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Artificial Intelligence as a Combinatorial Optimization Strategy for Cellulase Production by Trichoderma stromaticum AM7 Using Peach-Palm Waste Under Solid-State Fermentation

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Abstract

The use of agro-industrial waste as substrate to produce enzymes has been widely studied in order to adjust the high productions of these biocatalysts with a reduction of the final cost in an ecologically correct process in the industry. This is the first work to use peach-palm (Bactris gasipaes Kunth.) waste for the production of carboxymethylcellulases (CMCase) by the Trichoderma stromaticum AM7 under solid-state fermentation (SSF) using the artificial neural network and genetic algorithm (ANN-GA) to optimize the cellulase production. ANN-AG was used to determine the optimal influence of nitrogen source concentration (2.46%), time (12 days), and temperature (26 °C) on the cellulase production with 98% of efficiency for algorithm prediction of endoglucanase activity. The predicted and experimental values of the CMCase activity in U/g of dry initial substrate (gds) were 122.9 and 120.0, respectively. After all optimization processes, the variation of these parameters allowed a final increase of 31.58-fold when compared to the initial fermentation. Moreover, the treatment of peach-palm waste with T. stromaticum AM7 endoglucanase had an effect on the degradation of the fibers analyzed by scanning electron microscopy and the saccharification of the waste by releasing reducing sugar (807.80 mg/g) for 8 h of incubation. These results are very promising to waste valorization and the biotechnological and industrial applications of cellulase of the T. stromaticum AM7 to food processes and biofuel production.

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Acknowledgments

The authors would like to thank the Agroceres/Inaceres company (Uruçuca city, Bahia, Brazil) for supplying the peach-palm waste and the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) for assistance.

Funding

This work was supported by the Fundação de Amparo à Pesquisa do Estado da Bahia - FAPESB (grant number: 4624/2014 - PAM0002/2014) and Conselho Nacional de Desenvolvimento Científico e Tecnológico - CNPq (grant number: 446462/2014-4 - MCTI/CNPq/Universal 14/2014).

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Authors and Affiliations

  1. Department of Biological Science, UESC - Universidade Estadual de Santa Cruz, Jorge Amado Highway, Km 16 Salobrinho, Ilhéus, Bahia, 45662-900, Brazil

    Camila Oliveira Bezerra, Lucas Ribeiro de Carvalho, Ana Paula Trovatti Uetanabaro & Andréa Miura da Costa

  2. Department of Exact and Technological Sciences, Universidade Estadual de Santa Cruz, Jorge Amado Highway, Km 16 Salobrinho, Ilhéus, Bahia, 45662-900, Brazil

    Lucas Lima Carneiro, Thiago Pereira das Chagas & Erik Galvão Paranhos da Silva

  3. Food Technology Center, IF-Baiano - Instituto Federal Baiano, João Nascimento Street, Uruçuca, Bahia, 45680-000, Brazil

    Elck Alemeida Carvalho

  4. Department of Biological Sciences, UNEB - Universidade do Estado da Bahia, Lomanto Jr, Highway Br. 407 Km 127, s/n - Barbosa Santos, Sr. do Bonfim, Bahia, 48970-000, Brazil

    Gervásio Paulo da Silva

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  1. Camila Oliveira Bezerra
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Correspondence to Andréa Miura da Costa.

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Authors’ Contributions

Camila Oliveira Bezerra: developed the concept and methodology, data acquisition. Lucas Lima Carneiro: formal analysis and Validation. Elck Alemeida Carvalho: analysed the data and wrote the original draft. Thiago Pereira das Chagas: formal analysis and software, reviewed and edited final manuscript. Lucas Ribeiro de Carvalho: investigation and writing the original draft. Ana Paula Trovatti Uetanabaro: funding acquisition, reviewing and editing the manuscript. Gervásio Paulo da Silva: reviewing and editing the manuscript. Erik Galvão Paranhos da Silva: formal analysis and reviewing and editing the manuscript. Andréa Miura da Costa: conceptualization, resources, funding acquisition, acquisition of material used in the study, project initiation, reviewing and editing the manuscript, and supervision.

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Bezerra, C.O., Carneiro, L.L., Carvalho, E.A. et al. Artificial Intelligence as a Combinatorial Optimization Strategy for Cellulase Production by Trichoderma stromaticum AM7 Using Peach-Palm Waste Under Solid-State Fermentation. Bioenerg. Res. 14, 1161–1170 (2021). https://doi.org/10.1007/s12155-020-10234-4

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