., Ltd., Shanghai CHCNAV Co., Ltd. and Hunan Xiangshu Big Data Technology Co., Ltd. which adopted the BeiDou Navigation Satellite System. In 2021, the sales pattern of the BeiDou Navigation Satellite System changed significantly, and the dark horse sprung up, as a result of the sharp drop in the price of automatic navigation equipment.

Autonomous agricultural machinery has seen a higher sales volume but a lower price. It is experiencing a mature development period, with the market penetration rate swelling
In recent years, China's autonomous agricultural machinery systems have developed radically. They have been just applied in northern regions (Xinjiang and Heilongjiang), while they are still in the germination stage in other areas of China where the farmland scale is moderate. Despite the regional imparity, China's autonomous agricultural machinery systems as a whole have been growing swiftly.

More than 65,000 sets of the BeiDou Navigation Satellite System had been deployed for agricultural machinery as of 2021 when China might boast over 4.6 million domestic large and medium-sized agricultural tractors, which means the penetration rate of autonomous agricultural machinery systems was 1.4%. Among agricultural machinery, tractors are the first that realize autonomous driving in China. It is expected that the penetration rate of autonomous agricultural machinery systems will reach 6.5% by 2025 and about 20% by 2035.

The penetration rate of autonomous agricultural machinery systems in China is much lower than that in Europe and the United States. The EU plans to have 50% of agricultural machinery equipped with automatic navigation driving systems by 2025. According to Purdue University, the penetration rate of automatic navigation for agricultural machinery in the US hit 90% in 2019.


In 2020, the average price of autonomous agricultural machinery systems and equipment in China was RMB50,000-60,000 per set. In 2021, the substantial reduction in the subsidy standard dragged down the average price of automatic navigation equipment to only RMB36,000 per set.

With the completion of the ground base station network and the improvement of agricultural electrical control systems, the price of China's autonomous agricultural machinery systems and equipment will decline slowly in the future, may be less than RMB25,000 per set by 2025. 

In March 2022, China Association of Agricultural Machinery Manufacturers, China Agricultural Mechanization Herald, and China Agricultural Machinery Distribution Association jointly released the 2021 Best-selling Agricultural Machinery List (by the sales volume of subsidized agricultural machinery as of December 31, 2021), honoring Heilongjiang Huida Technology Development Co., Ltd., Shanghai CHCNAV Co., Ltd. and Hunan Xiangshu Big Data Technology Co., Ltd. which adopted the BeiDou Navigation Satellite System, as well as praising Heilongjiang Huida Technology Development Co., Ltd., Golden Field Technology Co., Ltd. and Beijing Agricultural Intelligent Equipment Technology Research Center for their best-selling agricultural operation monitoring terminals.

Chapter 1 Overview of Smart Agriculture and Autonomous Agricultural Machinery

1.1 Overview of Smart Agriculture
1.1.1 Development Stages of Agriculture
1.1.2 Definition of Smart Agriculture
1.1.3 Composition of Smart Agriculture
1.1.4 Smart Agriculture Industry Chain
1.1.5 Development Prospects of Smart Agriculture

1.2 Development of Autonomous Agricultural Machinery
1.2.1 Definition and Classification of Agricultural Machinery
1.2.2 Overview of Autonomous Agricultural Machinery
1.2.3 Autonomous Agricultural Machinery Industry Chain
1.2.4 Importance of Autonomous Agricultural Machinery Development

1.3 Policies Related to Smart Agriculture
1.3.1 The China Agricultural Outlook Report (2022-2031)
1.3.2 Guidance of the No.1 Central Document on Smart Agriculture in Years 
1.3.3 Policies Related to Integrated Development of Smart Agriculture
1.3.4 Land Transfer Policies and Trends
1.3.5 Key Tasks for China's Smart Agriculture Construction in 2022
1.3.6 China's Agricultural Mechanization Policy
1.3.7 New Ideas, New Measures and New Progress of China's Agricultural Machinery Development in 2021

