

How It Works
Based on the unique light emission of crops and food items, a 'molecular fingerprint' of the product is collected in real time, not its label or a barcode.
The proprietary machine learning algorithms are optimised for spectral data and the peculiar characteristics of each crop or food. Models provide prediction of commercial quality parameters such as maturity of fruits or provenance of food enabling optimal handling of the product.
Quality-based metrics are integrated into complex supply chain systems, provide data points to reduce the information risk and allow for mielstone-based payment release in complex import-export controls. Reduce waste, increase consumer confidence and allow for realignment of incentives in the value chain.
Features
Handheld spectral scanner
Interchangeable silicone cup for different fruit size
Battery operated
Data syncing, charging and calibration dock
The scanner connects to smartphone or tablet via Bluetooth
RubensTM mobile app for iOS(c) and AndroidTM
RubensTM Scanner Specifications
Spectroscopy Mode: Fluorescence, VIS reflectance and NIR reflectance
Wavelength Range: 350-900 nm
Resolution: 1 2 nm
Battery: Rechargeable 18650 type, 3400 mAh
Real time Prediction of Crop Quality Parameters
Predicting harvest timing is a key challenge to optimise yield, reduce waste and optimally deploy your workforce.
Predict maturity and quality parameters of your crops using Rubens hand-held sensor, in combination with a dedicated analytics model.
Rubens has been developed and validate dmodels for a large variety of crops, which enable assessing commercial quality metrics in real time.
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Ensuring food authenticity, traceability and reducing waste
With a unique combination of sensors and analytics Rubens can monitor quality and ensure proof of provenance of your crop and food.
Rubens' molecular fingerprint provides data and intelligence about a food product without damaging it (if it's fresh) or open it (it it's bottled or wrapped). Data will be acquired directly from the product itself, not a label or a barcode, uniquely linking your product itself, not a label or a barcode, uniquely linking your product to its digital image. For instance, we can prove the authenticity of a bottle of wine capturing data from the wine itself measured through the bottle.