TY - JOUR
T1 - Development of Fermented Teff-Based Probiotic Beverage and Its Process Monitoring Using Two-Dimensional Fluorescence Spectroscopy †
AU - Alemneh, Sendeku Takele
AU - Emire, Shimelis Admassu
AU - Jekle, Mario
AU - Paquet-Durand, Olivier
AU - Hitzmann, Bernd
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022
Y1 - 2022
N2 - This study aims to evaluate a teff-based substrate (hereinafter substrate) for its suitability to carry probiotics Lacticaseibacillus rhamnosus GG (LCGG) and Lactiplantibacillus plantarum A6 (LPA6). In addition, two-dimensional (2D) fluorescence spectroscopy was applied to monitor the fermentation process by analyzing its spectral data using partial least-squares regression (PLSR) and an artificial neural network (ANN). The fermentation process parameters time and inoculum were optimized to 15 h and 6 log cfu/mL, respectively. During a fermentation run using the optimized parameters, cell counts of LPA6 and LCGG were increased from 6 to 8.42 and 8.11 log cfu/mL, respectively. Values of pH, titratable acidity (TA), lactic acid, and acetic acid were measured in the ranges of 6.13–3.92, 0.37–1.5 g/L, 0–1.7 g/L, and 0.04–0.23 g/L, respectively. Glucose was progressively consumed throughout the fermentation process. For the prediction of cell counts of LPA6 and LCGG, relative root mean square error of predictions (pRMSEP) were measured between 0.25 and 0.37%. In addition, for lactic acid prediction, pRMSEP values of 7.6 and 7.7% were obtained. The findings of this research showed that cell counts of LPA6 and LCGG and content of lactic acid could be predicted accurately by 2D fluorescence spectroscopy coupled with PLSR and ANN. Moreover, whole teff flour alone could serve as a substrate to develop a probiotic-rich beverage.
AB - This study aims to evaluate a teff-based substrate (hereinafter substrate) for its suitability to carry probiotics Lacticaseibacillus rhamnosus GG (LCGG) and Lactiplantibacillus plantarum A6 (LPA6). In addition, two-dimensional (2D) fluorescence spectroscopy was applied to monitor the fermentation process by analyzing its spectral data using partial least-squares regression (PLSR) and an artificial neural network (ANN). The fermentation process parameters time and inoculum were optimized to 15 h and 6 log cfu/mL, respectively. During a fermentation run using the optimized parameters, cell counts of LPA6 and LCGG were increased from 6 to 8.42 and 8.11 log cfu/mL, respectively. Values of pH, titratable acidity (TA), lactic acid, and acetic acid were measured in the ranges of 6.13–3.92, 0.37–1.5 g/L, 0–1.7 g/L, and 0.04–0.23 g/L, respectively. Glucose was progressively consumed throughout the fermentation process. For the prediction of cell counts of LPA6 and LCGG, relative root mean square error of predictions (pRMSEP) were measured between 0.25 and 0.37%. In addition, for lactic acid prediction, pRMSEP values of 7.6 and 7.7% were obtained. The findings of this research showed that cell counts of LPA6 and LCGG and content of lactic acid could be predicted accurately by 2D fluorescence spectroscopy coupled with PLSR and ANN. Moreover, whole teff flour alone could serve as a substrate to develop a probiotic-rich beverage.
KW - 2D fluorescence spectroscopy
KW - functional beverage
KW - Lacticaseibacillus rhamnosus
KW - Lactiplantibacillus plantarum
KW - probiotic
KW - teff flour
UR - http://www.scopus.com/inward/record.url?scp=85144518149&partnerID=8YFLogxK
U2 - 10.3390/ECP2022-12650
DO - 10.3390/ECP2022-12650
M3 - Article
AN - SCOPUS:85144518149
SN - 2673-4591
VL - 19
JO - Engineering Proceedings
JF - Engineering Proceedings
IS - 1
M1 - 37
ER -