1.4 Policies Related to Autonomous Agricultural Machinery
1.4.1 China's Policies Related to Autonomous Agricultural Machinery
1.4.2 China's Autonomous Agricultural Machinery System Standardization Policy (2014-2020)
1.4.3 China's Agricultural Autonomous Driving System Standardization Policy (2021-2022) (1)
1.4.4 China's Agricultural Autonomous Driving System Standardization Policy (2021-2022) (2)
1.4.5 China's Autonomous Agricultural Machinery System Subsidy Policy
1.4.6 China's Autonomous Agricultural Machinery System Subsidy Standard
1.4.7 Beidou Satellite Network Helps the Development of Autonomous Agricultural Machinery
1.4.8 Technology Roadmap of Intelligent Agricultural Machinery
1.4.9 Development Direction of Autonomous Agricultural Machinery

Chapter 2 Status Quo of Smart Agriculture and Autonomous Agricultural Machinery Market

2.1 Status Quo of Global and Chinese Smart Agriculture
2.1.1 Overview of Global Smart Agriculture Development
2.1.2 Smart Agriculture Development in the United States
2.1.3 Smart Agriculture Development in Japan
2.1. Global Smart Agriculture Market Size
2.1.5 Major Smart Agricultural Technologies in the World
2.1.6 Smart Agriculture is the Most Promising Application Scenario of Artificial Intelligence and Machine Learning (1)
2.1.7 Smart Agriculture is the Most Promising Application Scenario of Artificial Intelligence and Machine Learning (2)
2.1.8 Smart Agriculture is the Most Promising Application Scenario of Artificial Intelligence and Machine Learning (3)
2.1.9 Main Investment Directions of Global Smart Agriculture

2.2 Status Quo of Smart Agriculture in China
2.2.1 Necessity of Developing Smart Agriculture in China
2.2.2 Smart Agriculture Industry Chain in China
2.2.3 Key Technologies and System Composition of Smart Agriculture in China
2.2. China’s Smart Agriculture Market Size
2.2.5 China's Agricultural Mechanization Rate Is Increasing Year by Year
2.2.6 Smart Agriculture Application Projects and Development Trends in China
2.2.7 Number of Registered Smart Agriculture Enterprises
2.2.8 Smart Agriculture Service Providers in China
2.2.9 Competitive Landscape of Smart Agriculture Market in China

2.3 Status Quo of Global and Chinese Autonomous Agricultural Machinery
2.3.1 Development History of Global Autonomous Agricultural Machinery
2.3.2 Status Quo of Autonomous Agricultural Machinery in the United States
2.3.3 Status Quo of Autonomous Agricultural Machinery in Japan
2.3.4 Development Stages of Autonomous Agricultural Machinery in China
2.3.5 Status Quo of Autonomous Agricultural Machinery in China 

2.4 China's Autonomous Agricultural Machinery Market Size
2.4.1 China's Agricultural Machinery Ownership
2.4.2 Sales Volume of China's Autonomous Agricultural Machinery Systems
2.4.3 China's Autonomous Agricultural Machinery System Market Size
2.4.4 Penetration Rate of Autonomous Agricultural Machinery Systems in China
2.4.5 Cost Estimation of Autonomous Agricultural Machinery Systems in China

2.5 Competitive Landscape of China's Autonomous Agricultural Machinery Industry
2.5.1 Competitive Landscape of China's Autonomous Agricultural Machinery Industry
2.5.2 Ranking of Autonomous Agricultural Machinery Systems in China by Sales Volume
2.5.3 Recent Financing and Cooperation of Autonomous Agricultural Machinery Enterprises in China
2.5.4 Project Implementation of Autonomous Agricultural Machinery Enterprises in China
2.5.5 Competitive Landscape of Xinjiang's Autonomous Agricultural Machinery Industry in 2021
2.5.6 Price of Autonomous Agricultural Machinery in China
2.5.7 Main Product Comparison of Autonomous Agricultural Machinery System Enterprises in China (1)
2.5.8 Main Product Comparison of Autonomous Agricultural Machinery System Enterprises in China (2)

2.6 China’s Agricultural UAV Market Size and Competitive Landscape 
2.6.1 China's Agricultural UAV Ownership
2.6.2 Penetration Rate of Agricultural UAVs in China
2.6.3 Operating Area of Agricultural UAVs in China
2.6.4 Application Scenarios and Operational Advantages of Agricultural UAVs
2.6.5 Performance and Features of Agricultural UAVs in China 
2.6.6 Plant Protection Efficiency of Agricultural UAVs in China 
2.6. 2.6 Competitive Landscape of China’s Agricultural UAV Market
2.6.8 Development Direction of China's Agricultural UAV Technology

