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NIR Sensing Technologies for the Detection of Fraud in Nuts and Nut Products: A Review.
Vega-Castellote, Miguel; Sánchez, María-Teresa; Torres-Rodríguez, Irina; Entrenas, José-Antonio; Pérez-Marín, Dolores.
Afiliación
  • Vega-Castellote M; Department of Bromatology and Food Technology, University of Cordoba, Rabanales Campus, 14071 Córdoba, Spain.
  • Sánchez MT; Department of Bromatology and Food Technology, University of Cordoba, Rabanales Campus, 14071 Córdoba, Spain.
  • Torres-Rodríguez I; Department of Animal Production, University of Cordoba, Rabanales Campus, 14071 Córdoba, Spain.
  • Entrenas JA; Department of Animal Production, University of Cordoba, Rabanales Campus, 14071 Córdoba, Spain.
  • Pérez-Marín D; Department of Animal Production, University of Cordoba, Rabanales Campus, 14071 Córdoba, Spain.
Foods ; 13(11)2024 May 22.
Article en En | MEDLINE | ID: mdl-38890841
ABSTRACT
Food fraud is a major threat to the integrity of the nut supply chain. Strategies using a wide range of analytical techniques have been developed over the past few years to detect fraud and to assure the quality, safety, and authenticity of nut products. However, most of these techniques present the limitations of being slow and destructive and entailing a high cost per analysis. Nevertheless, near-infrared (NIR) spectroscopy and NIR imaging techniques represent a suitable non-destructive alternative to prevent fraud in the nut industry with the advantages of a high throughput and low cost per analysis. This review collects and includes all major findings of all of the published studies focused on the application of NIR spectroscopy and NIR imaging technologies to detect fraud in the nut supply chain from 2018 onwards. The results suggest that NIR spectroscopy and NIR imaging are suitable technologies to detect the main types of fraud in nuts.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Foods Año: 2024 Tipo del documento: Article País de afiliación: España

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Foods Año: 2024 Tipo del documento: Article País de afiliación: España
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