Autor segons l'article: Rovira, Gloria; Whei Miaw, Carolina Sheng; Campos Martins, Mario Lucio; Sena, Marcelo Martins; Carvalho de Souza, Scheilla Vitorino; Callao, M Pilar; Ruisanchez, Itziar
Departament: Química Analítica i Química Orgànica
Autor/s de la URV: Callao Lasmarias, María Pilar / Rovira Garrido, Glòria / Ruisánchez Capelastegui, María Iciar
Paraules clau: Uncertainty intervals Soft independent modelling of class analogy Portability Nut adulteration Multivariate screening Decision thresholds
Resum: 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.
Àrees temàtiques: 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
Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
Adreça de correu electrònic de l'autor: mariapilar.callao@urv.cat gloria.rovira@urv.cat itziar.ruisanchez@urv.cat
Identificador de l'autor: 0000-0003-2691-329X 0000-0002-7097-3583
Data d'alta del registre: 2024-10-12
Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
Enllaç font original: https://www.sciencedirect.com/science/article/pii/S0039914022007123
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Referència a l'article segons font original: Talanta. 253 123916-
Referència de l'ítem segons les normes 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
DOI de l'article: 10.1016/j.talanta.2022.123916
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2023
Tipus de publicació: Journal Publications