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Production of Vegetable Protein from Rapeseed Press-Cake Using Response Surface Methodology, Weighted Multivariate Index, and Desirability Function: A Way to Handle Correlated Multiple Responses

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Version 2 2015-03-09, 20:42
Version 1 2015-03-09, 20:42
journal contribution
posted on 2015-03-09, 20:42 authored by Manashi Das Purkayastha, Anasuya Barthakur, Charu Lata Mahanta

The majority of present day industrial processes/products are defined by several quality characteristics, for which the process variables need to be precisely modulated to meet the required specifications. Hence, the multi-response process optimization has become an increasingly important and demanding task. In practice, many of these quality characteristics under consideration show conflicts among themselves, which need to be simultaneously satisfied. This situation is aggravated when the quality characteristics show correlation. To remedy this shortfall, we present a novel multi-objective process optimization approach, based on weighted principal components (principal component scores weighted by their respective eigen values), response surface methodology and desirability function. The implementation of the suggested approach is presented on a study that discusses the optimization of light-colored and reduced phytate containing protein extraction process from rapeseed press-cake. The effectiveness of the said approach was confirmed by performing additional confirmatory experiments at the predicted optimal condition. Furthermore, this study suggests the feasibility of the exploitation of the waste oilseed cake for extraction of high quality vegetable protein, using viable process and simple computational procedure. This study also briefly highlights performance analyses in cross-flow batch extraction scheme using optimized condition.

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