Advanced AI-driven inspection system to improve fresh produce quality and efficiency
With the help of Tecnalia, EROSKI pilot project focuses on developing a cutting-edge system for inspecting the quality of fresh produce, like potatoes, using advanced technologies such as X-ray, hyperspectral imaging, and near-infrared. These technologies allow for a deeper and more precise assessment of the internal and external qualities of the produce. The system combines AI-based algorithms to evaluate potential defects, seasonal variations, and overall quality, providing an efficient solution for grading fresh produce.
Farmers and distribution platforms will gain access to an automated inspection tool that ensures consistent quality control, reducing manual errors and improving efficiency. By integrating AI and advanced imaging, the system can detect hidden defects or variations that might be missed by the human eye, leading to higher-quality products reaching the market. Additionally, this system will help streamline the inspection process, potentially increasing throughput and reducing costs associated with quality checks.
Implementing this system offers significant benefits for farmers and processors, including improved productivity, reduced waste, and enhanced consumer satisfaction due to better-quality produce. The automated inspection system can also help farmers make more informed decisions about harvest timing and storage management, leading to less product loss and optimized operations. By adopting this technology, end-users can stay competitive in a market that increasingly demands high-quality, defect-free produce.
TOWARDS A NEW ZERO FOOD WASTE MINDSET BASED ON HOLISTIC ASSESSMENT
Ongoing | 2022-2027
- Main funding source
- Horizon Europe (EU Research and Innovation Programme)
- Geographical location
- Spain, Austria, Netherlands, Sweden, Greece