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Production and optimization of soybean biodiesel production at fixed temperature 50 °C with RSM and ANN.

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Title: Production and optimization of soybean biodiesel production at fixed temperature 50 °C with RSM and ANN.
Authors: Kumar, Sunil1 (AUTHOR) sunil508@rediffmail.com, Fore, Vivudh1 (AUTHOR), Singh, Jasbir1 (AUTHOR), Nainwal, Ashish1 (AUTHOR), Malik, Gorav Kumar1 (AUTHOR), Kumar, Amrish1 (AUTHOR)
Source: Environmental Science & Pollution Research. Feb2026, Vol. 33 Issue 6, p2223-2233. 11p.
Subject Terms: *Biodiesel fuel manufacturing, *Transesterification, *Biodiesel fuels, *Response surfaces (Statistics), *Experimental design, *Soy oil, *Artificial neural networks
Abstract: The study examined the extraction of bio-oil from soybean and the optimization of the production of the transesterification process using response surface methodology (RSM) and artificial neural network (ANN). This research uniquely highlights the utilization of soybean oil, a sustainable feedstock, and combines RSM and ANN methodologies to enhance the precision of biodiesel optimization at fixed temperature. The RSM-optimized conditions for maximum production were determined to be a 1.82% catalyst concentration, 8:1 methanol-to-oil ratio, 50 °C temperature, and 34-min time, resulting in an 80.86% biodiesel yield. Prediction models were created using transesterified soybean oil and the Box-Behnken architecture, varying three parameters of the process like the rate of reaction, m-ratio, and catalyst concentration time at a fixed temperature of 50. The RSM model and ANN model have been developed by using Box-Behnken design and by a trainlm algorithm having 4 neurons in the hidden layer (3:4:1). Developed models of RSM and ANN have been checked for the performance of biodiesel. The highest value of R2 = 0.989 and the lowest value of RMSE = 0.633 have been obtained, which is better than RSM. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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Header DbId: enr
DbLabel: Energy & Power Source
An: 192089317
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PubTypeId: academicJournal
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Production and optimization of soybean biodiesel production at fixed temperature 50 °C with RSM and ANN.
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  Data: <searchLink fieldCode="AR" term="%22Kumar%2C+Sunil%22">Kumar, Sunil</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> sunil508@rediffmail.com</i><br /><searchLink fieldCode="AR" term="%22Fore%2C+Vivudh%22">Fore, Vivudh</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Singh%2C+Jasbir%22">Singh, Jasbir</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Nainwal%2C+Ashish%22">Nainwal, Ashish</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Malik%2C+Gorav+Kumar%22">Malik, Gorav Kumar</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Kumar%2C+Amrish%22">Kumar, Amrish</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Environmental+Science+%26+Pollution+Research%22">Environmental Science & Pollution Research</searchLink>. Feb2026, Vol. 33 Issue 6, p2223-2233. 11p.
– Name: Subject
  Label: Subject Terms
  Group: Su
  Data: *<searchLink fieldCode="DE" term="%22Biodiesel+fuel+manufacturing%22">Biodiesel fuel manufacturing</searchLink><br />*<searchLink fieldCode="DE" term="%22Transesterification%22">Transesterification</searchLink><br />*<searchLink fieldCode="DE" term="%22Biodiesel+fuels%22">Biodiesel fuels</searchLink><br />*<searchLink fieldCode="DE" term="%22Response+surfaces+%28Statistics%29%22">Response surfaces (Statistics)</searchLink><br />*<searchLink fieldCode="DE" term="%22Experimental+design%22">Experimental design</searchLink><br />*<searchLink fieldCode="DE" term="%22Soy+oil%22">Soy oil</searchLink><br />*<searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The study examined the extraction of bio-oil from soybean and the optimization of the production of the transesterification process using response surface methodology (RSM) and artificial neural network (ANN). This research uniquely highlights the utilization of soybean oil, a sustainable feedstock, and combines RSM and ANN methodologies to enhance the precision of biodiesel optimization at fixed temperature. The RSM-optimized conditions for maximum production were determined to be a 1.82% catalyst concentration, 8:1 methanol-to-oil ratio, 50 °C temperature, and 34-min time, resulting in an 80.86% biodiesel yield. Prediction models were created using transesterified soybean oil and the Box-Behnken architecture, varying three parameters of the process like the rate of reaction, m-ratio, and catalyst concentration time at a fixed temperature of 50. The RSM model and ANN model have been developed by using Box-Behnken design and by a trainlm algorithm having 4 neurons in the hidden layer (3:4:1). Developed models of RSM and ANN have been checked for the performance of biodiesel. The highest value of R2 = 0.989 and the lowest value of RMSE = 0.633 have been obtained, which is better than RSM. [ABSTRACT FROM AUTHOR]
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=enr&AN=192089317
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s11356-025-36564-4
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 2223
    Subjects:
      – SubjectFull: Biodiesel fuel manufacturing
        Type: general
      – SubjectFull: Transesterification
        Type: general
      – SubjectFull: Biodiesel fuels
        Type: general
      – SubjectFull: Response surfaces (Statistics)
        Type: general
      – SubjectFull: Experimental design
        Type: general
      – SubjectFull: Soy oil
        Type: general
      – SubjectFull: Artificial neural networks
        Type: general
    Titles:
      – TitleFull: Production and optimization of soybean biodiesel production at fixed temperature 50 °C with RSM and ANN.
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            NameFull: Kumar, Sunil
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            NameFull: Fore, Vivudh
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            NameFull: Singh, Jasbir
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            NameFull: Nainwal, Ashish
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            NameFull: Malik, Gorav Kumar
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            NameFull: Kumar, Amrish
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            – D: 15
              M: 02
              Text: Feb2026
              Type: published
              Y: 2026
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              Value: 33
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            – TitleFull: Environmental Science & Pollution Research
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