Modelling of photosynthesis, respiration, and nutrient yield coefficients in Scenedemus almeriensis culture as a function of nitrogen and phosphorus

Photo-respirometric tecniques are applied for evaluating photosynthetic activity in phototrophic organisms. These methods allow to evaluate photosynthetic response under different conditions. In this work, the influence of nutrient availability (nitrate, ammonium, and phosphate) on the photosynthesis and respiration of Scenedesmus almeriensis was studied using short photo-respirometric measurements. Both photosynthesis and respiration increasing until saturation value and consecutively diminishing, presenting inhibition by high concentrations. Regarding the influence of phosphorus concentration in microalgae cells, a similar hyperbolic trend was observed but no inhibition was observed at high concentration. Based on these experimental data, the respiration, and the photosynthesis rate of S. almeriensis were modelled using Haldane equation for nitrate and ammonium data, and Monod equation for phosphate data. In addition, experiments were performed to determine the yield coefficients for both nitrogen and phosphorus in S. almeriensis cultures. The data showed that the nitrogen and phosphorous coefficient yields are not constant, being modified as a function of nutrients concentration, presenting the luxury uptake phenomena. Finally, the proposed models were incorporated into a simulation tool to evaluate the photosynthetic activity and the nutrient yield coefficients of S. almeriensis when different culture media and wastewaters are used as a nitrogen and phosphorous source for its growth.Key points• Microalgal photosynthesis/respiration vary as a function of nutrients availability.• Photosynthesis inhibition appears at high N-NO3-and N-NH4+concentrations.• Nutrient yield coefficients are influenced by luxury uptake phenomenon. Graphical abstract

Wastewater Treatment Process: A Modified Mathematical Model for Oxidation Ponds

Wastewater treatment aims to eliminate as many suspended solids as possible from the remaining water, known as effluent, before it is released into the environment. Pond oxidation methods have been practically proven successful for the wastewater treatment process because of their low construction and maintenance costs. This study aimed to investigate the degradation of wastewater pollutants through an oxidation pond treatment system. The purpose was to observe the relationship between the concentration of bacteria which are phototrophic and coliform, chemical oxygen demand (COD), and dissolved oxygen (DO). In this paper, a modified model consist of a set of an ordinary differential equation (ODE) has been developed by incorporating the Monod Equation. The model was solved numerically using the 4th order Runge Kutta method embedded in the MATLAB software. The sum of squared estimate of errors (SSE) for the modified model was compared with the SSE of the existing model. The results revealed that the modified model demonstrated a lower SSE compared to the existing model. Thus, the modified mathematical model gives better result than the existing model. The model provides an excellent approximation for concentration needed for an oxidized pond to produce good water quality.

Monod model is insufficient to explain biomass growth in nitrogen-limited yeast fermentation

The yeast Saccharomyces cerevisiae is an essential microorganism in food biotechnology; particularly, in wine and beer making. During wine fermentation, yeasts transform sugars present in the grape juice into ethanol and carbon dioxide. The process occurs in batch conditions and is, for the most part, an anaerobic process. Previous studies linked limited-nitrogen conditions with problematic fermentations, with negative consequences for the performance of the process and the quality of the final product. It is, therefore, of the highest interest to anticipate such problems through mathematical models. Here we propose a model to explain fermentations under nitrogen-limited anaerobic conditions. We separated the biomass formation into two phases: growth and carbohydrate accumulation. Growth was modelled using the well-known Monod equation while carbohydrate accumulation was modelled by an empirical function, analogous to a proportional controller activated by the limitation of available nitrogen. We also proposed to formulate the fermentation rate as a function of the total protein content when relevant data are available. The final model was used to successfully explain experiments taken from the literature, performed under normal and nitrogen-limited conditions. Our results revealed that Monod model is insufficient to explain biomass formation kinetics in nitrogen-limited fermentations of S. cerevisiae . The goodness-of-fit of the herewith proposed model is superior to that of previously published models, offering the means to predict, and thus control fermentations. Importance: Problematic fermentations still occur in the winemaking industrial practise. Problems include sluggish rates of fermentation, which have been linked to insufficient levels of assimilable nitrogen. Data and relevant models can help anticipate poor fermentation performance. In this work, we proposed a model to predict biomass growth and fermentation rate under nitrogen-limited conditions and tested its performance with previously published experimental data. Our results show that the well-known Monod equation does not suffice to explain biomass formation.

