🌾 Food Tracking With AI
Today's Highlights
- How AI is impacting food tracebility
- This Week On BuzzBelow - a recap on this week's topics
- In Other News - a few interesting developments we're tracking
Artificial intelligence (AI) is reshaping a fundamental aspect of how humans survive: agriculture. AI is revolutionizing the way we understand food production, distribution, and consumption. Among the various applications, food traceability has emerged as a critical aspect, ensuring the safety and quality of food from farm to fork. Here are some ways AI is impacting food traceability:
Real-time Monitoring
Environmental engineers utilize a variety of sensors like thermometers, hygrometers, and gas sensors to continuously monitor and record conditions crucial for maintaining product quality during storage and transportation. RFID (radio frequency identification) tags and NFC (near field communication) technology provides real-time tracking of products throughout the supply chain. RFID tags store data that can be updated and read remotely, essential for dynamic tracking. Libelium specializes in smart agriculture sensors, offering solutions for environmental monitoring and precision farming.
Image Processing
Convolutional Neural Networks (CNNs) are used for analyzing images to detect diseases in crops, pests, and quality of produce during sorting processes. Beyond visible light, hyperspectral imaging captures a broader spectrum of light to detect invisible signs of disease, ripeness, or spoilage. Blue River Technology (owned by John Deere) uses computer vision and machine learning for crop scouting and precision weed control.
Robotics & Automation
Automated Harvesting Systems, which are equipped with AI, can determine the optimal time for harvest, selectively picking ripe produce, and recording the exact time and condition of each item. Automated sorting and packaging lines uses AI to sort produce by size, weight, and quality, and embedding traceability information such as harvest date and origin. FFRobotics creates robots with AI capabilities for picking fruits and integrating traceability information at the time of harvesting.
The demand for these technologies in the agriculture industry will only grow rapidly in the coming years. The global AI in agriculture market size is expected to reach around $4.9 billion by 2028, expanding at a Compound Annual Growth Rate (CAGR) of approximately 24.1% during the forecast period. AI in agriculture, particularly in food traceability, is not just a technological advancement; it's a necessity for a sustainable, safe, and transparent food system. Its ability to manage data, provide real-time insights, and enhance record-keeping significantly improves the way we track and manage our food. However, addressing potential challenges and ensuring responsible implementation will be crucial for its long-term success and acceptance.