IR-Scan
Analysis of organic matter
IR-SCAN measures the recovery potential of an organic matter deposit in a fast, reliable and repeatable manner. IR-SCAN is a solution developed to meet the needs of producers and consumers of organic matter and their processing units. It is suitable for the analysis of any organic matter such as crop and livestock residues, by-products from food processing, station fats, etc.
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Biochemical analysis
The IR-SCAN method provides the complete biochemical characterization of an organic matter, information that is essential to the management of bio-processes.
Bio-processes valorizing organic matter such as anaerobic digestion, entomoculture or composting express real needs in terms of biochemical characterization of their substrates. Due to its reliability, speed and reduced cost (time reduction and analysis cost per 10), IR-SCAN is the only analytical solution compatible with the constraints of controlling a bio-process.
Value of the material
IR-SCAN determines the upgrading potential and market value of organic matters.
The circular economy and industrial ecology are topical issues that are making more and more ways of using organic by-products emerge. The determination of the value of an organic matter according to the different outlets is essential to optimize its valorization. By providing a complete characterization adapted to the problems of optimizing the valorization plants, IR-SCAN defines the fair value of the waste.
Disruptive innovation
In a single analysis, IR-SCAN is able to measure the many key indicators of the desired bio-processes.
IR-SCAN is a characterization method based on near-infrared spectroscopy analysis and processing algorithms developed by BioEnTech. This innovative approach has been the subject of two European patents (EU patent No. 3 205 629, Divisional application No. 3 047 582)
Timeliness
Complete analysis in 5 to 7 working days
Cost-effective
Reduced analytical costs by 10
Accuracy
Reliable, accurate and repeatable analytical method
Control
Biochemical characterization adapted to control constraints