Browsing by Person "Jekle, Mario"

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Application of two-dimensional fluorescence spectroscopy for the on-line monitoring of teff-based substrate fermentation inoculated with certain probiotic bacteria
(2022) Alemneh, Sendeku Takele; Emire, Shimelis Admassu; Jekle, Mario; Paquet-Durand, Olivier; von Wrochem, Almut; Hitzmann, Bernd
There is increasing demand for cereal-based probiotic fermented beverages as an alternative to dairy-based products due to their limitations. However, analyzing and monitoring the fermentation process is usually time consuming, costly, and labor intensive. This research therefore aims to apply two-dimensional (2D)-fluorescence spectroscopy coupled with partial least-squares regression (PLSR) and artificial neural networks (ANN) for the on-line quantitative analysis of cell growth and concentrations of lactic acid and glucose during the fermentation of a teff-based substrate. This substrate was inoculated with mixed strains of Lactiplantibacillus plantarum A6 (LPA6) and Lacticaseibacillus rhamnosus GG (LCGG). The fermentation was performed under two different conditions: condition 1 (7 g/100 mL substrate inoculated with 6 log cfu/mL) and condition 2 (4 g/100 mL substrate inoculated with 6 log cfu/mL). For the prediction of LPA6 and LCGG cell growth, the relative root mean square error of prediction (pRMSEP) was measured between 2.5 and 4.5%. The highest pRMSEP (4.5%) was observed for the prediction of LPA6 cell growth under condition 2 using ANN, but the lowest pRMSEP (2.5%) was observed for the prediction of LCGG cell growth under condition 1 with ANN. A slightly more accurate prediction was found with ANN under condition 1. However, under condition 2, a superior prediction was observed with PLSR as compared to ANN. Moreover, for the prediction of lactic acid concentration, the observed values of pRMSEP were 7.6 and 7.7% using PLSR and ANN, respectively. The highest error rates of 13 and 14% were observed for the prediction of glucose concentration using PLSR and ANN, respectively. Most of the predicted values had a coefficient of determination (R2) of more than 0.85. In conclusion, a 2D-fluorescence spectroscopy combined with PLSR and ANN can be used to accurately monitor LPA6 and LCGG cell counts and lactic acid concentration in the fermentation process of a teff-based substrate. The prediction of glucose concentration, however, showed a rather high error rate.
Effect of refrigerated storage on some physicochemical characteristics of a teff‐based fermented beverage and the viability of the fermenting Lactiplantibacillus plantarum and Lacticaseibacillus rhamnosus used
(2022) Alemneh, Sendeku Takele; Emire, Shimelis Admassu; Jekle, Mario; Hitzmann, Bernd
Probiotic beverages made from cereals become interesting in the recent food industries. In this contribution, a fermented teff-based probiotic beverage was produced using the whole grain teff flour and co-culture strains of Lactiplantibacillus plantarum (LPA6) and Lacticaseibacillus rhamnosus GG (LCGG). Then, the effect of 25 days of refrigerated storage on cell viability (LPA6 and LCGG), and contents of sugars, organic acids, and titratable acidity (TA), as well as pH values were examined. Furthermore, pathogenic microorganisms, hygiene indicators, and sensory tests of the beverage were analyzed. Presumptive cell counts of LPA6 and LCGG were observed to decrease throughout refrigerated storage. Glucose, lactic acid, maltose, and acetic acid contents were significantly (p < 0.05) increased over storage time. Also, pH reduction and TA increment were observed in storage time. Examined pathogenic microorganisms and hygiene indicators were not detected in the beverage. Sensory analysis of the beverage after 10 days of refrigerated storage was accepted by the panelists. Novelty Impact Statement Throughout refrigerated storage of teff-based probiotic beverage sugars and organic acids were produced. Sensory attributes of the newly produced teff-based probiotic beverage were accepted by the panelist after 10 days of refrigerated storage. The pH of the teff-based probiotic beverage became more acidic throughout 25 days of refrigerated storage.
Four-dimensional (4D) printing of dynamic foods - definitions, considerations, and current scientific status
(2023) Fahmy, Ahmed Raouf; Derossi, Antonio; Jekle, Mario
Since its conception, the application of 3D printing in the structuring of food materials has been focused on the processing of novel material formulations and customized textures for innovative food applications, such as personalized nutrition and full sensory design. The continuous evolution of the used methods, approaches, and materials has created a solid foundation for technology to process dynamic food structures. Four-dimensional food printing is an extension of 3D printing where food structures are designed and printed to perform time-dependent changes activated by internal or external stimuli. In 4D food printing, structures are engineered through material tailoring and custom designs to achieve a transformation from one configuration to another. Different engineered 4D behaviors include stimulated color change, shape morphing, and biological growth. As 4D food printing is considered an emerging application, imperatively, this article proposes new considerations and definitions in 4D food printing. Moreover, this article presents an overview of 4D food printing within the current scientific progress, status, and approaches.
Microscopic analysis of gluten network development under shear load—combining confocal laser scanning microscopy with rheometry
(2023) Vidal, Leonhard Maria; Ewigmann, Hans; Schuster, Clemens; Alpers, Thekla; Scherf, Katharina Anne; Jekle, Mario; Becker, Thomas
A comprehensive in‐situ analysis of the developing gluten network during kneading is still a gap in cereal science. With an in‐line microscale shear kneading and measuring setup in a conventional rheometer, a first step was taken in previous works toward fully comprehensible gluten network development evaluation. In this work, this setup was extended by an in‐situ optical analysis of the evolving gluten network. By connecting a laser scanning microscope with a conventional rheometer, the evaluation of the rheological and optical protein network evolution was possible. An image processing tool for analyzing the protein network was applied for evaluating the gluten network development in a wheat dough during the shear kneading process. This network evaluation was possible without interruption or invasive sample transfer comparing it to former approaches. The shear kneading system was able to produce a fully developed dough matrix within 125% of the reference dough development time in a classical kneader. The calculated network connectivity values from frequency testing ranged over all samples was in good agreement with traditional kneaded wheat dough just over peak consistency.
Multi‐scale dough adhesion analysis: Relation between laboratory scale, pilot scale and human sensory
(2023) Vogt, Ulrike Therese; Kwak, Ju Eun; Fahmy, Ahmed Raouf; Laukemper, Rita; Henrich, Alexander; Becker, Thomas; Jekle, Mario
Undesired dough adhesion is still a challenge during the production of baked goods. There are various methods for determining the adhesive texture properties of dough. In the majority of scientific papers, dough stickiness is measured analytically by the force‐distance recording of dough detachment. In this study, we describe a new multi‐scale approach to compare dough adhesion phenomena in a laboratory, pilot sale and human sensory assessment. In it, the adhesive material properties of dough were investigated using a pilot scale toppling device representing dough adhesion behavior in the production process, in the laboratory by texture analysis with the Chen–Hoseney method and furthermore with a new, implemented non‐oral human sensory analysis. To simulate different dough adhesion behavior, the dough mechanical and adhesion properties were varied by applying dough‐modifying enzymes and different dough storage times. The structural changes in the different wheat dough system were compared by rheological characterization. By characterizing the different adhesion phenomena of the doughs, the sample with bacterial xylanase showed the highest values after 80 min of storage time in all three methods. Correlation analysis revealed a strong relationship between the detachment time (pilot scale) and human sensory assessment attributes (Force R = 0.81, Time R = 0.87, Distance R = 0.92, Stickiness R = 0.80) after 80 min of storage time. Even though human sensory assessment showed limits in the detectability of differences in dough adhesion behavior compared to the Chen–Hoseney method, it was better suited to predict machinability.