2.7 Development Trends of Autonomous Agricultural Machinery
2.7.1 Advantages of Autonomous Agricultural Machinery
2.7.2 Constraints on Application of Autonomous Agricultural Machinery
2.7.3 Development Trends of Autonomous Agricultural Machinery Technology
2.7.4 A Development Trends of Autonomous Agricultural Machinery Market
2.7.5 Challenges in Promotion of Autonomous Agricultural Machinery

Chapter 3 Smart Agriculture System Solutions and Cases

3.1 Smart Agriculture System Solutions
3.1.1 Smart Agriculture Platform Architecture
3.1.2 IoT-based Smart Agriculture System
3.1.3 IoT-based Smart Agriculture System: Sensing Layer
3.1.4 Smart Agriculture System Functions (1)
3.1.5 Smart Agriculture System Functions (2)
3.1.6 Smart Agriculture System Functions (3)
3.1.7 Smart Agriculture System Functions (4)

3.2 Application Scenarios of Smart Agriculture
3.2.1 Application Scenarios of Smart Agriculture
3.2.2 Application Scenarios of Smart Agriculture - Digital Agriculture
3.2.3 Application Scenarios of Smart Agriculture - Development Direction of Digital Agriculture
3.2.4 Application Scenarios of Smart Agriculture - Agricultural Big Data Platforms
3.2.5 Application Scenarios of Smart Agriculture - Digital Agriculture (Production Digitization/Data Platform Services)
3.2.6 Application Scenarios of Smart Agriculture - Digital Agriculture (Production Digitization/Data Platform Services) Cases
3.2.7 Application Scenarios of Smart Agriculture - Digital Agriculture (Distribution/Sales Digitization)
3.2.8 Application Scenarios of Smart Agriculture - Plant Protection by Agricultural UAVs (1)
3.2.9 Application Scenarios of Smart Agriculture - Plant Protection by Agricultural UAVs (2)
3.2.10 Application Scenarios of Smart Agriculture - Plant Protection by Agricultural UAVs (3)
3.2.11 Application Scenarios of Smart Agriculture - Plant Protection by Agricultural UAVs (4)
3.2.12 Application Scenarios of Smart Agriculture - Precision Agriculture (Fine Farming)
3.2.13 Application Scenarios of Smart Agriculture - Smart Greenhouses

3.3 Agricultural Custody Service Solutions
3.3.1 Proportion and Trends of Household Land Transfer in China
3.3.2 China's Agricultural Custody Service (Plowing, Planting, Management and Harvesting) Market Size
3.3.3 Agricultural Custody Service (Plowing, Planting, Management and Harvesting) Solutions
3.3.4 Agricultural Custody Service (Plowing, Planting, Management and Harvesting) Solutions: Wheat
3.3.5 Agricultural Custody Service (Plowing, Planting, Management and Harvesting) Solutions: Corn
3.3.6 Agricultural Production Custody Service Models
3.3.7 Agricultural Custody Service (Plowing, Planting, Management and Harvesting) Cases (1)
3.3.8 Agricultural Custody Service (Plowing, Planting, Management and Harvesting) Cases (2)
3.3.9 Agricultural Custody Service (Plowing, Planting, Management and Harvesting) Cases (3)

3.4 Smart Agriculture Infrastructure
3.4.1 Infrastructure for Autonomous Agricultural Machinery - High-standard Farmland
3.4.2 Infrastructure for Autonomous Agricultural Machinery - Smart Irrigation

3.5 Huawei
3.5.1 Business Architecture for Digital Agriculture and Rural Areas
3.5.2 Development Stages of Smart Agriculture
3.5.3 Smart Agriculture Solution Architecture
3.5.4 Terminal Platform: Big Data of Agriculture and Rural Areas
3.5.5 Management Platform: NB-IoT Empowers Agricultural Digitalization
3.5.6 Edge Computing: Digital Farmland
3.5.7 Cloud Platform: Agricultural Fertile Soil Platform
3.5.8 AI Platform: End-to-End ICT Solutions
3.5.9 Cases of Smart Agriculture

