Optimization of Cellulase Production Using Agricultural Wastes by Artificial Neural Network and Genetic Algorithm

2011 ◽  
Vol 6 (1) ◽  
Author(s):  
Chun Chang ◽  
Guizhuan Xu ◽  
Junfang Yang ◽  
Duo Wang
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Solid State ◽  
Aspergillus Niger ◽  
Moisture Content ◽  
Trichoderma Viride ◽  
Cellulase Activity ◽  
Cellulase Production ◽  
Fermentation Time

The cellulase production by Trichoderma viride was optimized using artificial intelligence-based techniques under solid state fermentation. In this study, a back propagation network was designed with Levenberg-Marquardt training algorithm, and the tangent sigmoid and pure linear functions were used as the transfer functions in the hidden and output layers of the ANN, respectively. An artificial neural network coupling genetic algorithms was used to optimize the process parameters, which include the mass ratio of wheat straw to wheat bran, moisture content and fermentation time. The ultimate process parameters of optimization were mass ration of wheat straw to wheat bran 2.9, moisture content 69.6 percent, and fermentation time 123.3h. Further test experiment showed that the final cellulase activity can reach to 11.62 U/g, which was the highest value among all the experimental results. This result indicates that the genetic algorithm based on a neural network model is a better optimization method for cellulase production in solid state fermentation. To improve the cellulase production, a mixed culture system of Trichoderma viride and Aspergillus niger was also developed. The cellulase activity increased by 7.40 percent with the addition of Aspergillus niger at 72h.

scholarly journals PRODUCTION AND CHARACTERIZATION OF CELLULOLYTIC ENZYMES BY ASPERGILLUS NIGER AND RHIZOPUS SP. BY SOLID STATE FERMENTATION OF PRICKLY PEAR

2016 ◽  
Vol 29 (1) ◽  
pp. 222-233 ◽  
Author(s):  
TAMIRES CARVALHO DOS SANTOS ◽  
GEORGE ABREU FILHO ◽  
AILA RIANY DE BRITO ◽  
AURELIANO JOSÉ VIEIRA PIRES ◽  
RENATA CRISTINA FERREIRA BONOMO ◽  
...  
Keyword(s):  
Solid State ◽  
Aspergillus Niger ◽  
Water Activity ◽  
Solid State Fermentation ◽  
Cellulase Production ◽  
Cellulolytic Enzymes ◽  
Optimum Conditions ◽  
Thermostable Enzymes ◽  
Fermentation Time ◽  
Rhizopus Sp

ABSTRACT: Prickly palm cactus husk was used as a solid-state fermentation support substrate for the production of cellulolytic enzymes using Aspergillus niger and Rhizopus sp. A Box-Behnken design was used to evaluate the effects of water activity, fermentation time and temperature on endoglucanase and total cellulase production. Response Surface Methodology showed that optimum conditions for endoglucanase production were achieved at after 70.35 h of fermentation at 29.56°C and a water activity of 0.875 for Aspergillus niger and after 68.12 h at 30.41°C for Rhizopus sp. Optimum conditions for total cellulase production were achieved after 74.27 h of fermentation at 31.22°C for Aspergillus niger and after 72.48 h and 27.86°C for Rhizopus sp. Water activity had a significant effect on Aspergillus niger endoglucanase production only. In industrial applications, enzymatic characterization is important for optimizing variables such as temperature and pH. In this study we showed that endoglucanase and total cellulase had a high level of thermostability and pH stability in all the enzymatic extracts. Enzymatic deactivation kinetic experiments indicated that the enzymes remained active after the freezing of the crude extract. Based on the results, bioconversion of cactus is an excellent alternative for the production of thermostable enzymes.

scholarly journals Response surface methodology-artificial neural network based optimization and strain improvement of cellulase production by Streptomyces sp.

2020 ◽  
Vol 36 (4) ◽  
Author(s):  
Ega Soujanya Lakshmi ◽  
Manda Rama Narasinga Rao ◽  
Muddada Sudhamani
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Response Surface Methodology ◽  
Response Surface ◽  
Wild Strain ◽  
Cellulase Activity ◽  
Cellulase Production ◽  
Optimal Conditions ◽  
Zone Formation ◽  
Artificial Neural

