# Traditional Cereal Food as Container of Probiotic Bacteria “Lb. rhamnosus GG”: Optimization by Response Surface Methodology

Authors: Asma Gharbi Yahyaoui; Taroub Bouzaiene; Fathia Aouidi; Abdelkarim Aydi; Moktar Hamdi
Journal: Journal of Food Quality
 (2017)

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## Abstract

This research paper aims at optimizing three parameters involved in solid state fermentation (SSF) usingLactobacillus rhamnosus GG (LGG) to improve a traditional cereal food “Bsissa” in order to elaborate a new probiotic fermented breakfast cereal. A Box-Behnken experimental design was used and the optimal fermentation conditions were liquid to solid ratio: 1.2 (vw−1), fermentation time: 12 h, and sucrose concentration: 10.48 g (100 g DM)−1. Under these conditions, the viable LGG cells, the free amino nitrogen content, and the total acidity were obtained to be 9.1log10⁡(cfug-1), 12.95 (mg g−1), and 6.46 (μmol g−1), respectively. After three weeks of refrigerated storage, the viability of LGG in the fermented Bsissa was 8.23log10⁡(cfug-1). This study shows a new possibility to make an acceptable nonfermented dairy product based mainly on cereals, leguminous plants, spices, and aromatic herbs, which are suitable substrates able to support the high probiotic viability.


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## Body

## 1. Introduction

Nowadays, the demand of probiotic functional foods is growing rapidly due to increased awareness of consumers [1]. Probiotic foods are categorized as functional foods containing a single or mixed culture of microorganisms with various prophylactic properties and efficient at a level of 106 (cfu g−1) [2]. These foods affect beneficially the consumer’s health by improving their intestinal microbial balance and composition of intestinal flora. Moreover, they reduce blood pressure levels and the risk of colon cancer and increase the resistance against invasion of pathogens [3–6].Lactobacillus rhamnosus GG is one of the most monitored probiotic strains which was clinically studied and was found to enhance human natural resistance and healthy digestive system and inhibits the adhesion of some pathogenic bacteria [7]. These cells showed a high tolerance to the acidic conditions and responded to sudden changes in their environmental osmotic conditions by accumulating sucrose in order to protect both the membranes and internal organs. Thus, this strain could be successfully used in the processing of foods containing sugars and also in preservation processes. Technologically, the LGG adheres well to fibers, creating a possibility for cereal-based probiotic products [8].Lb. rhamnosus GG is used in food industry not only as probiotics but also as a protective culture in fermented and nonfermented dairy products, beverages, ready-to-eat foods, dry sausages, and salads.Dairy products provide a suitable environment for probiotics. They support the growth and the viability of these bacteria [9]. However, with an increase in the consumer vegetarianism and lactose intolerance, there is a demand for the vegetarian probiotic products. The development of new nondairy probiotic food products is challenging; that is why, other foods such as cereal-based products, meat products, ice creams, fruit drinks, vegetable drinks, and many others have been examined for their potential as probiotic carriers. Cereal-based probiotic products show a beneficent effect for the consumer’s health. They have health-benefiting microbes and potentially prebiotic fibers [9]. Moreover, cereal-based products belong to a highly nutritive culinary recipe category. They provide nutriments, such as minerals, polyphenols, dietary proteins, carbohydrates (glucose, glycerol, stachyose, xylose, fructose, maltose, sucrose, and arabinose), vitamins, and nonnutrients, such as dietary fiber and oligosaccharides. The traditional foods made from cereal grains usually lack flavor and aroma [10]. The production of volatile compounds during cereal fermentation, such as organic acids (butyric, succinic, formic, valeric, caproic, lactic, acetic, etc.), alcohols (ethanol, n-propanol, isobutanol, isoamyl alcohol, etc.), aldehydes and ketones (acetaldehyde, formaldehyde, isovaleraldehyde, n-valeraldehyde, 2-methyl butanol, etc.), and carbonyls compounds (furfural, methional, glyoxal, etc.), contributes to a complex blend of flavors in fermented cereals and makes them more appetizing [11]. In addition, the fermentation of cereals leads to a general improvement in the shelf life of cereal products [12]. Acids formed during the fermentation process lower the pH to value 4 or less, thus inhibiting the growth of numerous spoilage organisms [13, 14].Lactic acid fermentation of cereals is a long-established processing method used to realize various beverages (boza, bouza, and Kenya busaa), gruels (togwa), porridge (ogi, yosa), and mixtures (tarhana, balao balao) in Asia, Africa, and some other countries [12]. Bsissa, zumita, Utshu, Bazin, and Asida are the most common cereal-based breakfast in theMaghreb Union Countries. These water based porridges and beverages of semolina or grilled barley and wheat are known for their nutritional and satiating effect. The Bsissa is an aromatized cereal powder composed basically of cereals, leguminous plants, aromatized dried herbs, and spices. It is realized through four steps: cleaning the vegetable raw material, roasting cereals and leguminous seeds, grinding the mix into fine flour, sieving well, and storing away on a jar. The recipe of Bsissa changes according to each region standard of living as well as the urban or rural status of the people. There are several forms of uses for Bsissa. It could be consumed as a liquid meal or a solid one. It could be mixed with water, oil, or milk until it becomes a paste. Other components could be added such as sugar, dried fruit, honey, crushed almonds, crushed pomegranate seeds, and dates in order to improve the flavor of the meal.Response Surface Methodology (RSM), originally described by Box and Wilson, enables evaluation of the effects of several process parameters and their interactions on the response variables. RSM are useful tools: statistical and mathematical techniques that has been successfully used for developing, improving, and optimizing biochemical and biotechnological process related to food systems, such as fermentation of tempeh from hardened chickpeas [15], ash gourd beverage [16], apple juice and whey based novel beverage fermented using kefir grains [17].This study is evaluating, up to our knowledge for the first time, the potential of Bsissa as substrates for the development of a probiotic product by the use ofLactobacillus rhamnosus GG. Response surface methodology based on Box-Behnken design was applied in order to optimize fermentation conditions of solid state fermentation of Bsissa. Cells growth evaluation, total acidity, and free amino nitrogen production were investigated during the fermentation process of Bsissa.


