- Nestlé traced some of its Gerber baby food products using Food Trust, a blockchain system developed by IBM, in a test of the technology's ability to trace the source of fruits and vegetables that go into the products, the Wall Street Journal reported.
- The trial involves nine other food companies — Dole Food, Driscoll’s, Golden State Foods, Kroger, McCormick, McLane, Tyson Foods, Unilever and Walmart — to determine how effective blockchain is in food traceability on a global scale.
- During the test, Nestlé traced the ingredients for sweet potato, apple and pumpkin puree baby food to determine if the technology could make product recalls faster. The tests involved multiple ingredients and cross-border shipments.
Companies using a blockchain solution, such as Food Trust, store data about harvests, processing, packaging and shipping, which can be traced back in seconds compared to days or even weeks using traditional data storage and retrieval methods. Food Trust has performed traceback tests as fast as 2.2 seconds, compared to seven days before blockchain, FreightWaves reported.
For blockchain information to be most useful, suppliers and competitors will have to collaborate in a shared record-keeping system that could speed up investigations recalls for bad foods.
The recent romaine lettuce recalls highlighted to the FDA the need for the ability to quickly and accurately trace the source of food products, the Journal reported.
Food Trust has conducted tests previously, including tracking single-ingredient canned pumpkin for Nestlé and mango logistics for Walmart, aiming for complete farm-to-grocery aisle visibility into the food supply chain.
Nestlé found one of the challenges in adopting the Food Trust blockchain was the need to develop interfaces connecting shipping, trucking, processing and other software systems required to manage the ingredients. The team had to incorporate data from farms, processing plants and logistics operations and the company's ERP software, including paper-based and electronic data in different formats with multiple data sets for each ingredient.