Literature DB >> 29784377

Electronic eye for the prediction of parameters related to grape ripening.

G Orlandi1, R Calvini2, L Pigani3, G Foca2, G Vasile Simone4, A Antonelli2, A Ulrici5.   

Abstract

An electronic eye (EE) for fast and easy evaluation of grape phenolic ripening has been developed. For this purpose, berries of different grape varieties were collected at different harvest times from veraison to maturity, then an amount of the derived must was deposited on a white sheet of absorbent paper to obtain a sort of paper chromatography. Thus, RGB images of the must spots were collected using a flatbed scanner and converted into one-dimensional signals, named colourgrams, which codify the colour properties of the images. The dataset of colourgrams was used to build calibration models to relate the colour of the images with the phenolic composition of the samples - determined by reference analytical methods - and therefore to follow the ripening trend. Satisfactory calibration models were obtained for the prediction of the most important parameters related to phenolic ripening of grapes, such as colour index, tonality, total anthocyanins content, malvidin-3-O-glucoside and petunidin-3-O-glucoside.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Anthocyanins; Grapes; Image analysis; Multivariate calibration; Optical sensors; Phenolic ripening

Year:  2018        PMID: 29784377     DOI: 10.1016/j.talanta.2018.04.076

Source DB:  PubMed          Journal:  Talanta        ISSN: 0039-9140            Impact factor:   6.057


  2 in total

1.  Electronic Eye Based on RGB Analysis for the Identification of Tequilas.

Authors:  Anais Gómez; Diana Bueno; Juan Manuel Gutiérrez
Journal:  Biosensors (Basel)       Date:  2021-03-02

Review 2.  Toward the Development of Combined Artificial Sensing Systems for Food Quality Evaluation: A Review on the Application of Data Fusion of Electronic Noses, Electronic Tongues and Electronic Eyes.

Authors:  Rosalba Calvini; Laura Pigani
Journal:  Sensors (Basel)       Date:  2022-01-12       Impact factor: 3.576

  2 in total

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