Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis

Mishra, T.P.; Herrero Langreo, Ana; Barreiro Elorza, Pilar; Roger, Jean-Michel; Diezma Iglesias, Belen; Gorretta, Nathalie y Lleó García, Lourdes (2015). Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis. "Journal of Near Infrared Spectroscopy", v. 23 (n. 1); pp. 15-22. ISSN 0967-0335. https://doi.org/10.1255/jnirs.1141.

Descripción

Título: Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis
Autor/es:
  • Mishra, T.P.
  • Herrero Langreo, Ana
  • Barreiro Elorza, Pilar
  • Roger, Jean-Michel
  • Diezma Iglesias, Belen
  • Gorretta, Nathalie
  • Lleó García, Lourdes
Tipo de Documento: Artículo
Título de Revista/Publicación: Journal of Near Infrared Spectroscopy
Fecha: 2015
Volumen: 23
Materias:
Escuela: E.T.S.I. Agrónomos (UPM) [antigua denominación]
Departamento: Ingeniería Agroforestal
Grupo Investigación UPM: Técnicas Avanzadas en Agroalimentación LPF-TAGRALIA
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

The use of a common environment for processing different powder foods in the industry has increased the risk of finding peanut traces in powder foods. The analytical methods commonly used for detection of peanut such as enzyme-linked immunosorbent assay (ELISA) and real-time polymerase chain reaction (RT-PCR) represent high specificity and sensitivity but are destructive and time-consuming, and require highly skilled experimenters. The feasibility of NIR hyperspectral imaging (HSI) is studied for the detection of peanut traces down to 0.01% by weight. A principal-component analysis (PCA) was carried out on a dataset of peanut and flour spectra. The obtained loadings were applied to the HSI images of adulterated wheat flour samples with peanut traces. As a result, HSI images were reduced to score images with enhanced contrast between peanut and flour particles. Finally, a threshold was fixed in score images to obtain a binary classification image, and the percentage of peanut adulteration was compared with the percentage of pixels identified as peanut particles. This study allowed the detection of traces of peanut down to 0.01% and quantification of peanut adulteration from 10% to 0.1% with a coefficient of determination (r2) of 0.946. These results show the feasibility of using HSI systems for the detection of peanut traces in conjunction with chemical procedures, such as RT-PCR and ELISA to facilitate enhanced quality-control surveillance on food-product processing lines.

Más información

ID de Registro: 36557
Identificador DC: http://oa.upm.es/36557/
Identificador OAI: oai:oa.upm.es:36557
Identificador DOI: 10.1255/jnirs.1141
URL Oficial: http://www.impublications.com/content/abstract?code=J23_0015
Depositado por: Memoria Investigacion
Depositado el: 17 Jul 2015 14:24
Ultima Modificación: 24 Nov 2015 16:10
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