## 2. Materials and Methods

### 2.1. Preparation of Bsissa Powder

The Bsissa powder is a mixture of wheat grains, chickpea, carob, fenugreek seeds, and marjoram dried leaves. All materials were purchased from a local supermarket in Tunis. After sorting and cleaning, marjoram leaves were crumbled and carob pods were cut into pieces. Wheat grains, chickpeas, and fenugreek seeds were roasted in the oven at 250°C, respectively, for 6 minutes, 10 minutes, and 2 minutes. After mixing and cooling, the 5 ingredients were ground. Then, it was passed through a fine sieve and kept in a well-sealed jar until use.


### 2.2. Microorganism Inoculum Preparation

A strain ofLactobacillus rhamnosus GG (ATCC 53103) belonged to the collection of the Laboratory of Ecology and Microbial Technology (LETMI) and was stored frozen at Man Rogosa and Sharpe broth (MRS) containing glycerol (10% vv−1) at −80°C. The lactic acid bacteria were activated by transferring into MRS broth and cultured three times for 18 h at 37°C before use. For the preparation of the inoculum, the lactic strain was cultured in MRS broth for 12–14 h at 37°C. Then, the bacterial cells were pelleted by centrifugation at 500 g for 10 minutes at 4°C, washed twice with phosphate buffered saline (PBS), pH=7, and resuspended in physiological water. An inoculum with a population of probiotic cells of 107 cfu g−1 was used for the inoculation of Bsissa samples.


