The Nutritional Benefits and Bread Making Process

Nutritional Benefits Of Bread

Bread is a staple food used by several households across the world. It is one the mostly consumed food with many individuals often consuming it on a daily basis. It is among the most predominant food preparations ever and its preparation procedure has evolved for many decades from the traditional methods of preparing loaves in artisan and home-made wood-fired ovens modern automated systems for mass production (Peyronnard & Benzaazoua, 2012). The progress has brought about standardization of bread reparation process while also improving the bread features that meet the sensory needs for a wide customer base.

Fiber contains fiber- various bread products possess different amounts of fiber and there is generally at least a gram per serving. This makes it an essential nutrient for those who take bread daily. Fiber is mostly known to be keeping the digestive system moving, and does a lot more than that. Fiber is a feel fuller. Whenever the body operates to break down food possessing fiber, one always feels fuller longer. This could help one prevent overacting in one eating or sitting too much throughout the day. Several types of fiber with this can be helpful in losing weight. Fiber can also be used in managing blood sugar. High presence of fiber in bread indicates reduced glycemic index (GI), which is a rating that reflects how foods affect blood sugar (Pouliou & Besseris, 2013). Bread will always have insoluble fiber that originates from sources such as wheat flour. Considering the body cannot break own and absorb this form of fiber, it often remains intact, assisting in sweeping through the digestive system. There are bread ingredients that contains soluble fiber such as barley and oats that dissolve into a gel in water and helps in reducing cholesterol and blood sugar levels.

Prebiotic effect- this nutritional benefit is brought by fiber that acts as a prebiotic. Our bodies contain helpful bacteria referred to as probiotics that help protect the body and digestive systems from harmful fungi or bacteria. They consume prebiotics that originates from fiber and carbs acquired when eating bread (Krishnamoorthy & Kapadia, 2011). The body is thus maintained in a healthy balance. They also help the functions of our immune system, and manages obesity and depression symptoms

Protein- proper dietary recommendations suggest that one should consume at least 0.36 times your body weight in pounds of protein a day. Besides not containing a lot of protein, bread is a low-fat means of achieving our daily protein objectives. Achieving enough protein in the body can help lower our appetite, raise the muscle mass, and maintain bone health. Proteins helps lower the ghrelin hormone, which is the hunger hormone. It is also important for building and promoting muscle strength and mass (Roy, 2015). Proteins will also help avoid fractures and other related concerns by one’s body mass as they grow. Bread ensures we acquire these benefits. Its source of protein is mostly vegan and vegetarian friendly.

Bread Making Process

Traditionally, bread processing involved evaluating the effort of makeup or molding stages of dough in the manufacture of bread. Currently, it is used to describe the overall process of manufacturing buns and breads. In involves several steps such as mixing, fermentation, makeup, baking, proofing, cooling, and packaging (Besseris, 2018). Owing to their critical role, the processes should be managed properly to ensure the pre-set specifications and conditions are attained.

Weighing and mixing- the manufacturing process starts by mixing the ingredients. Wheat flour, water, yeast, salt and optionally sugar, emulsifiers and fat are mixed together in a desired proportion. The production of a white or brown bread depends on the meal/flower ratio. Wholegrain bread is prepared with only meal whereas white bread only uses flour. Considering that flour tends to absorb a lot of water than meal, when there is high quantity of flour, more water must be added to the mix (Sihombing et al, 2012). It is proper to ensure that the yeast does not get into contact with the salt during the mixing process to prevent deactivation of the yeast. Additives and preservatives are too added to improve flavor, texture, and shelf life of the bread.

Kneading- the dough is then kneaded after all the ingredients have been properly mixed. Kneading ensures formation of the network of gluten and creation of air bubbles, where there is accumulation of carbon dioxide that is formed by fermentation. The dough becomes elastic due to the ingredients ability to absorb moisture (Kumar et al, 2015). The kneading should ensure the dough structure is strong enough for the formation of a wafer-thin film. The dough temperature rises during this process to 27°C.

Proofing- this stage ensures putting the dough into a machine for about 30 to 50 minutes and at a steady 27°C temperature. It provides more time for the yeast to multiply, generate alcohol and C02. The outcome is a bigger size of the dough. The gluten network also gets highly elastic again. The process is completed once the dough becomes almost double in size.

