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Proceedings Paper

Dried fruits quality assessment by hyperspectral imaging
Author(s): Silvia Serranti; Aldo Gargiulo; Giuseppe Bonifazi
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Paper Abstract

Dried fruits products present different market values according to their quality. Such a quality is usually quantified in terms of freshness of the products, as well as presence of contaminants (pieces of shell, husk, and small stones), defects, mould and decays. The combination of these parameters, in terms of relative presence, represent a fundamental set of attributes conditioning dried fruits humans-senses-detectable-attributes (visual appearance, organolectic properties, etc.) and their overall quality in terms of marketable products. Sorting-selection strategies exist but sometimes they fail when a higher degree of detection is required especially if addressed to discriminate between dried fruits of relatively small dimensions and when aiming to perform an "early detection" of pathogen agents responsible of future moulds and decays development. Surface characteristics of dried fruits can be investigated by hyperspectral imaging (HSI). In this paper, specific and "ad hoc" applications addressed to propose quality detection logics, adopting a hyperspectral imaging (HSI) based approach, are described, compared and critically evaluated. Reflectance spectra of selected dried fruits (hazelnuts) of different quality and characterized by the presence of different contaminants and defects have been acquired by a laboratory device equipped with two HSI systems working in two different spectral ranges: visible-near infrared field (400-1000 nm) and near infrared field (1000-1700 nm). The spectra have been processed and results evaluated adopting both a simple and fast wavelength band ratio approach and a more sophisticated classification logic based on principal component (PCA) analysis.

Paper Details

Date Published: 7 May 2012
PDF: 11 pages
Proc. SPIE 8369, Sensing for Agriculture and Food Quality and Safety IV, 83690U (7 May 2012); doi: 10.1117/12.918561
Show Author Affiliations
Silvia Serranti, Univ. di Roma (Italy)
Aldo Gargiulo, Univ. di Roma (Italy)
Giuseppe Bonifazi, Univ. di Roma (Italy)


Published in SPIE Proceedings Vol. 8369:
Sensing for Agriculture and Food Quality and Safety IV
Moon S. Kim; Shu-I Tu; Kuanglin Chao, Editor(s)

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