### 2.3. Experimental Box-Behnken Design

The Box-Behnken design experiments were applied in order to study the main effects, the interaction effects, and the quadratic effects of sucrose concentration g (100 g DM)−1, fermentation time (h), and liquid to solid ratio (vw−1) on the growth ofLactobacillus rhamnosus (cfu g−1), free amino nitrogen content (mg−1), and total acidity (μmol eq. lactic acid g−1), following lactic fermentation of Bsissa.The three independent variables were studied at three different levels: low, medium, and high, coded as −1, 0, and +1, respectively (Table1). A total of 17 experiments were carried out (Table 2). Twelve experiments were augmented with five replications in the center points of the design to estimate the pure error and to check the absence of bias between several sets of experiments.Table 1
Levels and code of independent variables used for Box-Behnken experimental design.
Independent variable Coded symbol Variable levels Low Center High −1 0 1 Sucrose concentration g (100 g DM)−1 X 1 2.1 6.29 10.48 Fermentation time (h) X 2 4 11 18 Liquid to solid ratio (vw−1) X 3 1.2 1.5 1.8Table 2
Box-Behnken experimental design with experimental values of viableLb. rhamnosusGG cells, free amino nitrogen content, and total acidity.
Number Exp Actual and coded level of variables Experimental values Predicted values X 1 X 2 X 3 Y 1 Y 2 Y 3 Y 1 Y 2 Y 3 g (100 gDM)−1 (h) (vw−1) log 10 ⁡(cfu g−1) (mg g−1) (µmol eq. lactic acid g−1) log 10 ⁡(cfu g−1) (mg g−1) (µmol eq. lactic acid g−1) 1 2.1 (−1) 4   ( - 1 ) 1.5   ( 0 ) 8.390 12.440 5.700 8.391 12.438 5.650 2 10.48 (1) 4   ( - 1 ) 1.5   ( 0 ) 8.270 12.660 4.700 8.266 12.660 4.663 3 2.1 (−1) 18   ( 1 ) 1.5   ( 0 ) 9.030 13.700 8.100 9.034 13.700 8.138 4 10.48 (1) 18   ( 1 ) 1.5   ( 0 ) 8.890 11.260 8.100 8.889 11.263 8.150 5 2.1 (−1) 11   ( 0 ) 1.2   ( - 1 ) 8.870 14.010 6.950 8.869 14.011 6.944 6 10.48 (1) 11   ( 0 ) 1.2   ( - 1 ) 9.040 13.220 6.100 9.044 13.219 6.081 7 2.1 (−1) 11   ( 0 ) 1.8   ( 1 ) 8.990 13.270 6.100 8.986 13.271 6.119 8 10.48 (1) 11   ( 0 ) 1.8   ( 1 ) 8.540 11.850 6.000 8.541 11.849 6.006 9 6.29 (0) 4   ( - 1 ) 1.2   ( - 1 ) 8.270 13.070 5.400 8.270 13.071 5.456 10 6.29 (0) 18   ( 1 ) 1.2   ( - 1 ) 9.120 13.060 8.200 9.118 13.059 8.169 11 6.29 (0) 4   ( - 1 ) 1.8   ( 1 ) 8.290 12.070 4.700 8.293 12.071 4.731 12 6.29 (0) 18   ( 1 ) 1.8   ( 1 ) 8.710 11.950 8.050 8.710 11.949 7.994 13 6.29 (0) 11   ( 0 ) 1.5   ( 0 ) 9.000 12.880 7.370 8.986 12.830 6.920 14 6.29 (0) 11   ( 0 ) 1.5   ( 0 ) 8.970 12.710 7.100 8.986 12.830 6.920 15 6.29 (0) 11   ( 0 ) 1.5   ( 0 ) 9.120 12.960 6.500 8.986 12.830 6.920 16 6.29 (0) 11   ( 0 ) 1.5   ( 0 ) 8.960 12.680 6.700 8.986 12.830 6.920 17 6.29 (0) 11   ( 0 ) 1.5   ( 0 ) 8.880 12.920 6.930 8.986 12.830 6.920 X 1: sucrose concentration g (100 g DM)−1; X2: fermentation time (h); X3: liquid to solid ratio (vw−1); Y1: viable Lb. rhamnosus GG (log10⁡(cfu g−1)); Y2: free amino nitrogen content (mg g−1); Y3: total acidity (µmol eq. lactic acid g−1, Y3). ∗When t=0 h, LGG = 7.8 ± 0.075 log10⁡(cfu g−1) in all experimental samples; FAN = 13.11 ± 0.09 mgg−1 and total acidity = 4.7 ± 0.18 µmol g−1.To find the optimum set of fermentation conditions, a second-degree model was used according to(1)Y=b0+b1X1+b2X2+b3X3+b11X12+b22X22+b33X32+b12X12+b13X13+b23X23,where Xi=xi-x0/Δxi is the coded value:  xi is the actual value of the independent variable, xo is the actual value at the center point, and Δxi is the step change value. Y is the predicted response, ao is the constant, a1, a2, and a3 are linear coefficients, a12, a13, and a23 are cross product coefficients, and a11, a22, and a33 are quadratic coefficients.


### 2.4. Lactic Acid Fermentation of Bsissa

A mass of 50 g of autoclaved Bsissa was mixed with a volume of sterilized water and a mass of sucrose according to the Box-Behnken design (Table2). The paste was aseptically homogenized and inoculated with 1% (vw−1) ofLactobacillus rhamnosus inoculum. The solid state fermentation was carried out at 30°C for a fixed time, according to Box-Behnken design (Table 2).


### 2.5. Analytical Methods

#### 2.5.1. Viable Cells Enumeration

Bsissa samples were aseptically diluted (1 : 10) in sterile peptone water (0.1%). Sample dilutions (0.1 mL) were plated into MRS agar and were incubated at 37°C for 48 h under aerobic conditions. Total viable cells were estimated by colony forming units (cfu) and were expressed as log10 per gram.


