SYNCHRONIZATION IN CHAOTIC SYSTEMS

Abstract-- Sugar mixtures with different types are commonly used in biscuit formulation. This study investigates the mixture of crystal sucrose (CS) and fine sucrose (FS) for the quality of biscuits in terms of rheological, sensorial and physical properties. Mixture design approach was also used and the effect of model was significant for all dependent variables such as Tan δ in rheological, hardness and spread ratio (SR) in physical, general acceptability in sensorial analysis. With CS decrement in the formulation, a reduction was observed for Tan δ values. High level replacement of CS with FS (from 50% to 100%) causes dramatic increase in SR values of biscuits. Decreasing the replacement level of CS increased the hardness value of biscuits. The results of this study showed that the type of sucrose and the mixing ratio can significantly affect the physicochemical and sensory quality of the biscuit. The biscuit sample containing the 90% FS and 10% CS obtained the highest score for hardness, crispness, and general acceptability.

Keywords-- Fine sucrose, crystal sucrose, biscuit quality, mixture optimal design, rheology.

I. INTRODUCTION

Biscuits have a wide popularity since having a variety of flavors compared to other bakery products, easy availability with an affordable cost and longer shelf life. Short dough biscuits contain three main ingredients: fat, sugar, and water, in addition to flour (Laguna et al., 2013; Panghal et al., 2018). Soft wheat flour is commonly used to make biscuits because it produces biscuits with the acceptable spread and surface characteristics, as well as greater crispiness and a softer bite (Panghal, 2011). Biscuits are usually high in fat and sugar while having a limited amount of water. The sugar content of biscuits varies between 10% and 30% and influences the final product quality parameters such as taste, flavor, texture and spread ratio (Sahin et al., 2019). In the biscuit making process, the type and the amount of the sugar have a considerable effect from mixing to baking. According to Gallagher et al. (2003), sugar competes with flour for available water during the mixing process to prevent gluten development. In the baking stage, sugar plays a role in starch gelatinization, Maillard reaction and surface characteristics (Kulp et al., 1991, Laguna et al., 2013).

The effects of sugar used in biscuit may differ when they are used different combination of sugar types. Kweon et al. (2009) reported that sugar type could transform the baking performance of a biscuit flour from an excellent quality to a poor quality. Moreover, the gelatinization temperature of starch is increased by all sugars but the degree of increment is mostly related to sugar types. The main type of sugar utilizing in biscuit formulation is sucrose. The particle size (PS) of the crystal sugar is also another important factor for biscuit making. A study which was conducted to explore sugar functionality for two different crystal sizes of sugar showed that larger PS cause a reduction in biscuit spread ratio due to more development of gluten (Kweon et al., 2009).

Many studies have been carried out to understand the functionality of the sugars, especially sucrose, fructose, glucose, xylose (Kweon et al., 2009) and some polyols (Laguna et al., 2013) in biscuit formulation. However, the individual and combined effect of crystal sucrose (CS) and fine sucrose (FS) on biscuit formulation is lacking even though they are mostly included in the formulation. In this study, investigation of the effect of CS and FS on rheological properties of biscuit dough, sensorial and quality characteristics of biscuits was performed. Mixture optimal design (MOD) approach was also used in order to find the optimum amount of sucrose mixtures in biscuit formulation.

II. METHODS

A. Materials

Biscuit ingredients used in this study were; wheat flour, suitable for biscuit making (14.2% moisture and 56.2% water absorption); shortening (free fatty acid content, max.0.4); crystal sucrose (particle size from 450 to 800 µm); fine sucrose (particle size from 80 to 120 µm). These ingredients were obtained from Elvan Food Company (İstanbul, Turkey).

B. Methods

Experimental Design and Biscuit Formulation

The ingredients in biscuit formulation were as follows: 37% flour, 25% margarine, 3.40% maize starch, 0.40% lecithin, 1.00% fructose syrup, 0.6% baking powder, 0.20% salt, 0.20% vanilla, necessity amount of water, and sucrose 23.50% (crystal sucrose, fine sucrose or mixture of them). Crystal sucrose was replaced with fine sucrose at different levels (%) in the formulations. The formulation codes and replacements levels (%) were shown in Table 1. Preparation of biscuits was performed according to the method described by Laguna et al. (2013).

