Recently, the State Administration for Market Regulation, in collaboration with multiple technology enterprises, released the inaugural "Guideline for the Application of Smart Food Safety Detection Technologies," incorporating artificial intelligence, nanosensors, and blockchain traceability systems into the national standard system for the first time. This breakthrough marks the official entry of China's food safety detection into the era of "minute-level precise screening + full-chain traceability," where consumers can simply scan a QR code to view the entire safety data of food from farm to table.
New Technology Implementation: Detecting 300 Risky Substances in 10 Minutes
At the 7th Global Food Safety Innovation Summit held in Hangzhou, Keda Intelligent Inspection Technology showcased its newly developed "Lingmou" portable detector. Utilizing quantum dot fluorescence labeling technology coupled with deep learning-based image recognition algorithms, this device can simultaneously detect over 300 indicators, including pesticide residues, excessive heavy metals, and illegal additives, within 10 minutes, with a detection accuracy of 0.01ppm (parts per million), representing a 50-fold efficiency increase compared to traditional methods.
"For the first time, we have combined nanomaterials with microfluidic chips, enabling complex preprocessing with a single reagent kit," said Dr. Li Wei, the project leader. The device has been deployed in 2,000 terminals such as Hema Supermarket and Yonghui Supermarket, successfully intercepting 37 batches of potentially hazardous food, including pre-cooked dishes with excessive nitrite levels and poultry meat with excessive veterinary drug residues.
Blockchain Traceability System Covers the Entire Industry Chain
Relying on the National Food Safety Information Platform, the newly upgraded "Food Safety Chain" system has been connected to over 90% of food production enterprises above a certain scale nationwide. By uploading real-time data on temperature and humidity, transportation trajectories, and other information through IoT devices, combined with Beidou positioning and RFID electronic tags, it achieves full lifecycle monitoring from raw material procurement, production processing, to cold chain logistics.
In a pilot project in Zhaoqing, Guangdong Province, a brand of infant formula milk powder was traced through this system, successfully identifying the root cause of one batch of DHA ingredients not meeting standards—the algae oil raw material provided by a supplier experienced abnormally high temperatures during transportation. This batch of products was automatically intercepted before being placed on shelves, preventing a potential food safety incident.
Regulatory Model Innovation: Launch of AI Early Warning Platform
According to the latest data from the National Food Safety Risk Assessment Center, the accuracy rate of risk early warnings has increased to 89.7% since the six-month pilot operation of the intelligent regulatory platform. The system has built 12 prediction models for pathogenic bacteria contamination, seasonal risks, and other factors by analyzing 15 million random inspection data over the past decade. With the implementation of the Guideline, regulatory authorities are accelerating the formulation of supporting implementation details, aiming to cultivate 100 smart inspection demonstration laboratories by 2025 and stabilize the passing rate of food random inspections at above 98%. Consumers can now query the inspection data of surrounding supermarkets and hypermarkets in real-time through the "National Food Safety APP", marking a shift from government regulation to a new paradigm of collaborative governance by all citizens in terms of food safety.
Post time: Feb-14-2025