quality
prediction
Quality prediction using Hyperspectral Imaging (HSI) and spectroscopy anticipates product shelf life and deterioration risk, optimizing freshness and reducing waste.
Beyond's HSI technology analyzes the molecular composition of food products, predicting quality decline more accurately than conventional testing methods.
This predictive capability allows for better inventory management and improved product distribution.
benefits
Enhanced Freshness
Ensure that only the freshest products reach consumers.
Proactive Decision-Making
Make data-driven decisions to optimize storage and distribution.
Minimize Returns and Complaints
Reduce customer dissatisfaction by delivering high-quality goods.
Waste Reduction
Predict quality decline and manage inventory efficiently.
application examples
Meat & Seafood
Predict spoilage rates in perishable items, ensuring timely distribution.
Fresh Produce
Estimate the shelf life of fruits and vegetables based on molecular analysis.
Dairy Products
Assess quality indicators like pH and fat content for better inventory management.
data speaks
↓25%
Waste reduction in perishable
goods through accurate quality forecasting
(Source: Fresh Produce Journal)
↑10%
Sales increase due to improved
product quality management
(Source: Global Dairy Insights)
↓40%
Decrease in spoilage-related
losses for large retailers
(Source: Retail Food Science Association)
how does it work?
Molecular imaging and predictive models forecast shelf life, allowing proactive inventory management and reduced product spoilage.
(a)
HSI captures spectral data at the molecular level. By analyzing light interactions, it determines the internal composition of food products, such as moisture content or fat levels.
(b)
Beyond’s advanced algorithms use this data to forecast when a product will start to degrade. They take into account variables like temperature fluctuations and natural decay processes.
(c)
These models predict shelf life and quality changes over time. Insights are then provided to manufacturers, helping them optimize inventory management and distribution.
(d)
Real-time predictions enable proactive steps to be taken, such as adjusting storage conditions or expediting distribution to minimize waste.
