Andrea Mario

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The quantity of anthocyanins plays a crucial role in wine quality, since these phenolic compounds significantly influence the color, mouthfeel and organoleptic properties of red wines. It is therefore important to define accurate and precise methodologies to monitor the concentration of total anthocyanins in wine. Currently, this analysis is carried out using Ultraviolet-Visible (UV–visible) spectrophotometry. This work aims to determine an alternative methodology that is equally fast, accurate and allows in situ measurements while opening the measurement of the concentrations of other molecules of interest. The method presented consists of Raman analysis of Barbera wine samples using a portable Raman spectroscopy system. Subsequently, the collected spectra were processed using an algorithm that applies partial least squares (PLS) regression, making it possible to determine the concentration of total anthocyanins for each sample. This approach is characterized by an accuracy and precision comparable to the methodology currently in use, i.e., UV–visible spectrophotometry. It is indeed characterized by an RMSE (root mean square error) and R2 (the coefficient of determination) on the validation set of 0.010 g/L and 0.88 and on the test data of 0.007 g/L and 0.93, respectively.

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Biobank-scale imaging provides an unprecedented opportunity to characterise how thousands of organ phenotypes vary in populations.

Businesses today have access to an unprecedented volume of marketing data. Every website visit, advertising click, email interaction, and social