Microbial Growth Kinetics Research Articles

Exploring the potential of microcalorimetry to study soil microbial metabolic diversity

Microcalorimetry and BIOLOG are common tools in the study of soil microbial metabolism. When used combined, they may reveal further details about soil microbial metabolic diversity than individually. Through this study, we demonstrated the advantages of such a combinatorial methodology by comparing soil samples from two locations in China, each with (OM samples) and without (control) organic fertilization. We used BIOLOG and microcalorimetry to study soil microbes’ ability to metabolize different C substrates. Microcalorimetric measurements helped us further reveal the differences in the microbial growth kinetics under different BIOLOG-identified C substrates. Results showed that soils differed in the preferred C substrates, as denoted by the thermodynamic parameters. Some C substrates stimulated the active microbial biomass, while some stimulated microbial growth rate. Most interestingly, certain C substrates (e.g., l-arginine for Shandong soil and glycogen for Henan soil) showed stimulating effects on both OM and control soils, which could be attributed to the pH value and P availability in soil. Hence, we believe microcalorimetry could be potentially used to explore the soil microbial metabolic diversity by combining BIOLOG measurement, especially in determining how microbes assimilate different nutrient sources.

Statistical evaluation and discrimination of competing kinetic models and hypothesis for the mathematical description of poly-3(hydroxybutyrate) synthesis by Cupriavidus necator DSM 545

A robust statistical approach for discrimination of competing microbial growth kinetics models was applied. The phenomenological modeling approach based on unstructured and non-segregated kinetic models was formulated to describe PHB synthesis by Cupriavidus necator that experimentally was carried out in batch system for the given temperatures of 30; 32.5; 35 and 37.5°C. Further, PHB synthesis was assumed to be non-growth-associated under nitrogen limitation conditions. The stoichiometry of the microbial growth and PHB synthesis was successfully used in kinetics studies combining the knowledge with the deterministic models in ordinary differential equation system. The parameters of the models identification procedure was based on the Genetic Algorithms which were coded in Maple®15 software. Analysis of the normalized least square function, as well as the correlation coefficient, has shown that all competing kinetic models fitted well the experimental data in all studied temperatures. A sequence of statistical tests was used to evaluate the quality of the chosen competing kinetic models and their ability to fit to the experimental data, and more particularly to ensure the reliability of the best model predictions. Hence, as a result was ensured that the mathematical modeling based on Andrews (1968) model was the one that best described the experimental data under the given operational conditions and more particularly obtained at 32.5°C. The evaluated values of parameters indicated that the specific growth rate (SGR) of active biomass most likely was limited since the nutrient nitrogen concentration was SN ≤3.35gL−1, and the specific production rate (SPR) of PHB was maximum when the organic substrate concentration reached SC =10gL−1. Moreover, the experimental tests have shown that the highest biomass (0.361gcellL−1h−1) and PHB (0.50gPHBL−1h−1) productivity were attained at 32.5°C. Andrews (1968) model provide interesting findings for the given oxygen mass-transfer conditions from the gas to the liquid phase and the microbial respiration during the cultivation at 32.5°C. The cell respiration parameters estimated by GA were 0.89gcell gO2−1 in the growth phase and 0.31gcell gO2−1 in the PHB synthesis phase. These values agreed with those ones found from the stoichiometry of microbial growth and PHB synthesis demonstrated in this study. Thus, application of statistical test analysis can be considered as a powerful tool for discrimination of kinetic hypothesis about the dynamics of the cell growth and product synthesis.

