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. 2023 Sep 6;23(18):7681.
doi: 10.3390/s23187681.

Online Monitoring of Sourdough Fermentation Using a Gas Sensor Array with Multivariate Data Analysis

Marvin Anker  1 , Abdolrahim Yousefi-Darani  2 , Viktoria Zettel  2 , Olivier Paquet-Durand  2 , Bernd Hitzmann  2 , Christian Krupitzer  1
Affiliations

Online Monitoring of Sourdough Fermentation Using a Gas Sensor Array with Multivariate Data Analysis

Marvin Anker et al. Sensors (Basel). .

Abstract

Sourdough can improve bakery products' shelf life, sensory properties, and nutrient composition. To ensure high-quality sourdough, the fermentation has to be monitored. The characteristic process variables for sourdough fermentation are pH and the degree of acidity measured as total titratable acidity (TTA). The time- and cost-intensive offline measurement of process variables can be improved by utilizing online gas measurements in prediction models. Therefore, a gas sensor array (GSA) system was used to monitor the fermentation process of sourdough online by correlation of exhaust gas data with offline measurement values of the process variables. Three methods were tested to utilize the extracted features from GSA to create the models. The most robust prediction models were achieved using a PCA (Principal Component Analysis) on all features and combined two fermentations. The calibrations with the extracted features had a percentage root mean square error (RMSE) from 1.4% to 12% for the pH and from 2.7% to 9.3% for the TTA. The coefficient of determination (R2) for these calibrations was 0.94 to 0.998 for the pH and 0.947 to 0.994 for the TTA. The obtained results indicate that the online measurement of exhaust gas from sourdough fermentations with gas sensor arrays can be a cheap and efficient application to predict pH and TTA.

Keywords: food monitoring; gas sensor; machine learning; process analytics; process modeling; sourdough.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure A1
Figure A1
pH and TTA change during fermentation on the example of F9.
Figure 1
Figure 1
Set-up of the gas sensor array (GSA) system: The GSA contains a DC/AC converter (1), a tube connection from the oxygen gas cylinder (2), the gas measurement chamber (3), a flow meter (4), a tube connection from the bioreactor (5), and the Arduino microcontroller (6).
Figure 2
Figure 2
Schematic diagram of the GSA system [22] and its integration into the fermentation setup.
Figure 3
Figure 3
Peak height and area values from the feature extraction of MQ3 of F5.
Figure 4
Figure 4
Experimental set-up of the sourdough fermentation: The set-up contains a stainless-steel fermenter (1), a water bath (2), an offline sample outlet (3), an impeller mixer (4), an engine (5), and the connection to the gas sensor module (6).
See this image and copyright information in PMC

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