Optimization of Fermentable Sugars Production from Stale Bread using Response Surface Methodology

Food waste and loss has become a global problem in recent years. According to FAO (2013), every year, a third of the total amount of food produced for human use, around 1.3 billion tons, is lost or wasted. A significant part of wasted food is cereals and bakery by-products (Xue et al., 2017).
       
Bread is a staple food in many cultures around the world and is the most widely consumed floury product. However, the amount of bread wasted each day around the world throughout in life cycle, from production to distribution, is expected to be hundreds of tons, presenting both economic and environmental concerns (Gül et al., 2003; Verni et al., 2020). Despite the use of a small portion of bread waste for animal feed, the majority ends up in landfills.
       
Bread is an important source of energy due to its high content of easily digestible starch (39.3 to 42.7 g/100 g), making it a potential bio-resource for the production of fermentable sugars that are precursors to valuable bio-products through the fermentation process (Mckevith, 2004; Sükrü Demirci et al., 2017). As a result, bread waste provides an important fact as a potential carbon source for innovative industrial processes and several alternative pathways to utilize bread waste have been developed (Narisetty et al., 2021). The production of nutrient rich hydrolysate from bread waste involves the use of commercial enzymes that can be very expensive (Melikoglu and Webb, 2013).
       
Among cereals, barley possesses the highest diastasic activity when it is properly germinated. The most important physiological processes associated with the germination phase are the synthesis of amylases, proteases and other endogenous hydrolytic enzymes (Gebeyaw, 2021; Serna-Saldivar, 2012; Baranwal, 2017).
               
The objective of this study was to investigate the effect of malted barley as substitute for commercial enzyme for the production of fermentable sugars from stale bread, as well as to optimize the hydrolysis conditions using response surface methodology.

The experiment was conducted at LAPAPEZA laboratory, Institute of Veterinary Sciences and Agricultural Sciences, University of Batna 1 in March 2022.
       
Stale bread (without mold spoilage sign) was obtained from local bakeries in Collo (Skikda province, Algeria) as shown in Fig 1. It was sundried on aluminum trays for 7 days and grounded using laboratory hammer mill. The obtained stale bread powder (SBP) with particles size below 1 mm was stored in hermetic plastic bottles at 4°C. SBP has 6.56± 0.2% of moisture content, 58.56±0.7% of starch and 1.37± 0.01% of total sugars determined in triplicate according to AACC method 44-15A (AACC, 2000), Ewers polarimetric method whereas the starch is released from the sample by boiling in dilute hydrochloric acid HCl (ISO, 1997) and Anthrone assay (Laurentin et al., 2003) respectively.
 

       
Barley grains were purchased from local market (Collo, Algeria), cleaned, washed and dried.
       
A sample of 1 kg barley grains were soaked in water (1:3 w/v) for 72 h at ambient temperature (20°C) with continuous water replacement every 12 hours. Soaked barley grains were then placed in a sprouter at 30°C for 4 days. The sprouter contained a thin layer of 5 mm thickness of hydrophilic cotton moisturized with distilled water. The green malt was obtained when the acrospires reached about 5 mm and the rootlets 10 mm. Green malt was then laid into trays and dried for a full day in air oven at 40°C. Rootlets, acrospires and not germinated grains were discarded and the obtained malt was kept in opaque glass bottles at room temperature.
       
SBP was added to distilled water at the ratio of 25% (w/v) and pH was adjusted to 5.5 using HCL or NAOH (2M). The mixture was maintained at 80°C for 2 h to enable starch gelatinization. After cooling the suspension to the suitable temperature (55, 62.5 and 70°C), the malt was added in ratio of 1.25, 2.5 and 3.75% (w/v), then the enzymatic hydrolysis of starch was carried out for 1, 1.5 and 2 h. the resulted fermentable sugars were determined using DNS method (Miller, 1959). Fig 2 summarized the different steps of fermentable sugars production.


       
Response surface methodology was used to investigate the effect of hydrolysis parameters on fermentable sugars yield (FSY). In this study, 3 factor, 3 levels Box-Behnken experimental design (Box and Behnken, 1960) with three replicates at the center point was applied.
       
The actual variables were malt content, hydrolysis temperature and hydrolysis time coded as X₁, X₂ and X₃ respectively at three levels for each variable as follows: 1.25, 2.5 and 3.75% for malt content, 55, 62.5 and 70°C for hydrolysis temperature and 1, 1.5 and 2 h for hydrolysis time, while the response was FSY coded as Y. The order of experiments was fully randomized (Table 1).
 