Folding/ rising- following the first proofing, the dough is divided into smaller pieces of dough weighing a given number of grams. They are then folded using the folding machine and out in nets within the proffer. Folding ensures even distribution of the gas bubbles and attainment of a similar shape for the dough. The dough surface is also smoothened and its stickiness reduced. The dough rising often takes about 30 minutes, at a constant temperature of 34°C and 85% humidity.

Design Of Experiments (DoE)

Shaping- involves shaping the dough in a baking tin. Optional decoration of the bead is also conducted here

Final proof- occurs within the baking tin and takes about an hour at a temperature of 34°C and 85% humidity. The temperature develops a roper environment for mesophilic micro-organisms growth. The process should take place within a hygienic and clean environment.

Baking- once the dough has risen enough, it is then baked for about 30 to 40 minutes at 200°C to 260°C temperature. Steam is initially injected into the oven that ensures the dough does not form a tough outer layer immediately (Blackhall et al, 2016).

Cooling and packaging- cooling before packaging helps prevent condensation within the bag.

DoE involves a smart technique of statistically analyzing and validating combination of factors. It can be achieved by a few experiments and can be applied in all types of production processes. Making improvements in processes and products can be quite challenging. The most appropriate way of achieving reliability and quality is to eradicate defects in products (Shmal'ko & Smirnov, 2018). DoE carries out simultaneous assessments of two or more parameters on their ability to impact the resultant variability or average of a given product or process features. The object of the experimental design is to reduce the number of experiments needed to recognize the causes that are highly associated to the essential effects (Sanusi et al, 2020). The levels of the factors are arranged in a strategic manner, the outcomes observed, and analysis of the outcomes done to establish the most impactful factors and desired levels. It is the most viable and accepted tool for developing universally competitive processes and products.

Application of process optimization and engineering has generated massive improvements in bread mixing process. The optimization process does not have to stop at the quality control section to obtain the complete range of benefits (Volkova et al, 2020). Recent proposals for scientific ingredient evaluations have led to significant improvements in the molding process. The most significant steps that be considered by mixers to successfully adopt DoE include; planning, deciding an orthogonal array, carrying out the experiment, evaluating the outcomes, and confirming the results (BaÅŸataç et al, 2022). There has also been a mixing control system that led to improved turnaround, greater quality, and reduced costs for revising a design and recommissioning a mixing machine. DoE has been specifically responsible for resolving challenges in processing environments. There has been various home-grown software used in conducting most of the statistical analysis related with DoE.

Bakery products prepared from amaranth plant have always indicated diversified nutritional value and flavor. Amaranth plant, seeds and flour has several nutritious values. It produces seeds fully packed with nutrients and proteins. Its seeds contain higher protein than oats and are full of calcium, iron, zinc, magnesium, and vitamin B. this makes it a healthy bread recipe for everyone (Salcido, 2019). This study focuses on a new bakery product, Amaranth bread. To improve the nutritional content of the bread, walnuts and pumpkin seeds are also added. The amaranth bread is developed through Taguchi approach which is used to optimize the baking ingredients (product development). The following five factors were selected to for the Taguchi experiment design; amaranth sourdough (A), walnuts (B), pumpkin seeds (C), type of liquid (D) and white bread flour (E).

The Taguchi method is a systematic technique for design and analysis. The method has gained a lot of popularity over the years and has been adopted in several industries and sectors for quality development and product development in an economical way. With this approach, an orthogonal array is initially constructed by assigning assumed or known noise or control factors (Yang, 2016). The orthogonal array is represented by L_n (X^m), where n is the array columns, that is, the number of parameters and level combinations. X represents the number of levels and m the number of rows within the array, that is, the number of factors. This study adopted an orthogonal array presented by L₁₆(4⁵). This implies that it had five control factors with four levels in sixteen bakery product experiment. The five control factors adopted in this study include amaranth sourdough (A), walnuts (B), pumpkin seeds (C), type of liquid (D) and white bread flour (E). The ratio of the formula was set at four levels for every control factor. Other common ingredients used were oil, fresh yeast, egg, honey, and salt. The chosen orthogonal array and factor level assignments are presented in the table below;

Table 1: parameter design levels and factors

Factors/ level	1	2	3	4
A Amaranth sourdough	10%	20%	30%	40%
B Walnuts	1%	1.5%	2%	2.5%
C Pumpkin seeds	1%	1.5%	2%	2.5%
D Water/ milk	Distilled water	Fresh Milk	Sour cream	Coconut milk
E White bread flour	10%	12%	14%	16%
*Other common ingredients used were oil, fresh yeast, egg, honey, and salt.

