5 resultados para dependency of attributes

em Repositório Científico da Universidade de Évora - Portugal


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CONSUMERS SENSORY EVALUATION OF MELON SWEETNESS AND QUALITY Agulheiro Santos, A.C, Rato, A.E., Laranjo, M. and Gonçalves, C. Departamento de Fitotecnia, Escola de Ciências e Tecnologia, Instituto de Ciências Agrárias e Ambientais Mediterrânicas (ICAAM), Instituto de Investigação e Formação Avançada (IIFA), Universidade de Évora, Polo da Mitra, Ap.94, 7002-554 Évora, Portugal. ABSTRACT The sensory quality of fruits is made of a range of attributes like sweetness, acidity, aroma, firmness, color. Taste perception and perception threshold of these attributes are variable according to the psychological and cultural development of individuals. To better understand the quality evaluation of melon by consumers, consumers were invited to taste melon samples, in supermarkets in Évora (South region), Lisbon (Central region) and Vila Nova de Gaia (North region). The present work explored the importance given by consumers to sweetness in order to classify the overall quality of melon. Furthermore, the relationship of the chemical evaluation of Total Soluble Solids (TSS) with sweetness of melon was studied. Fruits from the variety Melão branco picked randomly from those that were exposed for sale in supermarkets were used for analysis. Fruits were chinned along the equatorial zone and only the central part of the fruit, opposite to the part that leaned on the soil, was used to obtain homogeneous samples. Consumers were invited to taste four small pieces of each fruit, previously referenced with a code number, and answer a questionnaire with two questions related to sweetness and overall quality. Each question had five possible levels, identified from “Nothing sweet”, to “Extremely sweet”, in one case, and from “Poor” to “Excellent” in the other. Simultaneously, the values of TSS (measured in ºBrix) for each melon used in the study were evaluated by refractometry. This sensory analysis allowed us to point out the following findings: first of all, there is good agreement between the results obtained to classify “Sweetness” and “Overall Quality” (Cohen’s Kappa=53.1%, p<0.001), which means, for example, that fruits with excellent quality are in general extremely sweet. Moreover, fruits with less than 9.6 °Brix are considered of poor quality and nothing sweet, whereas fruits with values between 10 °Brix and 12 °Brix are considered good in terms of overall quality. It seems that the thresholds for the stimulus/intensity of sweetness lied between 10 °Brix to 14 °Brix for this melon variety. Acknowledgments This work was support by national funds through Fundação para a Ciência e a Tecnologia (FCT) under the Strategic Project Pest-OE/AGR/UI0115/2014 and co-funded by FEDER funds through the COMPETE Program.

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The study of groundwater dependent ecosystems opened the opportunity to involve specialists of different areas of knowledge in order to obtain answers for complex interrelations between groundwater and the associated ecosystems. The actual study, carried out in two coastal lagoons of the Portuguese SW coast, showed the high dependency of the marine life and vegetation of the lagoons and associated streams discharging in the lagoons on the fresh water supply of these two lagoons and the high contribution they receive from groundwater in the dry period, which corresponds to more than half of each hydrologic year. Every year, the lagoons are artificially opened to the ocean for a few days to a few weeks, which dramatically changes the inside salinity. The sensitivity of these ecological niches is demonstrated by the strong dependence that some species that are more sensitive to high salinity waters show in relation to the entrance of freshwater resultant from the discharge of the phreatic aquifer of Sines sedimentary Basin. The great biodiversity of these lagoons and its precarious balance is only possible to preserve if the aquifer continue to act as a regulatory factor of the lagoon’s salinity. The equilibrium can be changed in the event of overexploitation of the phreatic aquifer, which is not at risk in the near future. In a scenario of climate change the lagoons will benefit from a slow increase in groundwater contribution, due to the rise of sea level, which will be accompanied by a rise in groundwater levels in the aquifer near the sea.

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Plants of genus Schinus are native South America and introduced in Mediterranean countries, a long time ago. Some Schinus species have been used in folk medicine, and Essential Oils of Schinus spp. (EOs) have been reported as having antimicrobial, anti-tumoural and anti-inflammatory properties. Such assets are related with the EOs chemical composition that depends largely on the species, the geographic and climatic region, and on the part of the plants used. Considering the difficulty to infer the pharmacological properties of EOs of Schinus species without a hard experimental setting, this work will focus on the development of an Artificial Intelligence grounded Decision Support System to predict pharmacological properties of Schinus EOs. The computational framework was built on top of a Logic Programming Case Base approach to knowledge representation and reasoning, which caters to the handling of incomplete, unknown, or even self-contradictory information. New clustering methods centered on an analysis of attribute’s similarities were used to distinguish and aggregate historical data according to the context under which it was added to the Case Base, therefore enhancing the prediction process.

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This paper presents a study made in a field poorly explored in the Portuguese language – modality and its automatic tagging. Our main goal was to find a set of attributes for the creation of automatic tag- gers with improved performance over the bag-of-words (bow) approach. The performance was measured using precision, recall and F1. Because it is a relatively unexplored field, the study covers the creation of the corpus (composed by eleven verbs), the use of a parser to extract syntac- tic and semantic information from the sentences and a machine learning approach to identify modality values. Based on three different sets of attributes – from trigger itself and the trigger’s path (from the parse tree) and context – the system creates a tagger for each verb achiev- ing (in almost every verb) an improvement in F1 when compared to the traditional bow approach.

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Sweet cherries (Prunus avium L.) ‘Sweetheart’ were harvested at different production regions from Portugal (Cova da Beira and Portalegre) and Spain (Valle de Jerte). Cherries were harvested at their commercial maturation according to the empirical knowledge of external color corresponding to good quality. Fruits were stored and evaluated in order to study their quality on the harvest day and during a period of 21 days, at cold storage (1 ºC, 95% RH). The sweet cherry ‘Sweetheart’ is a well-known variety and a highly appreciated one but fruits present a short shelf life. On the other hand the effect of different “terroir” on cherry characteristics should be known and clarified. Fruits from day 0, considered without storage, were kept at 20ºC and analyzed. Every weak, 3 replicas were randomly picked up and 10 fruits from each one were submitted to several analyses after fruit temperature stabilized at 20ºC. Several quality parameters were evaluated: external colour (L*, a*, b*), texture, soluble solids content (SSC), titratable acidity (TA) and the ratio between soluble solid contents (SSC) and tritratable acidity (TA). Fruits from different orchards and locations were significantly different according to these parameters. Fruits from Cova da Beira were less firm comparing with other two regions, Valle de Jerte and Portalegre, which may indicate a higher maturation rate at harvest in those fruits. This is in accordance with SSC/titratable acidity rate suggesting a late harvest in Cova da Beira comparing with other two orchards, however fruits from Cova da Beira exhibit a poor color at harvest. These results clearly showed a lower correlation between SSC and firmness considering fruits origin.