Articles producció científica> Química Analítica i Química Orgànica

Multivariate qualitative methodology for semi-quantitative information. A case study: Adulteration of olive oil with sunflower oil

  • Datos identificativos

    Identificador: imarina:9258972
    Autores:
    Ruisanchez, ItziarRovira, GloriaCallao, M Pilar
    Resumen:
    This paper proposes a strategy to assess the performance of a multivariate screening method for semi-quantitative purposes. The adulteration of olive oil with sunflower oil was considered as a case study using fluorescence spectroscopy and two-class Partial Least Squares Discriminant Analysis (PLS-DA). Building the proper screening methodology based on two-class multivariate classification model involve setting the cut-off value for the adulterated class (class 2). So, four classification models were established for four levels of adulterant (cut-off). Model validation involved calculating the main quality parameters (sensitivity, specificity and efficiency) and three additional semi-quantitative parameters (limit of detection, detection capability and unreliability region). The probability of successfully recognizing non-adulterated samples as such was set by the main performance parameters of the two-class model. However, the probability of successfully recognizing adulterated samples as such was more accurately extracted from the performance characteristic curves (PCC) curves instead of just from the sensitivity of the adulterated class. The main performance parameters of the PLS-DA models increased as the cut-off level increased although after a particular value the increase was less pronounced. As an example, when the cut-off was changed from 5% to 20%, sensitivity changed from 70 to 93%, specificity changed from 87 to 97%, and efficiency changed from 78 to 95%. The same can be stated for the semi-quantitative parameter's decision limit and detection capability, which moved from 0 to 1.6 and from 17.7 to 21.6 (% of adulterant), respectively.
  • Otros:

    Autor según el artículo: Ruisanchez, Itziar; Rovira, Gloria; Callao, M Pilar
    Departamento: Química Analítica i Química Orgànica
    Autor/es de la URV: Callao Lasmarias, María Pilar / Rovira Garrido, Glòria / Ruisánchez Capelastegui, María Iciar
    Palabras clave: Sunflower oil Semi-quantitative performance parameters Pls-da Performance characteristic curve Olive oil adulteration Olive oil Multivariate screening Midinfrared spectroscopy Least-squares analysis Food contamination Discriminant analysis validation semi-quantitative performance parameters pls-da performance characteristic curve performance multivariate screening
    Resumen: This paper proposes a strategy to assess the performance of a multivariate screening method for semi-quantitative purposes. The adulteration of olive oil with sunflower oil was considered as a case study using fluorescence spectroscopy and two-class Partial Least Squares Discriminant Analysis (PLS-DA). Building the proper screening methodology based on two-class multivariate classification model involve setting the cut-off value for the adulterated class (class 2). So, four classification models were established for four levels of adulterant (cut-off). Model validation involved calculating the main quality parameters (sensitivity, specificity and efficiency) and three additional semi-quantitative parameters (limit of detection, detection capability and unreliability region). The probability of successfully recognizing non-adulterated samples as such was set by the main performance parameters of the two-class model. However, the probability of successfully recognizing adulterated samples as such was more accurately extracted from the performance characteristic curves (PCC) curves instead of just from the sensitivity of the adulterated class. The main performance parameters of the PLS-DA models increased as the cut-off level increased although after a particular value the increase was less pronounced. As an example, when the cut-off was changed from 5% to 20%, sensitivity changed from 70 to 93%, specificity changed from 87 to 97%, and efficiency changed from 78 to 95%. The same can be stated for the semi-quantitative parameter's decision limit and detection capability, which moved from 0 to 1.6 and from 17.7 to 21.6 (% of adulterant), respectively.
    Áreas temáticas: Spectroscopy Química Odontología Medicina ii Medicina i Materiais Matemática / probabilidade e estatística Interdisciplinar Geociências General medicine Farmacia Environmental chemistry Engenharias iv Engenharias iii Engenharias ii Enfermagem Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências agrárias i Ciência de alimentos Ciência da computação Chemistry, analytical Biotecnología Biodiversidade Biochemistry Astronomia / física Analytical chemistry
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: mariapilar.callao@urv.cat gloria.rovira@urv.cat itziar.ruisanchez@urv.cat
    Identificador del autor: 0000-0003-2691-329X 0000-0002-7097-3583
    Fecha de alta del registro: 2024-10-12
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.sciencedirect.com/science/article/pii/S0003267022003567
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Analytica Chimica Acta. 1206 339785-
    Referencia de l'ítem segons les normes APA: Ruisanchez, Itziar; Rovira, Gloria; Callao, M Pilar (2022). Multivariate qualitative methodology for semi-quantitative information. A case study: Adulteration of olive oil with sunflower oil. Analytica Chimica Acta, 1206(), 339785-. DOI: 10.1016/j.aca.2022.339785
    DOI del artículo: 10.1016/j.aca.2022.339785
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2022
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Analytical Chemistry,Biochemistry,Chemistry, Analytical,Environmental Chemistry,Spectroscopy
    Sunflower oil
    Semi-quantitative performance parameters
    Pls-da
    Performance characteristic curve
    Olive oil adulteration
    Olive oil
    Multivariate screening
    Midinfrared spectroscopy
    Least-squares analysis
    Food contamination
    Discriminant analysis
    validation
    semi-quantitative performance parameters
    pls-da
    performance characteristic curve
    performance
    multivariate screening
    Spectroscopy
    Química
    Odontología
    Medicina ii
    Medicina i
    Materiais
    Matemática / probabilidade e estatística
    Interdisciplinar
    Geociências
    General medicine
    Farmacia
    Environmental chemistry
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Enfermagem
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências agrárias i
    Ciência de alimentos
    Ciência da computação
    Chemistry, analytical
    Biotecnología
    Biodiversidade
    Biochemistry
    Astronomia / física
    Analytical chemistry
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