Using identification markers and digital sorting technologies, the REDYSIGN project reports the successful detection of contaminants and effective sorting of smart packaging for fresh meat.
The REDYSIGN project was launched in October 2023 and is funded by Circular Bio-based Europe Joint Undertaking (CBE JU). It brings together thirteen industry partners with the eventual goal of manufacturing the tray, barrier coating, pad, and film of fresh meat packaging from wood-derived materials.
By fitting specific identification markers into the tray, absorbent pad, and lidding film of fresh meat packaging, REDYSIGN aims to facilitate accurate sorting and optimize specific sanitization treatments for bio-contaminated products.
The project has sought to develop, integrate, and detect specific markers using advanced sensors, and identification of organic contaminants like blood, oils, and fats in absorbent pads.
RAMAN spectroscopy has emerged as a ‘particularly effective’ solution, says REDYSIGN. This method uses an inelastic scattering of light from a laser on the sample to reveal information about the molecules’ vibrational and rotational modes, thus helping identify and characterize the substance via chemical and structural information.
The Fábrica Nacional de la Moneda y Timbre-Real Casa de la Moneda (FNMT) has developed a RAMAN marker, which has been successfully integrated into trays thermoformed by PackBenefit.
Tecnalia has reportedly conducted tests under static and dynamic conditions to prove the marker’s detection efficiency in industrial environments, which is believed to indicate the potential for fibre-based packaging to be effectively sorted and recycled.
Other methods include point spectral near-infrared (NIR) technology, which has been used to evaluate sample moisture and organic components like fats and proteins.
Matrix point measurements and RGB image captured from the same samples have also been overlapped to obtain compositional information from the spectroscopy and special information from the sample image – enabling the creation of AI models to visually delineate contaminated surfaces and connect visual data with chemical composition.
This is believed to indicate the effectiveness of spectroscopic sensors when detecting contaminants on food tray pads in both controlled scenarios and real-world conditions. Combining machine vision with spectroscopy is also believed to unlock predictive models that improve the accuracy of pollutant detection by combining visual segmentation with chemical identification.
Moving forward, REDYSIGN plans to adjust the maximum movement speed at which the sample moves along the surface, among other improvements.
Last year, the project reportedly found ways to lower the energy and water consumption of wood fibre production and fibre functionalization, respectively; it had also used LCAs to evaluate the environmental credentials of its progress, defined process flows, and conducted an initial screening of substances expected in the manufacturing phase to assess the availability of chemical data.
Its next steps were to pursue traceability for fibre-based packaging by testing sensor materials and substrates to indicate spoilage, prepare for traceability marker and contaminant detection, and develop identification markers for efficient sorting.
Since then, it has shared ‘important advances’ in developing recyclable-by-design trays, absorbent pads and anti-spoilage sensors in a meeting held by VTT and Valmet. Among other developments, two different spoilage sensors from VTT, tested in real food packaging over two weeks by Eroski, were demonstrated for rabbit and chicken meat.
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