Development of a colorimetric indicator label for food oxidation based on hexanal detection

In this work, a colorimetric indicator for food oxidation based on the detection of hexanal in gas-phase, has been developed. In fact, in recent years, the food packaging industry has evolved towards new generation of packaging, like active and intelligent. According to literature (Pangloli P. et al. 2002), hexanal is the main product of a fatty acid oxidation: the linoleic acid. So, it was chosen to analyse two kinds of potato chips, fried in two different oils with high concentration of linoleic acid: olive oil and sunflower oil. Five different formulas were prepared and their colour change when exposed to hexanal in gas phase was evaluated. The formulas evaluations were first conducted on filter paper labels. The next step was to select the thickener to add to the formula, in order to coat a polypropylene film, more appropriate than the filter paper for a production at industrial scale. Three kinds of thickeners were tested: a cellulose derivative, an ethylene vinyl-alcohol and a polyvinyl alcohol. To obtain the final labels with the autoadhesive layer, the polypropylene film with the selected formula and thickener was coat with a water based adhesive. For both filter paper and polypropylene labels, with and without autoadhesive layer, the detection limit and the detection time were measured. For the selected formula on filter paper labels, the stability was evaluated, when conserved on the dark or on the light, in order to determine the storage time. Both potato chips samples, stocked at the same conditions, were analysed using an optimised Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS) method, in order to determine the concentration of volatilized hexanal. With the aim to establish if the hexanal can be considered as an indicator of the end of potato chips shelf life, sensory evaluation was conducted each day of HS-SPME-GC-MS analysis.

Back-in-time void finder: dynamical detection of cosmic voids for precision cosmology

Cosmic voids are vast and underdense regions emerging between the elements of the cosmic web and dominating the large-scale structure of the Universe. Void number counts and density profiles have been demonstrated to provide powerful cosmological probes. Indeed, thanks to their low-density nature and they very large sizes, voids represent natural laboratories to test alternative dark energy scenarios, modifications of gravity and the presence of massive neutrinos. Despite the increasing use of cosmic voids in Cosmology, a commonly accepted definition for these objects has not yet been reached. For this reason, different void finding algorithms have been proposed during the years. Voids finder algorithms based on density or geometrical criteria are affected by intrinsic uncertainties. In recent years, new solutions have been explored to face these issues. The most interesting is based on the idea of identify void positions through the dynamics of the mass tracers, without performing any direct reconstruction of the density field. The goal of this Thesis is to provide a performing void finder algorithm based on dynamical criteria. The Back-in-time void finder (BitVF) we present use tracers as test particles and their orbits are reconstructed from their actual clustered configuration to an homogeneous and isotropic distribution, expected for the Universe early epoch. Once the displacement field is reconstructed, the density field is computed as its divergence. Consequently, void centres are identified as local minima of the field. In this Thesis work we applied the developed void finding algorithm to simulations. From the resulting void samples we computed different void statistics, comparing the results to those obtained with VIDE, the most popular void finder. BitVF proved to be able to produce a more reliable void samples than the VIDE ones. The BitVF algorithm will be a fundamental tool for precision cosmology, especially with upcoming galaxy-survey.