3.6 Meituan
3.6.1 Smart Agriculture Solutions (1)
3.6.2 Smart Agriculture Solutions (2)

3.7 Tencent
3.7.1 Overall Solution for Digital Rural Areas
3.7.2 Smart Agriculture Solutions
3.7.3 AI+ Smart Agriculture Solutions (1)
3.7.4 AI+ Smart Agriculture Solutions (2)
3.7.5 AI+ Smart Agriculture Solutions (3)

3.8.1 Smart Agriculture Solutions
3.8.2 Digital Farm Management and Control System
3.8.3 Cooperative Farm Bases

3.9 Baidu
3.9.1 Smart Agriculture Solutions
3.9.2 Smart Agriculture IoT Platform
3.9.3 AI Grows Vegetables

3.10 Alibaba
3.10.1 Development History of Smart Agriculture 
3.10.2 Smart Agriculture Architecture
3.10.3 Smart Agriculture Solutions
3.10.4 ET Agricultural Brain
3.10.5 ET Agricultural Brain Architecture
3.10.6 Smart Agriculture Projects (1)
3.10.7 Smart Agriculture Projects (2)
3.10.8 Digital Agriculture Platform

3.11 Lenovo
3.11.1 Smart Agriculture Solutions

3.12 Country Garden
3.12.1 Smart Farms
3.12.2 Smart Agriculture Projects
3.12.3 Smart Agriculture - Baoshan Agricultural Science and Technology Park
3.12.4 Development Trends of Smart Agriculture

3.13 Bayer
3.12.1 Smart Agriculture Solutions
3.12.2 Smart Agriculture Data Platform

Chapter 4 Autonomous Agricultural Machinery Technology Solutions and Cases

4.1 Introduction to Autonomous Agricultural Machinery Technology Solutions
4.1.1 Autonomous Agricultural Machinery Systems: System Architecture Based on Dual Antenna RTK-GNSS Positioning
4.1.2 Autonomous Agricultural Machinery Enterprises: Real-time Control and Management of Agricultural Machinery Connected to Internet of Vehicles by Means of Platform Services

4.2 Perception Solutions of Autonomous Agricultural Machinery
4.2.1 Autonomous Agricultural Machinery Systems: Navigation Positioning and Environment Perception Technology Based on Multi-source Information Fusion
4.2.2 Perception Solutions of Autonomous Agricultural Machinery Systems: Satellite Positioning System
4.2.3 Perception Solutions of Autonomous Agricultural Machinery Systems: Machine Vision Navigation
4.2.4 Perception Solutions of Autonomous Agricultural Machinery Systems: Obstacle Detection and Recognition

4.3 Decision-making Solutions of Autonomous Agricultural Machinery
4.3.1 Decision-making Solutions of Autonomous Agricultural Machinery: Route Planning
4.3.2 Decision-making Solutions of Autonomous Agricultural Machinery: Path Tracking and Control
4.3.3 Decision-making Solutions of Autonomous Agricultural Machinery: Bus integration technology
4.3.4 Decision-making Solutions of Autonomous Agricultural Machinery: Agricultural IoT

4.4 Action Solutions of Autonomous Agricultural Machinery
4.4.1 Controller Solutions for Autonomous Agricultural Machinery Actuators
4.4.2 Control Method Comparison of Autonomous Agricultural Machinery Actuators
4.4.3 Competitive Landscape of Control Methods of Autonomous Agricultural Machinery Actuators
4.4.4 Summary of Control Methods of Autonomous Agricultural Machinery Actuators

4.5 Infrastructure for Autonomous Agricultural Machinery
4.5.1 Infrastructure for Autonomous Agricultural Machinery Systems - Base Stations
4.5.2 Infrastructure for Autonomous Agricultural Machinery Systems - Beidou Ground-based Augmentation System (CORS System)
4.5.3 Agricultural Autonomous Driving System Infrastructure - Composition of Beidou Ground-based Augmentation System (CORS System)
4.5.4 Agricultural Autonomous Driving System Infrastructure - Working Principles of Beidou Ground-based Augmentation System (CORS System)
4.5.5 Infrastructure for Autonomous Agricultural Machinery Systems - Advantages of Beidou Ground-based Augmentation System (CORS System)

