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In-house validation of a visible and near infrared spectroscopy non-targeted method to support panel test of virgin olive oils.
Garrido-Cuevas, María-Del-Mar; Garrido-Varo, Ana-María; Oliveri, Paolo; Sánchez, María-Teresa; Pérez-Marín, Dolores.
Afiliação
  • Garrido-Cuevas MD; Faculty of Agriculture and Forestry Engineering (ETSIAM), University of Cordoba, Campus de Rabanales, 14071 Cordoba, Spain. Electronic address: g52gacum@uco.es.
  • Garrido-Varo AM; Faculty of Agriculture and Forestry Engineering (ETSIAM), University of Cordoba, Campus de Rabanales, 14071 Cordoba, Spain.
  • Oliveri P; Department of Pharmacy (DIFAR), University of Genova, Viale Cembrano 4, 16148 Genova, Italy.
  • Sánchez MT; Faculty of Agriculture and Forestry Engineering (ETSIAM), University of Cordoba, Campus de Rabanales, 14071 Cordoba, Spain.
  • Pérez-Marín D; Faculty of Agriculture and Forestry Engineering (ETSIAM), University of Cordoba, Campus de Rabanales, 14071 Cordoba, Spain. Electronic address: dcperez@uco.es.
Food Res Int ; 192: 114799, 2024 Sep.
Article em En | MEDLINE | ID: mdl-39147500
ABSTRACT
In this study, an in-house validation of Visible and Near Infrared Spectroscopy was performed to distinguish between extra virgin olive oil (EVOO) and virgin olive oil (VOO). A total of 161 samples of olive oil of three different categories (EVOO, VOO and lampante (LOO)) were analysed by transflectance using a monochromator instrument. One-class models were initially developed using Partial Least Squares (PLS) Density Modelling to characterize EVOO and VOO category. Once the LOO samples were discriminated, linear and non-linear discriminant models were built to classify EVOO and VOO. Different data pre-treatments and variable selection algorithms were evaluated to establish the best models in terms of Correct Classification Rate (CCR). The best model, obtained after variable selection using PLS Discriminant Analysis, yielded CCR values of 82.35 % for EVOO and 66.67 % for VOO in external validation. These results confirmed that VIS + NIRS technology may be used to provide rapid, non-destructive preliminary screening of olive oil samples for categorization; suspect samples may then be analysed by official analytical methods.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Espectroscopia de Luz Próxima ao Infravermelho / Azeite de Oliva Idioma: En Revista: Food Res Int Ano de publicação: 2024 Tipo de documento: Article País de publicação: Canadá

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Espectroscopia de Luz Próxima ao Infravermelho / Azeite de Oliva Idioma: En Revista: Food Res Int Ano de publicação: 2024 Tipo de documento: Article País de publicação: Canadá