#### 2.5.2. pH and Titrable Acidity Determination

A mass of 10 g of samples were homogenized with 90 mL of distilled water for 20 min in a Laboratory Incubator Shaker. The pH value was measured at room temperature after standardizing the combined glass electrode with pH 4.01 and 7.01 standard buffer solution. The total titrable acidity (TTA) was determined by titrating each fermented sample with 0.1 N NaOH, using phenolphthalein as an indicator, until pH of 8.5 was attained. Each mL of 0.1 N NaOH is equivalent to 9.008 mg of lactic acid. The total titrable acidity was expressed inμmolg−1(2)Totaltitrableacidityμmoleq.lacticacidg-1=VNaOH×9.008MW×10,where VNaOH is the volume of NaOH (mL) and MW is the molar mass of lactic acid (g mol−1).


#### 2.5.3. Determination of Free Amino Nitrogen Content

Free amino nitrogen content in the fermented Bsissa was determined according to the official AOAC [18] method 945.18-B.


### 2.6. Statistical Analysis

Data from the BBD were analyzed using NEMROD-W (Version 9901, LPRAI Company) for the regression analysis and the graphical optimization. Student’st-test permitted us to check the statistical significance of the regression coefficients. Fisher’s test for analysis of variance (ANOVA) was performed on experimental data to evaluate the statistical significance of the model. The models of each response for the full factorial design were expressed in terms of code variables and without taking into account the statistically insignificant terms.


## 2.1. Preparation of Bsissa Powder

The Bsissa powder is a mixture of wheat grains, chickpea, carob, fenugreek seeds, and marjoram dried leaves. All materials were purchased from a local supermarket in Tunis. After sorting and cleaning, marjoram leaves were crumbled and carob pods were cut into pieces. Wheat grains, chickpeas, and fenugreek seeds were roasted in the oven at 250°C, respectively, for 6 minutes, 10 minutes, and 2 minutes. After mixing and cooling, the 5 ingredients were ground. Then, it was passed through a fine sieve and kept in a well-sealed jar until use.


## 2.2. Microorganism Inoculum Preparation

A strain ofLactobacillus rhamnosus GG (ATCC 53103) belonged to the collection of the Laboratory of Ecology and Microbial Technology (LETMI) and was stored frozen at Man Rogosa and Sharpe broth (MRS) containing glycerol (10% vv−1) at −80°C. The lactic acid bacteria were activated by transferring into MRS broth and cultured three times for 18 h at 37°C before use. For the preparation of the inoculum, the lactic strain was cultured in MRS broth for 12–14 h at 37°C. Then, the bacterial cells were pelleted by centrifugation at 500 g for 10 minutes at 4°C, washed twice with phosphate buffered saline (PBS), pH=7, and resuspended in physiological water. An inoculum with a population of probiotic cells of 107 cfu g−1 was used for the inoculation of Bsissa samples.