4.6 Unmanned Farm Projects in China
4.6.1 Unmanned Farm rojects in China
4.6.2 Zengcheng Teaching and Research Base of South China Agricultural University - Academician Luo Xiwen Unmanned Farm
4.6.3 Beidahuang Sanjiang Unmanned Farm Project
4.6.4 “Full-process Unmanned Agricultural Operation Pilot Project” of Xinghua City, Jiangsu Province
4.6.5 “Unmanned Farm” in Wangcheng District, Changsha City, Hunan Province

4.7 Application Scenarios of Autonomous Agricultural Machinery Systems
4.7.1 Application Scenarios of Autonomous Agricultural Machinery Systems: Farming with Tractors (1)
4.7.2 Application Scenarios of Autonomous Agricultural Machinery Systems: Farming with Tractors (2)
4.7.3 Application Scenarios of Autonomous Agricultural Machinery Systems: Cotton Cultivation
4.7.4 Application Scenarios of Autonomous Agricultural Machinery Systems: Transplanting Rice
4.7.5 Application Scenarios of Autonomous Agricultural Machinery Systems: Ground Plant Protection
4.7.6 Application Scenarios of Autonomous Agricultural Machinery Systems: Harvesting

4.8 Application Summary of Autonomous Agricultural Machinery 
4.8.1 Summary of Autonomous Agricultural Machinery System Solutions
4.8.2 Application of OEM and AM Autonomous Agricultural Machinery Systems
4.8.3 OEM Autonomous Agricultural Machinery (1)
4.8.4 OEM Autonomous Agricultural Machinery (2)
4.8.5 AM Autonomous Agricultural Machinery Systems (1)
4.8.6 AM Autonomous Agricultural Machinery Systems (2)

Chapter 5 Autonomous Agricultural Machinery Suppliers

5.1 Zoomlion Agriculture Machinery
5.1.1 Profile
5.1.2 Development Trends of Smart Agriculture
5.1.3 Smart Agriculture Solutions
5.1.4 Zoomlion Eqiao Unmanned Smart Farm
5.1.5 Autonomous Driving System Architecture
5.1.6 Main Autonomous Driving Technologies
5.1.7 Autonomous Farming Machinery 
5.1.8 Autonomous Harvesting/Plant Protection Machinery
5.1.9 Application of Autonomous Farming Machinery
5.1.10 Application of Autonomous Agricultural Machinery
5.1.11 "Smart Agriculture Cloud" APP
5.1.12 Wuhu Smart Agriculture Demonstration Base Construction and Industry-University-Research Cooperation Project
5.1.13 Industry-University Cooperation: Joint R&D of Smart Agricultural Machinery (1)
5.1.14 Industry-University Cooperation: Joint R&D of Smart Agricultural Machinery (2)

5.2 Lovol
5.2.1 Profile
5.2.2 R&D System
5.2.3 Layout of Autonomous Agricultural Machinery
5.2.4 Arbos Tractors: Overall Intelligent System (1)
5.2.5 Arbos Tractors: Overall Intelligent System (2)
5.2.6 Arbos Tractors: Operation Mode of Overall Intelligent System 
5.2.7 Arbos Tractors: Overall Electronic Control Planning
5.2.8 Arbos Tractors: T-Box Development Method
5.2.9 Development Routes of Smart Agricultural Machinery: Arbos Tractors
5.2.10 Technical Solutions for Autonomous Harvesters
5.2.11 Autonomous Agricultural Machinery Systems (1)
5.2.12 Autonomous Agricultural Machinery Systems (2)
5.2.13 Cooperation with Baidu: Mass Production of Autonomous Agricultural Machinery

5.3.1 Profile
5.3.2 Overall Smart Farm Architecture
5.3.3 Unmanned Farm Solutions
5.3.4 Plow-plant-management-harvest Chain
5.3.5 Autonomous Agricultural Machinery Lineup
5.3.6 Autonomous Agricultural Machinery Systems 
5.3.7 Operation Process of Jiangyu Autonomous Driving Navigation System 
5.3.8 Application of Autonomous Agricultural Machinery Systems (1)
5.3.9 Application of Autonomous Agricultural Machinery Systems (2)
5.3.10 5G Smart Harvesters
5.3.11 Cooperation with Microsoft Azure
5.3.12 Cooperate with Jiangsu Provincial Agricultural Reclamation and Development Corporation in Building a Smart Agricultural Science and Technology Park

