OPTIMIZED METHODOLOGY FOR ALKALINE AND ENZYME-ASSISTED EXTRACTION OF PROTEIN FROM SACHA INCHI(PLUKENETIA VOLUBILIS) KERNEL CAKEROSANA CHIRINOS1, MARTIN AQUINO1, ROMINA PEDRESCHI2 and DAVID CAMPOS1,3

1Instituto de Biotecnolog�ıa, Universidad Nacional Agraria La Molina-UNALM, Lima, Peru2School of Agronomy, Pontificia Universidad Cat�olica de Valpara�ıso, Quillota, Chile

3Corresponding author.

TEL: 1051 1 6147800 ext. 436;

FAX: 1051 1 3495764;

EMAIL: dcampos@lamolina.edu.pe

Received for Publication February 9, 2016

Accepted for Publication April 21, 2016

doi:10.1111/jfpe.12412

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 5 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.

INTRODUCTION

Proteins are macronutrients necessary for human beings and

they constitute an important nutritional contribution not

only as energy source but as source of nitrogen and essential

aminoacids. Proteins are also important because they confer

physicochemical, functional and organoleptic properties to

foods (Scopes 1986).

Nonconventional sources of protein (e.g., by products

from agroindustry) could render added value as functional

ingredients, for nutritional purposes to fortify foods and for

pharmaceutical and cosmetics applications. Currently, the

food industry is in need of alternative protein sources that

can compete with the actual protein sources that dominate

the market (Pszczola 2004). Within this context, sacha inchi

(SI) or Plukenetia volubilis is a highly oil-containing seed

(54%) and with a relatively high protein content (27%)

(Hamaker et al. 1992). The cake remaining after oil extrac-

tion from SI presents a protein content of 59% dry weight

(DW) (Sathe et al. 2012; Ruiz et al. 2013). Hamaker et al.

(1992) have reported in SI protein a high content of cysteine,

tyrosine, threonine and tryptophan and a low content of

phenylalanine. In addition, Sathe et al. (2012) reported that

Journal of Food Process Engineering 00 (2016) 00–00 VC 2016 Wiley Periodicals, Inc. 1

Journal of Food Process Engineering ISSN 1745–4530

the water soluble albumin fraction constituted �25% (%) of

the defatted SI seed flour.

In the last few years, there is an increasing interest on

methods for extracting plant protein based on acid, alkaline

and enzyme-assisted extraction (Sari et al. 2013), being the

alkaline and enzyme-assisted methods more amenable for

practical applications. The number of studies dedicated to

protein extraction from SI is very limited up to date and

none of the previous studies have focused on the optimiza-

tion of the protein extraction parameters using the response

surface methodology (RSM). Sathe et al. (2012) evaluated

the defatted flour protein solubility of SI using a step by step

alkaline extraction with yields of �50% protein.

RSM is an excellent statistical technique for the optimiza-

tion of complex processes (Box and Draper 2007). RSM

explores the existing relationships between explicative varia-

bles and one or more response variables (Cao et al. 2012).

This methodology has been previously used in the optimiza-

tion of protein extraction either using alkaline or enzymatic-

assisted methods from different food sources such as flaxseed

(Oomah et al. 1994), pine seed (Wang et al. 2011), palm ker-

nel cake (Chee et al. 2012), soybean (Rosenthal et al. 2001;

Rosset et al. 2014), lentil (Jarpa-Parra et al. 2014), etc.

Since there are no previous studies on the optimization of

protein extraction yields from SI under alkaline and enzyme-

assisted methods in combination with RSM, the objectives

of this study were (1) to evaluate the effect of alkaline extrac-

tion parameters such as NaCl concentration, temperature

and solvent:meal ratio at pH 9.5 on the response variable

protein yield (%) from defatted SI cake meal (DSICM) by

applying RSM; (2) to evaluate the effect of enzyme-assisted

extraction parameters with Alcalase 2.4L enzyme concentra-

tion and time at pH 9.0, on the response variables protein

yield and hydrolysis degree (%, HD) by applying RSM. The

optimization of the protein extraction parameters in DSICM

offers an alternative process for obtaining protein from a

nonconventional source (SI cake) and simultaneously this

agro-industrial by-product could be re-valorized.

