Report Content
Chapter 1 Methodology & Scope
1.1 Market scope & definitions
1.2 Base estimates & calculations
1.3 Forecast calculations
1.4 Data sources
1.4.1 Primary
1.4.2 Secondary
1.4.2.1 Paid sources
1.4.2.2 Public sources
Chapter 2 Executive Summary
2.1 Industry 3600 synopsis, 2018-2032
Chapter 3 Industry Insights
3.1 Industry ecosystem analysis
3.2 Supplier landscape
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 Rising regulatory compliance requirements
3.8.1.2 Growing emphasis on disease control and management
3.8.1.3 Escalating technological advancements
3.8.1.4 Expanding market access and export opportunities
3.8.2 Industry pitfalls & challenges
3.8.2.1 Increasing costs of implementation
3.8.2.2 Challenges in standardization and interoperability
3.9 Growth potential analysis
3.10 Porter’s analysis
3.10.1 Supplier power
3.10.2 Buyer power
3.10.3 Threat of new entrants
3.10.4 Threat of substitutes
3.10.5 Industry rivalry
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 Component, 2018-2032 (USD Million)
5.1 Key trends
5.2 Hardware
5.2.1 Electronic identification tags
5.2.1.1 GPS tags
5.2.1.2 RFID tags
5.2.2 Visual identification tags
5.2.2.1 One-piece tags
5.2.2.2 Two-piece tags
5.2.2.3 Brisket tags
5.2.3 Readers & applicators
5.2.4 Others
5.3 Software
5.3.1 Cloud-based
5.3.2 On-premises
5.4 Services
5.4.1 Data analytics
5.4.2 Maintenance and support
Chapter 6 Market Estimates & Forecast, By Technology, 2018-2032 (USD Million)
6.1 Key trends
6.2 Ear tags
6.3 Leg tags
6.4 Collars tags & GPS
6.5 Tattoos
6.6 Visual markings
6.7 Others
Chapter 7 Market Estimates & Forecast, By End-Use, 2018-2032 (USD Million)
7.1 Key trends
7.2 Dairy farm
7.3 Goat and pig farm
7.4 Sheep farm
7.5 Deer farm
Chapter 8 Market Estimates & Forecast, By Region, 2018-2032 (USD Million)
8.1 Key trends
8.2 North America
8.2.1 U.S.
8.2.2 Canada
8.3 Europe
8.3.1 UK
8.3.2 Germany
8.3.3 France
8.3.4 Italy
8.3.5 Spain
8.3.6 Russia
8.3.7 Rest of Europe
8.4 Asia Pacific
8.4.1 China
8.4.2 India
8.4.3 Japan
8.4.4 South Korea
8.4.5 ANZ
8.4.6 Rest of Asia Pacific
8.5 Latin America
8.5.1 Brazil
8.5.2 Mexico
8.5.3 Rest of Latin America
8.6 MEA
8.6.1 South Africa
8.6.2 Saudi Arabia
8.6.3 UAE
8.6.4 Rest of MEA
Chapter 9 Company Profiles
9.1 AgriTech Solutions
9.2 Avid Identification Systems, Inc.
9.3 BioTrack
9.4 CattleTrace
9.5 DataLivestock
9.6 Datamars
9.7 EIDAP Inc.
9.8 FarmID Innovations
9.9 Global Animal ID
9.10 LivestockID Solutions
9.11 Merck Animal Health
9.12 Ranchers Choice Tech
9.13 Shearwell Data Limited
9.14 SmartTag Systems
9.15 TagTech Innovations
9.16 UHF Livestock
9.17 VirtualHerd Technologies
9.18 WISE Livestock Systems
Livestock Identification Market Trends
The adoption of advanced technologies, such as RFID (Radio-Frequency Identification) and GPS (Global Positioning System), is witnessing a significant surge. These, monitoring, and data collection capabilities, empowering livestock farmers with precise information about individual animals. RFID tags, for instance, enable unique identification, allowing farmers to track an animal's movement, health, and breeding history. The integration of GPS technology further enhances these capabilities, offering location-specific data for more comprehensive livestock management.
There is a growing emphasis on data analytics and artificial intelligence (AI) in the livestock identification sector. The increasing volume of data generated by identification systems is being harnessed to derive actionable insights for improved decision-making. Data analytics tools enable farmers to analyze patterns, predict disease outbreaks, optimize breeding programs, and enhance overall herd management. The application of AI adds another layer of sophistication, allowing for automated data interpretation and the identification of trends that might not be apparent through traditional analysis methods.
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