Optimized Methodology for Alkaline and Enzyme-Assisted Extraction of Protein from Sacha Inchi (Plukenetia volubilis) Kernel Cake

Rosana Chirinos, Martin Aquino, ROMINA PAOLA PEDRESCHI PLASENCIA, David Campos

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

The residue after oil extraction from sacha inchi (SI) presents a high protein content of ∼59% that can be further exploited to extract proteins. In this study, the protein extraction parameters for defatted SI cake meal (DSICM) were optimized using alkaline and enzyme-assisted extractions. A central composed design (CCD) was used to optimize the protein yield for both methods. The obtained response surface models (RSM) produced a satisfactory fitting of the results for both extraction methods (R2 = 0.9609–0.9761). For the alkaline extraction method, the optimal SI protein extraction conditions corresponded to 54.2C, solvent/meal 42/1 (v/w) ratio, NaCl concentration of 1.65 M, pH 9.5 for 30 min and yielded 29.7% protein. For the enzyme-assisted method, optimal extraction conditions corresponded to an enzyme concentration of 5.6%, 40.4 min extraction, solvent/meal 50/1 (v/w) ratio, pH 9.0 and 50C and yielded 44.7% protein and hydrolysis degree of 7.8%. Practical Applications: The cake obtained after oil extraction from SI seed is an important source of protein. Thus, efforts should focus on the development of protein extraction processes from the cake to add value to this by-product. Up to date, studies are very limited. Results obtained in this study allowed the optimization of the protein extraction process from SI cake meal. The enzyme-assisted protein extraction resulted in a higher quantity of protein recovery (∼1.5 fold more) than the alkaline protein extraction. The optimized protein extraction process will allow the food industry to obtain isolates or protein concentrates from SI cake meal to be used as techno-functional, nutritional and/or functional agent.

Original languageEnglish
Article numbere12412
JournalJournal of Food Process Engineering
Volume40
Issue number2
DOIs
StatePublished - 1 Apr 2017

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