MATERIALS AND METHODS

Defatted Sacha Inchi Cake

SI kernel cake was provided by Olivos del Sur enterprise

(Lima, Peru). SI cake was obtained after oil extraction from

SI seed using an expeller. Proximate analysis was performed

in SI kernel cake according to the method of AOAC (1995)

for nuts and nut products. Protein content was calculated

using a conversion factor of 5.70 (Sathe et al. 2012). The

cake was ground in a hammer mill to obtain particles of

�500 lm. Ground cake meal was defatted for 12 h using

petroleum ether at a solvent/meal ratio of 10/1 (w/v) under

300 rpm stirring conditions. The DSICM was air-dried at

40C for 2 h in an oven then was packed in polyethylene bags

and stored at 4C until use.

Enzyme and Chemicals

Alcalase 2.4L was provided by Novozyme (Bagsvaerd, Den-

mark). All chemicals used were of reagent grade and pur-

chased from Sigma (St Louis, MO) and Merck (Darmstadt,

Germany).

Protein Analyses

The soluble proteins were determined according to Lowry

et al. (1951) and total protein with the Kjeldhal method

(AOAC 1995). Protein yield (Y, %) was calculated as g of

soluble protein from extract/100 g of total protein of

DSICM.

Hydrolysis Degree

HD (%) was determined in each hydrolyzed sample using

the method of Adler-Nissen (1979) by assaying free amino

groups with 2,4,6-trinitrobenzenesulphonic acid (TNBS)

and using the following equation:

HD %ð Þ 5 h=htotð Þ3100 5 100 3 AN2– AN1ð Þ=Npb

� �;

where h is the number of peptide bonds broken, htot is total

number of bonds per unit weight, AN1 is the amino nitrogen

content of the protein substrate before hydrolysis (mg/g

protein), AN2 is the amino nitrogen content of the protein

substrate after hydrolysis (mg/g protein) and Npb is the

amino nitrogen content of the peptide bonds in the protein

substrate (mg/g protein) as determined after total hydrolysis

with 6 M HCl at 110C for 24 h. The values of AN2 and AN1

were obtained from a standard curve at 340 nm absorbance

versus mg/L amino nitrogen generated with L-leucine.

Protein Extraction

Alkaline Extraction of Sacha Inchi Protein. Protein

from DSICM was extracted using selected combinations of

independent variables: temperature (C), solvent/meal ratio

(v/w) and NaCl concentration (M) according to the experi-

mental design. All protein extractions were performed at pH

9.5, 300 rpm agitation for 30 min. These parameters were

kept constant based on preliminary studies. After extraction,

solutions were immediately centrifuged at 4,000 3 g for 30

min at 4C. The supernatant were filtered through Whatman

filter paper No. 1 and the soluble protein and protein yield

(%) were quantified. All the experiments were carried out in

triplicate.

OPTIMIZATION OF PROTEIN EXTRACTION FROM SACHA INCHI CAKE R. CHIRINOS ET AL.

2 Journal of Food Process Engineering 00 (2016) 00–00 VC 2016 Wiley Periodicals, Inc.

Enzyme-Assisted Extraction of Sacha Inchi

Protein. Protein from DSICM was extracted using Alcalase

2.4L and the selected combinations of independent variables:

enzyme concentration (% enzyme in relation to the DSICM

protein content) and time (min) according to the experi-

mental design. Protein extraction was carried at pH 9.0, 50C,

300 rpm stirring and at a solvent/meal ratio of 50/1 (v/w).

These parameters were kept constant as recommended for

Alcalase (pH and temperature) and the solvent/meal ratio

based on preliminary studies. After extraction, solutions

were immediately centrifuged at 4,000 3 g for 30 min at 4C.

The supernatants were filtered through Whatman filter

paper No. 1 and the soluble protein, protein yield (%) and

HD (%) were determined. All the experiments were carried

out in triplicate.

Experimental Design and Statistical Analysis

Alkaline Extraction of Protein. The RSM was used to

determine the influence of three independent variables and

the optimal conditions for protein extraction from DSICM.

The effect of the variables temperature (X1), solvent/meal

ratio (X2) and NaCl concentration (X3) on the protein

extraction yield (dependent variable, Y %) was investigated.

The selection ranges within which each factor varied was

based on preliminary experiments (data not shown). Each

variable was coded at five levels: 21.68, 21, 0, 1 and 1.68

(Table 1). The conversion of real values to coded values was

as follows:

xi5 Xi– Xoð Þ=DXi; (1)

where xi is the dimensionless value of an independent vari-

able, Xi is the real value of an independent variable, Xo is the

real value of an independent value at the center point and

DXi is the step change.

