scholarly journals Microbial Interactions between Amylolytic and Non-Amylolytic Lactic Acid Bacteria Strains Isolated during the Fermentation of Pozol

2021 ◽  
Author(s):  
Sandra Bolaños-Nuñez ◽  
Jorge A. Santiago-Urbina ◽  
Jean-Pierre Guyot ◽  
Gloria Díaz-Ruiz ◽  
Carmen Wacher
Keyword(s):  
Growth Rate ◽  
Lactic Acid ◽  
Specific Growth Rate ◽  
Kinetic Parameters ◽  
Acid Production ◽  
Specific Growth ◽  
Lactic Acid Production ◽  
Amylolytic Activity ◽  
Specific Rate ◽  
Acid Yield

Pozol is a Mexican beverage prepared from fermented nixtamalized maize dough. To contribute to understanding its complex microbial ecology, the effect of inoculating on MRS-starch pure and mixed cultures of amylolytic Sii-25124 and non-amylolytic W. confusa 17, isolated from pozol, were studied on their interactions and fermentation parameters. These were compared with L. plantarum A6, an amylolytic strain isolated from cassava. Microbial growth, kinetic parameters, amylolytic activity, lactic acid production, and hydrolysis products from starch fermentation were measured. The population dynamics were followed by qPCR. L. plantarum A6 showed higher enzymatic activity, lactic acid, biomass production, and kinetic parameters than pozol LAB in pure cultures. Mixed culture of each pozol LAB with L. plantarum A6 showed a significant decrease in amylolytic activity, lactic acid yield, specific growth rate, and specific rate of amylase production. The interaction between Sii-25124 and W. confusa 17 increased the global maximum specific growth rate (µ), the lactic acid yield from starch (Ylac/s), lactic acid yield from biomass (Ylac/x), and specific rate of lactic acid production (qlac) by 15, 30, 30, and 40%, respectively compared with the pure culture of Sii-25124. Interactions between the two strains are essential for this fermentation.

scholarly journals Mathematical Modeling of Lactobacillus paracasei CBA L74 Growth during Rice Flour Fermentation Performed with and without pH Control

2021 ◽  
Vol 11 (7) ◽  
pp. 2921
Author(s):  
Rosa Colucci Cante ◽  
Marianna Gallo ◽  
Federica Nigro ◽  
Francesca Passannanti ◽  
Andrea Budelli ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Growth Rate ◽  
Lactic Acid ◽  
Specific Growth Rate ◽  
Biomass Production ◽  
Acid Production ◽  
Specific Growth ◽  
Lactic Acid Production ◽  
Rice Flour ◽  
Ph Control

The mathematical modeling of fermentation processes allows for the formulation of predictions about the kinetics of biomass growth and metabolite production as well as setting or verifying the best operative conditions in view of the economical convenience of the process. For this purpose, we performed a kinetic study of a rice flour fermentation process using Lactobacillus paracasei CBA L74 with and without pH control; the pH value was set to 5.8 under pH control. Monod, Logistic, and Contois models were proposed to describe the bacterial growth rate in both conditions. The best mathematical model, which was able to describe the experimental data obtained without pH control, was the Contois model, as the specific growth rate was influenced by both the glucose reduction (from 14.31 g/L to 10.22 g/L) and the biomass production (2 log growth) that occurred during fermentation. Conversely, when pH control was implemented, both Monod and Contois models satisfactorily described the specific growth rate trend. The estimated kinetic parameters confirmed that biomass production (2 log growth) and glucose consumption (from 14.31 g/L to 6.06 g/L) did not affect the microorganism’s growth capacity when the fermenting medium was maintained at an optimal pH. The lactic acid production rate described by the Luedeking–Piret model did not appear to be linked to growth in the absence of pH control while, on the other hand, this model was unsuitable for describing the experimental lactic acid concentration when pH control was applied. The kinetic modeling of lactic acid production and the percentage of added glucose in the protocol with controlled pH will be optimized in the future.

scholarly journals Relationship between pH and Medium Dissolved Solids in Terms of Growth and Metabolism of Lactobacilli and Saccharomyces cerevisiae during Ethanol Production

2005 ◽  
Vol 71 (5) ◽  
pp. 2239-2243 ◽  
Author(s):  
Neelakantam V. Narendranath ◽  
Ronan Power
Keyword(s):  
Growth Rate ◽  
Lactic Acid ◽  
Specific Growth Rate ◽  
Ethanol Production ◽  
Growth Rates ◽  
Specific Growth ◽  
Lactic Acid Production ◽  
Good Practice ◽  
Medium Ph ◽  
Dissolved Solids