Storage of hybrid rough rice – Consideration of microbial growth kinetics and prediction models

The objective of this study was to determine kinetics of mold growth on popularly grown hybrid long-grain rough rice during storage at conditions that simulate delayed drying and prolonged storage. Three long-grain hybrid rice cultivars, XL753 (2014) and CL XL745 (2014, 2015) and XL760 (2015) conditioned to four different moisture contents (MCs) (12.5%, 16.0%, 19.0%, and 21.0% wet basis) were stored in rough rice form at temperatures ranging from 10 °C to 40 °C for a period of 16 weeks. The study was repeated using rice from two consecutive crop seasons, 2014 and 2015. For all cultivars, a direct relationship between mold counts and rice MC was observed – whereas more complex trends were observed for the effect of temperature and the duration of storage on mold growth. Kinetic models including Baranyi, Weibull, Gompertz, Richard and Buchanan were successfully modified and fitted using non-linear regression and used to predict the mold counts (log10 CFU/g) for varying conditions (correlations = 0.65–0.76). The study concluded that long-grain hybrid rough rice could be stored at low MC levels (≤17%) and moderate temperatures (≤27 °C) for up to 6 weeks without any change in the mold growth profile. However, storing rice at high MC (>17%) for more than 8 weeks, especially at higher (>27 °C) temperatures should be avoided due to the potential for high mold activity leading to loss of the grain quality.

Production of β-galactosidase in a Batch Bioreactor Using Whey through Microbial Route – Characterization of Isolate and Reactor Model

Whey was used as a source of isolation of bacterial strains, symbolized as, IB1, IB2 and IB3, capable of synthesizing β-galactosidase. The microbe labeled as IB1 was tested to be most tolerant against pH and temperature shocks, as well as, heavy metals. Subsequently, IB1 was identified as Bacillus safensis (JUCHE 1) by genetic information. In a later exercise, it was used for β-galactosidase production using whey through fermentative route. The initial concentration of substrate, i.e., lactose in microbial growth medium was varied ranging from of 5-50 g/L. It was found that the classical Monod kinetics and substrate inhibited Monod kinetics are able to describe the microbial growth kinetics at low (5-20 g/L), and high (>20 g/L) concentration ranges of lactose in growth medium respectively. Kinetics of β-galactosidase production followed the Monod incorporated modified Luedeking-Piret model and the Monod incorporated Luedeking-Piret model with substrate inhibition in the low, and high ranges of lactose concentration in growth medium respectively.

The effect of different matrices on the growth kinetics and heat resistance of Listeria monocytogenes and Lactobacillus plantarum

Microbial growth and inactivation kinetics in food can be predicted when the effects of food properties and environmental conditions on microbial responses are available. However the effects of these intrinsic and extrinsic variables on microbial kinetics are often obtained using laboratory media, and deviations between predictions and true behaviour might occur if the specific effect of a food product is not known or considered in the prediction. Therefore, knowing the food specific effect on microbial kinetics might not only result in a more realistic growth and inactivation prediction, but also extend the knowledge on factors influencing growth and heat resistance. In this study, growth predictions of Listeria monocytogenes and Lactobacillus plantarum were validated in laboratory media and in milk and ham as model food products. A good agreement between the predicted and observed growth kinetics in laboratory media highlighted the possibility to predict μmax based on cardinal growth parameters obtained from OD-based measurement in laboratory media. Only in two conditions (BHI pH5.5 at 7°C; and BHI pH5.5, undissociated lactic acid concentration of 1mM at 7°C) a possible interaction between growth limiting factors was observed, yet existing interaction models were not better in predicting growth. Growth validation in the two model foods showed that the food specific effects were strain dependent, which might further complicate accurate prediction. For both species the effect of strain variability on thermal inactivation was similar to the food specific effects, and the latter was mainly determined by the effect of ham as heating medium. The combination of both effects explained (almost) all variability found in literature, however, with some bias.

