Memorias de investigación
Communications at congresses:
Multispectral imaging for detection of foreign food material in powder food

Research Areas
  • Foodstuffs tecnology,
  • Engineering

Peanut, a common economical food source consumed worldwide has reached approximately 39.9 million metric tons production per year (Torres, Barros et al. 2014). Concurrently, there is an increasing concern regarding peanut allergenic effects and its influence on human health (Huang, Yang et al. 2014). Manufacturing industries dealing with the processing of multiple powder food products present a substantial risk for the contamination of powder foods with peanut traces and other adulterants. The need to detect the peanut traces at the early stages of food manufacturing is of crucial importance to people allergic to peanut as well as to food manufacturers. The analytical methods commonly used by the food industry and official food control agencies are enzyme-linked immunosorbent assay (ELISA) (Platteau et al. 2011) and Real time polymerase chain reaction (RT PCR) (López-Calleja et al. 2013). However, these methods require high cost, labor and chemical experimental skills. Various applications of hyperspectral imaging (HSI) like detection of infestation in soybean (Chelladurai, Karuppiah et al. 2014), melamine in milk powders (Fu, Kim et al. 2014) illustrated the good suitability of this technology for the detection of adulterants in powder food. Nevertheless, the high cost and complexity of hyperspectral imaging, together with its large data-storage requirements, represents an important limitation for its industrial application. In this context, feasibility studies carried out using complete spectral information are commonly a first step for further simplification into multispectral technology (J.A. Fernández Pierna et al. 2014). Multispectral technology is based only on a limited number of wavelengths and consequently cheaper and easier to apply on an industrial context. The aim of this study is to use and check the suitability of a multispectral index for identification of minimum level of peanut traces in wheat flour.
Hyperspectral Imaging and Applications Conference
Coventry, UK
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Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: LPF-TAGRALIA: Técnicas Avanzadas en Agroalimentación
  • Departamento: Ingeniería Agroforestal