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Provedor de dados:  CIGR Journal
País:  China
Título:  Influence of production and conservation conditions on the physical-chemical properties of blueberry with modeling through artificial neural networks
Autores:  Guiné, Raquel P.F.
Matos, Susana
Gonçalves, Christphe
Gonçalves, Fernando
Costa, Daniela
Mendes, Mateus
Data:  2018-11-02
Ano:  2018
Palavras-chave:  Food engineering artificial neural network
Production mode
Resumo:  Blueberry is a widely consumed fruit with major economic value, appreciated due to its characteristic flavor as well as health benefits. The present work aimed to evaluate the effect of several production factors and storage conditions on some chemical and physical properties of blueberries. Some physical and chemical characteristics (moisture, acidity, sugars, color and texture) of blueberries from three cultivars, originating from five different locations and conventional or organic farming, were evaluated. The variation of the properties along time was also evaluated for storage at room temperature and refrigeration. Moreover, artificial neural network models were developed to estimate the physical-chemical characteristics of the blueberries, as influenced by the production and conservation factors considered. The results showed that all the characteristics considered varied according to cultivar, place of cultivation and production mode. The storage conditions also induced changes in the chemical components as well as in color and texture. The changes were dependent on type and duration of storage, cultivar and production mode. Weight analysis of the ANN models highlighted the patterns and trends observed experimentally.
Tipo:  Info:eu-repo/semantics/article
Idioma:  Inglês
Editor:  International Commission of Agricultural and Biosystems Engineering
Formato:  application/pdf
Fonte:  Agricultural Engineering International: CIGR Journal; Vol 20, No 2 (2018): CIGR Journal; 226-238

Direitos:  Copyright (c) 2018 Agricultural Engineering International: CIGR Journal

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