Comparison of response surface methodology and artificial neural network to enhance the release of reducing sugars from non-edible seed cake by autoclave assisted HCl hydrolysis

Vinayaka B. Shet, Anusha M. Palan, Shama U. Rao, C. Varun, Uday Aishwarya, Selvaraj Raja, Louella Concepta Goveas, C. Vaman Rao, P. Ujwal

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In the current investigation, statistical approaches were adopted to hydrolyse non-edible seed cake (NESC) of Pongamia and optimize the hydrolysis process by response surface methodology (RSM). Through the RSM approach, the optimized conditions were found to be 1.17%v/v of HCl concentration at 54.12 min for hydrolysis. Under optimized conditions, the release of reducing sugars was found to be 53.03 g/L. The RSM data were used to train the artificial neural network (ANN) and the predictive ability of both models was compared by calculating various statistical parameters. A three-layered ANN model consisting of 2:12:1 topology was developed; the response of the ANN model indicates that it is precise when compared with the RSM model. The fit of the models was expressed with the regression coefficient R2, which was found to be 0.975 and 0.888, respectively, for the ANN and RSM models. This further demonstrated that the performance of ANN was better than that of RSM.

Original languageEnglish
Article number127
Journal3 Biotech
Volume8
Issue number2
DOIs
Publication statusPublished - 01-02-2018

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autoclaves
Neural Networks (Computer)
response surface methodology
reducing sugars
artificial neural network
neural networks
Pongamia
hydrolysis
Seeds
sugar
Hydrolysis
seed
seeds
topology
train
comparison

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Environmental Science (miscellaneous)
  • Agricultural and Biological Sciences (miscellaneous)

Cite this

Shet, Vinayaka B. ; Palan, Anusha M. ; Rao, Shama U. ; Varun, C. ; Aishwarya, Uday ; Raja, Selvaraj ; Goveas, Louella Concepta ; Vaman Rao, C. ; Ujwal, P. / Comparison of response surface methodology and artificial neural network to enhance the release of reducing sugars from non-edible seed cake by autoclave assisted HCl hydrolysis. In: 3 Biotech. 2018 ; Vol. 8, No. 2.
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Comparison of response surface methodology and artificial neural network to enhance the release of reducing sugars from non-edible seed cake by autoclave assisted HCl hydrolysis. / Shet, Vinayaka B.; Palan, Anusha M.; Rao, Shama U.; Varun, C.; Aishwarya, Uday; Raja, Selvaraj; Goveas, Louella Concepta; Vaman Rao, C.; Ujwal, P.

In: 3 Biotech, Vol. 8, No. 2, 127, 01.02.2018.

Research output: Contribution to journalArticle

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AU - Varun, C.

AU - Aishwarya, Uday

AU - Raja, Selvaraj

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AU - Ujwal, P.

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