scholarly journals Correction: Garcia et al. Primary Model for Biomass Growth Prediction in Batch Fermentation. Symmetry 2021, 13, 1468

Symmetry ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 19
Author(s):  
Blanca E. Garcia ◽  
Emmanuel Rodriguez ◽  
Yolocuauhtli Salazar ◽  
Paul A. Valle ◽  
Adriana C. Flores-Gallegos ◽  
...  
Keyword(s):  
Batch Fermentation ◽  
Biomass Growth ◽  
Growth Prediction ◽  
Primary Model

The authors wish to make the following corrections to this paper [...]

scholarly journals Primary Model for Biomass Growth Prediction in Batch Fermentation

Symmetry ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1468
Author(s):  
Yolocuauhtli Salazar ◽  
Emmanuel Rodriguez ◽  
Paul A. Valle ◽  
Blanca E. Garcia
Keyword(s):  
Mathematical Model ◽  
Batch Fermentation ◽  
Real Life ◽  
Maximum Growth ◽  
The Other ◽  
Coefficient Of Determination ◽  
Lag Phase ◽  
Biomass Growth ◽  
Phase Duration ◽  
Primary Model

Predictive models may be considered a tool to ensure food quality as they provide insights that support decision making on the design of processes, such as fermentation. Objective: To formulate a mathematical model that describes the growth of lactic acid bacteria (LAB) in batch fermentation. Methodology: Based on real-life experimental data from eight LAB strains, we formulated a primary model in the form of a third-degree polynomial function that successfully describes the four phases observed in LAB growth, i.e., lag, exponential, stationary, and death. Our cubic mathematical model allows us to understand the fundamental nonlinear dynamics of LAB as well as its time-variant dependencies. Parameters of the model are written in terms of initial biomass, maximum biomass, maximum growth rate, and lag phase duration. Further, a statistical analysis was performed to compare our cubic primary model with the ones proposed by Gompertz, Baranyi, and Vázquez-Murado by computing the coefficient of determination R2, the residual sum of squares RSS, and the Akaike Information Criterion AIC. Results: The average statistical results from the cubic model are as follows: R2=0.820 providing a better fit than the other three models, RSS=0.658 and AIC=−6.499, where both values are lower than the other models considered in this study. Conclusion: The cubic primary model formulated in this work describes the behavior of biomass as it accurately represents the four phases of biomass growth in batch fermentation process.

Investigation of culture conditions by Response Surface Methodology and kinetic modeling for exopolysaccharide production by Klebsiella oxytoca ICCF 419 strain, using lactose as substrate

2020 ◽  
Vol 25 (6) ◽  
pp. 2033-2044
Author(s):  
CATERINA TOMULESCU ◽  
◽  
MIŞU MOSCOVICI ◽  
ROXANA MĂDĂLINA STOICA ◽  
GABRIEL BUJOR ALBU ◽  
...  
Keyword(s):  
Citric Acid ◽  
Klebsiella Oxytoca ◽  
Fermentation Medium ◽  
Culture Conditions ◽  
Biomass Growth ◽  
Initial Value ◽  
Substrate Consumption ◽  
Polysaccharide Production ◽  
Crude Polysaccharide ◽  
Central Composite

The objective of this work was to optimize the bioprocess parameters, using Klebsiella oxytoca ICCF 419 to obtain an exopolysaccharide based on lactose as substrate. A kinetic study was employed and Logistic and Gompertz models were applied to describe the polysaccharide production, in relation with biomass growth and substrate consumption. The RSM methodology based on Central Composite Rotatable Design was used to evaluate and optimize the effect of lactose, corn extract, KH2PO4 and citric acid concentrations as independent variables on the polysaccharide production, biomass growth and substrate consumption as the response functions. The interaction effects and optimal parameters were obtained using Design Expert Software (version 9.0.6.2). The significance of the variables and their interactions was tested by means of ANOVA analysis with a 99% confidence level. The optimum culture conditions were determined and the model prediction was compared with experimental results. At an initial value of 23.45 for the C/N in the fermentation medium, the strain produces 17.41 g/L of crude polysaccharide and 2.53 g/L dry biomass. The EPS production was significantly influenced by lactose, corn extract and KH2PO4, while the citric acid had no influence. The biomass growth was influenced by the corn extract, KH2PO4 and citric acid.

A new potential of calcium carbonate production induced by Bacillus sphaericus in batch fermentation

2018 ◽  
Vol 10 (9) ◽  
Author(s):  
Nuraiffa Syazwi Adzami ◽  
◽  
Miskiah Fadzilah Ghazali ◽  
Amira Hidayati Ramli ◽  
Husnul Azan Tajarudin ◽  
...  
Keyword(s):  
Calcium Carbonate ◽  
Batch Fermentation ◽  
Bacillus Sphaericus ◽  
Carbonate Production

Glycerol Synthesis Attenuation ofCandida glycerinogenesin Fed-batch Fermentation

2012 ◽  
Vol 18 (5) ◽  
pp. 791
Author(s):  
Xiaoyun DING ◽  
Bin ZHUGE ◽  
Huiying FANG ◽  
Hong ZONG ◽  
Xiaoxiao LIU ◽  
...  
Keyword(s):  
Batch Fermentation ◽  
Fed Batch ◽  
Fed Batch Fermentation ◽  
Glycerol Synthesis

Nonlinear dispersion hyperbolic models of continuous media

2007 ◽  
Vol 5 ◽  
pp. 273-278
Author(s):  
V.Yu Liapidevskii
Keyword(s):  
Boussinesq Equations ◽  
Nonlinear Dispersion ◽  
Order Of Accuracy ◽  
Flow Models ◽  
Wave Approximation ◽  
Long Wave ◽  
Primary Model ◽  
Nonequilibrium Flows ◽  
Internal Inertia ◽  
Long Wave Approximation

Nonequilibrium flows of an inhomogeneous liquid in channels and pipes are considered in the long-wave approximation. Nonlinear dispersion hyperbolic flow models are derived allowing taking into account the influence of internal inertia during the relative motion of phases upon the structure of nonlinear wave fronts. The asymptotic derivation of dispersion hyperbolic models is shown on the example of classical Boussinesq equations. It is shown that the hyperbolic approximation of the equations has the same order of accuracy as the primary model.

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