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.

scholarly journals Growth of Listeria monocytogenes in Thawed Frozen Foods

2017 ◽  
Vol 80 (3) ◽  
pp. 447-453 ◽  
Author(s):  
Ai Kataoka ◽  
Hua Wang ◽  
Philip H. Elliott ◽  
Richard C. Whiting ◽  
Melinda M. Hayman
Keyword(s):  
Growth Rate ◽  
Listeria Monocytogenes ◽  
Growth Rates ◽  
Storage Temperature ◽  
Growth Parameters ◽  
Quadratic Model ◽  
Lag Phase ◽  
Frozen Foods ◽  
Phase Duration ◽  
Primary Model

ABSTRACT The growth characteristics of Listeria monocytogenes inoculated onto frozen foods (corn, green peas, crabmeat, and shrimp) and thawed by being stored at 4, 8, 12, and 20°C were investigated. The growth parameters, lag-phase duration (LPD) and exponential growth rate (EGR), were determined by using a two-phase linear growth model as a primary model and a square root model for EGR and a quadratic model for LPD as secondary models, based on the growth data. The EGR model predictions were compared with growth rates obtained from the USDA Pathogen Modeling Program, calculated with similar pH, salt percentage, and NaNO2 parameters, at all storage temperatures. The results showed that L. monocytogenes grew well in all food types, with the growth rate increasing with storage temperature. Predicted EGRs for all food types demonstrated the significance of storage temperature and similar growth rates among four food types. The predicted EGRs showed slightly slower rate compared with the values from the U.S. Department of Agriculture Pathogen Modeling Program. LPD could not be accurately predicted, possibly because there were not enough sampling points. These data established by using real food samples demonstrated that L. monocytogenes can initiate growth without a prolonged lag phase even at refrigeration temperature (4°C), and the predictive models derived from this study can be useful for developing proper handling guidelines for thawed frozen foods during production and storage.

Dynamic Predictive Model for Growth of Bacillus cereus from Spores in Cooked Beans

2017 ◽  
Vol 81 (2) ◽  
pp. 308-315 ◽  
Author(s):  
Vijay K. Juneja ◽  
Abhinav Mishra ◽  
Abani K. Pradhan
Keyword(s):  
Bacillus Cereus ◽  
Growth Rates ◽  
Linear Models ◽  
Growth Models ◽  
Maximum Growth ◽  
Effect Of Temperature ◽  
Coefficient Of Determination ◽  
Growth Data ◽  
Three Phase ◽  
Primary Model

ABSTRACT Kinetic growth data for Bacillus cereus grown from spores were collected in cooked beans under several isothermal conditions (10 to 49°C). Samples were inoculated with approximately 2 log CFU/g heat-shocked (80°C for 10 min) spores and stored at isothermal temperatures. B. cereus populations were determined at appropriate intervals by plating on mannitol–egg yolk–polymyxin agar and incubating at 30°C for 24 h. Data were fitted into Baranyi, Huang, modified Gompertz, and three-phase linear primary growth models. All four models were fitted to the experimental growth data collected at 13 to 46°C. Performances of these models were evaluated based on accuracy and bias factors, the coefficient of determination (R2), and the root mean square error. Based on these criteria, the Baranyi model best described the growth data, followed by the Huang, modified Gompertz, and three-phase linear models. The maximum growth rates of each primary model were fitted as a function of temperature using the modified Ratkowsky model. The high R2 values (0.95 to 0.98) indicate that the modified Ratkowsky model can be used to describe the effect of temperature on the growth rates for all four primary models. The acceptable prediction zone (APZ) approach also was used for validation of the model with observed data collected during single and two-step dynamic cooling temperature protocols. When the predictions using the Baranyi model were compared with the observed data using the APZ analysis, all 24 observations for the exponential single rate cooling were within the APZ, which was set between −0.5 and 1 log CFU/g; 26 of 28 predictions for the two-step cooling profiles also were within the APZ limits. The developed dynamic model can be used to predict potential B. cereus growth from spores in beans under various temperature conditions or during extended chilling of cooked beans.

scholarly journals Fuzzy Win-Win: A Novel Approach to Quantify Win-Win Using Fuzzy Logic