## 2.3. Experimental Box-Behnken Design

The Box-Behnken design experiments were applied in order to study the main effects, the interaction effects, and the quadratic effects of sucrose concentration g (100 g DM)−1, fermentation time (h), and liquid to solid ratio (vw−1) on the growth ofLactobacillus rhamnosus (cfu g−1), free amino nitrogen content (mg−1), and total acidity (μmol eq. lactic acid g−1), following lactic fermentation of Bsissa.The three independent variables were studied at three different levels: low, medium, and high, coded as −1, 0, and +1, respectively (Table1). A total of 17 experiments were carried out (Table 2). Twelve experiments were augmented with five replications in the center points of the design to estimate the pure error and to check the absence of bias between several sets of experiments.Table 1
Levels and code of independent variables used for Box-Behnken experimental design.
Independent variable Coded symbol Variable levels Low Center High −1 0 1 Sucrose concentration g (100 g DM)−1 X 1 2.1 6.29 10.48 Fermentation time (h) X 2 4 11 18 Liquid to solid ratio (vw−1) X 3 1.2 1.5 1.8Table 2
Box-Behnken experimental design with experimental values of viableLb. rhamnosusGG cells, free amino nitrogen content, and total acidity.
Number Exp Actual and coded level of variables Experimental values Predicted values X 1 X 2 X 3 Y 1 Y 2 Y 3 Y 1 Y 2 Y 3 g (100 gDM)−1 (h) (vw−1) log 10 ⁡(cfu g−1) (mg g−1) (µmol eq. lactic acid g−1) log 10 ⁡(cfu g−1) (mg g−1) (µmol eq. lactic acid g−1) 1 2.1 (−1) 4   ( - 1 ) 1.5   ( 0 ) 8.390 12.440 5.700 8.391 12.438 5.650 2 10.48 (1) 4   ( - 1 ) 1.5   ( 0 ) 8.270 12.660 4.700 8.266 12.660 4.663 3 2.1 (−1) 18   ( 1 ) 1.5   ( 0 ) 9.030 13.700 8.100 9.034 13.700 8.138 4 10.48 (1) 18   ( 1 ) 1.5   ( 0 ) 8.890 11.260 8.100 8.889 11.263 8.150 5 2.1 (−1) 11   ( 0 ) 1.2   ( - 1 ) 8.870 14.010 6.950 8.869 14.011 6.944 6 10.48 (1) 11   ( 0 ) 1.2   ( - 1 ) 9.040 13.220 6.100 9.044 13.219 6.081 7 2.1 (−1) 11   ( 0 ) 1.8   ( 1 ) 8.990 13.270 6.100 8.986 13.271 6.119 8 10.48 (1) 11   ( 0 ) 1.8   ( 1 ) 8.540 11.850 6.000 8.541 11.849 6.006 9 6.29 (0) 4   ( - 1 ) 1.2   ( - 1 ) 8.270 13.070 5.400 8.270 13.071 5.456 10 6.29 (0) 18   ( 1 ) 1.2   ( - 1 ) 9.120 13.060 8.200 9.118 13.059 8.169 11 6.29 (0) 4   ( - 1 ) 1.8   ( 1 ) 8.290 12.070 4.700 8.293 12.071 4.731 12 6.29 (0) 18   ( 1 ) 1.8   ( 1 ) 8.710 11.950 8.050 8.710 11.949 7.994 13 6.29 (0) 11   ( 0 ) 1.5   ( 0 ) 9.000 12.880 7.370 8.986 12.830 6.920 14 6.29 (0) 11   ( 0 ) 1.5   ( 0 ) 8.970 12.710 7.100 8.986 12.830 6.920 15 6.29 (0) 11   ( 0 ) 1.5   ( 0 ) 9.120 12.960 6.500 8.986 12.830 6.920 16 6.29 (0) 11   ( 0 ) 1.5   ( 0 ) 8.960 12.680 6.700 8.986 12.830 6.920 17 6.29 (0) 11   ( 0 ) 1.5   ( 0 ) 8.880 12.920 6.930 8.986 12.830 6.920 X 1: sucrose concentration g (100 g DM)−1; X2: fermentation time (h); X3: liquid to solid ratio (vw−1); Y1: viable Lb. rhamnosus GG (log10⁡(cfu g−1)); Y2: free amino nitrogen content (mg g−1); Y3: total acidity (µmol eq. lactic acid g−1, Y3). ∗When t=0 h, LGG = 7.8 ± 0.075 log10⁡(cfu g−1) in all experimental samples; FAN = 13.11 ± 0.09 mgg−1 and total acidity = 4.7 ± 0.18 µmol g−1.To find the optimum set of fermentation conditions, a second-degree model was used according to(1)Y=b0+b1X1+b2X2+b3X3+b11X12+b22X22+b33X32+b12X12+b13X13+b23X23,where Xi=xi-x0/Δxi is the coded value:  xi is the actual value of the independent variable, xo is the actual value at the center point, and Δxi is the step change value. Y is the predicted response, ao is the constant, a1, a2, and a3 are linear coefficients, a12, a13, and a23 are cross product coefficients, and a11, a22, and a33 are quadratic coefficients.


## 2.4. Lactic Acid Fermentation of Bsissa

A mass of 50 g of autoclaved Bsissa was mixed with a volume of sterilized water and a mass of sucrose according to the Box-Behnken design (Table2). The paste was aseptically homogenized and inoculated with 1% (vw−1) ofLactobacillus rhamnosus inoculum. The solid state fermentation was carried out at 30°C for a fixed time, according to Box-Behnken design (Table 2).


## 2.5. Analytical Methods

### 2.5.1. Viable Cells Enumeration

Bsissa samples were aseptically diluted (1 : 10) in sterile peptone water (0.1%). Sample dilutions (0.1 mL) were plated into MRS agar and were incubated at 37°C for 48 h under aerobic conditions. Total viable cells were estimated by colony forming units (cfu) and were expressed as log10 per gram.


### 2.5.2. pH and Titrable Acidity Determination

A mass of 10 g of samples were homogenized with 90 mL of distilled water for 20 min in a Laboratory Incubator Shaker. The pH value was measured at room temperature after standardizing the combined glass electrode with pH 4.01 and 7.01 standard buffer solution. The total titrable acidity (TTA) was determined by titrating each fermented sample with 0.1 N NaOH, using phenolphthalein as an indicator, until pH of 8.5 was attained. Each mL of 0.1 N NaOH is equivalent to 9.008 mg of lactic acid. The total titrable acidity was expressed inμmolg−1(2)Totaltitrableacidityμmoleq.lacticacidg-1=VNaOH×9.008MW×10,where VNaOH is the volume of NaOH (mL) and MW is the molar mass of lactic acid (g mol−1).


