When is simple good enough: a comparison of the Gompertz, Baranyi, and three-phase linear models for fitting bacterial growth curves

1997 ◽  
Vol 14 (4) ◽  
pp. 313-326 ◽  
Author(s):  
R.L Buchanan ◽  
R.C Whiting ◽  
W.C Damert
Keyword(s):  
Bacterial Growth ◽  
Linear Models ◽  
Growth Curves ◽  
Three Phase

scholarly journals Effect of erythritol and xylitol on Streptococcus pyogenes causing peritonsillar abscesses

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Siiri Kõljalg ◽  
Risto Vaikjärv ◽  
Imbi Smidt ◽  
Tiiu Rööp ◽  
Anirikh Chakrabarti ◽  
...  
Keyword(s):  
Streptococcus Pyogenes ◽  
Bacterial Growth ◽  
Growth Curves ◽  
Culture Collection ◽  
Exponential Phase ◽  
Clinical Isolates ◽  
Growth Inhibitors ◽  
Throat Culture ◽  
Potent Growth

AbstractPolyols are effective against caries-causing streptococci but the effect on oropharynx-derived pyogenic streptococci is not well characterised. We aimed to study the effect of erythritol (ERY) and xylitol (XYL) against Streptococcus pyogenes isolated from peritonsillar abscesses (PTA). We used 31 clinical isolates and 5 throat culture collection strains. Inhibition of bacterial growth by polyols at 2.5%, 5% and 10% concentrations was studied and the results were scored. Amylase levels in PTA pus were compared to polyol effectivity scores (PES). Growth curves of four S. pyogenes isolates were analysed. Our study showed that XYL was more effective than ERY inhibiting 71–97% and 48–84% of isolates, respectively, depending of concentrations. 48% of clinical and all throat strains were inhibited by polyols in all concentrations (PES 3). PES was negative or zero in 26% of the isolates in the presence of ERY and in 19% of XYL. ERY enhanced the growth of S. pyogenes isolated from pus with high amylase levels. Polyols in all concentrations inhibited the growth in exponential phase. In conclusion, ERY and XYL are potent growth inhibitors of S. pyogenes isolated from PTA. Therefore, ERY and XYL may have potential in preventing PTA in the patients with frequent tonsillitis episodes.

Growth and spatiotemporal distribution of juvenile shortfin mako (Isurus oxyrinchus) in the western and central North Pacific

2015 ◽  
Vol 66 (12) ◽  
pp. 1176 ◽  
Author(s):  
M. Kai ◽  
K. Shiozaki ◽  
S. Ohshimo ◽  
K. Yokawa
Keyword(s):  
North Pacific ◽  
Linear Models ◽  
North Pacific Ocean ◽  
Age Groups ◽  
Growth Curves ◽  
Growth Function ◽  
Gaussian Mixture ◽  
Isurus Oxyrinchus ◽  
Shortfin Mako ◽  
Central North Pacific

This paper presents an estimation of growth curves and spatiotemporal distributions of juvenile shortfin mako shark (Isurus oxyrinchus) in the western and central North Pacific Ocean using port sampling data collected from 2005 to 2013. The monthly length compositions show a clear transition of three modes in the size range of smaller than 150-cm precaudal length (PCL), which were believed to represent the growth of age-0 to age-2 classes, and they were then decomposed into age groups by fitting a Gaussian mixture distribution. Simulation data of lengths at monthly ages were generated from the mean and standard deviation of each distribution, and fit with a von Bertalanffy growth function. Parameters of the estimated growth curves for males and females were 274.4 and 239.4cm PCL for the asymptotic length and 0.19 and 0.25 year–1 for the growth coefficient indicating apparently faster growth than previously reported. Generalised linear models were applied to age-0 to explore the seasonal changes of PCL by area. They were born during late autumn and winter off the coast of north-eastern Japan, an area known to have relatively high productivity compared with other pelagic areas, and gradually expanded their habitat eastward and northward with the seasons as they grew.

Decomposition of Growth Curves into Growth Rate and Acceleration: a Novel Procedure to Monitor Bacterial Growth and the Time-Dependent Effect of Antimicrobials

2021 ◽  
Author(s):  
M. Luisa Navarro-Pérez ◽  
M. Coronada Fernández-Calderón ◽  
Virginia Vadillo-Rodríguez
Keyword(s):  
Growth Rate ◽  
Mathematical Models ◽  
Bacterial Growth ◽  
Time Course ◽  
Antimicrobial Agents ◽  
Numerical Procedure ◽  
Growth Curves ◽  
Predictive Microbiology ◽  
Insight Into ◽  
Over Time

In this paper, a simple numerical procedure is presented to monitor the growth of Streptococcus sanguinis over time in the absence and presence of propolis, a natural antimicrobial. In particular, it is shown that the real-time decomposition of growth curves obtained through optical density measurements into growth rate and acceleration can be a powerful tool to precisely assess a large range of key parameters [ i.e. lag time ( t 0 ), starting growth rate ( γ 0 ), initial acceleration of the growth ( a 0 ), maximum growth rate ( γ max ), maximum acceleration ( a max ) and deceleration ( a min ) of the growth and the total number of cells at the beginning of the saturation phase ( N s )] that can be readily used to fully describe growth over time. Consequently, the procedure presented provides precise data of the time course of the different growth phases and features, which is expected to be relevant, for instance, to thoroughly evaluate the effect of new antimicrobial agents. It further provides insight into predictive microbiology, likely having important implications to assumptions adopted in mathematical models to predict the progress of bacterial growth. Importance: The new and simple numerical procedure presented in this paper to analyze bacterial growth will possibly allow identifying true differences in efficacy among antimicrobial drugs for their applications in human health, food security, and environment, among others. It further provides insight into predictive microbiology, likely helping in the development of proper mathematical models to predict the course of bacterial growth under diverse circumstances.

