농업 애널리틱스 시장 : 오퍼링별, 농장 규모별, 용도별, 기술별, 예측(2024-2032년)

The agriculture analytics market is projected to exhibit 10% CAGR over 2024-2032, due to the adoption of advanced technologies like artificial intelligence (AI), machine learning, and big data analytics in agriculture sector. These technologies provide farmers with insights into crop health, soil conditions, and weather, enabling data-driven decisions. Precision agriculture, driven by these technologies, optimizes resource use, increasing yields and reducing environmental impact. Smart farming tools, such as drones and IoT sensors, further enhance data collection and analysis, improving farming practices and productivity.

The global demand for food security and sustainable agriculture are augmenting the market growth. As per the UN estimates, the world population is projected to reach 9.7 billion by 2050. Agriculture analytics help manage resources and optimize crops, boosting productivity while minimizing waste and environmental harm. Government initiatives and investments in agricultural technology are also promoting analytics adoption. For instance, in April 2024, The USDA announced a historic $1.5 billion investment in fiscal year 2024 to support partner-driven conservation and climate solutions through the Regional Conservation Partnership Program (RCPP), aligning with President Biden's Investing in America initiative. These efforts aim to enhance food security and address climate change and resource scarcity challenges.

The overall agriculture analytics industry is classified based on offering, farm size, application, technology, and region.

The precision farming application is set to experience robust growth through 2032, due to its ability to revolutionize traditional farming practices. By leveraging data from various sources such as satellite imagery, GPS, and IoT sensors, precision farming enables farmers to implement targeted interventions tailored to specific field conditions. This approach enhances the efficiency of resource use, optimizes crop management, and maximizes yields while minimizing environmental impact. Precision farming solutions facilitate real-time monitoring of soil health, weather patterns, and crop development, allowing for precise adjustments in irrigation, fertilization, and pest control. The integration of advanced analytics into precision farming not only boosts productivity but also supports sustainable agricultural practices by reducing waste and improving overall farm management.

The supply chain analytics segment will hold a notable market share by 2032, as it addresses the complexities of managing agricultural supply chains more effectively. By utilizing advanced data analytics and predictive modeling, it enables stakeholders to gain deep insights into every stage of the supply chain, from production and processing to distribution and retail. This enhanced visibility helps optimize logistics, reduce costs, and improve the accuracy of demand forecasting. By integrating data from various sources, such as weather conditions, market trends, and transportation logistics, supply chain analytics technology enhances decision-making, mitigates risks, and ensures the timely delivery of fresh produce.

Asia Pacific agriculture analytics industry will record rapid expansion through 2032, driven by the region's significant agricultural base and increasing investments in technology. The adoption of advanced technologies such as AI, machine learning, and IoT in agriculture is helping farmers optimize crop yields, manage resources more efficiently, and improve supply chain management. Additionally, government initiatives and support for digital agriculture innovations are bolstering market growth. As Asia-Pacific countries seek to modernize their agricultural practices to meet the demands of a growing population and changing climate conditions, the market players will find lucrative opportunities for growth.

Table of Contents

Chapter 1 Methodology & Scope

• 1.1 Market scope & definition
• 1.2 Research design
  • 1.2.1 Research approach
  • 1.2.2 Data collection methods
• 1.3 Base estimates & calculations
  • 1.3.1 Base year calculation
  • 1.3.2 Key trends for market estimation
• 1.4 Forecast model
• 1.5 Primary research and validation
  • 1.5.1 Primary sources
  • 1.5.2 Data mining sources

Chapter 2 Executive Summary

• 2.1 Industry 360° synopsis, 2021 - 2032

Chapter 3 Industry Insights

• 3.1 Industry ecosystem analysis
• 3.2 Supplier landscape
  • 3.2.1 Software providers
  • 3.2.2 Service provider
  • 3.2.3 Technology providers
  • 3.2.4 End-user
• 3.3 Profit margin analysis
• 3.4 Technology & innovation landscape
• 3.5 Patent analysis
• 3.6 Key news & initiatives
• 3.7 Regulatory landscape
• 3.8 Impact forces
  • 3.8.1 Growth drivers
    • 3.8.1.1 Increasing cyber security incidents
    • 3.8.1.2 Stringent regulatory compliance for strict data protection
    • 3.8.1.3 Growing adoption of digital platforms
    • 3.8.1.4 Increasing brand reputation concerns
    • 3.8.1.5 Growing adoption of artificial intelligence and machine learning
  • 3.8.2 Industry pitfalls & challenges
    • 3.8.2.1 Complexity of regulatory compliance
• 3.9 Growth potential analysis
• 3.10 Porter's analysis
• 3.11 PESTEL analysis

Chapter 4 Competitive Landscape, 2023

• 4.1 Introduction
• 4.2 Company market share analysis
• 4.3 Competitive positioning matrix
• 4.4 Strategic outlook matrix

Chapter 5 Market Estimates & Forecast, By Offering, 2021 - 2032 ($Bn)

• 5.1 Key trends
• 5.2 Software
• 5.3 Services
  • 5.3.1 Professional
  • 5.3.2 Managed

Chapter 6 Market Estimates & Forecast, By farm size, 2021 - 2032 ($Bn)

• 6.1 Key trends
• 6.2 Large farms
• 6.3 Small and medium farms

Chapter 7 Market Estimates & Forecast, By Application, 2021 - 2032 ($Bn)

• 7.1 Key trends
• 7.2 Livestock farming
• 7.3 Aquaculture farming
• 7.4 Precision farming
• 7.5 Conventional farming
• 7.6 Others

Chapter 8 Market Estimates & Forecast, By Technology, 2021 - 2032 ($Bn)

• 8.1 Key trends
• 8.2 Livestock analytics
  • 8.2.1 Yield mapping
  • 8.2.2 Field monitoring
  • 8.2.3 Weather tracking
  • 8.2.4 Others
• 8.3 Supply chain analytics
• 8.4 Farm analytics
• 8.5 Others

Chapter 9 Market Estimates & Forecast, By Region, 2021 - 2032 ($Bn)

• 9.1 Key trends
• 9.2 North America
  • 9.2.1 U.S.
  • 9.2.2 Canada
• 9.3 Europe
  • 9.3.1 UK
  • 9.3.2 Germany
  • 9.3.3 France
  • 9.3.4 Italy
  • 9.3.5 Spain
  • 9.3.6 Russia
  • 9.3.7 Rest of Europe
• 9.4 Asia Pacific
  • 9.4.1 China
  • 9.4.2 India
  • 9.4.3 Japan
  • 9.4.4 South Korea
  • 9.4.5 ANZ
  • 9.4.6 Southeast Asia
  • 9.4.7 Rest of Asia Pacific
• 9.5 Latin America
  • 9.5.1 Brazil
  • 9.5.2 Mexico
  • 9.5.3 Argentina
  • 9.5.4 Rest of Latin America
• 9.6 MEA
  • 9.6.1 UAE
  • 9.6.2 South Africa
  • 9.6.3 Saudi Arabia
  • 9.6.4 Rest of MEA

Chapter 10 Company Profiles

• 10.1 Accenture
• 10.2 AGCO Corporation
• 10.3 Bayer
• 10.4 Corteva Agriscience
• 10.5 Deere and Co.
• 10.6 DeLaval
• 10.7 Geosis, Inc.
• 10.8 IBM
• 10.9 Oracle
• 10.10 PrecisionHawk
• 10.11 SAP SE
• 10.12 Taranis
• 10.13 Trimble
• 10.14 Wipro
• 10.15 Xylem, Inc.