Literature DB >> 27374547

Potential application of machine vision technology to saffron (Crocus sativus L.) quality characterization.

Sajad Kiani1, Saeid Minaei2.   

Abstract

Saffron quality characterization is an important issue in the food industry and of interest to the consumers. This paper proposes an expert system based on the application of machine vision technology for characterization of saffron and shows how it can be employed in practical usage. There is a correlation between saffron color and its geographic location of production and some chemical attributes which could be properly used for characterization of saffron quality and freshness. This may be accomplished by employing image processing techniques coupled with multivariate data analysis for quantification of saffron properties. Expert algorithms can be made available for prediction of saffron characteristics such as color as well as for product classification.
Copyright © 2016. Published by Elsevier Ltd.

Keywords:  Characterization and quantification; Color; Image processing; Saffron

Mesh:

Year:  2016        PMID: 27374547     DOI: 10.1016/j.foodchem.2016.04.132

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  2 in total

1.  Nondestructive classification of saffron using color and textural analysis.

Authors:  Morteza Mohamadzadeh Moghadam; Masoud Taghizadeh; Hassan Sadrnia; Hamid Reza Pourreza
Journal:  Food Sci Nutr       Date:  2020-02-27       Impact factor: 2.863

2.  Optimization of the Appearance Quality in CO2 Processed Ready-to-Eat Carrots through Image Analysis.

Authors:  Gianmarco Barberi; Víctor González-Alonso; Sara Spilimbergo; Massimiliano Barolo; Alessandro Zambon; Pierantonio Facco
Journal:  Foods       Date:  2021-12-04
  2 in total

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