The Relationship between Fungal Growth Rate and Temperature and Humidity

In order to determine the relation among the three factors of wood fiber decomposition rate, mycelial elongation and moisture resistance, our team resorted to the Monod equation and the modified Logistic equation. Combing with the kinetic principle and the law of mass action, the equations between the decomposition rate of wood fiber, the elongation rate of mycelium and the moisture resistance were established. In the course of solving the model, we found that when the temperature ranges from 24? to 28? and the relative humidity from 60% to75%, the growth rate of fungi is the fastest.

Monod model is insufficient to explain biomass growth in nitrogen-limited yeast fermentation

The yeast Saccharomyces cerevisiae is an essential microorganism in food biotechnology; particularly, in wine and beer making. During wine fermentation, yeasts transform sugars present in the grape juice into ethanol and carbon dioxide. The process occurs in batch conditions and is, for the most part, an anaerobic process. Previous studies linked limited-nitrogen conditions with problematic fermentations, with negative consequences for the performance of the process and the quality of the final product. It is, therefore, of the highest interest to anticipate such problems through mathematical models. Here we propose a model to explain fermentations under nitrogen-limited anaerobic conditions. We separated the biomass formation into two phases: growth and carbohydrate accumulation. Growth was modelled using the well-known Monod equation while carbohydrate accumulation was modelled by an empirical function, analogous to a proportional controller activated by the limitation of available nitrogen. We also proposed to formulate the fermentation rate as a function of the total protein content when relevant data are available. The final model was used to successfully explain experiments taken from the literature, performed under normal and nitrogen-limited conditions. Our results revealed that Monod model is insufficient to explain biomass formation kinetics in nitrogen-limited fermentations of S. cerevisiae. The goodness-of-fit of the herewith proposed model is superior to that of previously published models, offering the means to predict, and thus control fermentations.

Modeling sulfide production in full flow concrete sewers based on the HRT variation of sewerage

The corrosion and odor in concrete sewers are mainly related to the sulfide production, which is, under certain circumstances, directly proportional to the hydraulic retention time (HRT) of the sewer. To reduce the corrosion and control the odor in the concrete sewers, it is necessary to model the production of sulfide in the concrete sewers with different HRTs. However, previous researches were mostly carried out in the simulated Perspex-made sewers, and the obtained theoretical formulas based on the Monod equation were impractical because of the complexity. An actual concrete pipe with domestic sewage was employed in this study to obtain a simple but practical model, which can be applied to quantitively describe the sulfide production according to the HRT of the sewer and the COD of the sewage. The empirical equation obtained was rs = (0.045 × lnHRT + 0.071) × ([COD] - b)0.6, the coefficient is a logarithmic function of the HRT, and the sulfide production rate and COD has a power relationship. Based on the data of COD and HRT obtained in the realistic sewer, the production of sulfide in the sewer can be predicted for better maintaining sewer through sulfide control.

