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Near infrared spectroscopy for the pre-cure freezing discrimination of Montanera Iberian dry-cured lomito .

Lucía LeónAlberto OrtizDavid Tejerina
Published in: Journal of food science and technology (2022)
The time lapse between the moment Montanera dry-cured products become available in the market and the consumers purchase could be overcome by freezing the raw meat prior to its curing technological process, i.e. the pre-cure freezing. This study is an attempt to assess the suitability of using Near Infrared Spectroscopy (NIRS) for the pre-cure freezing discrimination in Montanera Iberian dry-cured lomitos (the commercial name given to the Iberian dry-cured presa, Serratus ventralis muscle). The best fitting models developed through Partial Least Square-Discriminant Analysis (PLS-DA) offered a highly-discriminatory capacity, with sensitivity and specificity over 85%. The classification performance decreased in Soft Independent Modelling of Class Analogies (SIMCA) models due to the decrease of the specificity. These findings suggest that NIRS technology in combination with PLS-DA, may be useful for the control of the pre-cure freezing practice.
Keyphrases
  • healthcare
  • primary care
  • machine learning
  • skeletal muscle
  • deep learning
  • health insurance