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Research Article

Defatted Corn Protein Extraction: Optimization by Response Surface Methodology and Functional Properties

Jauricque Ursulla Kongo-Dia-Moukala and Hui Zhang

A number of operating parameters including temperature, pH, solvent/flour ratio and time influence the yield of protein during extraction. In order to effectively identify the good combinations of the extraction conditions, Response Surface Methodology (RSM) was employed to determine optimum conditions for extraction of protein from defatted corn. The coefficient of determination (0.9789) was good for the second-order model. Protein extraction from defatted corn was mainly affected by pH and solvent/flour ratio. From RSM-generated model, the optimum extraction conditions were 54°C, 11.55, 1:18 and 33 min for temperature, pH, solvent/flour ratio and time, respectively. Under these conditions, the experimental protein content was 69.25 mg mL-1 which agreed closely with the predicted value 71.23 mg mL-1. To ensure that the protein extract could be utilized for food application, some functional properties such as water holding capacity, oil holding capacity, emulsifying capacity, foaming capacity and foaming stability were evaluated. Defatted corn protein had a good water holding and foaming capacity. Thus, it can be used in food formulation systems.

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Jauricque Ursulla Kongo-Dia-Moukala and Hui Zhang, 2011. Defatted Corn Protein Extraction: Optimization by Response Surface Methodology and Functional Properties. American Journal of Food Technology, 6: 870-881.

DOI: 10.3923/ajft.2011.870.881

Received: March 31, 2011; Accepted: June 10, 2011; Published: September 07, 2011


Defatted corn flour is a byproduct of the corn starch manufacture and constitutes a promising protein source for human. The protein content in defatted corn flour is of superior nutritional quality consisting mostly of albumin and globulin (Gupta and Eggum, 1998).

Defatted corn flour contains approximately 27.6% proteins, 51.2% carbohydrates, 5% fat, 7.5 and 3.1% crude fiber (Siddiq et al., 2009). It has the potential for use in food industry because of its high protein content, nutritional quality, functionality and absence of toxic substances. The defatted corn flour is presently used almost exclusively as an animal feed. The demand for low-cost vegetable protein supplements to increase the nutritional value of cereal and other food has encouraged research on improved products from defatted corn flour. The food-grade germ meal can be used as a protein supplement in a variety of bakery, macaroni and traditional product and to prepare protein isolates and concentrates. Recent global shortages of food further warrant exploitation of defatted corn flour for human consumption (Salunkhe et al., 1992).

Protein isolates are intended to be additives in food products for improving functional properties, such as foaming/emulsifying capacity, gel formation, viscosity, texture and water-binding capacity. Protein isolates obtained from corn flour (Siddiq et al., 2009), sesame seed (Lopez et al., 2003) as well as wheat and soybean proteins (Ma et al., 2007; Karki et al., 2009), have been added to a variety of products, usually as replacements for egg albumin. Proteins from defatted corn flour have considerable potential for use as a supplement in a variety of foods as a new protein source.

Attention on plant protein isolates has been focused mainly on cotton seed, peanut, rapeseed, soya protein and sunflower seed and in some areas, commercial preparations are available (Kanu et al., 2007). In the present study, defatted corn was being extracted in order to get protein by using alkaline method which has been reported to be the most commonly used procedure for protein extraction (Aluko and Monu, 2003; Kain et al., 2009). Various parameters such as pH, temperature, ionic strength, solvent type, extraction time, solvent/flour ratio, presence of components causing linking, affect protein extractability. The protein extraction as well as its functionality as a nutritional ingredient may be affected by extraction conditions, solvent type and heat treatment (Liu, 1997). The extraction, isolation and fractionation procedures differ depending on the end use.

When many factors and interactions affect desired responses, Response Surface Methodology (RSM) is an effective tool for optimizing the process (Triveni et al., 2001). It is a statistical technique used to design experiments that yield the relevant information in the shortest time with the least cost. In addition to analyze the effects of the independent variables, the experimental methodology also generates a mathematical model that describes the overall process (Batista, 1999).

However, there is not yet any investigation about the optimization of defatted corn protein extraction. Moreover, limited information is available in the literature on the functional properties of the defatted corn protein; although studies have been reported on the refining processes and properties of defatted corn and their use in fortifying some foods. Thus, the objectives of the study were to optimize the protein extraction from defatted corn flour for the maximum protein content and to investigate some functional properties such as water holding capacity, oil holding capacity, emulsifying capacity and foaming capacity and stability in order to determine the potential application of the proteins extract in food processing.