scholarly journals Nonlinear modeling growth body weight of Mangalarga Marchador horses

2017 ◽  
Vol 47 (4) ◽  
Author(s):  
Felipe Amorim Caetano Souza ◽  
Tales Jesus Fernandes ◽  
Raquel Silva de Moura ◽  
Sarah Laguna Conceição Meirelles ◽  
Rafaela Aparecida Ribeiro ◽  
...  
Keyword(s):  
Body Weight ◽  
Linear Models ◽  
Nonlinear Modeling ◽  
Growth Curves ◽  
Live Weight ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Cross Sectional ◽  
Adult Body Weight ◽  
The Cross

ABSTRACT: The analysis of the growth and development of various species has been done using the growth curves of the specific animal based on non-linear models. The objective of the current study was to evaluate the fit of the Brody, Gompertz, Logistic and von Bertalanffy models to the cross-sectional data of the live weight of the MangalargaMarchador horses to identify the best model and make accurate predictions regarding the growth and maturity in the males and females of this breed. The study involved recording the weight of 214 horses, of which 94 were males and 120 were non-pregnant females, between 6 and 153 months of age. The parameters of the model were estimated by employing the method of least squares, using the iteratively regularized Gauss-Newton method and the R software package. Comparison of the models was done based on the following criteria: coefficient of determination (R²); Residual Standard Deviation (RSD); corrected Akaike Information Criterion (AICc). The estimated weight of the adult horses by the models ranged between 431kg and 439kg for males and between 416kg and 420kg for females. The growth curves were studied using the cross-sectional data collection method. For males the von Bertalanffymodel was found to be the most effective in expressing growth, while in females the Brody model was more suitable. The MangalargaMarchador females achieve adult body weight earlier than the males.

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 Microcalorimetry—Versatile Method of Describing Bacterial Growth

2021 ◽  
Vol 11 (20) ◽  
pp. 9740
Author(s):  
Mihnea Ioan Gabriel Popa ◽  
Adrian Cursaru ◽  
Bogdan Serban ◽  
Bogdan Cretu ◽  
Andrei Alexandru Muntean ◽  
...  
Keyword(s):  
Bacterial Growth ◽  
Growth Curves ◽  
Time Interval ◽  
Bacterial Identification ◽  
Industrialized Countries ◽  
Postoperative Infections ◽  
Bacterial Colony ◽  
Artificial Joints ◽  
Thermal Signal ◽  
Alternative Means

(1) Background: Due to the aging population in industrialized countries and due to the increase in the number of traffic or sports accidents, the number of artificial joints and implants for osteosynthesis will increase in the coming years. Therefore, the risk of postoperative infections will be higher as well. (2) Methods: For this study, we combined classical bacterial identification with the description of bacterial growth curves using microcalorimetry. (3) Results: We evaluated the growth of S. aureus and S. epedermidis, but we believe that this can be applied to any anaerobic or aerobic bacterial colony. We discovered that the time interval after which we can identify a growth curve does not exceed 15–20 h. (4) Conclusions: The diagnosis made by combining the methods of sonication and microcalorimetry manages to provide a great deal of information about the bacteria we studied. Microcalorimetry has real potential as a method for obtaining quick diagnosis in various cases of infection, but many more experiments need to be done to ensure the correct use of this technique. A detailed investigation (including kinetic analysis) of the reproducible thermal signal of bacterial growth can lead to the development of alternative means of rapid bacterial identification.

Notes on reparameterization of bacterial growth curves

1992 ◽  
Vol 9 (2) ◽  
pp. 169-171 ◽  
Author(s):  
József Baranyi
Keyword(s):  
Bacterial Growth ◽  
Growth Curves

Bacterial Normalized Binary Fission Growth Model

2021 ◽  
Author(s):  
John P Keady
Keyword(s):  
Growth Model ◽  
Bacterial Growth ◽  
Bacterial Population ◽  
Size Range ◽  
Control Sample ◽  
Growth Curves ◽  
Growth Cycle ◽  
Binary Fission ◽  
Bacterial Proliferation

Mathematical models have traditionally been used to facilitate the interpretation of bacterial growth curves in order to more accurately understand and identify variations in bacterial proliferation. Here, a binary fission growth model was developed to normalize starting bacterial levels, allowing for the identification of changes in bacterial growth and the separation of a bacterial population as it correlates to size. This normalized binary fission model (NBF) relies on a multi-bin growth mode, where each bin is associated with a size range during a growth cycle. The proposed NBF model allows for a determination of the percentage of treated bacteria eradicated compared to a control sample, either generally across all bacterial binary fission sizes or specific to a size range or bin. Comparisons between the NBF model and experimental observations demonstrates that bacterial growth curves, and the ratio of sample growth to a control, can be used to both determine and normalize initial variations in bacterial size, and quantity, among test samples, as well as identify final nutrient levels and the percentage of bacteria affected by treatment.

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