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Reduction of salt content variability of dry-cured ham production using non-invasive technologies in an industrial environment.
- Source :
-
Meat Science . Sep2024, Vol. 215, pN.PAG-N.PAG. 1p. - Publication Year :
- 2024
-
Abstract
- Salt content variability of dry-cured ham production is a challenge for the industry since many factors can influence salt uptake during the salting procedure. The aim of this work was to define and evaluate different modifications of the salting procedure to reduce the salt content variability of an industrial dry-cured ham production. Results showed that magnetic induction (MI) is a valid technology for industrial purposes as it can predict in-line the fat and salt contents of hams with a percentage error of 1.75% and 0.38%, respectively. Modifications of the salting process defined according to raw material characteristics obtained in-line reduced the salt content variability (SD) of the global production from 0.337% to 0.283%. Moreover, a 25% reduction of the salt content variability in hams of similar weight and fat content could be achieved when using a reclassification of the defined categories with MI technology after 6 days of salting. Because of the complexity of the salting process, new tools combined with strategies need to be investigated and developed to overcome the variability coming from other sources than weight and the fat content of hams. • Fat and salt contents are estimated with magnetic induction (MI) under industrial conditions. • Fat content estimated with MI is useful for industrial classification purposes. • Salting time can be adjusted with MI to achieve a target salt content. • Reclassification during salting with MI reduces the salt content variability by up to 25%. [ABSTRACT FROM AUTHOR]
- Subjects :
- *SALT
*ELECTROMAGNETIC induction
*HAM
*HAMMING weight
*RAW materials
Subjects
Details
- Language :
- English
- ISSN :
- 03091740
- Volume :
- 215
- Database :
- Academic Search Index
- Journal :
- Meat Science
- Publication Type :
- Academic Journal
- Accession number :
- 177846734
- Full Text :
- https://doi.org/10.1016/j.meatsci.2024.109539