NOVEL MATHEMATICAL MODELS FOR PREDICTION OF MICROBIAL GROWTH KINETICS AND CONTAMINANT DEGRADATION IN BIOREMEDIATION PROCESS

Bioremediation is defined as a process, which involves decomposition of organic pollutant compounds available in soil and water resources into safe and eco-friendly materials, like water and CO2, by the microorganisms. In the present article, mathematical modeling of the bioremediation process was conducted comprehensively, and new models proposed for the microbial growth kinetics and substrate consumption (contaminant degradation). Accordingly, six kinetic models were suggested for the biomass growth and six models for the substrate consumption. Moreover, two models were considered for specific growth rate constant of the microorganisms. Then, model predictions were compared to and validated by the available experimental data in the literature. According to the obtained results, the microbial growth kinetic model, entitled as “MVKH2”, the substrate (contaminant) consumption model, entitled as “MVKH2s”, and the Aiba specific growth rate constant model had the best performance and the least error value in predicting the bioremediation process. Results achieved from this study are a promising beginning for practical and experimental works.

A microbial growth kinetics model driven by hybrid stochastic colored noises in the water environment

This study develops three microbial growth models in the sewage biodegradation process driven by white noise, colored noise and hybrid noises, respectively. The proposed models are more universal in reflecting the impact of uncertainty on microbial systems, compared with the previous efforts. An improved Box–Mueller algorithm is used to solve the model. The modeling results show that the different noise types have remarkable effects on microbial growth kinetics. To better understanding the insights of various noises affecting the system, the growth process of microbial in the sewage biodegradation process is discussed under different conditions with varied noise properties (i.e. intensity and correlation time). The results indicate that the effect of noise on the microbial growth kinetics decreases with the reduction of the noise intensity and the correlation time. Therefore, a known noise can be relieved by changing the noise intensity or the correlation time. As the model driven by noises is capable of addressing the system’s uncertainty, it is useful in supporting stochastic simulation, risk analysis, and process design of a sewage biological treatment system. Future works may focus on the development of more effective statistical-inference methods for the noises based on observed data.

Antimicrobial Activity and Possible Mechanism of Action of Citral against Cronobacter sakazakii.

Citral is a flavor component that is commonly used in food, beverage and fragrance industries. Cronobacter sakazakii is a food-borne pathogen associated with severe illness and high mortality in neonates and infants. The objective of the present study was to evaluate antimicrobial effect of citral against C. sakazakii strains. The minimum inhibitory concentration (MIC) of citral against C. sakazakii was determined via agar dilution method, then Gompertz models were used to quantitate the effect of citral on microbial growth kinetics. Changes in intracellular pH (pHin), membrane potential, intracellular ATP concentration, and membrane integrity were measured to elucidate the possible antimicrobial mechanism. Cell morphology changes were also examined using a field emission scanning electron microscope. The MICs of citral against C. sakazakii strains ranged from 0.27 to 0.54 mg/mL, and citral resulted in a longer lag phase and lower growth rate of C. sakazakii compared to the control. Citral affected the cell membrane of C. sakazakii, as evidenced by decreased intracellular ATP concentration, reduced pHin, and cell membrane hyperpolarization. Scanning electron microscopy analysis further confirmed that C. sakazakii cell membranes were damaged by citral. These findings suggest that citral exhibits antimicrobial effect against C. sakazakii strains and could be potentially used to control C. sakazakii in foods. However, how it works in food systems where many other components may interfere with its efficacy should be tested in future research before its real application.

Quantifying Variability in Growth and Thermal Inactivation Kinetics of Lactobacillus plantarum.