Materials: Defatted corn flour was obtained from China Corn Oil Company Ltd, Shandong Province, P.R. China. The chemicals and reagents used were of analytical and food grade quality obtained from Sinopharm Chemical Reagent Co., Ltd., Shanghai P.R. China.

This study was conducted in the state Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, PR China between January 2010 and September 2010.

Protein extraction: The protein was extracted from defatted corn flour with selected 21 combinations of independent variables such as temperature (42-58), pH (9.30-12.70), solvent/flour ratio (1:15-1:1:25) and extraction time (22-38 min) (Table 2). After optimization, the proteins were extracted with the optimum conditions. The defatted corn flour (10 g) was mixed with distilled water and stirred in water bath. The supernatant was adjusted to pH 4.5 with 1.0 mol L-1 HCl to precipitate the proteins and centrifuged at 4500 rpm for 15 min. The precipitates were washed several times with distilled water, dispersed in a small amount of distilled water and adjusted to pH 7.0 by using 0.1 mol L-1 NaOH and 0.1 mol L-1 HCl.

Table 1: Independent variables and their coded levels used in central composite design studies for optimizing extraction of protein from defatted corn flour
aTemp: Temperature bSFR: Solvent/flour ratio

Table 2: Central composite design-variable and responses
aSFR: Solvent/flour ratio

The dispersed product was freeze-dried (-70°C) for further experimental analysis.

Protein determination: Soluble protein in supernatant was estimated by the method of Bradford (1976) using the coomassie protein assay reagent with bovine serum albumin as the standard.

Experimental design: In the experimental design temperature (X1), pH (X2), solvent/flour ratio (X3) and time (X4) were chosen as independent variables. Response Surface Methodology (RSM) was used to establish the optimum conditions of protein extraction, each independent variable had five level, coded as -α, -1, 0, +1, +α (Table 1). The design consisted of eight factorial points, eight axial points and five center points. Protein content was the dependant variable. All experiments were carried out in a randomized order to minimize any effect of extraneous factors on the observed responses.

A Central Composite Design (CCD) was arranged to allow for fitting of second-order model (Nakai et al., 2006) (Table 2).

Statistical analysis: Analysis was done using Design-Expert software version 7.1.3 to fit the experimental data to the second-order polynomial equation to obtain coefficients of the Eq. 1. The model proposed for response (Y) was:


The coefficients of the polynomial were represented by β0 (constant term), βi (linear effects), βii (quadratic effects) and βij (interaction effects). Each treatment was subjected to Analysis of Variance (ANOVA) to determine the effects of independent variables, as well as their interactions with the responses at different probabilities (p).

Proximate analysis: The proximate analysis of defatted corn and protein extract was determined according to AOAC (2005). The moisture content was determined by drying in an oven at 105°C until a constant weight was obtained. Ash was determined by weighing the incinerated residue obtained at 550°C for 8-12 h. The crude protein was determined by the micro-Kjeldahl method and a Conversion factor of N x6.25 was used to quantify the crude protein content as previously reported (Kamara et al., 2010). Fat was determined by Soxhlet extraction (James, 1995).

Determination of functional properties
Water-Holding Capacity (WHC):
To determine the Water Holding Capacity of defatted corn protein, the method outlined by Diniz and Martin (1997) was followed with slight modifications. Triplicate samples (0.5 g) of protein were dissolved with 10 mL of distilled water in centrifuge tubes and vortexed for 30 sec. The dispersions were allowed to stand at room temperature for 30 min, centrifuged at 2,800x g for 25 min. The supernatant was filtered with Whatman No. 1 filter paper and the volume retrieved was accurately measured. The difference between initial volumes of distilled water added to the protein sample and the volume retrieved. The results were reported as mL of water absorbed per gram of protein sample.

Oil-Holding Capacity (OHC): Oil-holding capacity of defatted corn protein was determined as the volume of edible oil held by 0.5 g of material according to the method of Shahidi et al. (1995).

Emulsifying Capacity (EC): Emulsifying capacity was measured using the procedure described by Rakesh and Metz (1973) with modification. A 0.5 g of each freeze-dried sample was transferred into a 250 mL beaker and dissolved in 50 mL of 0.5 N NaCl and then 50 mL of soybean oil (Gold Ingots Brand, QS310002012787, Suzhou, P.R. China) was added. The homogenizer equipped with a motorized stirrer driven by a rheostat Ultra-T18 homogenizer (Shanghai, China) was immersed in the mixture and operated for 120 s at 10,000 rpm to make an emulsion. The mixture was transferred to centrifuge tubes, maintained in water-bath at 90°C for 10 min and then centrifuged at 2800x g for 20 min. Emulsifying capacity was calculated as in equation:


where, VA is the volume of oil added to form an emulsion, VR is the volume of oil released after centrifugation and WS is the weight of the sample.