A central composite design (CCD) was used to allow fit-

ting a second-order model (Nakai et al. 2006). A total of 19

randomized runs that included five central points were per-

formed (Table 1). The proposed model for the response vari-

able (Y (%), protein yield) corresponded to:

y5b01X4

i51

bizi1X4

i51

biiz2i 1X4

i 6¼j51

bijzizj; (2)

where b0 is the value of the adjusted response to the central

point of the design, bi, bii and bij are the linear, quadratic

coefficients and the intercept, respectively.

The optimum protein extraction conditions consisted on

determining the maximum protein extraction yield (maxima

desirability) through a combination of different variables or

factors. Predicted values (Y) were transformed into a desir-

ability value (d). The generated RSM to obtain maximum

protein yield from DSICM was experimentally validated

with three experimental replicates and the obtained values

compared to the ones predicted by the RSM model. The

TABLE 1. CENTRAL COMPOSITE DESIGN ARRANGEMENT AND EXPERIMENTAL AND PREDICTED PROTEIN YIELD VALUES FOR ALKALINE

EXTRACTION

Run

Coded variables Uncoded variables Protein yield (Y) %

x1 x2 x3 X1 X2 X3 Experimental Predicted

1 21 21 21 40 20 0.5 13.06 11.38

2 1 21 21 70 20 0.5 11.59 12.68

3 21 1 21 40 50 0.5 16.53 18.45

4 1 1 21 70 50 0.5 23.95 23.61

5 21 21 1 40 20 2 22.92 24.17

6 1 21 1 70 20 2 20.52 19.52

7 21 1 1 40 50 2 26.58 26.4

8 1 1 1 70 50 2 23.02 25.62

9 21.68 0 0 29.8 35 1.25 22.61 22.27

10 1.68 0 0 80.2 35 1.25 23.67 22.71

11 0 21.68 0 55 9.8 1.25 13.85 14.49

12 0 1.68 0 55 60.2 1.25 27.5 25.56

13 0 0 21.68 55 35 0 13.43 13.28

14 0 0 1.68 55 35 2.51 26.87 25.72

15 0 0 0 55 35 1.25 28.56 28.03

16 0 0 0 55 35 1.25 27.51 28.03

17 0 0 0 55 35 1.25 28.08 28.03

18 0 0 0 55 35 1.25 27.93 28.03

19 0 0 0 55 35 1.25 27.83 28.03

X1, temperature; X2, solvent/meal ratio; X3, NaCl concentration.

R. CHIRINOS ET AL. OPTIMIZATION OF PROTEIN EXTRACTION FROM SACHA INCHI CAKE

Journal of Food Process Engineering 00 (2016) 00–00 VC 2016 Wiley Periodicals, Inc. 3

surface plots were generated by varying two variables within

the experimental range and holding the other constant

(zero) at the central point. All the statistical analysis were

carried out with Statgraphics Centurion XV software 15.2.06

(Stat Point Inc., VA).

Enzyme-Assisted Extraction of Protein. The RSM

was used to determine the influence of two independent var-

iables on the optimal conditions for enzyme-assisted protein

extraction from DSICM. In addition, the influence of the

same variables on the HD (%) of protein was examined. The

effect of the variables: enzyme concentration (X1) and time

(X2) on the protein extraction yield (maximum) and protein

HD (minimum) were investigated. The selection ranges

within which each factor was varied based on preliminary

experiments (data not shown). Each variable was coded at

five levels: 21.41, 21, 0, 1 and 1.41 (Table 2). The conver-

sion of real values to coded values was conducted as

described in Eq. (1) for the two evaluated responses (protein

yield and HD).

A central composite design (CCD) allowed fitting of a

second-order model. A total of 13 runs that included five

central points were performed (Table 2). The proposed

model for the response variables (second order polynomial),

desirability values, validation of RSM and generated surface

plots were calculated as described previously. A multiple

response optimization was performed to determine the com-

bination of the experimental parameters (independent varia-

bles) that simultaneously maximize the protein yield and

minimize the protein HD. The obtained result was experi-

mentally validated with three experimental replicates. The

optimization of two variables was displayed as an overlaid

contour plot. All the statistical analysis were carried out

with Statgraphics Centurion XV software 15.2.06 (Stat

Point Inc., VA).