2021 ◽  
Author(s):  
Ahmad B. Hassanat ◽  
Ghada A. Altarawneh ◽  
Ahmad S. Tarawneh
Keyword(s):  
Mathematical Model ◽  
Fuzzy Logic ◽  
Iron Ore ◽  
Real Life ◽  
The Other ◽  
Uranium Enrichment ◽  
Single Product ◽  
Novel Approach

Abstract The classic win-win has a key flaw in that it cannot offer the parties with right amounts of winning because each party believes they are winners. In reality, one party may win more than the other. This strategy is not limited to a single product or negotiation; it may be applied to a variety of situations in life. We present a novel way to measure the win-win situation in this paper. The proposed method employs the Fuzzy logic to create a mathematical model that aids negotiators in quantifying their winning percentages. The model is put to the test on real-life negotiation scenarios such as the Iranian uranium enrichment negotiations, the Iraqi-Jordanian oil deal, and the iron ore negotiation (2005-2009). The presented model has shown to be a useful tool in practice and can be easily generalized to be utilized in other domains as well.

scholarly journals Prediction of growth kinetics of Pseudomonas spp. in meat products under isothermal and non-isothermal storage conditions

2021 ◽  
Vol 7 (3) ◽  
pp. 194-202
Author(s):  
Fatih Tarlak
Keyword(s):  
Goodness Of Fit ◽  
Storage Temperature ◽  
Food Products ◽  
Storage Conditions ◽  
Chicken Meat ◽  
Lag Phase ◽  
Phase Duration ◽  
Pseudomonas Spp ◽  
Primary Model ◽  
One Step

The main objective of the present study was to develop and validate a new alternative modelling method to predict the shelf-life of food products under non-isothermal storage conditions. The bacterial growth data of the Pseudomonas spp. was extracted from published studies conducted for aerobically-stored fish, pork and chicken meat and described with two-step and one-step modelling approaches employing different primary models (the modified Gompertz, logistic, Baranyi and Huang models) under isothermal storage temperatures. Temperature dependent kinetic parameters (maximum specific growth rate ‘µmax’ and lag phase duration ‘λ’) were described as a function of storage temperature via the Ratkowsky model integrated with each primary model. The Huang model based on the one-step modelling approach yielded the best goodness of fit results (RMSE = 0.451 and adjusted-R2 = 0.942) for all food products at isothermal storage conditions, therefore, was also used to check it’s the prediction capability under non-isothermal storage conditions. The differential form of the Huang model provided satisfactorily statistical indexes (1.075 > Bf > 1.014 and 1.080 > Af > 1.047) indicating reliably being able to use to describe the growth behaviour of Pseudomonas spp. in fish, pork and chicken meat subjected to non-isothermal storage conditions.

A Predictive Model for the Growth of Listeria monocytogenes in Commercial Blue Crab (Callinectes sapidus)

2017 ◽  
Vol 80 (11) ◽  
pp. 1872-1876
Author(s):  
Salina Parveen ◽  
Channel White ◽  
Mark L. Tamplin
Keyword(s):  
Listeria Monocytogenes ◽  
Blue Crab ◽  
Callinectes Sapidus ◽  
Lag Phase ◽  
Published Data ◽  
Predictive Tool ◽  
Phase Duration ◽  
Primary Model ◽  
Increasing Temperature ◽  
Crab Meat

ABSTRACT During the processing and handling of commercial blue crab (Callinectes sapidus), Listeria monocytogenes can potentially contaminate cooked meat and grow to hazardous levels. To manage this risk, predictive models are useful tools for designing and implementing preventive controls; however, no model specific for blue crab meat has been published or evaluated. In this study, a cocktail of L. monocytogenes strains was added to pasteurized blue crab meat, which was incubated at storage temperatures from 0 to 35°C. At selected time intervals, L. monocytogenes was enumerated by direct plating onto modified Oxford agar. A primary model was fitted to kinetic data to estimate the lag-phase duration (LPD) and growth rate (GR). Listeria monocytogenes replicated from 0 to 35°C, with GR ranging from 0.004 to 0.518 log CFU/h. Overall, the LPD decreased with increasing temperature, displaying a maximum value of 187 h at 0°C; however, this trend was not consistent. The LPD was not detected at 10°C, and it occurred inconsistently from trial to trial. A secondary GR model (R2 = 0.9892) for pasteurized crab meat was compared with the L. monocytogenes GR in fresh crab meat, demonstrating bias and accuracy factors of 0.98 and 1.36, respectively. The model estimates varied from other published data and models, especially at temperatures ≥5°C, supporting the need for a specific predictive tool for temperature deviations.

