Non-Structured Kinetic Model of Aspergillus niger Growth and Substrate Uptake in a Batch Submerged Culture

Ardestani, Fatemeh; Kasebkar, Roxana

doi:10.9734/bbj/2014/11472

Cited by 7 publications

(4 citation statements)

References 13 publications

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Section: Resultssupporting

confidence: 91%

“…Michel et al (2021) applied the Gompertz model to analyze the biomass growth of A. oryzae, they found a comparable lag phase of 2.58 h. After hyphae formation, the fungi entered the exponential phase, with an estimated specific growth rate of 1.77 d −1 . This value is comparable with values in literature, 0.4-1.8 d −1 (Ardestani & Kasebkar, 2014;Cui et al, 1998;Gamarra et al, 2010;Tlecuitl-Beristain et al, 2008;Xu et al, 2008), for fungal growth. By considering the determination coefficient (R 2 ), root mean squared error (RMSE), sum of squared errors (SSE), and reasonability of estimated kinetic parameters from cube root model and the modified Gompertz model, the modified Gompertz model was found to be more suitable to describe the growth behavior of A. awamori under the studied culture conditions.…”

Section: Kinetics Of Fungal Pellet Growthsupporting

confidence: 91%

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Potential of utilizing almond hull extract for filamentous fungi production by submerged cultivation

Cao,

Barzee,

El Mashad

et al. 2024

Food Bioengineering

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Almond hulls can be used as an inexpensive source of nutrients for producing fungi that can be used as nontraditional foods such as alternative protein, probiotics, and food ingredients. Nutrients were extracted from almond hulls using hot water and their utility in cultivating filamentous fungus Aspergillus awamori (A. awamori) in submerged cultivation was investigated using batch fermentation in flasks with passive aeration. The almond hulls extract supplied all the nutrients required for A. awamori growth. The uptake preference of various sugars was investigated and the growth kinetic parameters of A. awamori were determined. Utilization of sugars by A. awamori grown in almond hull extract proceeded sequentially with preference for glucose followed by sucrose, fructose, and then xylose. Compared to potato dextrose broth medium, the fungal biomass produced using almond hull extract as growth medium had higher protein (19.59%) and lower fat (1.50%) contents. The modified Gompertz model described the kinetics of A. awamori well with a lag phase of 0.18 days and a specific growth rate of 1.77 d−1.

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Section: Resultssupporting

confidence: 91%

Section: Kinetics Of Fungal Pellet Growthsupporting

confidence: 91%

Potential of utilizing almond hull extract for filamentous fungi production by submerged cultivation

Cao,

Barzee,

El Mashad

et al. 2024

Food Bioengineering

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show abstract

“…Approximate results were obtained by Ardestani and Shafiei [ 37 ], who proved that the Verhulst kinetic model with R 2 equal to 0.97 was the most appropriate to describe the biomass growth rate of S. cerevisiae. In contrast, Ardestani and Kasebkar [ 38 ], applied an unstructured kinetic model of Aspergillus niger growth and substrate uptake in a submerged batch culture and have confirmed that Monod and Verhulst kinetic models were not in an acceptable range to fit a growth of Aspergillus niger.…”

Section: Resultsmentioning

confidence: 99%

Optimization of Baker’s Yeast Production on Date Extract Using Response Surface Methodology (RSM)

Ali

Outili

Kaki

et al. 2017

Foods

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This work aims to study the production of the biomass of S. cerevisiae on an optimized medium using date extract as the only carbon source in order to obtain a good yield of the biomass. The biomass production was carried out according to the central composite experimental design (CCD) as a response surface methodology using Minitab 16 software. Indeed, under optimal biomass production conditions, temperature (32.9 °C), pH (5.35) and the total reducing sugar extracted from dates (70.93 g/L), S. cerevisiae produced 40 g/L of their biomass in an Erlenmeyer after only 16 h of fermentation. The kinetic performance of the S. cerevisiae strain was investigated with three unstructured models i.e., Monod, Verhulst, and Tessier. The conformity of the experimental data fitted showed a good consistency with Monod and Tessier models with R2 = 0.945 and 0.979, respectively. An excellent adequacy was noted in the case of the Verhulst model (R2 = 0.981). The values of kinetic parameters (Ks, Xm, μm, p and q) calculated by the Excel software, confirmed that Monod and Verhulst were suitable models, in contrast, the Tessier model was inappropriately fitted with the experimental data due to the illogical value of Ks (−9.434). The profiles prediction of the biomass production with the Verhulst model, and that of the substrate consumption using Leudeking Piret model over time, demonstrated a good agreement between the simulation models and the experimental data.

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“…On literature we find a diverse type of those systems, such as nonlinear PID, sliding mode control, parametrized nonlinear MPC, and game theory nonlinear MPC to name some examples. In general, although those control schemes have shown an affordable performance, the implementation is the main drawback, specially if the system is subjected to constraints [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Control with On-line Kinetic Parameter Identification Strategy on Anaerobic Digestion Reactors

Ocaña¹,

Barbancho²,

Rubia³

et al. 2022

Preprint

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This work presents a nonlinear model predictive control scheme that challenges overcoming the obstacles holding back over decades to develop affordable autonomous control and monitoring systems applied in the large-scale industry. Among the numerous proposals in the literature, most do not consider the significant fluctuation of kinetic parameters in the reduced mathematical model ADM2, widely used for control and monitoring purposes. The prevalent cause, on a basis, is the lack of information caused by some dynamics and parameters that cannot be measured in real-time by reliable sensors. In addition, to make matters worse, those systems inherently act with nonlinear nature and have a high sensitiveness to uncontrollable inputs and perturbations. Therefore, to prevent these drawbacks, this work proposes a new methodology that reconstructs the lack of information from the non-measurable dynamics, concentration of bacterias, and the kinetic parameters related to reaction rates. Simulations results demonstrate the effectiveness of the methodology compared with traditional industrial control schemes.

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Non-Structured Kinetic Model of Aspergillus niger Growth and Substrate Uptake in a Batch Submerged Culture

Cited by 7 publications

References 13 publications

Potential of utilizing almond hull extract for filamentous fungi production by submerged cultivation

Potential of utilizing almond hull extract for filamentous fungi production by submerged cultivation

Optimization of Baker’s Yeast Production on Date Extract Using Response Surface Methodology (RSM)

Model Predictive Control with On-line Kinetic Parameter Identification Strategy on Anaerobic Digestion Reactors

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