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Optimization of Molecular Distillation for Recovery of Tocopherol from Rapeseed Oil Deodorizer Distillate Using Response Surface and Artificial Neural Network Models

Paper ID Volume ID Publish Year Pages File Format Full-Text
19556 43074 2007 8 PDF Available
Title
Optimization of Molecular Distillation for Recovery of Tocopherol from Rapeseed Oil Deodorizer Distillate Using Response Surface and Artificial Neural Network Models
Abstract

Back-propagation artificial neural network and response surface methodology were used to build a predictive model of the combined effects of molecular distillation's independent variables including evaporating temperature, feed flow rate and wiper rolling speed for the recovery of tocopherol from rapeseed oil deodorizer distillate. The optimum operating conditions obtained from the quadratic form of the response surface methodology and artificial neural network models were evaporating temperature 473 K, wiper rolling speed 150 r min−1, feed flow rate 90 ml h−1 when feed temperature 353 K and vacuum 0.02 torr. The results demonstrated a high predictive accuracy of artificial neural network compared to response surface methodology. The interior relationships between parameters are shown well by response surface methodology.

Keywords
artificial neural network; response surface methodology; molecular distillation; tocopherol; deodorizer distillate
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Optimization of Molecular Distillation for Recovery of Tocopherol from Rapeseed Oil Deodorizer Distillate Using Response Surface and Artificial Neural Network Models
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Publisher
Database: Elsevier - ScienceDirect
Journal: Food and Bioproducts Processing - Volume 85, Issue 2, June 2007, Pages 85–92
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us