Use of Response Surface Methodology to Optimize Gluten-free Bread Fortified with Soy Flour and Dry Milk H.D. Sa´nchez*, C.A. Osella and M.A. de la Torre Instituto de Tecnologia de Alimentos, Facultad de Ingenierı´a Quı´mica, Universidad Nacional del Litoral, C.C. 266, 3000 Santa Fe, Argentina The percentages of soy flour (X1) and dry milk (X2) were varied for the production of gluten-free bread to optimize batter softness (Y1), specific volume (Y2), crumb grain score (Y3), bread score (Y4) and bread protein content (Y5). A central composite design was used and second-order models for Y1 were employed to generate response surfaces. When bread protein content was decreased from 10 to 3%, specific volume increased from 3.2 to 4.6 cm3/g and bread score increased too. Nevertheless, the highest crumb grain score was obtained at 7.3% of bread protein content. The results demonstrated that a gluten-free bread can be prepared by adding 7.5% soy flour and 7.8% dry milk to a previously developed formulation, increasing its protein content from 1 to 7.3% and modifying in a small degree, its sensory quality. Key Words: celiac disease, gluten-free bread, soy flour, dry milk
INTRODUCTION There are people intolerant to prolamins of wheat, rye and barley. This serious syndrome, characterized by intestinal malabsorption, is called celiac disease, that may lead to severe malnutrition (Davison and Bridges, 1987). Many researchers have investigated the possibilities of substituting other starches for wheat flour in bread making, but little is known about the impact of such substitutions on mixing requirements and gas retention capacity during fermentation and baking of a composite flour dough (Defloor et al., 1993). Special products such as gluten-free bread may exhibit poor sensory quality and technological problems during production because of their lack of gluten proteins (Torres et al., 1999). Such products often have very low protein content, suggesting the desirability of fortification, in which one or more nutrients are added to improve nutritional quality (Araya et al., 1994). In Argentina, soy flour, dry milk and whey protein concentrate are important sources of high-quality proteins that can be used to prepare fortified bread (Sa´nchez et al., 1998). Response surface methodology (RSM) is an effective statistical technique used to optimize processes or formulations with minimal experimental trials when many factors and their interactions may be involved
*To whom correspondence should be sent (e-mail:
[email protected]). Received 31 December 2002; revised 23 October 2003. Food Sci Tech Int 2004;10(1):0005–5 ß 2004 Sage Publications ISSN: 1082-0132 DOI: 10.1177/1082013204042067
(Malcolmson et al., 1993). RSM uses an experimental design such as central composite design to fit a model using least squares regression analysis. Adequacy of a proposed model is revealed by diagnostic checking provided by analysis of variance (ANOVA) and residual plots. Contour plots are useful to study RSM data and determine optimal conditions (Rustom, 1991). The aim of this study was to increase the protein content of gluten-free bread by adding soy flour and dry milk to a previous formulation containing only 1% protein (Sa´nchez et al., 2002) and to apply RSM to optimize specific volume and sensory quality.
MATERIALS AND METHODS Materials The following starches and flours were used: Perla corn starch [14.4% moisture, 0.2% protein (% N 5.7), 70 C gelatinization temperature; Industrias de Maı´ z S.A., Buenos Aires, Argentina]. Aldeman cassava starch [14.3% moisture, 0.08% protein (% N 6.25), 63 C gelatinization temperature; Cooperativa Agrı´ cola Industrial San Alberto Ltda., Misiones, Argentina]. Trimacer rice flour [13.7% moisture, 6.0% protein (% N 6.25), 70 C gelatinization temperature; Atilio Betella y Cı´ a, Santa Fe, Argentina]. Trimacer soy flour [8.6% moisture, 42.6% protein (% N 6.25), 17.4% fat, from Atilio Betella y Cı´ a, Santa Fe, Argentina]. Sancor dry milk [5.5% moisture, 26.6% protein (% N 6.38), 26% fat; Sancor Cul, Santa Fe, Argentina]. The fat used was Optima oleomargarine (melting point 36 C, from Molinos Rı´ o de la Plata S.A., Buenos Aires, Argentina). Hydroxypropylmethylcellulose (2% viscosity: 3000–5600 cp, Dow Chemical Company, Midland, Mi) was also used. 5
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H.D. SA´NCHEZ ET AL.