Dependent variables included information retrieved from the evaluation of texture profile, color evaluation, and sensory analysis. The analysis for texture profile involved the product chewiness, brittleness, gumminess, cohesiveness and springiness.  The sensory analysis involved overall acceptance, sourness, appearance, sourness, aroma, chewiness, and bitterness (CoÅ£ovanu & Mironeasa, 2022). Taguchi analysis will be used to assess the optimal conditions dependent on the above stated factors and ultimately highlight the importance of this inventive optimization procedure.

Determination of signal-to-noise-ratio values

Experimental values from the several quality characteristics within the orthogonal table were applied to establish the signal to noise ratio (S/N ratio, η). This ratio developed a transformation function of the repetition data to another vale and was adopted as a measure of the variation available in the experiment. The S/N ration represents a function indicator that establishes performance. Higher S/N values represents smaller quality losses (Parenti et al, 2020).  This study focused on establishing the optimal operational features for the production of amaranth bread retaining supple flavors, nutrients and taste. It adopted the larger-the-best function to establish the S/N ratio using the formula;

Where; n represents the number of trials, y_i represents the i^th value of the quality attribute.

This study adopted an orthogonal array presented by L₁₆(4⁵). This implies it had four levels for each of the five control factors resulting to 16 bakery product experiments. After setting the four levels/ ration of formula and the common ingredients as provided in table 1 above, the orthogonal array and factor or level assignments are as shown below;

Factor/ level	(Amaranth Sourdough)	(Walnuts)	(Pumpkin Seeds)	(Water/ Milk)	(White bread Flour)
1	10 (1)	300 (1)	7.5 (1)	1125 (1)	10 (1)
2	10 (1)	500 (2)	15 (2)	1150 (2)	15 (2)
3	10 (1)	700 (3)	22.5 (3)	1175 (3)	20 (3)
4	10 (1)	900 (4)	30 (4)	1200 (4)	25 (4)
5	20 (2)	300 (1)	15 (2)	1175 (3)	25 (4)
6	20 (2)	500 (2)	7.5 (1)	1200 (4)	20 (3)
7	20 (2)	700 (3)	30 (4)	1125 (1)	15 (2)
8	20 (2)	900 (4)	22.5 (3)	1150 (2)	10 (1)
9	30 (3)	300 (1)	22.5 (3)	1200 (4)	15 (2)
10	30 (3)	500 (2)	30 (4)	1175 (3)	10 (1)
11	30 (3)	700 (3)	7.5 (1)	1150 (2)	25 (4)
12	30 (3)	900 (4)	15 (2)	1125 (1)	20 (3)
13	40 (4)	300 (1)	30 (4)	1150 (2)	20 (3)
14	40 (4)	500 (2)	22. (3)	1125 (1)	25 (4)
15	40 (4)	700 (3)	15 (2)	1200 (4)	10 (1)
16	40 (4)	900 (4)	7.5 (1)	1175 (3)	15 (2)

 Table 2:  L16 (45) orthogonal array and factor level assignments (Kinner et al, 2011)

The experimentation bean by first establishing the potential significant factors that can impact the quality of bread bakery and were further adopted for the experimental design. The factors were used in preparing the new product, amaranth bread. The five selected factors included the inclusion or non-inclusion of amaranth sourdough, walnuts, pumpkin seeds, water or milk product, and white bread flour. Assessments were conducted to prepare an experiment with an established number of tests and distinct ranges for every test.

