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Related Concept Videos

Computed Tomography01:10

Computed Tomography

Tomography refers to imaging by sections. Computed tomography (CT) is a non-invasive imaging technique that uses computers to analyze several cross-sectional X-rays to reveal minute details about structures in the body.
The technique was invented in the 1970s and is based on the principle that as X-rays pass through the body, they are absorbed or reflected at different levels. In the technique, a patient lies on a motorized platform while a computerized axial tomography (CAT) scanner rotates...
Imaging Studies III: Computed Tomography01:27

Imaging Studies III: Computed Tomography

DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...

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Tools for studying dry-cured ham processing by using computed tomography.

Eva Santos-Garcés1, Israel Muñoz, Pere Gou

  • 1Food Technology, IRTA, XaRTA, Finca Camps i Armet, E-17121 Monells, Spain.

Journal of Agricultural and Food Chemistry
|December 7, 2011
PubMed
Summary

This study developed nondestructive computed tomography (CT) tools to monitor salt, water, and water activity (a(w)) during dry-cured ham production. These tools optimize quality and reduce costs, though fat content can affect predictions.

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Area of Science:

  • Food Science and Technology
  • Agricultural Engineering
  • Biophysics

Background:

  • Optimizing dry-cured ham production is crucial for reducing costs and enhancing product quality.
  • Nondestructive methods for monitoring key chemical parameters like salt and water content, and water activity (a(w)), are highly desirable during processing.

Purpose of the Study:

  • To develop and validate predictive models for salt content, water content, and a(w) throughout the dry-cured ham elaboration process.
  • To integrate these models with computed tomography (CT) scans to create analytical tools for quantitative assessment and spatial distribution analysis of these parameters.

Main Methods:

  • Development of predictive models for salt, water, and a(w) using quantitative data from the entire ham processing.
  • Application of these models to computed tomography (CT) scans to generate analytical tools like distribution diagrams, line profiles, and regions of interest (ROIs).
  • Validation of the developed CT analytical tools through industrial case studies.

Main Results:

  • Successfully developed predictive models with high accuracy for salt content (R(2) = 0.960), water content (R(2) = 0.912), and a(w) (R(2) = 0.906).
  • Demonstrated the utility of CT analytical tools for quantitative assessment and distribution mapping of salt, water, and a(w) during ham processing.
  • Identified fat as a confounding factor that can disturb water content and a(w) predictions.

Conclusions:

  • Nondestructive CT-based analytical tools, powered by predictive models, offer valuable insights into the dry-cured ham elaboration process.
  • These tools enable precise monitoring of salt, water, and a(w) content and distribution, aiding in process optimization and quality control.
  • Further research is needed to mitigate the interference of fat in water and a(w) predictions for enhanced accuracy.