ABSTRACT Thirty seven different colonies were isolated from decomposing logs of textile industries. From among these, a thermotolerant, grampositive, filamentous soil bacteria Streptomyces durhamensis vs15 was selected and screened for cellulase production. The strain showed clear zone formation on CMC agar plate after Gram’s iodine staining.  Streptomyces durhamensis vs15 was further confirmed for cellulase production by estimating the reducing sugars through dinitrosalicylic acid (DNS) method. The activity was enhanced by sequential mutagenesis using three mutagens of ultraviolet irradiation (UV), N methyl-N’-nitro-N-nitrosoguanidine (NTG) and Ethyl methane sulphonate (EMS). After mutagenesis, the cellulase activity of GC23 (mutant) was improved to 1.86 fold compared to the wild strain (vs15). Optimal conditions for the production of cellulase by the GC 23 strain were evaluated using Response Surface Methodology (RSM) and Artificial Neural Network (ANN). Effect of pH, temperature, duration of incubation, , and substrate concentration on cellulase production were evaluated. Optimal conditions for the production of cellulase enzyme using Carboxy Methyl Cellulase as a substrate are 55 oC of temperature, pH of 5.0 and incubation for 40 h. The cellulase activity of the mutant Streptomyces durhamensis GC23 was further optimised to 2 fold of the activity of the wild type by RSM and ANN.  

Artificial neural network hybridized with a genetic algorithm for optimization of lipase production from Penicillium roqueforti ATCC 10110 in solid-state fermentation

2021 ◽  
Vol 31 ◽  
pp. 101885
Author(s):  
Luiz Henrique Sales de Menezes ◽  
Lucas Lima Carneiro ◽  
Iasnaia Maria de Carvalho Tavares ◽  
Pedro Henrique Santos ◽  
Thiago Pereira das Chagas ◽  
...  
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Solid State ◽  
Solid State Fermentation ◽  
Lipase Production ◽  
Penicillium Roqueforti ◽  
Artificial Neural

scholarly journals Solid State Fermentation Parameters Effect on Cellulase Production from Empty Fruit Bunch

2018 ◽  
Vol 13 (3) ◽  
pp. 553
Author(s):  
Vita Wonoputri ◽  
Subiantoro Subiantoro ◽  
Made Tri Ari Penia Kresnowati ◽  
Ronny Purwadi
Keyword(s):  
Solid State ◽  
Trichoderma Reesei ◽  
Solid State Fermentation ◽  
Trichoderma Viride ◽  
Cellulase Activity ◽  
Cellulase Production ◽  
Contact Method ◽  
Empty Fruit Bunch ◽  
Liquid Ratio ◽  
Fermentation Parameters

In this study, agriculture waste palm empty fruit bunch (EFB) was used as carbon/cellulose source in solid state fermentation for cheaper cellulase production. Fermentation operation parameters, such as: solid to liquid ratio, temperature, and pH, were varied to study the effect of those parameters towards crude cellulase activity. Two different fungi organisms, Trichoderma viride and Trichoderma reesei were used as the producers. Extracellular cellulase enzyme was extracted using simple contact method using citrate buffer. Assessment of the extracted cellulase activity by filter paper assay showed that Trichoderma viride is the superior organism capable of producing higher cellulase amount compared to Trichoderma reesei at the same fermentation condition. The optimum cellulase activity of 0.79 FPU/g dry substrate was obtained when solid to liquid ratio used for the fermentation was 1:1, while the optimum fermentation temperature and pH were found to be 30 °C and 5.5, respectively. The result obtained in this research showed the potential of EFB utilization for enzyme production. Copyright © 2018 BCREC Group. All rights reservedReceived: 14th December 2017; Revised:29th July 2018; Accepted: 3rd August 2018How to Cite: Wonoputri, V., Subiantoro, S., Kresnowati, M.T.A.P., Purwadi, R. (2018). Solid State Fermentation Parameters Effect on Cellulase Production from Empty Fruit Bunch. Bulletin of Chemical Reaction Engineering & Catalysis, 13 (3): 553-559 (doi:10.9767/bcrec.13.3.1964.553-559)Permalink/DOI: https://doi.org/10.9767/bcrec.13.3.1964.553-559 

Research on Conditions of Producing Cellulose by Mixed Fermentation for Bioethanol

2011 ◽  
Vol 383-390 ◽  
pp. 3986-3991
Author(s):  
Xiang Ping Su ◽  
Da Chun Gong ◽  
Xiao Li ◽  
Guo Hua Chen
Keyword(s):  
Enzyme Activity ◽  
Solid State ◽  
Trichoderma Viride ◽  
Cellulase Production ◽  
Cultivation Condition ◽  
Mass Ratio ◽  
Single Factor ◽  
Mixed Fermentation ◽  
Fermentation Time ◽  
Orthogonal Experiments