Table 1. Biscuit formulation (%)

Formulation Code	Fine Sucrose (FS)	Crystal Sucrose (CS)
F1	0	100
F2	10	90
F3	25	75
F4	50	50
F5	75	25
F6	90	10
F7	100	0
F8	50	50
F9	50	50

Process Optimization

Process optimization was performed using Mixture optimal design (MOD) for obtaining the highest sensorial score. Crystal sucrose and fine sucrose selected as mixture parameters while general sensory score, hardness, spread ratio and Tan δ value were selected as response variables.

Two-factor Mixture Optimal Design including 3 center points were performed in the study to determine optimum sucrose mixture. Nine experimental points (Table 2) set by the use of the Design Expert software (Version7 Stat-Easy Co., Minneapolis, MN, USA).

In the MOD, backward elimination procedure was carried out to remove insignificant model terms (P > 0.05) to simplify the models to be established. A quadratic model type was used in response part of the design. Model acceptability was evaluated according to the R² values and adj R².

Rheological Properties of Biscuit Dough

A stress/strain-controlled rheometer (Anton Paar MCR 302, Australia) equipped with parallel plate configuration at 25 °C was used for dynamic rheological measurements of biscuit dough. Determination of the linear viscoelastic region (LVR) was carried out between 0.1 and 100% strain values at 1 Hz. The strain value of LVR was selected as 0.2% applied at the frequency sweep test. A frequency range of 0.1-30 Hz was used with a 2 mm gap. Storage modulus () and loss modulus () were calculated according to the following Eqs. 1 and 2 (Yoo and Rao, 1996). Tan δ values (/) were also calculated in order to determine the proportions of viscous and elastic parts in a dough system.

(1)

(2)

Spread Ratio

Electronic caliper (0.001 mm, Mitutoyo, Tokyo, Japan) was used to measure the diameter and thickness of biscuits. Spread ratio (SR) was calculated by dividing the diameter by thickness. Three biscuits were analyzed to calculate a mean value.

Texture Measurements

The hardness of the biscuits was measured in grams using a Brookfield brand CT3 model device (Brookfield, Massachusetts, USA) and knife-shaped probe (TA7 blade). Biscuit samples was placed horizontally in a platform and hardness value (g) was determined as follows: pretest speed of 2.0 mm. s^-1, test speed of 5.0 mm. s^-1, trigger force of 0.07 N and distance of 8.0 mm (Cervejeira Bolanho et al., 2014).

Color Measurement

Color lightness (L), redness (a), and yellowness (b) values of the biscuits were determined by using Minolta Chromameter (CR-400 Konica, Japan). Calibration was carried out by standard illuminant (D65). Triplicate measurements were performed.

Sensory Analysis

Sensorial evaluation of the biscuit samples was performed by the experienced and professional team of Elvan Food Ind. Co. The total 7 panelists aged 24-40 years old were carried out sensory analysis. The sensory attributes were determined as hardness, crispness, sweet taste, and general acceptability using a hedonic scale from 0 to 9 (1: extremely dislike, 5: neither like nor dislike, 9: extremely like).

Statistical Analysis

All analysis was carried out in triplicate and values expressed as mean. Design expert software, v7 (Stat-Ease, Minneapolis, MN), was used to specified regression and variance analysis (ANOVA) of experimental points. The effects of the dependent variables on the responses were assessed by quadratic models and response surface plots. The model practically was determined by Regression coefficient (β), coefficient of determination (R2) and F test value of predicted, the lack of fit test, and model p-value (p< 0.05). The statistical analysis was performed using the Statistica software program (StatSoft, Inc., Tulsa, OK). ANOVA was used to determine the differences between samples. Duncan, multiple comparison tests at 95% significance level was performed to evaluate effect of sucrose type on color values of the biscuit samples.

III. RESULTS AND DISCUSSIONS

Rheological Properties of Biscuit Dough

The effect of crystal sucrose (CS) replacement with fine sucrose (FS) on the storage modulus () and loss modulus () was shown in Fig. 1.

