Tesis doctoralsDepartament de Química

Development and validaton of multivariate strategies for food quality control

  • Identification data

    Identifier:  TDX:4446
    Authors:  Rovira Garrido, Glòria
    Abstract:
    This thesis aims to develop and validate qualitative multivariate methods for the detection of adulteration or authentication of foods, including the next issues: i) using different molecular spectroscopic instruments such as Near-Infrared (NIR), Attenuated Total Reflectance Fourier Transform Infrared (ATR-FTIR), Fluorescence, and Low-Field Nuclear Magnetic Resonance (LF-NMR); ii) defining an uncertainty region from the semi-quantitative information in adulteration cases; iii) optimizing the performance parameters obtained from the multivariate analysis, and iv) applying a transfer method technique to demonstrate the applicability of models created under different conditions.Three different adulteration problems are presented in this work; olive oil adulterated with sunflower oil, cashew nuts adulterated with other nuts (Brazilian nut, Pecan nut, Macadamia nut, and Peanut), and honey adulterated with syrups (Inverted sugar, corn and rice syrup). In each case of study, different strategies to extract semi-quantitative information have proved its usefulness, including the use of Performance Characteristic Curves (PCC) and Receiver Operating Characteristic (ROC) curves, and the proposed strategy of setting two class limits to define uncertainty regions.In the authentication problem of extra virgin olive oils from two Protected Denominations of Origin (PDO), a standardization approach is proposed to manage the variations between harvests. The usefulness of the standardization techniques has been demonstrated to maintain the performance of a multivariate classification model.The research carried out in this thesis significantly contributes to advancing the detection and prevention of food fraud, ensuring safer consumer products, and preserving market integrity. The developed methods improve over traditional protocols in speed, sustainability, and non-destructiveness.
  • Others:

    Publisher: Universitat Rovira i Virgili
    Date: 2024-07-12, 2024-07-19T11:14:20Z, 2024-07-19T11:14:20Z
    Identifier: http://hdl.handle.net/10803/691838
    Departament/Institute: Departament de Química Analítica i Química Orgànica, Universitat Rovira i Virgili.
    Language: eng
    Author: Rovira Garrido, Glòria
    Director: Ruixánchez Capelastegui, María Itxiar, Callao Lasmarias, María Pilar
    Source: TDX (Tesis Doctorals en Xarxa)
    Format: application/pdf, 244 p.
  • Keywords:

    Qualitative analysis
    Multivariate classification
    Food fraud
    Análisis cualitativo
    Clasificación multivariante
    Fraude en alimentos
    Anàlisi qualitatiu
    Classificació multivariant
    Frau d'aliments
    663/664
    Ciències
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