5.4 YTO Group
5.4.1 Profile
5.4.2 Autonomous Agricultural Machinery Systems: Dongfanghong Autonomous Tractor System (1)
5.4.3 Autonomous Agricultural Machinery Systems: Dongfanghong Autonomous Tractor System (2)
5.4.4 Layout of Autonomous Agricultural Machinery
5.4.5 Dongfanghong LX904 Autonomous Tractor
5.4.6 5G Autonomous Tractors
5.4.7 Cooperation with UniStrong/Huawei/ST: Strategic Cooperation in Autonomous Agricultural Machinery 

5.5 XAG
5.5.1 Profile
5.5.2 Equity Structure
5.5.3 Development of Smart Agriculture
5.5.4 Main Products
5.5.5 Application of Main Products
5.5.6 Development of Agricultural UAVs
5.5.7 Agricultural UAVs
5.5.8 Remote Sensing UAVs
5.5.9 Autonomous Agricultural Vehicles (1)
5.5.10 Autonomous Agricultural Vehicles (2)
5.5.11 Agricultural Autopilots (1)
5.5.12 Agricultural Autopilots (2)
5.5.13 Agricultural IoT Devices
5.5.14 Smart Agriculture Management Systems
5.5.15 Business Scope
5.5.16 Global Partners

5.6 DJI
5.6.1 Profile
5.6.2 Development of Smart Agriculture
5.6.3 Plant Protection Machine Solution 2.0 (1)
5.6.4 Plant Protection Machine Solution 2.0 (2)
5.6.5 Series Products of Smart Agriculture
5.6.6 Plant Protection UAV Series (1)
5.6.7 Plant Protection UAV Series (2)
5.6.8 T40 Agricultural UAVs
5.6.9 T30 Agricultural UAVs
5.6.10 Plant Protection UAVs (1)
5.6.11 Plant Protection UAVs (2)
5.6.12 Agricultural Service Platform
5.6.13 Agricultural Data Platform
5.6.14 Cases of Smart Agriculture
5.6.15 Cases of Plant Protection UAVs
5.6.16 Use Cases of Digital Agriculture Solutions
5.6.17 Partners in Smart Agriculture

5.7 CNH Industrial
5.7.1 Profile
5.7.2 Cooperation in Autonomous Agricultural Machinery
5.7.3 Autonomous Agricultural Machinery (1)
5.7.4 Autonomous Agricultural Machinery (2)
5.7.5 Autonomous Agricultural Machinery Systems
5.7.6 Development in China

5.8 John Deere
5.8.1 Profile
5.8.2 Autonomous Agricultural Machinery Systems (1)
5.8.3 Autonomous Agricultural Machinery Systems (2)
5.8.4 5G Autonomous Tractors
5.8.5 M&A in Autonomous Driving Industry

5.9 AGCO Group + Tianjin Ztron Beyond Intelligent Technology  
5.9.1 Profile
5.9.2 Autonomous Driving Systems
5.9.3 Autonomous Agricultural Machinery (1)
5.9.4 Autonomous Agricultural Machinery (2)

5.10 Iseki
5.10.1 Profile
5.10.2 Autonomous Agricultural Machinery Development Planning
5.10.3 Manned Tractors with Surveillance Robots
5.10.4 Autonomous Tractors: T1054-PVCY
5.10.5 Dongfeng Iseki: Autonomous Rice Transplanters
5.10.6 Dongfeng Iseki: Autonomous Demonstration Projects

5.11 Kubota
5.11.1 Profile
5.11.2 Smart Agriculture System: KSAS
5.11.3 Development of Autonomous Agricultural Machinery Business
5.11.4 Planning of Autonomous Agricultural Machinery Business
5.11.5 Functions of Autonomous Tractors
5.11.6 Autonomous Rice Transplanters with Linear Assist
5.11.7 Autonomous Rice Transplanters
5.11.8 Cooperation with NVIDIA in Developing Highly Sophisticated Autonomous Tractors