### 2.5.3. Determination of Free Amino Nitrogen Content

Free amino nitrogen content in the fermented Bsissa was determined according to the official AOAC [18] method 945.18-B.


## 2.5.1. Viable Cells Enumeration

Bsissa samples were aseptically diluted (1 : 10) in sterile peptone water (0.1%). Sample dilutions (0.1 mL) were plated into MRS agar and were incubated at 37°C for 48 h under aerobic conditions. Total viable cells were estimated by colony forming units (cfu) and were expressed as log10 per gram.


## 2.5.2. pH and Titrable Acidity Determination

A mass of 10 g of samples were homogenized with 90 mL of distilled water for 20 min in a Laboratory Incubator Shaker. The pH value was measured at room temperature after standardizing the combined glass electrode with pH 4.01 and 7.01 standard buffer solution. The total titrable acidity (TTA) was determined by titrating each fermented sample with 0.1 N NaOH, using phenolphthalein as an indicator, until pH of 8.5 was attained. Each mL of 0.1 N NaOH is equivalent to 9.008 mg of lactic acid. The total titrable acidity was expressed inμmolg−1(2)Totaltitrableacidityμmoleq.lacticacidg-1=VNaOH×9.008MW×10,where VNaOH is the volume of NaOH (mL) and MW is the molar mass of lactic acid (g mol−1).


## 2.5.3. Determination of Free Amino Nitrogen Content

Free amino nitrogen content in the fermented Bsissa was determined according to the official AOAC [18] method 945.18-B.


## 2.6. Statistical Analysis

Data from the BBD were analyzed using NEMROD-W (Version 9901, LPRAI Company) for the regression analysis and the graphical optimization. Student’st-test permitted us to check the statistical significance of the regression coefficients. Fisher’s test for analysis of variance (ANOVA) was performed on experimental data to evaluate the statistical significance of the model. The models of each response for the full factorial design were expressed in terms of code variables and without taking into account the statistically insignificant terms.


## 3. Results

### 3.1. Efficiency of the Bsissa Fermentation

During the fermentation of Bsissa under a liquid to solid ratio of 1.2 and sucrose concentration of 10.48 g (100 g DM)−1, the cell population increased rapidly from 7.87log10(cfug-1) to 9.33log10(cfug-1) after 18 h of fermentation and then remained constant until 48 h of fermentation (Figure 1(a)).Figure 1
Evolution ofLb. rhamnosus (a) and pH and total acidity (b) during fermentation of Bsissa.
(a) (b)Kinetics of pH changes during the fermentation period showed a significant (p<0.05) reduction in the pH from 5.5 to 4.9 after 18 h of fermentation. The pH showed a gradual reduction from 4.9 at 18 h to 4.63 at 48 h of fermentation (stationary phase). Hence, the total acidity increased significantly (p<0.05) from 4.5 μmol  g−1 up to 9.57 μmol  g−1 at the end of the fermentation (48 h) (Figure 1(b)).


### 3.2. Experimental Results of the BBD

The matrix design of the coded independent variables and experiment are shown in Table2. Each test was performed in duplicate and the central point was repeated five times (runs 13, 14, 15, 16, and 17). Results demonstrate that sucrose concentration, fermentation time, liquid to solid ratio, and their interactions have an effect on LGG growth and total acidity. In particular, the highest results of LGG growth (9.12log10(cfug-1)) and total acidity (8.2 μmol eq. lactic acid g−1) were obtained working with the highest fermentation time (18 h), an intermediate sucrose concentration (6.29%), and a lowest liquid to solid ratio (1.2). On the other hand, the maximum free amino nitrogen (13.7 mg g−1) was reached at the highest fermentation time (18 h), an intermediate liquid to solid ratio (1.5), and the lowest sucrose concentration (2.1%). For this reason, a simultaneous optimization of the three responses was considered to be necessary to select the best overall conditions for the process.