Growth of a Methane-Utilizing Mixed Culture HD6T on Methanol and Poly-β-Hydroxybutyrate Biosynthesis

2010 ◽  
Vol 160-162 ◽  
pp. 171-175 ◽  
Author(s):  
Jing Dong ◽  
Jia Ying Xin ◽  
Ying Xin Zhang ◽  
Lin Lin Chen ◽  
Hong Ye Liang ◽  
...  
Keyword(s):  
Mixed Culture ◽  
Mineral Salt Medium ◽  
Biomass Concentration ◽  
Dry Weight ◽  
Maximum Growth ◽  
Maximum Growth Rate ◽  
Production Costs ◽  
Lag Phase ◽  
Phase Duration ◽  
Phb Production

Methane-utilizing mixed culture HD6T was successfully cultivated in a brief non-sterile process using methanol as a sole carbon and energy source for the production of poly-β-hydroxybutyrate(PHB). Shake-flask experiments showed HD6T could grow well in the mineral salt medium with the addition of methanol exposed to the air directly. This non-sterile process and the use of cheap substrates (methanol) can reduce the production costs of PHB. It was found that HD6T grew better and PHB production in a more effective way with an initial liquid methanol concentration of 0.15%(v/v).The lag phase duration, the maximum growth rate, the biomass concentration and the PHB yield, for the optimal conditions were, respectively, 12.03h, 0.04h-1(OD600), 1.54g/l(dry weight), 0.424g/l(dry weight). Methane-utilizing mixed culture HD6T appears to be a promising organism for PHB production.

scholarly journals Phosphotransferase System-Dependent Extracellular Growth of Listeria monocytogenes Is Regulated by Alternative Sigma Factors σLand σH

2014 ◽  
Vol 80 (24) ◽  
pp. 7673-7682 ◽  
Author(s):  
Siyun Wang ◽  
Renato H. Orsi ◽  
Silin Tang ◽  
Wei Zhang ◽  
Martin Wiedmann ◽  
...  
Keyword(s):  
Listeria Monocytogenes ◽  
Carbon Source ◽  
Parent Strain ◽  
Carbon Sources ◽  
Maximum Growth ◽  
Fine Tuning ◽  
Lag Phase ◽  
Phosphotransferase System ◽  
Phase Duration ◽  
Content Type

ABSTRACTAlternative sigma (σ) factors and phosphotransferase systems (PTSs) play pivotal roles in the environmental adaptation and virulence ofListeria monocytogenes. The growth of theL. monocytogenesparent strain 10403S and 15 isogenic alternative σ factor mutants was assessed in defined minimal medium (DM) with PTS-dependent or non-PTS-dependent carbon sources at 25°C or 37°C. Overall, our results suggested that the regulatory effect of alternative σ factors on the growth ofL. monocytogenesis dependent on the temperature and the carbon source. One-way analysis of variance (one-way ANOVA) showed that the factor “strain” had a significant effect on the maximum growth rate (μmax), lag phase duration (λ), and maximum optical density (ODmax) in PTS-dependent carbon sources (P< 0.05) but not in a non-PTS-dependent carbon source. Also, the ODmaxwas not affected by strain for any of the three PTS-dependent carbon sources at 25°C but was affected by strain at 37°C. Monitoring by quantitative real-time PCR (qRT-PCR) showed that transcript levels forlmo0027, a glucose-glucoside PTS permease (PTSGlc-1)-encoding gene, were higher in the absence of σL, and lower in the absence of σH, than in the parent strain. Our data thus indicate that σLnegatively regulateslmo0027and that the increased μmaxobserved for the ΔsigLstrain in DM with glucose may be associated with increased expression of PTSGlc-1 encoded bylmo0027. Our findings suggest that σHand σLmediate the PTS-dependent growth ofL. monocytogenesthrough complex transcriptional regulations and fine-tuning of the expression of specificptsgenes, includinglmo0027. Our findings also reveal a more important and complex role of alternative σ factors in the regulation of growth in different sugar sources than previously assumed.

