Salt Content

Monitoring the salt content in dry-cured ham production lines still remain a major challenge for the sector. Monitoring salt content is important to ensure the quality of the product, particularly when addressing the production of ham with reduced salt content. Moreover, it provides also an effective mean to optimize the production process, and to establish the influence of the process parameters on the final salt uptake.

In the framework of the project, we have developed a magnetic induction scanner that determines the total salt content in hams after the salting stage. The scanning of the hams is performed non-destructively, without altering meat properties. The measurements can be done in-line at practical speed rates used by industry (700 hams/hour), with a prediction error for the total salt content of the sample of just 0.15%.


Magnetic Induction Spectroscopy module integrated in the ProCured prototype, which allows determining the total salt content in hams after the salting stage

Meat Quality

Meat water holding capacity has a strong impact on meat quality. Pale, soft and exudative (PSE) meats are characterized by a very low water retention capacity, which directly worsens their organoleptic properties. In the production of dry-cured ham, PSE meats result in meat with undesirable textures, and with an abnormally high salt content. Besides quality issues, PSE meat leads also to technological problems, particularly during the product slicing.

To assess meat water holding capacity, in the ProCured project we have developed a vision probe that provides an accurate assessment of meat colour. Lean neat colour, particularly lightness, can be used to predict meat water holding capacity. Compared to conventional colorimeters, the integration of a vision system allows preprocessing the image area to remove fatty spots, leading to a more accurate measurement of lean colour parameters. The vision system developed can be used also to evaluate other relevant characteristics of the ham, including morphological parameters, and the amount of lean exposed after trimming.

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Estimated exposed lean area in a Parma ham, as computed by the Artificial Vision System developed in the Project