The seven-point scale measure is an appropriate tool for evaluating the overall acceptability of the amaranth bread. The test was conducted on 60 participants randomly chosen within the university. The score sheets involved four categories of sensory attributes namely overall acceptability, texture/ chewiness, smell/taste, and appearance. Every item is scored between 1 and 7. (1: dislike extremely, 2: dislike moderately, 3: dislike slightly, 4: neither like nor dislike, 5: like slightly, 6: like moderately, 7: like extremely). All the bread samples are scored one by one for aroma, chewiness, sourness, bitterness, and overall acceptability. The sensory evaluation tests are conducted in triplicate (n=3), implying all the participants will have to do the tests three times on three different days. The final score is then calculated and acquired by averaging the three-replicate data. Sensory evaluation of the bread samples was conducted using raw sensory information retrieved from questionnaires.  The results will establish the trial number that received consistent higher scores on the sensory attributes.

The study involved preparing 16 round-top amaranth sliced bread samples through various formula dependent on the L16 (4⁵) factor level assignments and orthogonal array as presented above. The samples are numbered from 1 to 16.  Up to 16 different bakery experiments were carried out. In every experiment, the quantities and combinations of the ingredients were varied. Thus, every experiment is based on the combination of level values as indicated in the orthogonal array table (Kamoto et al, 2018). For instance, the eighth experiment is carried out by keeping the independent design variable A at level 2, variable B at level 4, variable C at level 3, variable D at level 2, and variable E at level 1.

The SN is determined for every experiment that was carried out. The average SN ratio value for every factor is also calculated. The outcome enables determination of the effect of each of the five factors. We are therefore able o establish which factor or component has the greatest or least effect on the product outcome (Parenti et al, 2020). There is also need to determine the bread shelf life. To achieve this, the individual effect of the factors (independent variable) is first segregated considering that every experiment represents the combination of various factors levels. The performance parameter values for the corresponding level settings are summed up. Several other nutritional aspects and parameters for this innovating bread product can still be suggested for more studies (Rødbotten et al, 2015). For instance, other ingredients that can be included in the above setup include amaranth porridge made of amaranth seeds and water, and rice flour mainly for dusting (Bhol & Bosco, 2014). The Taguchi method allows experimentation of several parameters in a bid to achieve the best quality for the product.

The approach focuses on a mean performance feature value close to the target value instead of a value within distinct specification limits, which helps in improving the quality of the product. The approach is generally straightforward and easy in several product development scenarios. The approach can be adopted to quickly narrow down a research project scope and point out concerns within the product development process from already existing information. It also enables the evaluation of several different parameters without conducting several experimentations (Lee & Joo, 2012). It identifies the vital parameters that have the greatest impact on the performance feature value hence further experimentation of the parameters can be conducted while ignoring the parameters with minimal impact. It considers the design phase as the most critical and provides a means of developing effective and reliable products as it eradicates variances in the production before they happen (Flander et al, 2017). The approach is important in reducing costs, presenting robust design solutions and improving quality.

The outcomes achieved are only relative and never indicate the parameter with the greatest impact on the performance characteristic value. Besides, considering that the orthogonal arrays do not experiment all variable combinations, the approach is not appropriate when all relationships between the variables are required (Pojić et al, 2017). The approach is generally concerned with designing a product for quality and does not handle the correction of poor quality. The approach is often adopted during the initial stages of the product development (Abd-El-Khalek, 2020).

Conclusion

The general evaluation of the bread taste can be used to establish the most influential factor that determines the bread taste of the innovative product. The Taguchi approach can be adopted in investigating the impact of processing parameters on the quality of amaranth bread as well as the optimal features for preparing the new bakery items when several parameters are used. The innovative product is developed mainly for economic purposes and thus, the several parameters of the breads such as texture, taste, color, aroma etc. are quite significant to the end consumers. Currently, there have little systematic approaches put in place in the bakery industry to help that can manage several parameters when developing new bread products. Thus, the Taguchi experimentation method described in this study emerges as a prospective optimization approach that can be used in the development of new products. Taguchi method can also offer a reference of foundation for the improvement of consumer-focused items within the bakery industry. The application can be used as a reference for enhancing the quality of dread products. The achieved bread product in this study has massive potential for commercial production due to the economic and nutritional importance that it possesses.

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