The presence and growth of spoilage organisms in food might affect the shelf life. In this study, the effects of experimental, reproduction, and strain variabilities were quantified with respect to growth and thermal inactivation using 20 Lactobacillus plantarum strains. Also, the effect of growth history on thermal resistance was quantified. The strain variability in μmax was similar (P > 0.05) to reproduction variability as a function of pH, aw, and temperature, while being around half of the reproduction variability (P < 0.05) as a function of undissociated lactic acid concentration [HLa]. The cardinal growth parameters were estimated for the L. plantarum strains, and the pHmin was between 3.2 and 3.5, the aw,min was between 0.936 and 0.953, the [HLamax], at pH 4.5, was between 29 and 38 mM, and the Tmin was between 3.4 and 8.3°C. The average D values ranged from 0.80 min to 19 min at 55°C, 0.22 to 3.9 min at 58°C, 3.1 to 45 s at 60°C, and 1.8 to 19 s at 63°C. In contrast to growth, the strain variability in thermal resistance was on average six times higher than the reproduction variability and more than ten times higher than the experimental variability. The strain variability was also 1.8 times higher (P < 0.05) than the effect of growth history. The combined effects of strain variability and growth history on D value explained all of the variability as found in the literature, although with bias. Based on an illustrative milk-processing chain, strain variability caused ∼2-log10 differences in growth between the most and least robust strains and >10-log10 differences after thermal treatment. Accurate control and realistic prediction of shelf life is complicated by the natural diversity among microbial strains, and limited information on microbiological variability is available for spoilage microorganisms. Therefore, the objectives of the present study were to quantify strain variability, reproduction (biological) variability, and experimental variability with respect to the growth and thermal inactivation kinetics of Lactobacillus plantarum and to quantify the variability in thermal resistance attributed to growth history. The quantitative knowledge obtained on experimental, reproduction, and strain variabilities can be used to improve experimental designs and to adequately select strains for challenge growth and inactivation tests. Moreover, the integration of strain variability in prediction of microbial growth and inactivation kinetics will result in more realistic predictions of L. plantarum dynamics along the food production chain.

Microbial growth and degradation kinetics of perchlorate by Proteus sp. LMNCRE in a batch reactor system

The present work is a laboratory-scale study of perchlorate (ClO−4) degradation using Proteus sp. LMNCRE in a batch reactor. The average hourly value of perchlorate degradation rate in this system was 1.95 mg/L at optimum pH 7.5 and 0.25% NaCl salinity. The microbial growth and degradation kinetics have been studied to a variety of ClO−4 levels (0 to 100 mg/L) under anoxic conditions. The biomass optical-density value of strain gradually increased from 0-0.37 during the operating period of 30h. The perchlorate level in which the bacterium could withstand for effective removal was found to be 75 ± 2.0 mg/L with zero order reaction coefficient (k) of 2.08 mg/L/h. The observed anoxic degradation rate of strain was 87.0 ± 0.6 % within 12 h of incubation period at 25 mg/L of initial perchlorate level. From the experimental findings, the uptake of perchlorate by the bacterium is suggested to obey a zero-order substrate-utilising kinetic model, allowed the growth rates constants to be determined.

Substrate quality affects microbial‐ and enzyme activities in rooted soil

AbstractThe rhizosphere reflects a sphere of high substrate input by means of rhizodeposits. Active microorganisms and extracellular enzymes are known to be responsible for substrate utilization in soil, especially in rooted soil. We tested for microbial‐ and enzyme activities in arable soil, in order to investigate the effects of continuous input of easily available organics (e.g., root‐exudates) to the microbial community. In a field experiment with maize, rooted and root‐free soil were analyzed and rhizosphere processes were linked to microbial activity indicators such as specific microbial growth rates and kinetics of six hydrolytic extracellular enzymes: β‐glucosidase, β‐cellobiohydrolase, β‐xylosidase, acid phosphatase, leucine‐ and tyrosine‐aminopeptidase.Higher potential activities of leucine‐aminopeptidase (2‐fold) for rooted vs. root‐free soil suggested increased costs of enzyme production, which retarded the specific microbial growth rates. Total microbial biomass determined by the substrate‐induced respiration technique and dsDNA extraction method was 23% and 42% higher in the rooted surface‐layer (0–10 cm) compared to the root‐free soil, respectively. For the rooted soil, potential enzyme activities of β‐glucosidase were reduced by 23% and acid phosphatase by 25%, and increased by 300% for β‐cellobiohydrolase at 10–20 cm depth compared to the surface‐layer. The actively growing microbial biomass increased by the 17‐fold in rooted soil in the 10–20 cm layer compared to the upper 10 cm. Despite the specific microbial growth rates showing no changes in the presence of roots, these rates decreased by 42% at 10–20 cm depth compared to the surface‐layer. This suggests the dominance in abundances of highly active but slower growing microbes with depth, reflecting also their slower turnover. Shifts in microbial growth strategy, upregulation of enzyme production and increased microbial respiration indicate strong root effects in maize planted soil.

