Year: 2025
Type: article
Abstract: The quality of artisanal bread is strongly influenced by sourdough fermentation, where aroma development and microbial stability are key factors. This study evaluates the use of an electronic nose (E-nose) to monitor cold fermentation, integrating it with microbiological analysis and gas chromatography–mass spectrometry (SPME-GC-MS) to characterize the dough’s volatile profile. A clear correlation was observed between microbial dynamics, pH reduction (from 5.8 to 3.8), and the evolution of volatile compounds, with notable increases in acetic acid (up to 12.75%), ethanol (11.95%), and fruity esters such as isoamyl acetate (33.33%). Linear discriminant analysis (LDA) explained 96.31% of the total variance in a single component, successfully separating the fermentation stages. An artificial neural network discriminant analysis (ANNDA) model achieved 95% accuracy in the validation phase. These results confirm the E-nose’s ability to track biochemical transformations in real time and identify optimal fermentation points. This approach enhances quality control and sensory standardization in sourdough-based bakery products.
Source: Chemosensors
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,413
Awards: G1154813483, G675437911
OpenAlex ID: W4410503173
