Molybdenum Blue Production from Serratia sp. strain DRY5: Secondary Modeling

In this work, kinetic growth models such as Luong, Yano, Teissier-Edward, Aiba, Haldane, Monod, Han and Levenspiel were used to model molybdenum blue production from Serratia sp. strain DRY5. Based on statistical analyses such as root-mean-square error (RMSE), adjusted coefficient of determination (adjR2), bias factor (BF), and accuracy factor (AF), the Monod model was chosen as the best. The calculated values for the monod constants qmax (the maximum specific substrate degradation rate (h−1), and Ks (concentration of substrate at the half maximal degradation rate (mg/L)) were found to be 3.86 (95% confidence interval of 2.29 to 5.43), and 43.41 (95% confidence interval of 12.36 to 74.46) respectively. The novel constants discovered during the modelling exercise could be used in further secondary modelling.

Modeling and Use of Inter-Criteria Decision Analysis for Selecting Growth Rate Models for Batch Cultivation of Yeast Kluyveromyces marxianus var. lactis MC 5

Ten unstructured models of Monod, Mink, Tessier, Moser, Aiba, Andrews, Haldane, Luong, Edward, and Han-Levenspiel are considered in this paper to explain the kinetics of cell growth for batch cultivation of the yeast Kluyweromyces marxianus var. lactis MC 5. For the first time, two independent kinetic models are used to model the process for the two basic substrates—lactose and oxygen. The selection of the most appropriate growth rate models has been made through a new multi-criteria decision-making approach called the Inter-Criteria Decision Analysis (ICDA) method. The application of ICDA to the growth rate of lactose and oxygen alone has shown that there have been many correlations between the studied models. Thus, the models for the growth rate, depending only on lactose, are reduced to one—Monod model and there are two models—Monod and Mink—depending on oxygen only. Separate kinetic process models have been developed for the combination of Monod–Monod and Monod–Mink models. For the first time, in addition to the multiplicative form, the additive form of a specific growth rate has been studied. The comparison of the obtained results has shown that the additive form has shown better results than the multiplicative one. For this reason, the additive form of the Monod–Monod model will be used to model the process.

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.

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.

Nitrification Process in a Nuclear Wastewater with High Load of Nitrogen, Uranium and Organic Matter under ORP Controlled

To produce nuclear fuels, it is necessary to convert uranium′s ore into UO2-ceramic grade, using several quantities of kerosene, methanol, nitric acid, ammonia, and, in low level, tributyl phosphate (TBP). Thus, the effluent generated by nuclear industries is one of the most toxic since it contains high concentrations of dangerous compounds. This paper explores biological parameters on real nuclear wastewater by the Monod model in an ORP controlled predicting the specific ammonia oxidation. Thermodynamic parameters were established using the Nernst equation to monitor Oxiders/Reductors relationship to obtain a correlation of these parameters to controlling and monitoring; that would allow technical operators to have better control of the nitrification process. The real nuclear effluent is formed by a mixture of two different lines of discharges, one composed of a high load of nitrogen, around 11,000 mg/L (N-NH4+-N-NO3−) and 600 mg/L Uranium, a second one, proceeds from uranium purification, containing TBP and COD that have to be removed. Bioprocesses were operated on real wastewater samples over 120 days under controlled ORP, as described by Nernst equations, which proved to be a robust tool to operate nitrification for larger periods with a very high load of nitrogen, uranium, and COD.

Growth Kinetic Study of Blue-green Microalgae Arthrospira platensis Using Buffalo Manure as Alternative Media

North Sumatera is one of the provinces in Indonesia with the highest buffalo population, which is responsible for the high accumulation of buffalo manure that can cause environmental and aesthetic problems if left untreated. One of the possible alternatives for solving this issue is by implementing buffalo manure as growth media for microorganisms, e.g. microalgae. In this research, buffalo manure was used as alternative media for Arthospira platensis cultivation. Buffalo manure was taken from Sitoluama village, Laguboti, Toba Regency of North Sumatra Province. Research steps included media and culture preparation, cultivation, sampling, sample analysis and verification of constructed models and validation. Buffalo manure concentration in media is varied from 1 g.L-1 to 8 g.L-1 which is analogous to nitrogen content of 0.002 mg.L-1 to 0.018 mg.L-1. Growth data was used for growth kinetic modelling, which was most satisfactory for Monod model (µmax = 0.5915 day-1, Ks = 0.421 g.L-1).

Kinetics of Organic Biodegradation and Biogas Production in the Pilot-Scale Moving Bed Biofilm Reactor (MBBR) for Piggery Wastewater Treatment

In this research, the kinetics of COD biodegradation and biogas production in a moving bed biofilm reactor (MBBR) at pilot scale (10 m3) for piggery wastewater treatment were investigated. Polyethylene (PE) was used as a carrying material, with organic loading rates (OLRs) of 10, 15, and 18 kgCOD/m3 day in accordance to hydraulic retention times (HRTs) of 0.56, 0.37, and 0.3 day. The results showed that a high COD removal efficiency was obtained in the range of 68–78% with the influent COD of 5.2–5.8 g/L at all 3 HRTs. About COD degradation kinetics, in comparison to the first- and second-order kinetics and the Monod model, Stover–Kincannon model showed the best fit with R2 0.98 and a saturation value constant (KB) and a maximum utilization rate (Umax) of 52.40 g/L day and 82.65 g/L day, respectively. The first- and second-order kinetics with all 3 HRTs and Monod model with the HRT of 0.56 day also obtained high R2 values. Therefore, these kinetics and models can be further considered to be used for predicting the kinetic characteristics of the MBBR system in piggery wastewater treatment process. The result of a 6-month operation of the MBBR was that biogas production was mostly in the operating period of days 17 to 80, around 0.2 to 0.3 and 0.15–0.20 L/gCODconverted, respectively, and then reduction at an OLR of 18 kgCOD/m3. After the start-up stage, day 35 biogas cumulative volume fluctuated from 20 to 30 m3/day and reached approximately 3500 m3 for 178 days during the whole digestive process. Methane is accounted for about 65–70% of biogas with concentration around 400 mg/L.

Modelling of Molasses Fermentation for Bioethanol Production: A Comparative Investigation of Monod and Andrews Models Accuracy Assessment

Modelling has recently become a key tool to promote the bioethanol industry and to optimise the fermentation process to be easily integrated into the industrial sector. In this context, this study aims at investigating the applicability of two mathematical models (Andrews and Monod) for molasses fermentation. The kinetics parameters for Monod and Andrews were estimated from experimental data using Matlab and OriginLab software. The models were simulated and compared with another set of experimental data that was not used for parameters’ estimation. The results of modelling showed that μmax = 0.179 1/h and Ks = 11.37 g.L−1 for the Monod model, whereas μmax = 0.508 1/h, Ks = 47.53 g.L−1 and Ki = 181.01 g.L−1 for the Andrews model, which are too close to the values reported in previous studies. The validation of both models showed that the Monod model is more suitable for batch fermentation modelling at a low concentration, where the highest R squared was observed at S0 = 75 g.L−1 with an R squared equal to 0.99956, 0.99954, and 0.99859 for the biomass, substrate, and product concentrations, respectively. In contrast, the Andrews model was more accurate at a high initial substrate concentration and the model data showed a good agreement compared to the experimental data of batch fermentation at S0 = 225 g.L−1, which was reflected in a high R squared with values 0.99795, 0.99903, and 0.99962 for the biomass, substrate, and product concentrations respectively.