Simultaneous treatment of phenol and cyanide containing aqueous solution by adsorption, biotreatment and simultaneous adsorption and biotreatment (SAB) process

This study presents a comparative study of adsorption and biotreatment process alone with simultaneous adsorption and biotreatment (SAB) process. Adsorption studies were conducted with coconut husk activated carbon (CHAC), as adsorbent. SAB and biodegradation studies were carried out with immobilized and suspended cultures of Serratia odorifera MTCC 5700, respectively. Phenol and cyanide solution were used for all studies with initial concentration of 300mg/L and 30mg/L, respectively, initial pH of 8 and temperature of 30°C. The optimum adsorbent dose was found 30g/L for adsorption process and SAB process. In SAB process, the removal efficiency was found more than adsorption and biodegradation process and achieved removal efficiency of 89.88% for phenol and 93.06% for cyanide. Three mono components and six multicomponent equilibrium isotherm models were considered. Non-linear regression technique was used for estimation of model parameters. Among tested multicomponent isotherm models Extended Freundlich model found to fit well with the experimental data. The kinetics of microbial growth and biotreatment of phenol and cyanide were also investigated. Haldane’s and Monod model have been used to interpret experimental data on phenol and cyanide biotreatment. It was established that simultaneous adsorption and biotreatment process is more effective than biotreatment and adsorption process alone.

Quantitative Polymerase Chain Reaction for Microbial Growth Kinetics of Mixed Culture System.

Microbial growth kinetics is often used to optimize environmental processes owing to its relation to the breakdown of substrate (contaminants). However, the quantification of bacterial populations in the environment is difficult owing to the challenges of monitoring a specific bacterial population within a diverse microbial community. Conventional methods are unable to detect and quantify the growth of individual strains separately in the mixed culture reactor. This work describes a novel quantitative PCR (qPCR)-based genomic approach to quantify each species in mixed culture and interpret its growth kinetics in the mixed system. Batch experiments were performed for both single and dual cultures of Pseudomonas putida and Escherichia coli K12 to obtain Monod kinetic parameters (μmax and Ks). The growth curves and kinetics obtained by conventional methods (i.e., dry weight measurement and absorbance reading) were compared with that obtained by qPCR assay. We anticipate that the adoption of this qPCR-based genomic assay can contribute significantly to traditional microbial kinetics, modeling practice, and the operation of bioreactors, where handling of complex mixed cultures is required.

Optimization of continuous microbiological synthesis processes with nonlinear microbial growth kinetics

A methodology for solving the optimization problem for a widespread microbiological synthesis process is considered, and a numerical solution of the problem is presented. The methodology developed is based on substrate and product inhibition kinetics. The optimization problem is solved using the target component productivity Qp as the optimality criterion. Three variants of optimization problem formulation are considered: optimization of substrate concentration in the feed stream at a fixed dilution rate; dilution rate optimization at a fixed substrate concentration in the feed, Sf; optimization with respect to two variables—Sf and Qp. A specific feature of the solution is that it is necessary to check whether the optimal values obtained are usable in the practical implementation of the synthesis process. Numerical results of optimization are presented for the three variants of problem formulation.

Comparison of the experimentally obtained growth model of Listeria monocytogenes on cucumber and zucchini with existing model generated by ComBase Predictor

The quality and microbiological safety of produced and stored food is a challenge for its producers and official control. Numerous examples have shown how important it is for them to have access to precise data about the growth time and rate of microorganisms in stored products, especially in the case of those which are the etiology of digestive system diseases such as Listeria monocytogenes. It is one of the most virulent foodborne pathogens, showing a mortality rate of approximately 20–30 %, which is the highest among food microbiota. In order to determine the microbial growth kinetics in time on food matrices, so-called growth modeling is used. It allows to determine the growth of microorganisms in time and depending on the temperature, pH, water activity (a w), or content of acids. In this paper, we verified the growth model of Listeria monocytogenes on cucumber and zucchini with an existing model in the ComBase Predictor.