ABSTRACT The specific growth rates of four species of lactobacilli decreased linearly with increases in the concentration of dissolved solids (sugars) in liquid growth medium. This was most likely due to the osmotic stress exerted by the sugars on the bacteria. The reduction in growth rates corresponded to decreased lactic acid production. Medium pH was another factor studied. As the medium pH decreased from 5.5 to 4.0, there was a reduction in the specific growth rate of lactobacilli and a corresponding decrease in the lactic acid produced. In contrast, medium pH did not have any significant effect on the specific growth rate of yeast at any particular concentration of dissolved solids in the medium. However, medium pH had a significant (P < 0.001) effect on ethanol production. A medium pH of 5.5 resulted in maximal ethanol production in all media with different concentrations of dissolved solids. When the data were analyzed as a 4 (pH levels) by 4 (concentrations of dissolved solids) factorial experiment, there was no synergistic effect (P > 0.2923) observed between pH of the medium and concentration of dissolved solids of the medium in reducing bacterial growth and metabolism. The data suggest that reduction of initial medium pH to 4.0 for the control of lactobacilli during ethanol production is not a good practice as there is a reduction (P < 0.001) in the ethanol produced by the yeast at pH 4.0. Setting the mash (medium) with ≥30% (wt/vol) dissolved solids at a pH of 5.0 to 5.5 will minimize the effects of bacterial contamination and maximize ethanol production by yeast.

scholarly journals Use of wheat straw and chicken feather hydrolysates as a complete medium for lactic acid production

2018 ◽  
Vol 36 (No. 2) ◽  
pp. 146-153 ◽  
Author(s):  
Gharwalová Lucia ◽  
Paulová Leona ◽  
Patáková Petra ◽  
Branská Barbora ◽  
Melzoch Karel
Keyword(s):  
Lactic Acid ◽  
Wheat Straw ◽  
Acid Production ◽  
Low Cost ◽  
Lactic Acid Production ◽  
Nitrogen Sources ◽  
Batch Process ◽  
Complete Medium ◽  
Biotechnological Production ◽  
Acid Yield

Biotechnological production of lactic acid has experienced a boom that is hindered only by the lack of low-cost, abundant material that might be used as a substrate for lactic acid bacteria. Such material should contain not only carbon but also complex nitrogen sources, amino acids and vitamins necessary for the balanced growth of the bacteria. Here, for the first time, a combination of hydrolysates of wheat straw and chicken feathers was used as a complete waste cultivation medium for lactic acid production. It was shown to be a promising substrate for lactic acid production, reducing the medium price by 73% compared with MRS broth, providing more than 98% lactic acid yield and high productivity (2.28 ± 0.68 g/l/h) in a fed-batch process using Lactobacillus reuterii LHR14.

The effect of specific growth rate on protein synthesis and secretion in the filamentous fungus Trichoderma reesei

Microbiology ◽  
2005 ◽  
Vol 151 (1) ◽  
pp. 135-143 ◽  
Author(s):  
Tiina M. Pakula ◽  
Katri Salonen ◽  
Jaana Uusitalo ◽  
Merja Penttilä
Keyword(s):  
Growth Rate ◽  
Protein Synthesis ◽  
Specific Growth Rate ◽  
Trichoderma Reesei ◽  
Growth Rates ◽  
Protein Production ◽  
Specific Growth ◽  
Synthesis Rate ◽  
Specific Rate ◽  
Specific Growth Rates

Trichoderma reesei was cultivated in chemostat cultures on lactose-containing medium. The cultures were characterized for growth, consumption of the carbon source and protein production. Secreted proteins were produced most efficiently at low specific growth rates, 0·022–0·033 h−1, the highest specific rate of total protein production being 4·1 mg g−1 h−1 at the specific growth rate 0·031 h−1. At low specific growth rates, up to 29 % of the proteins produced were extracellular, in comparison to only 6–8 % at high specific growth rates, 0·045–0·066 h−1. To analyse protein synthesis and secretion in more detail, metabolic labelling of proteins was applied to analyse production of the major secreted protein, cellobiohydrolase I (CBHI, Cel7A). Intracellular and extracellular labelled CBHI was quantified and analysed for pI isoforms in two-dimensional gels, and the synthesis and secretion rates of the molecule were determined. Both the specific rates of CBHI synthesis and secretion were highest at low specific growth rates, the optimum being at 0·031 h−1. However, at low specific growth rates the secretion rate/synthesis rate ratio was significantly lower than that at high specific growth rates, indicating that at low growth rates the capacity of cells to transport the protein becomes limiting. In accordance with the high level of protein production and limitation in the secretory capacity, the transcript levels of the unfolded protein response (UPR) target genes pdi1 and bip1 as well as the gene encoding the UPR transcription factor hac1 were induced.