Foaming Capacity (FC) and Foam Stability (FS): The foaming capacity was determined using the method described by Makri et al. (2005) with minor modifications. Concentrations of 1% protein were prepared in deionized water and adjusted to pH 7.4 with 1.0 N NaOH and 1.0 N HCl. Volumes of 100 mL (V1) of defatted corn protein suspension was blended for 3 min using a high-speed blender, poured into 250 mL graduated cylinders and the volume of foam (Vt) were immediately recorded at 0, 30 and 60 min. FC was calculated using the following equation:



Model fitting: The application of response surface methodology (RSM) yields the regression Equation (4) which represents an empirical relationship between the response (protein content) and the tested variables in coded units, as given in the following Eq. 4:


where, Y is the predicted response in real value; X1 is the coded value of variable temperature; X2 is the coded value of variable pH; X3 is the coded value of variable SFR and X4 is the coded value of variable extraction time.

The plot of experimental values of extracted protein (mg mL-1) versus those calculated from Eq. 1 indiacated a good fit, as presented in Fig. 1. The results of Analysis of Variance (ANOVA) for the RSM are shown in Table 3. The coefficient of determination in the models defined R2 expresses the degree of fitness of the proposed model to the empiric. For the model fitted, the coefficient of determination (R2) which is a measure of degree of fit (Haber and Runyon, 1977), was 0.98. This implies that 98% of the variations could be explained by the fitted model, indicating a reasonable fit of the model to the experimental data. Joglekar and May (1987) suggested that, for a good fit of a model, R2 should be at least 0.80. F-value was high (45.82) while p-value was less than 0.05 which implied that the model itself is significant.

Fig. 1: Correlation between predicted and actual extracted protein (mg mL-1)

Table 3: Analysis of variance (ANOVA) of the regression parameters for the response surface model
R2: 0.98 R2 adj: 0.97 CV = 3.76

Table 4: Estimation regression model of relationship between response variable and independent variable

A lack of fit probability of 0.1791 was obtained which illustrated that it was not significant (p>0.05). The Coefficient of Variation (CV) indicates the degree of precision with which the experiments are compared (Claver et al., 2010). It is a measure of reproducibility of the models. The CV of the model was calculated as 3.76%. As a general rule, a model can be considered reasonably reproducible if its CV is not greater than 10%.

Effects of independent variables on responses: The significance of each coefficient was determined using the p-value. As shown from Table 4, the regression coefficients in their linear term (temp, pH, SFR and time), as well as two quadratic terms (pH and SFR), were significant (p<0.05). Three cross-product terms (temp • SFR, pH • time and SFR • time) were significant (p<0.05). The results indicated that the effects of pH and solvent/flour ratio were the major contributing factors to protein extraction from defatted corn flour.

The response surface graphs for extracted protein from defatted corn are shown in Fig. 2, to illustrate the main and interactive effects of the independent variables on the protein extraction. The response surface and contour plots of the effects of temperature and pH on defatted corn protein extraction are presented in Fig. 2a. The results indicated that temperature displayed a linear effect on the response and the extracted protein increased with an increase of temperature. However, pH demonstrated a quadratic effect on the response. In Fig. 2b, both temperature and solvent/flour ratio exerted quadratic effects on protein extraction.

Effect of temperature and time are shown in Fig. 2c, it can be seen as a linear effect for both temperature and extraction time. The effects of pH and solvent/flour ration are shown in Fig. 2d. The results indicated that solvent/flour ratio had a linear effect whereas; the effect of pH was quadratic.

Fig. 2(a-f): Surface plot to show the combined effect of (a) temp and pH, (b) temp and SFR, (c) temp and time, (d) pH and SFR, (e) SFR and time and (f) time and pH. prot. cont. = Protein content

The graph shown in Fig. 2e indicates that both extraction time and solvent/flour ratio had a quadratic effect on protein extraction. Figure 2f depicts the influence of extraction time and pH; the result revealed a linear effect for extraction time and quadratic effect for pH. Therefore, increases of extraction time and pH both resulted in a higher protein extraction. Similar observations have been reported previously with others plant material. Wani et al. (2008) studied the extraction of Watermelon seed protein and found that optimum conditions were as follows: 0.12 g L-1 alkali concentration, 15 min extraction time and 70:1 (v/w) solvent/meal ratio at 50°C. Firatligil-Durmus and Evranuz (2010) worked on protein extraction from red pepper seed and found significant effect for pH and solvent/meal ratio and concluded that maximum protein yield was obtained by extracting seed meal with a temperature of 31°C, solvent/meal ratio of 21:1 v/w, mixing time of 20 min and pH of 8.8.