RESULTS AND DISCUSSION

Proximal Composition and Protein Analysis

SI kernel cake presented 7.9% humidity and the contents of

protein, fat, fiber, ash and carbohydrates in dry weight

(DW) corresponded to 58.4, 8.9, 4.1, 5.7 and 22.7%, respec-

tively, these values are close to the ones reported by Ruiz

et al. (2013). DSICM reached values of 61.9% of protein

(DW), this value was superior to the protein content

reported for other defatted meals obtained from soybean,

palm, and sesame (50, 16.8 and 42%, respectively) (Onsaard

et al. 2010; Chee et al. 2012; Rosset et al. 2014). Moure et al.

(2006) reported that protein content of defatted meals from

dehulled oilseeds depend on the seed type and ranges

between 35 and 60% (DW).

Optimization of Alkaline Extraction

The experimental design of five-levels, three-variable CCD

and the experimental results of protein extraction are shown

in Table 1. Protein yield varied from 11.5 to 28.5% (or from

7.1 to 17.6 g protein/100 g of DSICM). Using alkaline extrac-

tion and the RSM, protein recoveries from different defatted

cakes from oilseeds ranged between 10.9 and 32.6; 3.3 and

5.7; 12.3 and 16.5; and 40.8 and 58.7 g of protein/100 g for

flaxseed, pigeon pea, soybean and lentil (Oomah et al. 1994;

Jarpa-Parra et al. 2014; Tan et al. 2014).

The application of RSM yielded the following regression

equation, which is an empirical relationship between protein

yield (Y) and the evaluated variables (Eq. (3)):

TABLE 2. CENTRAL COMPOSITE DESIGN ARRANGEMENT AND EXPERIMENTAL AND PREDICTED PROTEIN YIELD AND DEGREE HYDROLYSIS

VALUES FOR ENZYME-ASSISTED EXTRACTION

Run

Coded variables Uncoded variables Protein yield (Y) % Hydrolysis degree (HD, %)

x1 x2 X1 X2 Experimental Predicted Experimental Predicted

1 21 21 2.00 15.00 28.97 28.60 0.96 0.92

2 1 21 5.00 15.00 34.45 34.80 4.03 5.01

3 21 1 2.00 45.00 29.18 28.51 3.75 3.91

4 1 1 5.00 45.00 40.33 40.37 5.38 6.55

5 21.41 0 1.38 30.00 28.79 29.46 1.56 1.71

6 1.41 0 5.62 30.00 42.58 42.23 7.72 6.42

7 0 21.41 3.50 8.79 28.41 28.36 2.97 2.54

8 0 1.41 3.50 51.21 31.85 32.23 6.44 5.74

9 0 0 3.50 30.00 34.80 34.99 4.07 4.12

10 0 0 3.50 30.00 35.00 34.99 4.25 4.12

11 0 0 3.50 30.00 34.91 34.99 4.49 4.12

12 0 0 3.50 30.00 35.07 34.99 4.03 4.12

13 0 0 3.50 30.00 35.18 34.99 3.72 4.12

X1, enzyme concentration (%); X2, time (min).

OPTIMIZATION OF PROTEIN EXTRACTION FROM SACHA INCHI CAKE R. CHIRINOS ET AL.

4 Journal of Food Process Engineering 00 (2016) 00–00 VC 2016 Wiley Periodicals, Inc.

Y %ð Þ 5 241:894 1 0:9801 � X1 1 0:9972 � X2

1 29:3638 � X3 2 0:0086X12

1 0:0:0042X1 � X2 2 0:1323 � X1 � X3

2 0:0125 � X22 2 0:1074 � X2 � X3

2 5:35729 � X32:

(3)

Analysis of variance (Table 1 and Supporting Information)

revealed that DCC application resulted in a highly significant

model (P< 0.000) indicative of a good generated response

model for optimization with R2 5 0.9609 and an adjusted

R2 5 0.9218. These coefficients suggest good fitting of the

model given that at least the R2 should be higher than

0.8000 (Joglekar and May 1999). Within the experimental

evaluated range, the factor time did not significantly affected

(P> 0.05) protein extraction yield meanwhile the other

components solvent/meal ratio and NaCl concentration had

a high significant effect (P< 0.01). These results indicate

that solvent/meal ratio and NaCl concentration are the main

factors contributing to protein extraction from DSICM.

Similar results have been previously obtained for extracted

protein from flaxseed and cowpea flour (Oomah et al. 1994;

Mune et al. 2008).