Baked Samples Cornstarch, rice flour and cassava starch were used in the following proportions: 74.2–17.2–8.6 (Sa´nchez et al., 2002) while soy flour and dry milk were varied between 2% and 12% related to powder ingredients. Powder ingredients (corn starch, rice flour, cassava starch, soy flour and dry milk) 300 g, fat 30 g, hydroxypropylmethylcellulose 9 g, sugar 15 g, salt 9 g, yeast 30 g and water 250 mL were mixed at 400 rpm for 1 min and 600 rpm for 2 min. Then 300 g of the resulting batter was placed in a greased bread pan and proofed at 27 C and 80% humidity, controlling the rising with the pushmeter, where 25 g of batter rise from 15 to 30 mm. Bread was then baked at 210 C for 40 min without steam. Equipment used included a General Electric mixer with two stainless steel whisks at 400 and 600 rpm. The Dalvo proofing box, temperature and humidity controlled, was a product of Ojalvo S.A., Santa Fe, Argentina. The apparatus used to measure proofing was a push-meter consisting of a glass cylinder (75 mm height, 45 mm i.d.) with a tight-fitting plastic piston that rises during proofing. The Dalvo oven (Ojalvo S.A., Santa Fe, Argentina) had an electrical heating and temperature control up to 300 C. A cone penetrometer (Stanhope-Seta Limited, Surrey, England) was fitted with a flat-nosed cone (greater diameter: 3.2 cm; smaller diameter: 1.1 cm; length: 2.5 cm; weight: 55 g). Displacement in the batter was measured at 3 s (range 0–400 units, equivalent to 0–40 mm penetration).
one hour after they were baked. Experts scored each sample once. As recommended by Pyler (1973) for standard white bread and modified by Sa´nchez et al. (1996) for gluten-free bread, a typical scoring card for standard gluten-free bread has the following point values: Volume, 15 (specific volume of 5 cm3/g corresponded to the maximum value: 15); crust, 15 (colour and thickness); texture, 15 (elasticity and stickiness); crumb colour, 10 (cream white maximum score); crumb grain, 10 (alveolus size and shape); aroma, 15 (fresh breadlike); and taste, 20 (flavour and mouth feeling). Bread score was qualified as follows: Excellent (90–100), very good (80–89), good (70–79), acceptable (60–69), poor (50–59), very poor (40–49), extremely poor (30–39). Crumb grain was also analysed alone, as crumb grain score with a maximum point value of 10. Experimental Design Five responses were measured: batter softness (Y1), specific volume (Y2), crumb grain score (Y3), bread score (Y4) and bread protein content (Y5). Variables chosen were soy flour percentage (X1) and dry milk percentage (X2); both ranged between 2 and 12% (central point, 7%). Each variable to be optimized was coded at five levels: 1.41421, 1, 0, 1 and 1.41421 (Table 1). Selection of level extremes was based on previous studies. A central composite design (Table 2) Table 1. Central composite design – variables and levels.
Methods Coded Variable Levels
Consistency Measurement Batter consistency was measured as softness at the end of mixing. A sample of this batter was put into a glass vessel of 10 cm diameter and 4 cm height. Then a cone penetrometer for three seconds was used. The measurement range was 0–400 penetration units. Higher penetration units indicate increased batter softness.
Variable % Soy flour % Dry milk
The loaves obtained in experimental baking tests were subjected to scoring to determine their physical characteristics on a comparative basis. Experts in a number of three, scored the individual characteristics of the loaf which were related to those of a hypothetical standard loaf. Each sample was served as slices at the same time,
X1 X2
2 2
1
0
1
1.41421
3.5 3.5
7 7
10.5 10.5
12 12
Responsesa
Coded Variable Levels Run
Sensory Analysis
1.41421
Table 2. Central composite design – arrangement and responses.
