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Ripeness determination in food processing

The high priority placed on food safety makes food sorting a very demanding application. High classifi cation and spatial accuracy are required to eliminate any chance that slightly defective products or small foreign materials (e.g. glass shards or metal wires) will reach the customer. It is therefore the case that the reputation and financial well-being of food producers depends on the effectiveness of the food inspection and sorting systems they use. The complete surveillance of food quality, from sensor-based sorting of raw materials, in-line inspection during production and final inspection before packaging, is rapidly becoming an imperative in today’s high standard food industry.

Problem

To date there exists no in-line inference method for the determination of fruit ripeness covering the whole product stream.

Solution

Hyperspectral Imaging can be used to quantitatively determine fruit ripeness in real-time, 24/7. This can replacemore traditional spot checks and lab-based analysis that are discontinuous and slow. Real-time quantitative data of fruit ingredients such as water, sugar and other SSC (soluble solids concentration) can be interfaced with existing PAT (process analytical technology) to optimise grade sorting to reduce costs and ensure high product quality.

Peach
Concentration mesurements
Defects
Application Scan Peach Application Peach
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Technology

Near Infrared Hyperspectral Imaging offers the degree of classification accuracy necessary for Food applications, by directly measuring the chemical molecular composition through the absorption of light (spectroscopy). 

EVK’s portfolio of sensor-based sorting technology includes Colour, Hyperspectral and Inductive sensor systems, which can be used individually or, with Sensor- Fusion, can be combined to form a powerful sorting application that can process multiple material types.

Hyperspectral Imaging
Data Analysis Tools

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