Analytical solution of Luedeking-Piret equation for a batch fermentation obeying Monod growth kinetics.

Not so many fermentation mathematical models allow analytical solutions of batch process dynamics. The most widely used is the combination of the logistic microbial growth kinetics with Luedeking-Piret bioproduct synthesis relation. However, the logistic equation is principally based on formalistic similarities and only fits a limited range of fermentation types. In this article, we have developed an analytical solution for the combination of Monod growth kinetics with Luedeking-Piret relation, which can be identified by linear regression and used to simulate batch fermentation evolution. Two classical examples are used to show the quality of fit and the simplicity of the method proposed. A solution for the combination of Haldane substrate-limited growth model combined with Luedeking-Piret relation is also provided. These models could prove useful for the analysis of fermentation data in industry as well as academia.

Kinetics and methane gas yields of selected C1 to C5 organic acids in anaerobic digestion

Volatile fatty acids (VFAs) and other short-chain organic acids such as lactic and pyruvic acids are intermediates in anaerobic organic degradation. In this study, anaerobic degradation of seven organic acids in salt form was investigated, including formate (C1), acetate (C2), propionate (C3), pyruvate (C3), lactate (C3), butyrate (C4), and valerate (C5). Microbial growth kinetics on these organic acids were determined individually at 37 °C through batch anaerobic digestion tests by varying substrate concentrations from 250 to 4000 mg COD/L. The cumulative methane generation volume was determined real-time by respirometry coupled with gas chromatographic analysis while methane yield and related kinetics were calculated. The methane gas yields (fe, mg CH4 COD/mg substrate COD) from anaerobic degradation of formate, acetate, propionate, pyruvate, lactate, butyrate, and valerate were 0.44 ± 0.27, 0.58 ± 0.05, 0.53 ± 0.18, 0.24 ± 0.05, 0.17 ± 0.05, 0.43 ± 0.15, 0.49 ± 0.11, respectively. Anaerobic degradation of formate showed self-substrate inhibition at the concentrations above 3250 mg COD/L. Acetate, propionate, pyruvate, butyrate, lactate, and valerate did not inhibit methane production at the highest concentrations tested (i.e., 4000 mg COD/L). Microbes growing on acetate had the highest overall specific growth rate (0.30 d−1) in methane production. For comparison, the specific microbial growth rates on formate, propionate, pyruvate, butyrate, lactate, and valerate for methane production were 0.10, 0.06, 0.08, 0.07, 0.05, 0.15 d−1, respectively.

Quantifying strain variability in modeling growth of Listeria monocytogenes

Prediction of microbial growth kinetics can differ from the actual behavior of the target microorganisms. In the present study, the impact of strain variability on maximum specific growth rate (μmax) (h−1) was quantified using twenty Listeria monocytogenes strains. The μmax was determined as function of four different variables, namely pH, water activity (aw)/NaCl concentration [NaCl], undissociated lactic acid concentration ([HA]), and temperature (T). The strain variability was compared to biological and experimental variabilities to determine their importance. The experiment was done in duplicate at the same time to quantify experimental variability and reproduced at least twice on different experimental days to quantify biological (reproduction) variability. For all variables, experimental variability was clearly lower than biological variability and strain variability; and remarkably, biological variability was similar to strain variability. Strain variability in cardinal growth parameters, namely pHmin, [NaCl]max, [HA]max, and Tmin was further investigated by fitting secondary growth models to the μmax data, including a modified secondary pH model. The fitting results showed that L. monocytogenes had an average pHmin of 4.5 (5–95% prediction interval (PI) 4.4–4.7), [NaCl]max of 2.0mM (PI 1.8–2.1), [HA]max of 5.1mM (PI 4.2–5.9), and Tmin of −2.2°C (PI (−3.3)–(−1.1)). The strain variability in cardinal growth parameters was benchmarked to available literature data, showing that the effect of strain variability explained around 1/3 or less of the variability found in literature. The cardinal growth parameters and their prediction intervals were used as input to illustrate the effect of strain variability on the growth of L. monocytogenes in food products with various characteristics, resulting in 2–4 logCFU/ml(g) difference in growth prediction between the most and least robust strains, depending on the type of food product. This underlined the importance to obtain quantitative knowledge on variability factors to realistically predict the microbial growth kinetics.

