2 resultados para MICROBIOTA REPRESENTATIVENESS

em Repositório Científico da Universidade de Évora - Portugal


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Meat industry needs to reduce salt in their products due to health issues. The present study evaluated the effect of salt reduction from 6% to 3% in two Portuguese traditional blood dry-cured sausages. Physicochemical and microbiological parameters, biogenic amines, fatty acids and texture profiles and sensory panel evaluations were considered. Differences due to salt reduction were perceptible in a faint decline of water activity, which slightly favoured microbial growth. Total biogenic amines content ranged from 88.86 to 796.68 mg kg 1 fresh matter, with higher amounts, particularly of cadaverine, histamine and tyramine, in low-salt products. Still, histamine and other vasoactive amines remained at low levels, thus not affecting consumers’ health. Regarding fatty acids, no significant differences were observed due to salt. However, texture profile analysis revealed lower resilience and cohesiveness in low-salt products, although no textural changes were observed by the sensory panel. Nevertheless, low-salt sausages were clearly preferred by panellists.

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Aim When faced with dichotomous events, such as the presence or absence of a species, discrimination capacity (the ability to separate the instances of presence from the instances of absence) is usually the only characteristic that is assessed in the evaluation of the performance of predictive models. Although neglected, calibration or reliability (how well the estimated probability of presence represents the observed proportion of presences) is another aspect of the performance of predictive models that provides important information. In this study, we explore how changes in the distribution of the probability of presence make discrimination capacity a context-dependent characteristic of models. For the first time,we explain the implications that ignoring the context dependence of discrimination can have in the interpretation of species distribution models.