Enhanced denitrification of secondary effluent using composite solid carbon source based on agricultural wastes and synthetic polymers

Solid-phase denitrification is a promising approach to enhance nitrate removal. In this work, polybutylene succinate (PBS) and peanut shell (PS) (with crosslinked polyvinyl alcohol–sodium alginate (PVA-SA) as carrier) were used to prepare a composite solid carbon source (3P) to denitrify the secondary effluent. The results showed that for carbon release performance, 3P had not only a large release of organics, like PS, but also the excellent sustainability of PBS. Among the short chain fatty acids released by PBS, PS, PVA-SA and 3P, the percentages of acetic acid were 59.42%, 72.54%, 72.29% and 92.11%, respectively. When 3P was used as external carbon source, denitrification performance could be enhanced with effluent dissolved organic carbon lower than 20 mg/L. The prepared 3P could improve denitrification, from both microbial and kinetic aspects. The relative abundance of Gammaproteobacteria increased from 39.32% to 43.58%, and the half saturation constant of the fitting Monod equation was 21.28 mg/L. The prepared 3P is an ideal carbon source for secondary effluent denitrification. Using multiple crosslinking methods to produce carrier is an effective way to show the properties of each material.

Characterization of 1,4-Dioxane Biodegradation by a Microbial Community

In this study, a microbial community of bacteria was investigated for 1,4-dioxane(1,4-D) biodegradation. The enriched culture was investigated for 1,4-dioxane mineralization, co-metabolism of 1,4-dioxane and extra carbon sources, and characterized 1,4-dioxane biodegradation kinetics. The mineralization test indicates that the enriched culture was able to degrade 1,4-dioxane as the sole carbon and energy source. Interestingly, the distribution of 1,4-dioxane into the final biodegrading products were 36.9% into biomass, 58.3% completely mineralized to CO2, and about 4% escaped as VOC. The enriched culture has a high affinity with 1,4-dioxane during biodegradation. The kinetic coefficients of the Monod equation were qmax = 0.0063 mg 1,4-D/mg VSS/h, Ks = 9.42 mg/L, YT = 0.43 mg VSS/mg 1,4-dioxane and the decay rate was kd = 0.023 mg/mg/h. Tetrahydrofuran (THF) and ethylene glycol were both consumed together with 1,4-dioxane by the enriched culture; however, ethylene glycol did not show any influence on 1,4-dioxane biodegradation, while THF proved to be a competitive.

Applying Logistic and Monod models in a single equations system framework for cell culture growth modeling and estimation

In modeling cell culture growth, two types of modeling equations are normally used: logistic and Monod. These two equations are known for their strengths and weaknesses in modeling cell culture growth. In this contribution, we show how these equations can be used in a single equations system framework to model cell culture growth that is supported by experimental observation. Specifically, we propose that logistic equation is used to model the dynamic of total cells growth that is simply the summation of viable and dead cells populations in the system. Subsequently, Monod equation is used to model the dynamic of viable cells growth that is subjected to growth-limiting substrate and cells death rate term. With this paradigm, a rate equation can be written for the accumulation of dead cells in the system with a simple understanding that dead cells population is simply the difference between total and viable cells. These equations can be adjoined with appropriate substrate consumption and product generation rate equations to depict a complete time course profiles of batch culture experiment. This modeling framework has been fitted successfully to depict a batch growth data of IgG-secreting murine hybridoma cell from published literature.

Applying Logistic and Monod models in a single equations system framework for cell culture growth modeling and estimation

In modeling cell culture growth, two types of modeling equations are normally used: logistic and Monod. These two equations are known for their strengths and weaknesses in modeling cell culture growth. In this contribution, we show how these equations can be used in a single equations system framework to model cell culture growth that is supported by experimental observation. Specifically, we propose that logistic equation is used to model the dynamic of total cells growth that is simply the summation of viable and dead cells populations in the system. Subsequently, Monod equation is used to model the dynamic of viable cells growth that is subjected to growth-limiting substrate and cells death rate term. With this paradigm, a rate equation can be written for the accumulation of dead cells in the system with a simple understanding that dead cells population is simply the difference between total and viable cells. These equations can be adjoined with appropriate substrate consumption and product generation rate equations to depict a complete time course profiles of batch culture experiment. This modeling framework has been fitted successfully to depict a batch growth data of IgG-secreting murine hybridoma cell from published literature.