Optimizing biodiesel production from underutilized Garcinia indica oil through empirical, Coati Optimization and Salp Swarm Algorithm

The novel Garcinia Indica feedstock grown on non-arable land with 37 % oil content ensures sustainable biofuel production resources. A two-stage transesterification process (catalyst: H2SO4 followed by NaOH) is applied to reduce the free fatty acid content of 12.58 % in crude oil for biodiesel conve...

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Published inBiomass & bioenergy Vol. 200; p. 108020
Main Authors Ajith, B.S., Prakash, S.B., Manjunath Patel, G.C., Thomas, Likewin, Hasan, Mudassir, Yadav, Krishna Kumar, Samuel, Olusegun D.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.09.2025
Subjects
Online AccessGet full text
ISSN0961-9534
DOI10.1016/j.biombioe.2025.108020

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Abstract The novel Garcinia Indica feedstock grown on non-arable land with 37 % oil content ensures sustainable biofuel production resources. A two-stage transesterification process (catalyst: H2SO4 followed by NaOH) is applied to reduce the free fatty acid content of 12.58 % in crude oil for biodiesel conversion. Central composite design matrices were used to conduct transesterification experiments and collect biodiesel yield data. Methanol followed by catalyst concentration showed dominant individual and interaction effects on biodiesel yield. The model-determined coefficient of determination (R2 = 0.9772) ensured an average absolute prediction deviation of 1.53 % for 27 experimental runs. Two bio-inspired metaheuristic algorithms, the coati optimization algorithm (COA) and the salp swarm algorithm (SSA), were used to determine transesterification conditions to maximize biodiesel yield to 98.8 %. However, COA was found to be computationally more efficient than SSA. The optimal transesterification conditions were tested experimentally with NaOH and calcium oxide nano-catalyst (grain size: 65 nm) and resulted in the yield of 96.4 % and 97.5 %, respectively. The reusability of the CaO nano-catalyst demonstrated its effective catalytic activity, with a biodiesel yield of 89.2 ± 0.4 % for 5 cycles. FTIR and GC-MS tests confirmed the biodiesel quality and oxidation stability. The GI-biodiesel tested against thermophysical properties was found to be within the biodiesel standard limits. [Display omitted] •GI feedstock grown on non-arable forest land with high oil content (37%) and socio-economic value is used for biodiesel production.•The derived equation predicts 27 cases with deviations from −3.13 % to +3.72 %, averaging an absolute error of 1.53 %.•COA and SSA determined transesterification conditions maximize the biodiesel yield to 98.8 %.•Optimal transesterification with NaOH and 65 nm CaO nano-catalyst gave 96.4 % and 97.5 % biodiesel conversion, respectively.•CaO nano-catalysts retained activity over 5 cycles, yielding 89.2 ± 0.4 % biodiesel, demonstrating effective reusability.
AbstractList The novel Garcinia Indica feedstock grown on non-arable land with 37 % oil content ensures sustainable biofuel production resources. A two-stage transesterification process (catalyst: H2SO4 followed by NaOH) is applied to reduce the free fatty acid content of 12.58 % in crude oil for biodiesel conversion. Central composite design matrices were used to conduct transesterification experiments and collect biodiesel yield data. Methanol followed by catalyst concentration showed dominant individual and interaction effects on biodiesel yield. The model-determined coefficient of determination (R2 = 0.9772) ensured an average absolute prediction deviation of 1.53 % for 27 experimental runs. Two bio-inspired metaheuristic algorithms, the coati optimization algorithm (COA) and the salp swarm algorithm (SSA), were used to determine transesterification conditions to maximize biodiesel yield to 98.8 %. However, COA was found to be computationally more efficient than SSA. The optimal transesterification conditions were tested experimentally with NaOH and calcium oxide nano-catalyst (grain size: 65 nm) and resulted in the yield of 96.4 % and 97.5 %, respectively. The reusability of the CaO nano-catalyst demonstrated its effective catalytic activity, with a biodiesel yield of 89.2 ± 0.4 % for 5 cycles. FTIR and GC-MS tests confirmed the biodiesel quality and oxidation stability. The GI-biodiesel tested against thermophysical properties was found to be within the biodiesel standard limits. [Display omitted] •GI feedstock grown on non-arable forest land with high oil content (37%) and socio-economic value is used for biodiesel production.•The derived equation predicts 27 cases with deviations from −3.13 % to +3.72 %, averaging an absolute error of 1.53 %.•COA and SSA determined transesterification conditions maximize the biodiesel yield to 98.8 %.•Optimal transesterification with NaOH and 65 nm CaO nano-catalyst gave 96.4 % and 97.5 % biodiesel conversion, respectively.•CaO nano-catalysts retained activity over 5 cycles, yielding 89.2 ± 0.4 % biodiesel, demonstrating effective reusability.
ArticleNumber 108020
Author Samuel, Olusegun D.
Prakash, S.B.
Yadav, Krishna Kumar
Thomas, Likewin
Hasan, Mudassir
Ajith, B.S.
Manjunath Patel, G.C.
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  givenname: S.B.
  surname: Prakash
  fullname: Prakash, S.B.
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  surname: Manjunath Patel
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  organization: Department of Mechanical Engineering, PES Institute of Technology and Management, Visvesvaraya Technological University, Shivamogga, 577204, Karnataka, India
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  givenname: Likewin
  surname: Thomas
  fullname: Thomas, Likewin
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  givenname: Mudassir
  surname: Hasan
  fullname: Hasan, Mudassir
  email: m-hasan@kku.edu.sa
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  givenname: Krishna Kumar
  orcidid: 0000-0002-4228-2726
  surname: Yadav
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  givenname: Olusegun D.
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Keywords Garcinia indica
SSA
Transesterification process
COA
CaO nano-catalyst
Composite design matrix
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Snippet The novel Garcinia Indica feedstock grown on non-arable land with 37 % oil content ensures sustainable biofuel production resources. A two-stage...
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StartPage 108020
SubjectTerms CaO nano-catalyst
COA
Composite design matrix
Garcinia indica
SSA
Transesterification process
Title Optimizing biodiesel production from underutilized Garcinia indica oil through empirical, Coati Optimization and Salp Swarm Algorithm
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