The surface responses are displayed in Fig. 1. The effect of

temperature and solvent/meal ratio on protein yield is dis-

played in Fig. 1a. Solvent/meal ratio exerted a quadratic

effect on protein yield that can be evidenced in Fig. 1a, where

its interaction with temperature is also displayed and with

solvent/meal ratios between 40/1 and 50/1 displaying the

highest protein yields. In Fig. 1a, a linear effect of tempera-

ture on protein yield can be observed, and within the 30–

70C range, no big variations were observed for the different

evaluated solvent/meal ratios. Temperature exerted a slight

quadratic effect on protein yield at different NaCl concentra-

tions (Fig. 1b). The interaction of solvent/meal ratio and

NaCl concentration is displayed in Fig. 1c, where the quad-

ratic effect of both components is evidenced. The quadratic

effect of NaCl concentration was also evidenced in Fig. 1c,

reaching the maximum protein yield at NaCl concentrations

close to 1.5 M. Results indicate that solvent/meal ratio and

NaCl concentration are the main contributors to the protein

extraction from DSICM.

The desirability maxima function was used to obtain the

optimal extraction conditions. The dependent variable was

set to the maximum possible (d 5 1), the optimal conditions

corresponded to 54C, a solvent/meal ratio of 42/1 (v/w),

NaCl 1.65 M at a pH of 9.5 and 30 min extraction time,

obtaining a protein yield of 29.7% (18.4 g protein/100 g

DSICM). Higher extraction yields (40.9 and 47 g solubilized

protein/100 g defatted SI flour) were reported by Sathe et al.

(2012) for SI meal defatted with hexane, using a step by step

methodology, at conditions of 1M NaCl, 15–30 min extrac-

tion time, two extraction steps, pH 9–12 and room tempera-

ture. The differences with that study can be attributed to the

solvent/meal ratio and differences of the raw materials. The

SI cake used in our study was exposed to a mechanical force

and friction generated in the expeller during the process to

obtain SI oil that could have affected the physicochemical

characteristics of the SI protein disfavoring its extraction.

Finally, the suitability of the generated mathematical model

to predict maximum protein yield was experimentally vali-

dated using the conditions determined in the optimization.

Thus, the experimental protein yield at the optimum condi-

tions was 30.2 6 0.33% being this value close to the value

generated by the mathematical model.

Optimization of Enzyme-Assisted Extraction

This study evaluated Alcalase 2.4L with the aim to increase

the protein yield from DSICM with a low HD. A low HD is

key to obtain a not highly hydrolyzed protein that can be

used as raw material in different food applications.

FIG. 1. RESPONSE SURFACE PLOTS AND CONTOURS FOR THE

EFFECTS OF (a) TEMPERATURE VERSUS SOLVENT/MEAL RATIO, (b)

TEMPERATURE VERSUS NaCl CONCENTRATION AND (c) SOLVENT/

MEAL RATIO VERSUS NaCl CONCENTRATION ON PROTEIN YIELD FOR

ALKALINE METHOD OF PROTEIN EXTRACTION

R. CHIRINOS ET AL. OPTIMIZATION OF PROTEIN EXTRACTION FROM SACHA INCHI CAKE

Journal of Food Process Engineering 00 (2016) 00–00 VC 2016 Wiley Periodicals, Inc. 5

The experimental design corresponded to five-levels and

two CCD variables. The experimental results of protein yield

as well as the HD are shown in Table 2. Protein yield and

HD varied from 28.4 to 40.3% (or from 17.3 to 24.5 g pro-

tein/100 g of DSICM) and from 0.96 to 5.38%, respectively.

Protein yield significantly increased (�40%) when the Alca-

lase was employed in the protein extraction process in com-

parison to the alkaline extraction. The efficiency of

proteolytic enzymes during protein extraction from different

sources has been extensively reported. Sari et al. (2013) by

using different proteases (1% of enzyme for 3 h) extracted

more protein from rapeseed, microalgae and soybean meals

(�60, 80 and 90%, respectively) in comparison to alkaline

extraction (pH 9.5; �15, 30 and 80%, respectively). A signif-

icantly (P< 0.05) higher trypsin extracted protein yield

(61.9 g/100 g) was obtained from palm kernel in comparison

to the alkaline (pH 9.5) method (10.2 g/100 g) (Chee et al.