The conditions for cellulase production were studied with the mixed germs of Aspergillus niger (A.niger) and Trichoderma viride (R.viride) using straw stalk powder as carbon recourse by solid-state fermentation (SSF). The conditions of the mixed strains SSF were optimized by single factor experiments and orthogonal experiments in four aspects: the inoculation ratio, the bran-straw mass ratio, fermentation time and the filled volume. The optimal SSF conditions of the mixed strains were as follows: inoculation ratio of R.viride to A.niger was 1, the bran-straw mass ratio was 0.3, the time of fermentation was four days and the filled volume is 100 mL /1000 mL. The enzyme activity of FPA, CMC and β-glucosidase are 5.29 IU/mL, 9.33 IU/mL and 49.91 IU/mL in the optimal cultivation condition, which were 2.28~2.47 times, 2.39~2.45 times, 1.38~2.09 times as high as single-germ fermentation, respectively. The enzyme activity of cellulose from the mixed fermentation was higher than that from the fermentation of single bacteria.

Modelling and analysis of compressive strength properties of parboiled paddy and milled rice

2014 ◽  
Vol 28 (1) ◽  
pp. 73-83 ◽  
Author(s):  
Abozar Nasirahmadi ◽  
Mohammad H. Abbaspour-Fard ◽  
Bagher Emadi ◽  
Nasser Behroozi Khazaei
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Artificial Neural Network ◽  
Compressive Strength ◽  
Moisture Content ◽  
Mean Squared Error ◽  
Strength Properties ◽  
Milled Rice ◽  
Artificial Neural ◽  
Hidden Layer

Abstract The present investigation deals with analyzing the compressive strength properties of two varieties (Tarom and Fajr) of parboiled paddy and milled rice including: ultimate stress, modulus of elasticity, rupture force and rupture energy. Combined artificial neural network and genetic algorithm were also applied to model these properties. The parboiled samples were prepared with three soaking temperatures (25, 50 and 75°C) and three steaming times (10, 15 and 20 min). The samples were then dried to final moisture contents of 8, 10 and 12% (w.b.). In general, Tarom variety had higher compressive strength properties for paddy and milled rice than Fajr variety. With increase in steaming time from 10 to 20 min, all mentioned properties increased significantly, whereas these properties were decreased with increasing moisture content from 8 to 12% (w.b.). Coupled artificial neural network and genetic algorithm model with one hidden layer, three inputs (soaking temperature, steaming time and moisture content), was developed to predict the compressive strength properties as model outputs. Results indicated that this model could predict these properties with high correlation and low mean squared error.

scholarly journals Optimisation of solid-state fermentation of Aspergillus niger JL-15 for xylanase production and xylooligosaccharides preparation

2011 ◽  
Vol 29 (No. 5) ◽  
pp. 557-567 ◽  
Author(s):  
X.-J. Dai ◽  
M.-Q. Liu ◽  
H.-X. Jin ◽  
M.-Y. Jing
Keyword(s):  
Solid State ◽  
Aspergillus Niger ◽  
Moisture Content ◽  
Solid State Fermentation ◽  
Xylanase Activity ◽  
Orange Peel ◽  
Basic Medium ◽  
Relative Molecular Mass ◽  
Xylanase Production ◽  
Fermentation Time

The production of xylanase (XylA) by Aspergillus niger JL-15 in solid-state fermentation (SSF) on orange peel was optimised by the response surface methodology (RSM). The results revealed that four factors had significant effects on the XylA production (P &lt; 0.05), that is the concentrations of the added glycerin and ammonium sulfate, the moisture content, and fermentation time. Exploying orange peel as the solid substrate, maximum xylanase activity (917.7&nbsp;U/g dry fermentation product) was obtained at 4.2% glycerin, 3.1% (NH<sub>4</sub>)<sub>2</sub>SO<sub>4</sub>, 61% moisture content, and 73.4-h fermentation, this activity being close to the predicted one and 3.2 times higher than that of the basic medium (218.5&nbsp;U/g). Optimum temperature and pH for XylA activity were 55&deg;C and pH 5.0, respectively. SDS-PAGE analysis showed that the relative molecular mass of XylA was about 30.0 kDa. XylA exhibited K<sub>m</sub> and V<sub>max </sub>values of 9.24 mg/ml and 54.05&nbsp;&mu;mol/min/ml, respectively. XylA liberated mainly xylotriose from birchwood xylan and wheat bran, respectively. XylA was an endo-acting xylanase with transglycosylation activity, with the ability to hydrolyse, xylobiose, xylotriose, xylotetraose, xylopentaose, and xylohexaose.

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