All biscuit dough samples showed typical viscoelastic properties since the value of was lower than the value of . With the crystal sucrose decrement, a reduction was observed for both moduli (, ) (Fig. 1). This reduction was also shown for Tan δ values (Table 2), meaning more dominant elastic matrix except for low level replacement of FS (F1 and F2). Gluten development in biscuit dough can cause increased elasticity (Pareyt et al., 2008; Laguna et al., 2013). Tan δ was also kept constant from the addition of 50% FS to the inclusion of 90% FS (F4, F5, F6) (Table 2). It can be shown that there are no structural alterations in these biscuit doughs since Tan δ value is also an indicator of the molecular interactions in a material (Ahmed, 2015). Tan δ value of the sample with 100% FS addition (F7) was the lowest (Table 2), indicating that well-developed gluten network in biscuit dough would lead to more elastic properties (Zhang et al., 2020; Bigne et al., 2021).

Quality Characteristics of Biscuits

Spread Ratio

The shape characteristics of the biscuits are explained by spread ratio (SR). The diameter to thickness ratio of biscuits is known as the spread ratio. Taylor et al. (2008) explained that diameter of biscuits was related to sucrose dissolution and height of biscuits was related to inhibiting gluten development. Thus, SR is the combination of these two parameters. Table 2 shows SR values of biscuit samples as a response of mixture design. The biscuits containing low level FS (F1, F2, F3) have a lower SR value than the biscuits containing high level FS (F5, F6, F7). High level replacement of CS with FS caused a dramatic increase in SR values (from F4 to F7). This can be due to the reduction of particle size of sucrose mixture containing CS and FS. Similar results were also observed in a study which investigated the effect of different sucrose granule sizes on the sensory and physical properties of shortbread biscuits. The samples including 100% sucrose with a finest granule size showed highest diameter and lowest thickness (Tyuftin et al., 2021). Boz (2019) also stated that SR of the cookie samples increased with the decrease in particle sizes of sucrose. The highest SR value was found in the cookie samples containing sucrose particle size between 150–180 μm (Boz, 2019). According to Kweon et al. (2009), the biscuits containing sucrose with large particle size have lower spread ratio due to the delaying effect of sucrose dissolution.

Textural Properties

Hardness (g) values of biscuit samples are presented in Table 2. The hardness (g) of the samples varied between 1977 g and 2794 g. Decreasing the particle size by the replacement of CS with FS increased the hardness value (g) of the biscuits especially in the samples F5, F6, and F7 (Table 2). This increment can be explained by the competition between sucrose and gluten for available water. When gluten competes with less sucrose or sucrose having a less particle size, strong gluten network is formed. Therefore, fracture strength increases for the biscuit samples (Tyuftin et al., 2021; Pareyt et al. 2008). Similar observations were reported by Boz (2019) who described that the hardness values of the cookie samples increased with the decrease in the particle size of sucrose. The hardness increase for sample F7 containing 100% FS was also in accordance with the Tan δ value of this sample (Table 2). This also indicates more gluten development when compared to the samples replaced by CS with low level (F1, F2, and F3).

Color Properties

Instrumental results of color characteristics (L, a, b) are shown in Table 3 and the images of biscuits are presented in Fig. 2. The samples F5, F6, and F7 obtained significantly higher L (lightness) value than the samples F1, F2, F3, and F4, which means these samples were significantly lighter (P < 0.05). Color redness (a value) de-

Table 3. Color values of biscuit samples

	L	a	b
F1	52.38±0.01^f	13.40±0.01^a	35.98±0.03^f
F2	54.60±0.01^d	12.92±0.05^c	36.98±0.03^b
F3	53.23±0.01^e	12.62±0.03^d	36.29±0.01^d
F4	52.16±0.01^g	13.06±0.03^b	36.57±0.03^c
F5	54.72±0.01^c	12.36±0.02^e	37.24±0.02^a
F6	68.57±0.06^a	6.03±0.01^g	33.34±0.02^g
F7	59.25±0.00^b	10.74±0.02^f	36.10±0.02^e

a-g Mean values in the same column bearing different superscripts are significantly different (P < 0.05)