### 3.3. Statistics

#### 3.3.1. Application Response Surface Methodology to ViableLb. rhamnosus GG (Y1)

The second-order model describing viableLb. rhamnosus GG as a simultaneous function of sucrose concentration (X1), fermentation time (X2), and liquid to solid ratio (X3) is described by (3) after neglecting the statistically insignificant terms (p<0.05): (3)Y1=8.986-0.068X1+0.316X2-0.096X3-0.302X22-0.087X32-0.155X13-0.107X23±0.066,where Y1 is the viableLb.rhamnosus GG response, X13 is the interaction effect between sucrose concentration (X1) and liquid to solid ratio (X3), and X23 is the interaction effect between fermentation time (X2) and liquid to solid ratio (X3).The regression coefficients obtained to predict polynomial model for LGG growth are summarized in Table3. The significance of all regression coefficient was checked by means of Student’s test (variation of data about mean value) and p values (probability) (Table 3). We can see that X12 (sucrose concentration × sucrose concentration) and X12 (sucrose concentration × fermentation time) were found to be statistically insignificant (p>0.05). The goodness of fit of the model was examined by F-test and the determination coefficient R2. The analysis of variance (Table 4) showed that this elaborated regression model was highly significant (p<0.1%) as is evident from the Fisher F-test and has a very low probability value [(pmodel>F)<0.1%]. The value of 1 (>0.05) for lack of fit implies that it is not significant compared to the pure error and that the model equation was adequate for predicting viableLb. rhamnosus GG (log10⁡cfug-1, Y1). The fitness of the model was further confirmed by a satisfactory value of determination coefficient (R2), which was calculated to be 0.980 (Y1). Furthermore, the predicted responses of the final quadratic model, along with the corresponding values observed, are given in Table 2. The agreement between the predicted results of the model and the experimental data is very strong as shown by a high value of correlation coefficient, R2pred (0.968 (Y1)). The residuals were examined to check the adequacy of the model. The residuals were plotted against the predicted value. No unusual behavior was notified (horizontal band) [19], confirming the adequacy of the regression model. The effect of interaction of the three components on growth of LGG was tested by contour plots for all possible combinations of factors, keeping one factor constant at a time. The interactions between the variables can be inferred from the shapes of the contour plots [20]. Circular contour plots indicate that the interactions between the variables are negligible. In contrast, elliptical ones indicate the evidence of the interactions (Figure 2).Table 3
Coefficients by regression analysis and their significance values obtained by ANOVA.
Nomenclature of the coefficients ViableLb. rhamnosusGG (log10 cfu g−1, Y1) Free amino nitrogen content (mg g−1, Y2) Total acidity (µmol eq. lactic acid g−1, Y3) Coefficient Ecart-type t.exp. Signif. % Coefficient Ecart-type t.exp. Signif. % Coefficient Ecart-type t.exp. Signif. % b 0 8.986 0.029 304.93 ∗  ∗  ∗ 12.830 0.043 299.04 ∗  ∗  ∗ 6.920 0.117 59.30 ∗  ∗  ∗ b 1 −0.068 0.023 −2.90 ∗ −0.554 0.034 −16.33 ∗  ∗  ∗ −0.244 0.092 −2.64 ∗ b 2 0.316 0.023 13.57 ∗  ∗  ∗ −0.034 0.034 −1.00 35.5% 1.494 0.092 16.19 ∗  ∗  ∗ b 3 −0.096 0.023 −4.13 ∗  ∗ −0.528 0.034 −15.55 ∗  ∗  ∗ −0.225 0.092 −2.44 ∗ b 11 −0.039 0.032 −1.22 26.1% 0.118 0.047 2.51 ∗ −0.285 0.127 −2.24 5.8% b 22 −0.302 0.032 −9.40 ∗  ∗  ∗ −0.432 0.047 −9.25 ∗  ∗  ∗ 0.015 0.127 0.12 90.5% b 33 −0.087 0.032 −2.70 ∗ 0.140 0.047 2.99 ∗ −0.348 0.127 −2.73 ∗ b 12 −0.005 0.033 −0.15 87.8% −0.665 0.048 −13.86 ∗  ∗  ∗ 0.250 0.130 1.92 9.5% b 13 −0.155 0.033 −4.70 ∗  ∗ −0.158 0.048 −3.28 ∗ 0.188 0.130 1.44 19.2% b 23 −0.107 0.033 −3.26 ∗ −0.028 0.048 −0.57 58.9% 0.138 0.130 1.05 32.8% Test Student (t.exp.); ∗: p<5%; ∗∗: p<1%; ∗∗∗: p<0.1%.Table 4
Analysis of variance and regression analysis.
Source Sum of squares DF Mean squares F-value Signif. % ViableLb. rhamnosusGG (log10 cfu g−1, Y1) Model 1.4966 9 0.1663 38.2972 ∗  ∗  ∗ Residual 0.0304 7 0.0043 Lack of fit 0.0001 3 0.0000 0.0033 100.0% Pure error 0.0303 4 0.0076 Total 1 .5270 16 Free amino nitrogen content (mg g−1, Y2) Model 7.4485 9 0.8276 89.9226 ∗  ∗  ∗ Residual 0.0644 7 0.0092 Lack of fit 0.0000 3 0.0000 0.0005 100.0% Pure error 0.0644 4 0.0161 Total 7.5129 16 Total acidity (µmol eq. lactic acid g−1, Y3) Model 20.0954 9 2.2328 32.7892 ∗  ∗  ∗ Residual 0.4767 7 0.0681 Lack of fit 0.0169 3 0.0056 0.0489 98.4% Pure error 0.4598 4 0.1149 Total 20.5721 16 DF: degrees of freedom;F: variance ratio; ∗∗∗: P (probability) <0.1%.Figure 2
Response surface and contour plots that represent the effect of fermentation time and sucrose concentration (A); liquid to solid ratio and sucrose concentration (B); liquid to solid ratio and fermentation time (C) and their interaction on (1) viableLb. rhamnosus GG cells when X1, X2, and X3 are 6.29 g (100 g DM)−1, 11 h, and 1.5(vw−1); (2) free amino nitrogen content when X1, X2, and X3 are 6.29 g (100 g DM)−1, 11 h, and 1.5(vw−1); (3) total acidity when X1, X2, and X3 are 6.29 g (100 g DM)−1, 11 h, and 1.5(vw−1). X1: sucrose concentration g (100 g DM)−1; X2: fermentation time (h); X3: liquid to solid ratio (vw−1).Figure2(B1) showed that there was a significant decrease in LGG growth from 8.97log10⁡(cfug-1) to 8.66log10⁡(cfug-1), when liquid to solid ratio was between 1.5 (vw−1) and 1.8 (vw−1) and sucrose concentration was between 6.29% and 10.48%, which was corresponding to the extremely significant interaction of X1X3, shown in Table 4. However, the greater LGG values were shown for a liquid to solid ratio of [1.2;1.65] and for fermentation time between 11 h and 13 h (Figure 2(C1)). This interaction is, indeed, confirmed by the interaction X2X3 shown in Table 4.


