Meat

salami segmentation meat spoilage meat adulteration

Rapid, Non-Destructive, Versatile Methods

Multispectral imaging makes it possible to make numerous assessments of your meat. In order for you to check the quality, authenticity and safety.

Documented Application

The VideometerLab Meat application has been documented and reviewed in a large number of scientific papers.

Measuring Muscle Color in Meat

This application note describes how to make a session recipe that quantifies color on the muscle part of a flesh slice.

The session is made for pork flesh and may later be adapted to beef, lamb or other meat types, and even to other products.

Read More: PDF (751 KB)

Meat Spoilage

The scientific article shows how multispectral imaging can be applied for meat spoilage detection. This method is considered non-invasive for beef contamination estimation.

Find out more about the analysis of spectral data and its application.

Read More: sciencedirect.com

Quality Control in Continuous Frying

Videometer’s technology has been used for quality control in the process of continuous frying.

The paper concluded that spectral vision can partially or totally substitute the operator’s visual inspection.

Read More: sciencedirect.com

Adulteration of Meat

The Agricultural University of Athens has presented exciting results on the detection of meat adulteration. The study concerned pork located in raw beef flesh and vice versa.

The university decided to use the VideometerLab for 220 samples they prepared.

Read More: sciencedirect.com

Color Formation in Fermented Sausages

The Meat Science paper, published article on the analysis how colour formation in fermented salami can be visible through multispectral imaging.

This study can be further used for product stability, as well as the effect of oxidation on meat.

Read More: sciencedirect.com

Detection of Frozen-Then-Thawed Meat

In this experiment by the Agricultural University of Athens, the VideometerLab was used for the detection of frozen-then-thawed minced beef.

The results of the experiment showed an overall correct classification of the frozen-then-thawed meat at a 100% rate.

Read More: How to detect frozen-then-thawed meat?

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