Anna Lisa Gilioli

Dr. Anna Lisa Gilioli

orcid

Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 May 2025 in Talanta Open
Verified
Journal Article
Open access
Anna Lisa GilioliAnna Lisa Gilioli
Anna Lisa Gilioli
ASAlessio Sacco
Alessio Sacco
Andrea Mario GiovannozziAndrea Mario Giovannozzi
Andrea Mario Giovannozzi
Simone GiacosaSimone Giacosa
Simone Giacosa
ABAntonella Bosso
Antonella Bosso
ARAndrea Mario Rossi
Andrea Mario Rossi

17 November 2025 in Beverages
Verified
Journal Article
Open access
PDF file
Anna Lisa GilioliAnna Lisa Gilioli
Anna Lisa Gilioli
ASAlessio Sacco
Alessio Sacco
Andrea Mario GiovannozziAndrea Mario Giovannozzi
Andrea Mario Giovannozzi
Simone GiacosaSimone Giacosa
Simone Giacosa
ABAntonella Bosso
Antonella Bosso
ARAndrea Mario ROSSI
Andrea Mario ROSSI
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.