Food Traceability Market, Opportunity, Growth Drivers, Industry Trend Analysis and Forecast, 2024-2032

Description

The Food Traceability Market size will grow at over 8% CAGR during 2024-2032, driven by the increasing use of AI for predictive analytics. According to Exploding Topics, approximately 48% of businesses are leveraging AI to harness the power of big data effectively. AI technologies are revolutionizing how food traceability systems manage and interpret data, offering advanced capabilities for forecasting and decision-making. By leveraging machine learning algorithms and big data analytics, AI enables organizations to predict potential disruptions in the supply chain, anticipate demand fluctuations, and identify patterns that may affect food safety and quality. This predictive power enhances operational efficiency, reduces risk, and supports proactive measures to address issues before they impact the supply chain.

As consumers become increasingly concerned about environmental impact and ethical sourcing, there is a heightened demand for food traceability solutions that provide clear visibility into the origins and journey of food products. Companies are investing in technologies and practices that not only enhance traceability but also support sustainability goals, such as reducing carbon footprints and minimizing waste. This shift towards sustainable practices is driving innovation in the market, adding to the revenues.

The food traceability industry is classified based on component, deployment model, technology, software, application, and region.

The services segment will grow rapidly through 2032, as they ensure the accuracy and reliability of traceability systems. With the implementation of sophisticated data analytics and blockchain technology, food traceability services enable real-time tracking of food products from farm to table, thereby enhancing consumer safety and confidence. Companies offering these services are continuously innovating to meet the evolving needs of food producers, retailers, and regulators, creating a dynamic and competitive landscape.

The hybrid deployment model will gain traction through 2032, as it combines both on-premises and cloud-based solutions, providing a flexible and scalable framework for food traceability systems. It provides advantages like improved data integration, enhanced security, and cost-effectiveness. By leveraging the strengths of both on-premises infrastructure and cloud technology, organizations can achieve greater agility and responsiveness in managing their traceability operations. This approach allows for seamless data synchronization, real-time monitoring of traceability data across multiple platforms, catering to the diverse needs of food industry stakeholders.

Europe food traceability market size will grow at a decent pace through 2032, owing to the implementation of stringent food safety regulations. The European Food Safety Authority (EFSA) and other regulatory bodies have set high standards for food traceability, necessitating the adoption of robust systems by food producers and distributors. As a result, there is a growing emphasis on integrating advanced technologies such as IoT, blockchain, and AI into traceability solutions to ensure compliance and enhance transparency.

Product Code: 10088

Chapter 1 Methodology and Scope

1.1 Market scope and definition
1.2 Base estimates and calculations
1.3 Forecast calculation
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 360º synopsis, 2021 - 2032

Chapter 3 Industry Insights

3.1 Industry ecosystem analysis
3.2 Vendor matrix
3.3 Profit margin analysis
3.4 Technology and innovation landscape
3.5 Patent analysis
3.6 Key news and initiatives
3.7 Regulatory landscape
3.8 Impact forces
- 3.8.1 Growth drivers
  - 3.8.1.1 Regulatory compliance requirements
  - 3.8.1.2 Consumer demand for transparency
  - 3.8.1.3 Technological advancements in IOT
  - 3.8.1.4 Increase in foodborne illnesses
  - 3.8.1.5 Globalization of food supply chain
- 3.8.2 Industry pitfalls and challenges
  - 3.8.2.1 High implementation costs
  - 3.8.2.2 Data privacy concerns
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 and Forecast, By Component, 2021 - 2032 (USD Billion)

5.1 Hardware
5.2 Software
5.3 Services

Chapter 6 Market Estimates and Forecast, By Deployment mode, 2021 - 2032 (USD Billion)

6.1 Cloude based
6.2 On- premises
6.3 Hybrid

Chapter 7 Market Estimates and Forecast, By Technology, 2021 - 2032 (USD Billion)

7.1 Radio frequency identification
7.2 Barcodes
7.3 Infrared
7.4 Biometrics
7.5 Global positioning systems
7.6 Others

Chapter 8 Market Estimates and Forecast, By Software, 2021 - 2032 (USD Billion)

8.1 Enterprise resources planning (ERP)
8.2 Friction welding
8.3 Laboratory information systems
8.4 Warehouse software
8.5 Supply chain management (SCM)
8.6 Others

Chapter 9 Market Estimates and Forecast, By Application, 2021 - 2032 (USD Billion)

9.1 Fruits and vegetables
9.2 Fruit pulp and concentrates
9.3 Dairy products
9.4 Fish, meat, and seafood
9.5 Processed food
9.6 Bakery and confectionary
9.7 Others

Chapter 10 Market Estimates and Forecast, By Region, 2021 - 2032 (USD Billion)

10.1 Key trends
10.2 North America
- 10.2.1 U.S.
- 10.2.2 Canada
10.3 Europe
- 10.3.1 UK
- 10.3.2 Germany
- 10.3.3 France
- 10.3.4 Italy
- 10.3.5 Spain
- 10.3.6 Rest of Europe
10.4 Asia Pacific
- 10.4.1 China
- 10.4.2 India
- 10.4.3 Japan
- 10.4.4 South Korea
- 10.4.5 ANZ
- 10.4.6 Rest of Asia Pacific
10.5 Latin America
- 10.5.1 Brazil
- 10.5.2 Mexico
- 10.5.3 Rest of Latin America
10.6 MEA
- 10.6.1 UAE
- 10.6.2 South Africa
- 10.6.3 Saudi Arabia
- 10.6.4 Rest of ME

Chapter 11 Company Profiles

11.1 Bar Code Integrators
11.2 Bext360
11.3 C.H. Robinson
11.4 Carlisle
11.5 Cognex
11.6 Covectra
11.7 Food Forensics
11.8 FoodLogiQ
11.9 Honeywell International Inc
11.10 Merit-Trax
11.11 rfxcel
11.12 Safe Traces
11.13 SGS SA
11.14 Zebra Technologies