Sensory intensity assessment of olive oils using an electronic tongue

Olive oils may be commercialized as intense, medium or light, according to the intensity perception of fruitiness, bitterness and pungency attributes, assessed by a sensory panel. In this work, the capability of an electronic tongue to correctly classify olive oils according to the sensory intensity perception levels was evaluated. Cross-sensitivity and non-specific lipid polymeric membranes were used as sensors. The sensor device was firstly tested using quinine monohydrochloride standard solutions. Mean sensitivities of 14±2 to 25±6 mV/decade, depending on the type of plasticizer used in the lipid membranes, were obtained showing the device capability for evaluating bitterness. Then, linear discriminant models based on sub-sets of sensors, selected by a meta-heuristic simulated annealing algorithm, were established enabling to correctly classify 91% of olive oils according to their intensity sensory grade (leave-one-out cross-validation procedure). This capability was further evaluated using a repeated K-fold cross-validation procedure, showing that the electronic tongue allowed an average correct classification of 80% of the olive oils used for internal-validation. So, the electronic tongue can be seen as a taste sensor, allowing differentiating olive oils with different sensory intensities, and could be used as a preliminary, complementary and practical tool for panelists during olive oil sensory analysis.

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.

Improving buildings energy performance: comparison between simple payback period and life cycle costs analysis

The building sector is one of the Europeâ s main energy consumer, making buildings an important target for a wiser energy use, improving indoor comfort conditions and reducing the energy consumption. To achieve the European Union targets for energy consumption and carbon reductions it is crucial to act in new, but also in existing buildings, which constitute the majority of the building stock. In existing buildings, the significant improvement of their efficiency requires important investments. Therefore, costs are a major concern in the decision making process and the analysis of the cost effectiveness of the interventions is an important path in the guidance for the selection of the different renovation scenarios. The Portuguese thermal legislation considers the simple payback method for the calculations of the time for the return of the investment. However, this method does not take into consideration inflation, cash flows and cost of capital, as well as the future costs of energy and the building elements lifetime as it happens in a life cycle cost analysis. In order to understand the impact of the economic analysis method used in the choice of the renovation measures, a case study has been analysed using simple payback calculations and life cycle costs analysis. Overall results show that less far-reaching renovation measures are indicated when using the simple payback calculations which may be leading to solutions less cost-effective in a long run perspective.