Articles producció científica> Química Analítica i Química Orgànica

One-class model with two decision thresholds for the rapid detection of cashew nuts adulteration by other nuts

  • Identification data

    Identifier: imarina:9282464
    Authors:
    Rovira, GloriaWhei Miaw, Carolina ShengCampos Martins, Mario LucioSena, Marcelo MartinsCarvalho de Souza, Scheilla VitorinoCallao, M PilarRuisanchez, Itziar
    Abstract:
    A green screening method to determine cashew nut adulteration with Brazilian nut, pecan nut, macadamia nut and peanut was proposed. The method was based on the development of a one-class soft independent modelling of class analogy (SIMCA) model for non-adulterated cashew nuts using near-infrared (NIR) spectra obtained with portable equipment. Once the model is established, the assignment of unknown samples depends on the threshold established for the authentic class, which is a key aspect in any screening approach. The authors propose innovatively to define two thresholds: lower model distance limit and upper model distance limit. Samples with distances below the lower threshold are assigned as non-adulterated with a 100% probability; samples with distance values greater than the upper threshold are assigned as adulterated with a 100% probability; and samples with distances within these two thresholds will be considered uncertain and should be submitted to a confirmatory analysis. Thus, the possibility of error in the sample assignment significantly decreases. In the present study, when just one threshold was defined, values greater than 95% for the optimized threshold were obtained for both selectivity and specificity. When two class thresholds were defined, the percentage of samples with uncertain assignment changes according to the adulterant considered, highlighting the case of peanuts, in which 0% of uncertain samples was obtained. Considering all adulterants, the number of samples that were submitted to a confirmatory analysis was quite low, 5 of 224 adulterated samples and 3 of 56 non-adulterated samples.
  • Others:

    Author, as appears in the article.: Rovira, Gloria; Whei Miaw, Carolina Sheng; Campos Martins, Mario Lucio; Sena, Marcelo Martins; Carvalho de Souza, Scheilla Vitorino; Callao, M Pilar; Ruisanchez, Itziar
    Department: Química Analítica i Química Orgànica
    URV's Author/s: Callao Lasmarias, María Pilar / Rovira Garrido, Glòria / Ruisánchez Capelastegui, María Iciar
    Keywords: Uncertainty intervals Soft independent modelling of class analogy Portability Nut adulteration Multivariate screening Decision thresholds
    Abstract: A green screening method to determine cashew nut adulteration with Brazilian nut, pecan nut, macadamia nut and peanut was proposed. The method was based on the development of a one-class soft independent modelling of class analogy (SIMCA) model for non-adulterated cashew nuts using near-infrared (NIR) spectra obtained with portable equipment. Once the model is established, the assignment of unknown samples depends on the threshold established for the authentic class, which is a key aspect in any screening approach. The authors propose innovatively to define two thresholds: lower model distance limit and upper model distance limit. Samples with distances below the lower threshold are assigned as non-adulterated with a 100% probability; samples with distance values greater than the upper threshold are assigned as adulterated with a 100% probability; and samples with distances within these two thresholds will be considered uncertain and should be submitted to a confirmatory analysis. Thus, the possibility of error in the sample assignment significantly decreases. In the present study, when just one threshold was defined, values greater than 95% for the optimized threshold were obtained for both selectivity and specificity. When two class thresholds were defined, the percentage of samples with uncertain assignment changes according to the adulterant considered, highlighting the case of peanuts, in which 0% of uncertain samples was obtained. Considering all adulterants, the number of samples that were submitted to a confirmatory analysis was quite low, 5 of 224 adulterated samples and 3 of 56 non-adulterated samples.
    Thematic Areas: Zootecnia / recursos pesqueiros Spectroscopy Saúde coletiva Química Nutrição Medicina veterinaria Medicina iii Medicina ii Medicina i Materiais Interdisciplinar Geociências General medicine General chemistry Farmacia Ensino Engenharias iv Engenharias iii Engenharias ii Engenharias i Ciências biológicas iii Ciências biológicas ii Ciências biológicas i Ciências ambientais Ciências agrárias i Ciência de alimentos Chemistry, analytical Chemistry (miscellaneous) Biotecnología Biodiversidade Biochemistry Astronomia / física Analytical chemistry Administração pública e de empresas, ciências contábeis e turismo
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: mariapilar.callao@urv.cat gloria.rovira@urv.cat itziar.ruisanchez@urv.cat
    Author identifier: 0000-0003-2691-329X 0000-0002-7097-3583
    Record's date: 2024-10-12
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.sciencedirect.com/science/article/pii/S0039914022007123
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Talanta. 253 123916-
    APA: Rovira, Gloria; Whei Miaw, Carolina Sheng; Campos Martins, Mario Lucio; Sena, Marcelo Martins; Carvalho de Souza, Scheilla Vitorino; Callao, M Pilar; (2023). One-class model with two decision thresholds for the rapid detection of cashew nuts adulteration by other nuts. Talanta, 253(), 123916-. DOI: 10.1016/j.talanta.2022.123916
    Article's DOI: 10.1016/j.talanta.2022.123916
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2023
    Publication Type: Journal Publications
  • Keywords:

    Analytical Chemistry,Biochemistry,Chemistry (Miscellaneous),Chemistry, Analytical,Spectroscopy
    Uncertainty intervals
    Soft independent modelling of class analogy
    Portability
    Nut adulteration
    Multivariate screening
    Decision thresholds
    Zootecnia / recursos pesqueiros
    Spectroscopy
    Saúde coletiva
    Química
    Nutrição
    Medicina veterinaria
    Medicina iii
    Medicina ii
    Medicina i
    Materiais
    Interdisciplinar
    Geociências
    General medicine
    General chemistry
    Farmacia
    Ensino
    Engenharias iv
    Engenharias iii
    Engenharias ii
    Engenharias i
    Ciências biológicas iii
    Ciências biológicas ii
    Ciências biológicas i
    Ciências ambientais
    Ciências agrárias i
    Ciência de alimentos
    Chemistry, analytical
    Chemistry (miscellaneous)
    Biotecnología
    Biodiversidade
    Biochemistry
    Astronomia / física
    Analytical chemistry
    Administração pública e de empresas, ciências contábeis e turismo
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