5.12 Yanmar
5.12.1 Profile
5.12.2 Main Products
5.12.3 Autonomous Agricultural Machinery Lineup
5.12.4 Autonomous Rice Transplanters
5.12.5 Application of Autonomous Rice Transplanters

5.13 Monarch
5.13.1 Profile
5.13.2 Financing
5.13.3 Development History of Autonomous Tractors
5.13.4 Parameters of Autonomous Tractors
5.13.5 Business Models

Chapter 6 Autonomous Agricultural Machinery System Providers

6.1.1 Profile
6.1.2 Beidou Precision Agriculture Solutions
6.1.3 Smart Agriculture Cloud Platform
6.1.4 Autonomous Navigation and Driving Systems (1)
6.1.5 Autonomous Navigation and Driving Systems (2)
6.1.6 Autonomous Navigation and Driving Systems (3)
6.1.7 Autonomous Agricultural Machinery Systems
6.1.8 HR100 Autonomous Harvester System
6.1.9 SR100 Autonomous Plant Protection Machinery System
6.1.10 TPR100 Autonomous Rice Transplanter System
6.1.11 TR100 Autonomous Tractor System 
6.1.12 Application of Autonomous Agricultural Machinery Systems
6.1.13 Business Models of Autonomous Navigation and Driving Systems 

6.2 UniStrong
6.2.1 Profile
6.2.2 Development History
6.2.3 Farm Information Solutions
6.2.4 Autonomous Agricultural Machinery Systems (1)
6.2.5 Autonomous Agricultural Machinery Systems (2)
6.2.6 Autonomous Agricultural Machinery Systems (3)
6.2.7 Satellite Navigation Assisted Driving System
6.2.8 Application of Autonomous Agricultural Machinery Systems (1)
6.2.9 Application of Autonomous Agricultural Machinery Systems (2)
6.2.10 Major Customers of Autonomous Agricultural Machinery Systems  

6.3.1 Profile
6.3.2 Autonomous Agricultural Machinery Solutions 
6.3.3 Autonomous Agricultural Machinery Systems (1)
6.3.4 Autonomous Agricultural Machinery Systems (2)
6.3.5 Autonomous Rice Transplanter Systems
6.3.6 Intelligent Monitoring Terminals for Operation of Agricultural Machinery
6.3.7 Application of Autonomous Agricultural Machinery Systems

6.4 ComNav Technology
6.4.1 Profile
6.4.2 Autonomous Agricultural Machinery Systems (1)
6.4.3 Autonomous Agricultural Machinery Systems (2)
6.4.4 Autonomous Agricultural Machinery Systems (3)
6.4.5 Autonomous Agricultural Machinery Systems (4)
6.4.6 Application of Autonomous Agricultural Machinery

6.5 Huida Technology
6.5.1 Profile
6.5.2 Autonomous Agricultural Machinery Systems
6.5.3 Parameters of Autonomous Agricultural Machinery Systems
6.5.4 Application Cases of Autonomous Agricultural Machinery Systems

6.6 Qianxun SI
6.6.1 Profile
6.6.2 Digital Villages
6.6.2 Smart Agriculture Solutions (1)
6.6.4 Smart Agriculture Solutions (2)
6.6.5 Autonomous Agricultural Machinery Systems (1)
6.6.6 Autonomous Agricultural Machinery Systems (2)
6.6.7 Autonomous Agricultural Machinery Systems (3)
6.6.8 Autonomous Agricultural Machinery Systems (4)
6.6.9 Operation of Autonomous Agricultural Machinery  

6.7 Kalman
6.7.1 Profile
6.7.2 Autonomous Agricultural Machinery Systems: KM-502 Agricultural Machinery Autopilot (Hydraulic)
6.7.3 Automatic driving agricultural machinery system: KM-503 Agricultural Machinery Autopilot (Electric Steering Wheel Solution)
6.7.4 Autonomous Agricultural Machinery Systems: KM-507
6.7.5 Application Cases of Autonomous Agricultural Machinery Systems
6.7.6 Marketing and Business Models of Autonomous Agricultural Machinery Systems

6.8 Topcon+Xingtu Navigation
6.8.1 Profile
6.8.2 150 Precision Autonomous Navigation and Driving System 
6.8.3 Autonomous Agricultural Machinery Systems

6.9 Trimble
6.9 Autonomous Navigation and Driving Systems

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