Estimating Bacterial Growth Parameters by Means of Detection Times

1999 ◽  
Vol 65 (2) ◽  
pp. 732-736 ◽  
Author(s):  
József Baranyi ◽  
Carmen Pin
Keyword(s):  
Growth Rate ◽  
Specific Growth Rate ◽  
Bacterial Growth ◽  
Specific Growth ◽  
Growth Parameters ◽  
Physiological State ◽  
Cell Number ◽  
Maximum Specific Growth Rate ◽  
Specific Rate ◽  
The Individual

ABSTRACT We developed a new numerical method to estimate bacterial growth parameters by means of detection times generated by different initial counts. The observed detection times are subjected to a transformation involving the (unknown) maximum specific growth rate and the (known) ratios between the different inoculum sizes and the constant detectable level of counts. We present an analysis of variance (ANOVA) protocol based on a theoretical result according to which, if the specific rate used for the transformation is correct, the transformed values are scattered around the same mean irrespective of the original inoculum sizes. That mean, termed the physiological state of the inoculum,α̂, and the maximum specific growth rate, μ, can be estimated by minimizing the variance ratio of the ANOVA procedure. The lag time of the population can be calculated as λ = −ln α̂/μ; i.e. the lag is inversely proportional to the maximum specific growth rate and depends on the initial physiological state of the population. The more accurately the cell number at the detection level is known, the better the estimate for the variance of the lag times of the individual cells.

scholarly journals Selection of the StrainLactobacillus acidophilusATCC 43121 and Its Application to Brewers’ Spent Grain Conversion into Lactic Acid

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Rossana Liguori ◽  
Carlos Ricardo Soccol ◽  
Luciana Porto de Souza Vandenberghe ◽  
Adenise Lorenci Woiciechowski ◽  
Elena Ionata ◽  
...  
Keyword(s):  
Lactic Acid ◽  
Yeast Extract ◽  
Acid Production ◽  
Lactic Acid Production ◽  
Synthetic Medium ◽  
Glucose Consumption ◽  
Acid Yield ◽  
Aqueous Ammonia Soaking ◽  
Spent Grain ◽  
Selection Of

SixLactobacillusstrains were analyzed to select a bacterium for conversion of brewers’ spent grain (BSG) into lactic acid. Among the investigated strains,L. acidophilusATCC 43121 showed the highest yield of lactic acid production (16.1 g/L after 48 hours) when grown in a synthetic medium. It was then analyzed for its ability to grow on the hydrolysates obtained from BSG after acid-alkaline (AAT) or aqueous ammonia soaking (AAS) pretreatment. The lactic acid production byL. acidophilusATCC 43121 through fermentation of the hydrolysate from AAS treated BSG was 96% higher than that from the AAT treated one, although similar yields of lactic acid per consumed glucose were achieved due to a higher (46%) glucose consumption byL. acidophilusATCC 43121 in the AAS BSG hydrolysate. It is worth noting that adding yeast extract to the BSG hydrolysates increased both the yield of lactic acid per substrate consumed and the volumetric productivity. The best results were obtained by fermentation of AAS BSG hydrolysate supplemented by yeast extract, in which the strain produced 22.16 g/L of lactic acid (yield of 0.61 g/g), 27% higher than the value (17.49 g/L) obtained in the absence of a nitrogen source.

The Growth of Brown Trout (Salmo Trutta Linn.)