Volume Measurement and Protein Determination Specific bread volume (cm3/g) was determined 60 min after baking by millet-seed displacement. Protein determination of bread (% dry basis) was done by AACC Method 46 - 11A (AACC, 1983).
Symbol
1 2 3 4 5 6 7 8 9 10 11 12
X1
X2
Y1
Y2
Y3
Y4
Y5
1 1.41421 þ1 0 0 0 þ1.41421 1 0 0 þ1 0
þ1 0 þ1 0 0 1.41421 0 1 0 0 1 þ1.41421
170 210 165 160 170 165 165 175 175 160 120 165
3.61 4.20 3.38 3.73 3.68 4.26 3.13 4.28 3.67 3.82 3.58 3.21
8 8 7 8 8 8 7 8 8 8 8 8
80 79 72 75 75 82 64 79 75 75 70 77
5.9 4.2 9.2 6.5 6.5 5.1 8.9 3.9 6.5 6.5 7.2 7.9
a Y1 ¼ batter softness (penetration units); Y2 ¼ specific volume (cm3/g); Y3 ¼ crumb grain score (max. 10); Y4 ¼ bread score (max. 100); Y5 ¼ bread protein content (% d. b.).
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Gluten-free Bread Fortified with Soy Flour and Dry Milk
was arranged to fit second-order model. The star points were added to the factorial design to estimate the curvature of the model (Montgomery, 1991). Four replicates (runs 4, 6, 9, 10) at the centre of the design were used to estimate the sum of the squares error. Statistical Analysis A software package (STATGRAPHICS) was used to fit second-order models and generate response surface plots. The model proposed for each response is given by the following expression: Y ¼ b0 þ b1 X1 þ b2 X2 þ b11 X12 þ b22 X22 þ b12 X1 X2 ð1Þ where b0 is the value of the fitted response at the centre point of the design [point (0,0)]; b1 and b2 are linear regression terms; b11 and b22 are quadratic regression terms; and b12 is the cross-product regression term (Montgomery, 1991).
RESULTS AND DISCUSSION Changes in mixture consistency produced by soy flour (X1), measured in batter penetration units, were significant (Tables 2 and 3). Other variables such as X2, X12 , X22 and X1 X2 produced no significant effect on that response. Relative to specific volume, a significant effect is exhibited by soy flour (X1) and dry milk (X2); Samples had no large holes in the crumb structure, which would have caused large changes in specific volume. Polynomial coefficients for the second-order equation (Table 4) showed the relative importance of each variable. Almost all variables had significant effects on crumb grain score and bread score. Batter softness (Y1) decreased (batter consistency increased) when soy flour was added to the mixture, mainly at low levels of dry milk (Figure 1). When high levels of soy flour were used,
however, batter softness increased because of the increased dry milk added to the mixture. Sa´nchez et al. (1998) found that soy flour increases farinograph water absorption while milk proteins decrease water absorption. The specific volume of bread (Y2) diminished by the addition of soy flour and dry milk (Figure 2(a)). This reduction could be caused by the crumb structure modification due to partial starch substitution, indicating a dilution of the gel formed by the starch–gum system. Each ingredient added separately had a significant effect, but no synergism existed when they were used together (see Table 3, variable X1 X2). Response surface for crumb grain score (Y3) (Figure 2(b)) and bread score (Y4) (Figure 2(c)) indicated that optimal crumb grain and bread score can be obtained with high dry milk and low soy flour content in the mixture. As expected, bread with the highest protein content resulted from the use of maximum soy flour and dry milk in the mixture (Figure 3). Evaluation of response surface contour plots revealed the following observations: (i) Bread with the highest protein content (Y5 ¼ 10%) contained 11.5% soy flour and 11.5% dry milk (Figure 4(a)). Specific volume, Y2