Table 5: Predicted and experimental protein content (mg mL-1) under the optimum conditions
aSFR: Solvent/flour ratio

Table 6: Proximate composition of defatted corn flour and protein extract (g/100 g, dry matter basis)
Values are means±standard deviation of three determinations

Table 7: Functional properties of defatted corn protein extract
Values are means±standard deviation of three determinations. DCPE: Defatted corn protein extract

Optimum conditions and model verification: In order to validate the model, the defatted corn protein was extracted under optimum conditions and the protein content in the supernatant was determined. Under the optimum conditions of temperature 54°C, pH 11.55, solvent/flour ratio 1:18 and extraction time 33 min, a maximum protein content of 71.23 mg mL-1 was predicted (Table 5). The suitability of the model equation for predicting the optimum response value was tested using the recommended optimum conditions. The results indicated that the experimental protein value (69.25 mg mL-1) was not significantly different from the predicted protein value (71.23 mg mL-1).

Proximate analysis: The proximate analysis of defatted corn flour and corn protein extract is presented in Table 6. The defatted corn flour contained 20.10% crude protein; protein extracted 65.65% crude protein. There was a significant difference (p<0.05) in the crude protein content among the samples and this result is in agreement with that of Zhang et al. (2009) and Siddiq et al. (2009). The lipid content of defatted corn was 2.82% and for protein extracted was 1.19%. The decrease lipid content in the protein extracted might significantly increase stability towards lipid oxidation which may also enhance product stability (Diniz and Martin, 1997; Kristinsson and Rasco, 2000; Shahidi et al., 1995).

Functional properties
Water/oil holding capacity: The ability of protein to imbibe water and retain it against a gravitational force within a protein matrix is known as Water Holding Capacity (WHC). Defatted corn protein had a good water-holding capacity of 3.54 mL g-1 protein (Table 7). This is likely due to the fact that the defatted corn protein had great ability to swell because it contained proteins and crude fiber which could be responsible for the increased water-holding capacity (Kinsella, 1979).

Fig. 3: Foam stability of defatted corn protein. Values represent the Means±Standard Deviation (SD) of triplicate

An important functionality that influences taste of the product that is required in various food industries is the ability of protein to absorb oil. The oil holding capacity of defatted corn protein was 1.87 mL g-1 protein (Table 7). Defatted corn protein shown a lower oil holding capacity when compared to peanut (Yu et al., 2007) and cashew nut (Ogunwolu et al., 2009).

Emulsifying capacity: The emulsifying capacity is a measure of the effectiveness of proteinceous emulsifiers (Pearce and Kinsella, 1978). Proteins are composed of charged amino acids, non-charged polar amino acids and nonpolar amino acids which makes protein a possible emulsifier, the surfactant possessing both hydrophilic and hydrophobic properties and be able to interact with both water and oil in food system (Ghavidel and Prakash, 2006). From the results (Table 7), the emulsifying capacity of defatted corn protein was 63.39 mL g-1 protein. Defatted corn protein had an emulsifying capacity higher than that of soy protein (Amadou et al., 2010) and fish protein concentrate (Foh et al., 2011).

Foaming capacity and stability: The capacity of proteins to form stable foams with gas by forming impervious protein films is an important property and it was likely due to the increased net charges on the protein which weakened the hydrophobic interactions but increased the flexibility of the protein. This allowed the protein to diffuse more rapidly to the air–water interface to encapsulate air particles and then enhance the foam formation (Wierenga and Gruppen, 2010) Dispersed proteins lower the surface tension at the water-air interface, thus creating foaming capacity (Turgeon et al., 1992).

To have foam stability (Fig. 3), protein molecules should form continuous intermolecular polymers enveloping the air bubbles, since intermolecular cohesiveness and elasticity are important to produce stable foams (Kamara et al., 2009). Defatted corn protein had a foam capacity of 50% (Table 7). This is consistent with the results reported by Wu et al. (2009).


Defeated corn protein was effectively extracted by alkaline method. The production of protein from defatted corn was optimized using RSM of design-expert software version 7.1.3. The extraction of protein from defatted corn was significantly influenced by the pH and the solvent/flour ratio. Under optimum conditions, experimental protein value was lower than predicted by second-order model. Furthermore, the defatted corn protein also has an effect on improving functionality such as water holding capacity, emulsifying capacity and foaming capacity. Defatted corn protein could find potential use in food formulation systems.


The work reported in this study is a continuation of the on-going research supported by the financial assistance of Chinese Scholarship Council.

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