1946 ◽  
Vol 22 (3-4) ◽  
pp. 130-144
Author(s):  
MARGARET E. BROWN
Keyword(s):  
Growth Rate ◽  
Specific Growth Rate ◽  
Rapid Growth ◽  
Salmo Trutta ◽  
Specific Growth ◽  
Condition Factor ◽  
Specific Rate ◽  
Annual Growth Rate ◽  
Size Hierarchy ◽  
Rate Of Growth

1. Two-year-old trout were grown in environments where the following factors were controlled: temperature, amount and intensity of illumination, rate of flow, composition and aeration of the water, quality and quantity of food and amount of living space. 2. The specific growth rate of an individual depended on its size relative to that of the others in the group. It is suggested that subgroups of four or five individuals existed within the size hierarchy and were reorganized at intervals of about 3 months. 3. There was an optimum degree of crowding for rapid growth, and overcrowding led to lower appetite and efficiency of utilization of food, while under-crowded trout ate and grew erratically. 4. In spite of constant environmental conditions, all the fish had an annual growth-rate cycle, with an autumn check, a spring maximum, rapid summer growth and another autumn check, which coincided with maturation of the gonads when they became 3 years old. 5. Individual specific growth rates fluctuated over periods of 4-6 weeks, and rapid growth in length alternated with rapid growth in weight. The specific rate of growth in length was directly proportional to the condition factor. The amount of food eaten, the efficiency of utilization of food and the specific rate of growth in weight varied with the condition factor and were maximal for a factor of about 1·10. 6. The growth-rate fluctuations were exaggerated and the efficiency was greater when the food supply was restricted. At the maintenance level the change in weight was directly proportional to the amount of food eaten. The maintenance requirement decreased, relatively, with increase in body weight. 7. The mean specific growth rate was higher with less than 12 hr. per diem of the standard illumination.

The Growth of Brown trout (Salmo Trutta Linn.)

1946 ◽  
Vol 22 (3-4) ◽  
pp. 118-129
Author(s):  
MARGARET E. BROWN
Keyword(s):  
Growth Rate ◽  
Specific Growth Rate ◽  
Growth Rates ◽  
Salmo Trutta ◽  
Specific Growth ◽  
Specific Rate ◽  
Size Hierarchy ◽  
Living Space ◽  
Brown Trout Salmo Trutta ◽  
Specific Growth Rates

1. Groups of trout fry of the same parentage were grown in environments where the following factors were controlled: temperature, amount and intensity of illumination, rate of water flow, aeration and chemical composition of the water, amount of living space and quality of food supply. They were allowed to eat as much as they would, and individual weights were recorded during the first 8 months after the beginning of feeding. 2. There was soon an increase in the range of individual weight in each group of fry, and thereafter the larger fry grew faster than smaller ones. When the larger fry were removed, the smaller ones grew at an increased specific rate, and when larger fry were added, the smaller ones grew more slowly. It is suggested that a ‘size hierarchy’ was established within each group, and an individual's specific growth rate depended on its position in the order of decreasing weight. 3. There was an optimum degree of crowding for maximum productivity. Compared with the fry in this group, the specific growth rates of individuals in larger, more crowded groups depended on the number of fish of larger size, while in smaller, less crowded groups, individuals grew at rates depending on the proportion of fish which were larger and smaller. 4. Alevin weight had little effect on the specific growth rates of fry. 5. There were differences between the growth histories of fry derived from alevins of the same weight and descended from the same father but different mothers (all of the same stock, age and size). 6. The specific growth rates decreased as the fry grew older, but there was no correlation between body weight and specific growth rate, except for the size hierarchy effect within each group. This effect had a greater influence on the size of individual fry than had either alevin weight or heredity.

Estimation of Kinetic Parameters by a Hybrid Algorithm of Nonlinear Model Based Differential Evolution for Lactic Acid Production

2016 ◽  
Vol 11 (2) ◽  
pp. 141-148
Author(s):  
J. Satya Eswari
Keyword(s):  
Lactic Acid ◽  
Kinetic Model ◽  
Differential Evolution ◽  
Kinetic Parameters ◽  
Acid Production ◽  
Hybrid Algorithm ◽  
Lactic Acid Production ◽  
Model Parameters ◽  
Time Interval ◽  
Experimental Conditions

Abstract The kinetic model parameters are estimated for lactic acid production using mixed microbial consortium in batch fermentation by using different optimization methods. For every time interval concentrations are measured and formulated the parameter appraisal delinquent. Cellular progression kinetic model of exponential or logistic was verified for the effect of various substrates and lactic acid production of mixed culture. This paper proposed hybrid algorithm such as nonlinear models in conjunction with differential evolution and kinetic model. The nonlinear regression with graphical method and Nelder-Mead simplex linked kinetic model was compared with the differential evolution for parameter estimation. The optimized kinetic parameters are found to be within the range of experimental conditions for which the model is developed offers a significant enhancement of lactic acid production. From the computational results, the proposed kinetic model linked differential evolution strategy is thus found effective in exploring the input search space and optimizing the kinetic parameters.

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