Literature DB >> 22688037

Preliminary study to determine the phenolic maturity stage of grape seeds by computer vision.

Francisco J Rodríguez-Pulido1, Raúl Ferrer-Gallego, M Lourdes González-Miret, Julián Carlos Rivas-Gonzalo, María Teresa Escribano-Bailón, Francisco J Heredia.   

Abstract

The applications of computer vision technology for acquiring and analysing images have been extended to the quality evaluation in food industry. This technique involves great advantages for the objective, rapid, non-contact and automated quality inspection and control. The aim of this work was to evaluate the potential of the computer vision to determine the phenolic maturity stage of grape seeds. Up to 21 phenolic compounds were determined by HPLC-DAD-MS in order to obtain reference values to develop the model. The CIELAB parameters, area, aspect, roundness, length, width and heterogeneity of seeds were analysed using a DigiEye(®) system. The technique reported in this work can be a good and rapid tool for taking decisions at harvest time. Notwithstanding, a comprehensive study should be made in order to develop more robust models.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 22688037     DOI: 10.1016/j.aca.2012.01.005

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  4 in total

1.  Comparative Study of Phenolic Profile, Antioxidant Capacity, and Color-composition Relation of Roselle Cultivars with Contrasting Pigmentation.

Authors:  Gustavo A Camelo-Méndez; M José Jara-Palacios; M Luisa Escudero-Gilete; Belén Gordillo; Dolores Hernanz; Octavio Paredes-López; Pablo E Vanegas-Espinoza; Alma A Del Villar-Martínez; Francisco J Heredia
Journal:  Plant Foods Hum Nutr       Date:  2016-03       Impact factor: 3.921

2.  Research Progress in Imaging Technology for Assessing Quality in Wine Grapes and Seeds.

Authors:  Francisco J Rodríguez-Pulido; Ana Belén Mora-Garrido; María Lourdes González-Miret; Francisco J Heredia
Journal:  Foods       Date:  2022-01-18

3.  Slight crack identification of cottonseed using air-coupled ultrasound with sound to image encoding.

Authors:  Chi Zhang; Wenqian Huang; Xiaoting Liang; Xin He; Xi Tian; Liping Chen; Qingyan Wang
Journal:  Front Plant Sci       Date:  2022-09-15       Impact factor: 6.627

4.  Assessment of Sensory and Texture Profiles of Grape Seeds at Real Maturity Stages Using Image Analysis.

Authors:  María Jesús Cejudo-Bastante; Francisco J Rodríguez-Pulido; Francisco J Heredia; M Lourdes González-Miret
Journal:  Foods       Date:  2021-05-15
  4 in total

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