Figure 3. Sensorial evaluation of biscuit samples

creased significantly after the replacement of crystal sucrose (CS) with 50% fine sucrose (FS) (Table 3). These results indicated that CS contributes more to Maillard browning reactions. In a study conducted by Tyuftin et al. (2021), a significantly lower L* value was observed for the biscuit formulation containing 100% fine sucrose (124 to 179 μm). In this study, reducing the particle size resulted in increasing L value by the substitution of 90% FS (Table 3). However, a clear trend was not observed for b (yellowness) value of the biscuits.

Sensorial Evaluation of Biscuit Samples

The results of sensory attributes of biscuit samples are shown in Table 2 and Fig. 3. The biscuit sample containing the 90% FS and 10% CS (F6) obtained the highest score for hardness, crispness, and general acceptability (Fig.3). The hardness and crispness values of this sample (F6) were found to be compatible with each other. These findings are in agreement with Boz (2019) who presented that the most favoured formulations were identified as the formulations containing finer sucrose particle size (150 µm).

The lowest score was observed for the sample F1 containing 100% CS for the hardness and crispness parameters. This sample also obtained the lowest score for general acceptability and sweet taste parameter. For the sweet taste, the highest score was observed for samples F5 (25% CS + 75% FS).

Model parameters on response and formulation optimization

The mixture optimal design was used in order to find the optimum sucrose mixing ratio. A quadratic model was used to determine the effect of different sucrose types on the overall sensory scores, hardness, spread ratio of biscuit and dynamic rheological properties of the biscuit dough.

In Table 4, the statistical results of the quadratic model parameters are shown. The model p value was lower than 0.01 for all responses, indicating that sucrose type and mixing ratio significantly affected all responses shown in Table 4. For the sensory response, both linear and interaction were significant. This result shows that sucrose types and their mixing ratio were significant in their interactions as well as their linear effects. In other responses, interaction values were found to be insignificant. In addition, it was observed that the quadratic effect was significant for the quadratic model parameters for Tan δ value. Since the lack of fit value was insignificant, the linear and interaction values were found to be important, and the maximum peak was formed, the sensory score value was used to determine the optimum formulation. 73.81 FS and 26.19 CS were determined as the optimum sucrose mixture formulation based on the maximum sensorial scores.

As can be seen in Fig. 4a, the sensory score value increased as the FS ratio increased and the peak was observed at about 75 % FS ratio. After peak point, the sensory score decreased. This result shows that sensory score can be used to determine the optimum sucrose ratio. In Fig. 4b, the effect of sucrose mixture ratio on the hardness value is shown. As seen in the figure, the increase in the FS ratio in the mixture caused an increase in the hardness value. Figure 4c presented the effect of sucrose mixing ratio on the spread ratio. As with the hardness value, the SR value increased with increasing of the FS ratio in the mixture. Figure 4d depicted the effect of different sucrose types on the dynamic rheological properties of biscuit dough. As the FS ratio increased, at the low FS concentration the decrease in Tan δ value was observed and a second peak was observed at 75% FS. A rapid decrease in Tan δ value was observed in the use of 100% F.

IV. CONCLUSION

This study described the role of crystal sucrose, fine sucrose and their mixture in the biscuit formulation using mixture design. The results obtained from mixture design

indicated that replacement of crystal sucrose with fine sucrose increased the hardness and spread ratio of biscuits while decreasing the Tan δ value. The results of this study showed that the type of sucrose and the mixing ratio could significantly affect the physicochemical and sensory quality of the biscuit. The mixture of 73.81% fine sucrose and 26.19% crystal sucrose obtained the highest score for general acceptability in the sensorial evaluation. This finding promotes the use of this sucrose mixture in the biscuit formulation and may be useful for the reduction of sucrose content in biscuit.

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Received: September 27, 2021

Sent to Subject Editor: November 20, 2021

Accepted: April 15, 2022

Recommended by Subject Editor Maria Laura Foresti