Effect of physico-chemical and operating conditions on the growth and activity of Acidithiobacillus ferrooxidans in a simulated heap bioleaching environment

Recent understanding of microbial retention within heap bioleaching systems has highlighted the importance of quantifying microbial growth and activity in both the bulk flowing solution and in the ore-associated phases. Typically, industrial heap bioleaching operations report variations in process conditions such as inoculum preparation and concentration and elevated copper concentrations in the recycled irrigation solution. In this paper, a mini-column reactor system containing pre-constructed and agglomerated, low-grade ore samples representing grab samples from a larger heap, were used to investigate the effect of a selection of physico-chemical and operating conditions on microbial growth, colonisation and substrate utilisation kinetics, considering both the planktonic and sessile populations of Acidithiobacillus ferrooxidans. The factors studied included inoculum size, inoculum cultivation conditions, availability of ferrous iron in the bulk flowing solution and copper concentration in the bulk flowing solution. The microbial population in the interstitial phase, i.e. associated with, but not bound to, the ore, remained the most abundant within the heap under all physico-chemical conditions considered. A comparison of the tests with different inoculum sizes found that a smaller inoculum size resulted in an increased delay in microbial growth and ferrous iron oxidation, but similar apparent maximum specific growth rates and iron oxidation rates. In contrast to the microbial culture grown on pyrite, a delay in microbial activity was observed for the culture grown on ferrous iron. However, greater microbial cell densities were reached, in the interstitial and attached phases compared with the pyrite-grown culture. The introduction of 6gL−1 cupric ions into the feed solution containing 0.2gL−1 ferric iron resulted in decreased microbial growth rate in the interstitial phase but not in the attached phase. Where the pyrite culture was pre-exposed to cupric ion, the microbial growth rate in the interstitial and attached phases was significantly enhanced. Nevertheless, the presence of cupric ion in the irrigation solution resulted in a decrease in microbial ferrous iron oxidation rate, irrespective of pre-culture conditioning. This study emphasises the important role played by the stagnant interstitial phase during the colonisation of a low-grade heap, particularly under adverse conditions for microbial growth and activity. It also highlights the role of inoculum culture conditions on the potential trade-off between increased heap colonisation and increased lag periods in microbial activity during heap start-up.

Theoretic similitude of the aerobic biological growth kinetics for the stabilization of organic matter in wastewaters treatment

Para la estabilización de la materia orgánica en el tratamiento de las aguas residuales no solo es significativo establecer la cinética de crecimiento microbiano sino la interrelación de la remoción de nutrientes como el nitrógeno, dada la similitud de coeficientes, tasa de crecimiento específica y los ajustes por temperatura del agua, que lo representa tanto para la remoción de la materia orgánica como para los procesos de nitrificación y denitrificación presentes en el tratamiento biológico de las aguas residuales. Por ello, esta similitud teórica de las cinéticas de crecimiento microbiano y de los procesos de remoción de nitrógeno constituye consideraciones concisas para el proceso de dimensionamiento de sistemas de tratamiento biológicos de tratamiento de aguas residuales, que ayudan a entender el proceso simultáneo de remover materia orgánica y nutrientes del agua residual cruda.