 
A polynomial second degree quadratic equation for this model is represented by equation 1:

Y = b₀ + b₁X₁ + b₂X₂ + b₃X₃ + b₁₁X₁₂ + b₂₂X₂₂ + b₃₃X₃₂ + b₁₂X₁X₂ + b1₃X1X₃ + b₂₃X₂X₃ .............................(1)                                
 
Where,
Y = Predicted response (FSY).
b₀ = Average value of the response at the center point of the design.
b₁, b₂, b₃ = Linear terms.
b₁₂, b₁₃ and b₂₃ = Interaction terms.
b₁₁, b₂₂ and b₃₃ = Quadratic terms.
       
The optimum values of the variables were obtained by analyzing three-dimensional plots and desirability function. After optimization, experiments were conducted to validate the predicted FSY under the optimum hydrolysis conditions predicted by the statistical model.
               
Design Expert software (Version, 11.0, Stat-Ease. USA) was employed for experimental design, data analysis and model building. The coefficient of determination (R²) was used to validate the model and an F-test ascertained its statistical significance. Models were considered significant at p values <0.05.

Model adequacy
 
F-test value of the regression model was 14.47 with p-value of 0.0045 including that the model is statistically significant. A lack of fit p-value greater than 0.05 further confirmed the adequacy of model fitting (Table 2) and a satisfactory value of coefficient of determination (R²=0.963) indicates that 96.3% of the variability in the response could be explained by the statistical model.
 

 
Effect of processing variables on fermentable sugars yield
 
The results of the different experiments are presented in Table 3.
 

 
The mathematical model was expressed by equation 2:
 
FSY= -1204.29 + 16.64X₁ + 36.88X₂ + 85.71X₃ + 0.113X₁X₂ + 1.748X₁X₃ - 1.143X₂X₃ - 4.757X₁X₁ - 0.277X₂X₂ - 6.64X₃X₃ ........(2)
 
Malt content (X₁) showed a positive significant effect on FSY. This increased with the increase of malt content up to 61.79% (Fig 3 A and B). This result could be explained by the proportional relation between enzyme concentration and the obtained hydrolysates (Robinson, 2015). Further increase in malt content resulted in a decreased in FSY, which may be due to the feedback inhibition of produced fermentable sugars or the presence of enzyme inhibitors since wheat flour contains endogenous amylase inhibitors as reported by Hammer (1995). Ebrahimi et al., (2008) showed that the increase in amylase activity due the increase in temperature did not increase the degree of solids dissolution.
 

       
Hydrolysis temperature (X₂) had a great positive effect on FSY; from 55°C to 64°C, there was an increase in FSY and beyond 64°C, FSY decreased (Fig 3 A and C). This finding is related to the optimal temperature of amylolytic stage. According to Evans et al., (2005), the optimal temperature of enzymatic hydrolysis ranged from 60 to 65°C.
       
Fig 3B and C showed that hydrolysis time had no significant effect (p>0.05) on FSY, Olsen (2008), Kuddus (2019) and Sirohi et al., (2020) have reported similar findings.
 
Optimal conditions for fermentable sugars production
 
From the model predictions showed in Fig 4, the optimal conditions to obtain the highest FSY were determined as follows: 2.75% for malt content, 64.41°C for hydrolysis temperature and 1.31 h for hydrolysis time with a desirability of 0.97.
 

               
After hydrolysis of stale bread powder under the optimal conditions, the FSY was 63.21±1.1% that was not significantly different from the predicted value of 62.49%. This value was lower than 97.04% obtained by Yilmaz et al., (2021) and 59.8% reported by Sadaf et al., (2021) using commercial enzymes. However, our result is close to the outcomes of Nwaga et al., (2008) and Torabi et al., (2021) who reported a yield of 67.8% and 69.8% respectively. In contrast, it was higher than that obtained by Hudečková et al., (2017) and Mihajlovski et al., (2020) with 7.75% of total sugars and 1.98% of reducing sugars respectively.

The effect of hydrolysis parameters on fermentable sugars yield from stale bread was studied using response surface methodology based on a Box-Behnken design. Both malt content and hydrolysis temperature highlighted a significant effect on fermentable sugars yield.
               
This study presented the possibility of using stale bread as bio-resource for the production of fermentable sugars (63.21%) suitable as an added-value product by enzymatic hydrolysis with 2.75% of malted barley (instead of commercial enzyme) at 64.41°C during 1.31 h. Response surface methodology successfully optimized the hydrolysis conditions studied and then maximized the level of fermentable sugars.