2012). Also Latif and Anwar (2011) found that proteases

Protex 7L and Alcalase 2.4L successfully extracted proteins

from sesame meal (87.1 and 79.6%, respectively). For the

HD, the maximum obtained corresponded to 5.38%. Sari

et al. (2013) reported that certain amount of hydrolysis is

needed and acceptable for protein extraction but a high

hydrolysis is detrimental because proteins would be con-

verted to peptides displaying an increased solubility and

thus altering the functional properties of the extracted pro-

teins (Rosenthal et al. 2001; Taha and Ibrahim 2002) and the

bitterness associated with a high HD. Taha and Ibrahim

(2002) reported that low protein HD (range between 8.8

and 9.5%) for soybean, sesame and rice bran meals enzy-

matically hydrolyzed with papain (0.06–0.21%) for 5 min

produced improvements in wettability, flow ability and

emulsifying capacity properties and a direct relation between

increasing HD, nitrogen solubility and dispersibility was

found.

A quadratic (Eq. (4)) and lineal (Eq. (5)) relationship was

found between protein yield and HD with the different

extraction parameters evaluated by SRM. The relationship

established between protein yield (Y) and HD (in real val-

ues) with the evaluated parameters is shown:

Y %ð Þ 5 21:2596 2 0:2097 � X11 0:4973

� X21 0:1901X121 0:063X1 � X2– 0:0104 � X2

2; (4)

HD %ð Þ 5 22:0681 1 1:1176 � X11 0:0753 � X2: (5)

Analysis of variance (Table 2 and 3 in Supporting Informa-

tion) revealed that CCD application resulted in a highly sig-

nificant model (P< 0.000) indicative of a good generated

response model for optimization with a good R2 5 0.9934

and the adjusted R2 5 0.9887 for protein yield and with a

moderate R2 5 0.8551 and adjusted R2 5 0.8261 for HD.

Within the experimental evaluated range, the factors enzyme

concentration and time significantly affected (P< 0.05) pro-

tein extraction yield as well as HD. Thus enzyme concentra-

tion and time contribute to protein extraction from DSICM

and protein HD. Similar results were reported for soybean

meal, soybean, sesame and rice bran meals and palm kernel

meal (Rosenthal et al. 2001; Taha and Ibrahim 2002; Chee

et al. 2012).

The surface response for protein yield is displayed in

Fig. 2a. The effect of the enzyme concentration (%) in the

evaluated range on protein yield presented an increasing

trend (from �20 to 28%) as the enzyme concentration was

incremented (from 1.38 to 5.62%). Time exerts a quadratic

effect on protein yield. High protein yields were observed

between 40 and 50 min of extraction. The dependent variable

was set to the maximum possible (d 5 1.00) and the obtained

optimal conditions corresponded to a time of 54 min and

enzyme concentration of 5.5% considering a 50/1 (v/w) sol-

vent/meal ratio, pH 9.0 and 50C, respectively, obtaining a

protein yield of 43.4% (26.8 g protein/100 g DSICM). Using

the predicted optimum conditions, experiments carried out

in triplicates gave good results (43.78 6 0.28%) that coin-

cided with the predicted value implying that the model was

adequate. The surface response for HD is displayed in

Fig. 2b. The effect of the enzyme concentration (%) in the

evaluated range of HD presented a lineal effect. Increasing

concentrations of Alcalasa 2.4L resulted in higher HD. Also

time exerted a lineal effect but its effect was less pronounced

on HD. The optimization consisted on a minimization

(d 5 0) because a low as possible HD was aimed. The

obtained optimal conditions corresponded to 8.78 min and

FIG. 2. RESPONSE SURFACE PLOTS AND CONTOURS FOR THE

EFFECTS OF ENZYME CONCENTRATION AND EXTRACTION TIME ON

(a) PROTEIN YIELD AND (b) HYDROLYSIS DEGREE FOR THE ENZYME-

ASSISTED METHOD OF PROTEIN EXTRACTION

OPTIMIZATION OF PROTEIN EXTRACTION FROM SACHA INCHI CAKE R. CHIRINOS ET AL.

6 Journal of Food Process Engineering 00 (2016) 00–00 VC 2016 Wiley Periodicals, Inc.

1.37% of enzyme concentration obtaining a HD of 0.13%.

Using the predicted optimum conditions, experiments car-

ried out in triplicate gave good results (1.51 6 0.11%) very

close to the values predicted by the generated SRM model.

