Improvement of L-asparaginase, an Anticancer Agent of Aspergillus arenarioides EAN603 in Submerged Fermentation Using a Radial Basis Function Neural Network with a Specific Genetic Algorithm (RBFNN-GA)

Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi and Efaq Ali Noman, Efaq Ali Noman and Muhanna Mohammed Al-shaibani, Muhanna Mohammed Al-shaibani and Adel Al-Gheethi, Adel Al-Gheethi and Radin Mohamed, Radin Maya Saphira and Reyad Almoheer, Reyad Almoheer and Mubarak Seif, Mubarak Seif and Kim Gaik Tay, Kim Gaik Tay and Mohamad Zin, Noraziah and Hesham Ali El Enshasy, Hesham Ali El Enshasy (2023) Improvement of L-asparaginase, an Anticancer Agent of Aspergillus arenarioides EAN603 in Submerged Fermentation Using a Radial Basis Function Neural Network with a Specific Genetic Algorithm (RBFNN-GA). Fermentation, 9 (200). pp. 1-15.

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Official URL: https://doi.org/10.3390/fermentation9030200

Abstract

The present study aimed to optimize the production of L-asparaginase from Aspergillus arenarioides EAN603 in submerged fermentation using a radial basis function neural network with a specific genetic algorithm (RBFNN-GA) and response surface methodology (RSM). Independent factors used included temperature (x1), pH (x2 ), incubation time (x3), and soybean concentration(x4). The coefficient of the predicted model using the Box–Behnken design (BBD) was R2 = 0.9079(p < 0.05); however, the lack of fit was significant indicating that independent factors are not fitted with the quadratic model. These results were confirmed during the optimization process, which revealed that the standard error (SE) of the predicted model was 11.65 while the coefficient was 0.9799, at which 145.35 and 124.54 IU mL−1 of the actual and predicted enzyme production was recorded at 34 ◦C, pH 8.5, after 7 days and with 10 g L−1 of organic soybean powder concentrations. Compared to the RBFNN-GA, the results revealed that the investigated factors had benefits and effects on L-asparaginase, with a correlation coefficient of R = 0.935484, and can classify 91.666667% of the test data samples with a better degree of precision; the actual values are higher than the predicted values for the L-asparaginase data.

Item Type:	Article
Uncontrolled Keywords:	L-asparaginase; Aspergillus arenarioides; submerged fermentation; organic soybean
Subjects:	T Technology > T Technology (General)
Divisions:	Faculty of Electrical and Electronic Engineering > FKEE
Depositing User:	Mr. Mohamad Zulkhibri Rahmad
Date Deposited:	01 Aug 2024 02:59
Last Modified:	01 Aug 2024 02:59
URI:	http://eprints.uthm.edu.my/id/eprint/11473

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