Browsing by Author "Costa, Daniela Vasconcelos Teixeira da"
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- Modeling the influence of production and storage conditions on the blueberry qualityPublication . Guiné, Raquel; Matos, Susana; Gonçalves, Christophe; Costa, Daniela Vasconcelos Teixeira da; Mendes, Mateus; Gonçalves, FernandoBlueberry 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 artificial neural network models highlighted the patterns and trends observed experimentally.
- Modelling Through Artificial Neural Networks of the Phenolic Compounds and Antioxidant Activity of BlueberriesPublication . Guiné, Raquel; Gonçalves, Christophe; Matos, Susana; Gonçalves, Fernando; Costa, Daniela Vasconcelos Teixeira da; Mendes, MateusThe present study aimed at investigating the influence of several production factors, conservation conditions, and extraction procedures on the phenolic compounds and antioxidant activity of blueberries from different cultivars. The experimental data was used to train artificial neural networks, using a feed-forward model, which gave information about the variables affecting the antioxidant activity and the concentration of phenolic compounds in blueberries. The ANN input variables were location, cultivar, the age of the bushes, the altitude of the farm, production mode, state, storage time, type of extract and order of extract, while the output variables were total phenolic compounds, tannins as well as ABTS and DPPH antioxidant activity. The ANN model was fairly good, with values of the correlation factor for the whole dataset varying from 0.948 to 0.979, while the values of mean squared error were ranging from 0.846 to 0.018, for DPPH antioxidant acidity and anthocyanins, respectively. The results obtained showed that the methanol extracts contained higher amounts of total phenols and anthocyanins as compared to acetone: water extracts, while presenting similar quantities of tannins in both extracts. The blueberries from organic farming were richer in phenolic compounds and possessed higher antioxidant activity than those from conventional agriculture. Even though the effect of storage was not established with high certainty, a trend was observed for an increase in the phenolic compounds and antioxidant activity along storage, either when under refrigeration or under freezing, for the storage periods evaluated.