Modeling and optimization of the oyster mushroom growth using artificial neural network: Economic and environmental impacts

Tarahom Mesri Gundoshmian; Sina Ardabili; Mako Csaba; Amir Mosavi; Tarahom Mesri Gundoshmian; Sina Ardabili; Mako Csaba; Amir Mosavi

doi:10.3934/mbe.2022453

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 10: 9749-9768. doi: 10.3934/mbe.2022453

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Research article

Modeling and optimization of the oyster mushroom growth using artificial neural network: Economic and environmental impacts

1.
Department of Biosystem Engineering, University of Mohaghegh Ardabili, Ardabil 5619911367, Iran
2.
Department of Informatics, J. Selye University, Komarom 94505, Slovakia
3.
Institute of the Information Society, University of Public Service, Budapest 1083, Hungary
4.
John von Neumann Faculty of Informatics, Obuda University, Budapest 1034, Hungary
5.
Institute of Information Engineering, Automation and Mathematics, Slovak University of Technology in Bratislava, Bratislava 81107, Slovakia

Academic Editor: De Li Liu

Received: 22 March 2022 Revised: 24 May 2022 Accepted: 27 May 2022 Published: 06 July 2022

The main aim of the study is to investigate the growth of oyster mushrooms in two substrates, namely straw and wheat straw. In the following, the study moves towards modeling and optimization of the production yield by considering the energy consumption, water consumption, total income and environmental impacts as the dependent variables. Accordingly, life cycle assessment (LCA) platform was developed for achieving the environmental impacts of the studied scenarios. The next step developed an ANN-based model for the prediction of dependent variables. Finally, optimization was performed using response surface methodology (RSM) by fitting quadratic equations for generating the required factors. According to the results, the optimum condition for the production of OM from waste paper can be found in the paper portion range of 20% and the wheat straw range of 80% with a production yield of about 4.5 kg and a higher net income of 16.54 $ in the presence of the lower energy and water consumption by about 361.5 kWh and 29.53 kg, respectively. The optimum condition delivers lower environmental impacts on Human Health, Ecosystem Quality, Climate change, and Resources by about 5.64 DALY, 8.18 PDF*m2*yr, 89.77 g CO₂ eq and 1707.05 kJ, respectively. It can be concluded that, sustainable production of OM can be achieved in line with the policy used to produce alternative food source from waste management techniques.
- oyster mushroom,
- life cycle assessment,
- food production,
- artificial intelligence,
- machine learning,
- big data
Citation: Tarahom Mesri Gundoshmian, Sina Ardabili, Mako Csaba, Amir Mosavi. Modeling and optimization of the oyster mushroom growth using artificial neural network: Economic and environmental impacts[J]. Mathematical Biosciences and Engineering, 2022, 19(10): 9749-9768. doi: 10.3934/mbe.2022453

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Abstract

The main aim of the study is to investigate the growth of oyster mushrooms in two substrates, namely straw and wheat straw. In the following, the study moves towards modeling and optimization of the production yield by considering the energy consumption, water consumption, total income and environmental impacts as the dependent variables. Accordingly, life cycle assessment (LCA) platform was developed for achieving the environmental impacts of the studied scenarios. The next step developed an ANN-based model for the prediction of dependent variables. Finally, optimization was performed using response surface methodology (RSM) by fitting quadratic equations for generating the required factors. According to the results, the optimum condition for the production of OM from waste paper can be found in the paper portion range of 20% and the wheat straw range of 80% with a production yield of about 4.5 kg and a higher net income of 16.54 $ in the presence of the lower energy and water consumption by about 361.5 kWh and 29.53 kg, respectively. The optimum condition delivers lower environmental impacts on Human Health, Ecosystem Quality, Climate change, and Resources by about 5.64 DALY, 8.18 PDF*m2*yr, 89.77 g CO₂ eq and 1707.05 kJ, respectively. It can be concluded that, sustainable production of OM can be achieved in line with the policy used to produce alternative food source from waste management techniques.

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