Finally, the obtained optimization results for both responses

did not offer concluding results when they were evaluated in

separate. Thus, a multiple optimization response was gener-

ated and the factors time and enzyme concentration that

resulted in a high protein yield and a low HD (lower to 10%)

were included. The optimization of these two responses is

displayed as an overlaid contour plot in Fig. 3. After the mul-

tiple response optimization, values of 5.62% Alcalase 2.4L

enzyme and 40.4 min at pH 9.0, 50C and 50/1 solvent/meal

ratio resulted in a maximum protein yield of 44.7% (27.6 g

protein/100 g DSICM) with a HD of 7.86%. Same conditions

were experimentally validated resulting in protein yield and

HD of 44.7 6 0.4 and 7.86 6 0.14%, respectively. Our results

indicate that the enzyme-assisted protein extraction was able

to extract 1.46 fold more protein than the alkaline extraction

from DSICM.

CONCLUSIONS

RSM allowed optimization of the alkaline and enzyme-

assisted protein extraction conditions from DSICM. For the

protein alkaline method, the factors: solvent/meal ratio and

NaCl concentration significantly affected the extraction con-

ditions, but not extraction time. For the enzyme-assisted

protein extraction method, the Alcalase 2.4L enzyme con-

centration and time of hydrolyses affected the protein yield

and the HD. By means of a multiple response methodology

(MRM) with the responses: protein yield and HD which

were maximized and minimized, respectively, it was possible

to obtain the maximum protein extraction with a low HD.

Results of the MRM for the enzyme-assisted protein extrac-

tion method indicated that maximum protein yield (optimal

conditions, enzyme concentration of 5.6%, 40.4 min extrac-

tion, solvent/meal 50/1 (v/w) ratio, pH 9.0 and 50C) was

46% higher in comparison to the alkaline method (optimal

conditions, temperature: 54.2C, solvent/meal 42/1 (v/w)

ratio, NaCl concentration of 1.65 M, pH 9.5 for 30 min).

The predicted values for protein yield from all generated

models were consistent and experimentally validated. These

results indicate that the enzyme-assisted protein extraction

from sacha inchi kernel cake is an alternative protein extrac-

tion method with higher yields than the traditional alkaline

method. Additionally, the recovered protein from this by-

product could be considered as potential source of proteins

to be used in multiple industrial applications.

ACKNOWLEDGMENT

This research was supported by the grant in Science and

Technology (2013–2014) supported by the Universidad

Nacional Agraria La Molina (Lima, Peru).

REFERENCES

ADLER-NISSEN, J. 1979. Determination of the degree of hydroly-

sis of food protein hydrolysates by trinitrobenzenesulfonic acid.

J. Agric. Food Chem. 27, 1256–1262.

AOAC. 1995. Officials Methods of Analysis, 15th Ed., Association

of the Official Analytical Chemists, Washington, D.C., Gaithers-

burg, Maryland.

BOX, G. and DRAPER, M. 2007. Response Surfaces, Mixtures, and

Ridge Analyses. 2nd Ed., John Wiley & Sons Inc., Hoboken,

New Jersey.

CAO, W., ZHANG, C., JI, H. and HAO, J. 2012. Optimization of

peptic hydrolysis parameters for the production of angiotensin

I-converting enzyme inhibitory hydrolysate from Aceteschinen-

sis through Plackett–Burman and response surface methodo-

logical approaches. J. Sci. Food Agric. 92, 42–48.

CHEE, L., LING, H.K. and AYOB, K. 2012. Optimization of

trypsin-assisted extraction, physochemical characterization,

nutritional qualities and functionalities of palm kernel cake

protein. LWT - Food Sci. Technol. 46, 419–427.

HAMAKER, B.R., VALLES, C., GILMAN, R., HARDMEIER,

R.M., CLARK, D., GARC�IA, H., GONZALES, A.E.,

KOHLSTAD, I., CASTRO, M., VALDIVIA, R., et al., 1992.

Amino acid and fatty acid profiles of the inca peanut (Plukene-

tia volubilis). Cereal Chem. 69, 461–463.

JARPA-PARRA, M., BAMDAD, F., WANG, Y., TIAN, Z., TEMELI,

F., HAN, J. and CHEN, L. 2014. Optimization of lentil protein

extraction and the influence of process pH on protein structure

and functionality. LWT - Food Sci. Technol. 57, 461–469.

JOGLEKAR, M. and MAY, T. 1999. Product excellence through

experimental design. In Food Product and Development: From

Concept to the Market Place (E. Graf and I.S. Saguy, eds.), Aspen

Publishers Inc., Gaithersburg, Maryland.