Growth Kinetics of Listeria Isolated from Salmon and Salmon Processing Environment: Single Strains versus Cocktails

2012 ◽  
Vol 75 (7) ◽  
pp. 1227-1235 ◽  
Author(s):  
TORSTEIN SKÅRA ◽  
ASTRID M. CAPPUYNS ◽  
EVA VAN DERLINDEN ◽  
JAN THOMAS ROSNES ◽  
VASILIS P. VALDRAMIDIS ◽  
...  
Keyword(s):  
Growth Rate ◽  
Relative Rate ◽  
Growth Parameter ◽  
Optimal Growth ◽  
Maximum Growth ◽  
Estimation Methods ◽  
Lag Phase ◽  
Phase Duration ◽  
Average Growth ◽  
Single Strain

The growth dynamics of Listeria monocytogenes strains isolated from salmon or a salmon processing environment and two reference Listeria innocua strains were investigated at refrigerated and close-to-optimal growth temperatures. Estimates for the growth rates and the lag-phase duration at 4, 8, 12, and 30°C were obtained for optical density measurements by using different growth parameter estimation methods, i.e., the serial dilution (SD) method and the relative rate to detection (RRD) method. Both single L. innocua and L. monocytogenes strains and mixtures of L. monocytogenes strains (cocktails) were studied. Both methods show an increase in maximum growth rate (μmax) of Listeria with increasing temperatures. Generally, single-strain growth rate estimates were quite similar for both species, although L. monocytogenes showed slightly higher μmax estimates at 4°C. The SD method gave the highest estimates for the growth rate, i.e., the estimates from the RRD method were 10 to 20% lower. This should lead to caution when using the latter method for Listeria, particularly at lower temperatures. Overall, the SD method is preferred as this method yields μmax estimates close to the biological value and provides estimates for the duration of lag time (λ). For discrimination between different strains, λ appeared to be a more suitable parameter than μmax. This effect was most prominent for L. innocua. Significant differences were observed between μmax and/or λ of L. monocytogenes cocktails and single strains at all temperatures investigated. At 4°C, the average growth rate of cocktails was higher than that of single strains. At 8 and 30°C, this trend was reversed. The average λ of single strains were more than twice as long as those of cocktails at 4°C. At 8 and 30°C, the λ of cocktails were significantly slower than those of single strains, but the variation was considerably less and the differences were less pronounced.

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 Reciprocal hemizygosity analysis reveals that the Saccharomyces cerevisiae CGI121 gene affects lag time duration in synthetic grape must

2021 ◽  
Author(s):  
Runze Li ◽  
Rebecca C Deed
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Low Temperatures ◽  
Lag Time ◽  
Lag Phase ◽  
Phenotypic Traits ◽  
Time Duration ◽  
Phase Duration ◽  
Grape Must ◽  
The Impact ◽  
Reciprocal Hemizygosity Analysis

Abstract It is standard practice to ferment white wines at low temperatures (10-18 °C). However, low temperatures increase fermentation duration and risk of problem ferments, leading to significant costs. The lag duration at fermentation initiation is heavily impacted by temperature; therefore, identification of Saccharomyces cerevisiae genes influencing fermentation kinetics is of interest for winemaking. We selected 28 S. cerevisiae BY4743 single deletants, from a prior list of open reading frames (ORFs) mapped to quantitative trait loci (QTLs) on chromosomes VII and XIII, influencing the duration of fermentative lag time. Five BY4743 deletants, Δapt1, Δcgi121, Δclb6, Δrps17a, and Δvma21, differed significantly in their fermentative lag duration compared to BY4743 in synthetic grape must (SGM) at 15 °C, over 72 h. Fermentation at 12.5 °C for 528 h confirmed the longer lag times of BY4743 Δcgi121, Δrps17a, and Δvma21. These three candidate ORFs were deleted in S. cerevisiae RM11-1a and S288C to perform single reciprocal hemizygosity analysis (RHA). RHA hybrids and single deletants of RM11-1a and S288C were fermented at 12.5 °C in SGM and lag time measurements confirmed that the S288C allele of CGI121 on chromosome XIII, encoding a component of the EKC/KEOPS complex, increased fermentative lag phase duration. Nucleotide sequences of RM11-1a and S288C CGI121 alleles differed by only one synonymous nucleotide, suggesting that intron splicing, codon bias, or positional effects might be responsible for the impact on lag phase duration. This research demonstrates a new role of CGI121 and highlights the applicability of QTL analysis for investigating complex phenotypic traits in yeast.

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