FIG. 3. SUPERIMPOSED CONTOUR PLOT FOR PROTEIN YIELD AND

HYDROLYSIS DEGREE (HD) AS A FUNCTION OF ENZYME

CONCENTRATION (%) AND EXTRACTION TIME (min) AT 50C,

SOLVENT/MEAL RATIO OF 50/1 AND pH 9.0

R. CHIRINOS ET AL. OPTIMIZATION OF PROTEIN EXTRACTION FROM SACHA INCHI CAKE

Journal of Food Process Engineering 00 (2016) 00–00 VC 2016 Wiley Periodicals, Inc. 7

LATIF, S. and ANWAR, F. 2011. Aqueous enzymatic sesame oil

and protein extraction. Food Chem. 125, 679–684.

LOWRY, H., ROSEBROUGH, J., FARR, L. and RANDALL, J.

1951. Protein measurement with the Folin phenol reagent. J.

Biol. Chem. 193, 265–275.

MOURE, A., SINEIRO, J., DOMINGUEZ, H. and PARAJ�O, J.

2006. Functionality of oilseed protein products: A review. Food

Res. Int. 39, 945–963.

MUNE, M.A., MINKA, S.R. and MBOME, I.L. 2008. Response

surface methodology for optimisation of protein concentrate

preparation from cowpea [Vigna unguiculata (L.)Walp]. Food

Chem. 110, 735–741.

NAKAI, S., LI-CHEN, Y. and DOU, J. 2006. Experimental design

and response surface methodology. In Handbook of Food and

Bioprocess Modeling Techniques (S. Sablani, A. Datta, M.S. Rah-

man and A. Mujumdar, eds.), CRC Press, Boca Raton, FL.

ONSAARD, E., POMSAMUD, P. and AUDTUM, O. 2010. Func-

tional properties of sesame protein concentrate from sesame

meal. Asian J. Food Agro-Ind. 3, 420–431.

OOMAH, B.D., MAZZA, G. and CUI, W. 1994. Optimization

of protein extraction from flaxseed meal. Food Res. Int. 27,

355–361.

PSZCZOLA, D. 2004. Ingredients of food technology. J. Food Sci.

58, 56–69.

ROSENTHAL, A., PYLE, D.L., NIRANJAN, K., GILMOUR, S.

and TRINCA, L. 2001. Combined effect of operational varia-

bles and enzyme activity on aqueous enzymatic extraction of

oil and protein from soybean. Enzyme Microb. Technol. 28,

499–509.

ROSSET, M., ACQUARO, R. and BEL�EIA, P. 2014. Protein extrac-

tion from defatted soybean flour with Viscozyme L pretreat-

ment. J. Food Process. Preserv. 38, 784–790.

RUIZ, C., D�IAZ, C., ANAYA, J. and ROJAS, R. 2013. An�alisis

proximal, antinutrientes, perfil de �acidos grasos y de amino�aci-

dos de semillas y tortas de 2 especies de sacha inchi (Plukenetia

volubilis y Plukenetia huayllabambana). Rev. Sociedad Qu�ımica

Per�u 79, 29–36.

SARI, Y., BRU~N�IS, M. and SANDERS, J. 2013. Enzyme assisted

protein extraction from rapeseed, soybean and microalgae

meals. Ind. Crops Prod. 43, 78–83.

SATHE, S., KSHIRSAGAR, H. and SHARMA, G. 2012. Solubiliza-

tion, fractionation, and electrophoretic characterization of Inca

Peanut (Plukenetia volubilis L.) proteins. Plant Foods Hum.

Nutr. 67, 247–255.

SCOPES, R. (1986). Protein Purification. Principles and Practice,

3rd Ed., Springer, New York.

TAHA, F.S. and IBRAHIM, M.A. 2002. Effect of degree of hydro-

lysis on the functional properties of some oilseed proteins.

Grasas y Aceites 53, 273–281.

TAN, E.S., NGOH, Y.Y. and GAN, C. H.Y. 2014. A comparative

study of physicochemical characteristics and functionalities of

pinto bean protein isolate (PBPI) against the soybean protein

isolate (SPI) after extraction optimization. Food Chem. 152,

447–455.

WANG, S., JIANG, L., LI, Y., LI, D. and SUI, X. 2011. Optimi-

zation on aqueous enzymatic extraction conditions of pine

seed protein by response surface method. Proc. Eng. 15,

4956–4996.

OPTIMIZATION OF PROTEIN EXTRACTION FROM SACHA INCHI CAKE R. CHIRINOS ET AL.

8 Journal of Food Process Engineering 00 (2016) 00–00 VC 2016 Wiley Periodicals, Inc.