#### 3.3.2. Application Response Surface Methodology to Free Amino Nitrogen Content (Y2)

The second-order model describing free amino nitrogen (FAN) content as a simultaneous function of sucrose concentration (X1), fermentation time (X2), and liquid to solid ratio (X3) is described by (4)Y2=12.83-0.554X1-0.528X3+0.118X12-0.432X22+0.14X32-0.665X12-0.158X13±0.096,where Y2 is the free amino nitrogen content, X12 is the interaction between sucrose concentration (X1) and fermentation time (X2), and X13 is the interaction between sucrose concentration (X1) and liquid to solid ratio (X3).Figure2(A2) represents the FAN response surface versus the actual level of fermentation time and sucrose concentration. The results of the Fisher test for analysis of variance (Table 3) revealed that the regression is statically significant at 100% of confidence level. Moreover, the value of the determination coefficient (R2=0.991) points out the goodness of the regression, which can be used to explain 99.1% of the total variation in the response.We can see from Table3 that X2 (fermentation time) and X23 (fermentation time × liquid to solid ratio) had no significant effect on free amino nitrogen content (p>0.05). The linear term of the fermentation time seems to have no significant effect on the response, contrary to the quadratic term. This last increase is when the fermentation time is between 10 h and 12 h. Under 10 h and below 12 h of fermentation, FAN keeps decreasing.


#### 3.3.3. Application Response Surface Methodology to Total Acidity (Y3)

The application of the response surface methodology to total acidity yielded the following regression equation:(5)Y3=6.92-0.244X1+1.494X2-0.225X3-0.348X32±0.261,where Y3 is total acidity response and X1, X2, and X3 are the coded value of sucrose concentration, fermentation time, and liquid to solid ratio, respectively.The coefficients ofX12 (sucrose concentration × sucrose concentration), X22 (fermentation time × fermentation time), X12 (sucrose concentration × fermentation time), X13 (sucrose concentration × liquid to solid ratio), and X23 (fermentation time × liquid to solid ratio) were found to be statistically insignificant (p>0.05). Besides, the analysis of variance reveals that this regression is statically significant at 98.4% confidence level. Besides R2=97.7% points out that only 2.3% of the total variation in the response is not explained by the model. The linear regression coefficient of fermentation time (X2) puts in evidence the positive effect of this parameter on the response, making the total acidity clearly growing with the fermentation time. The response surface to predict the total acidity within the region under investigation is shown in Figure 2(B3). The quadratic term of fermentation time is insignificant. The maximum total acidity (8.25 μmol g−1) was obtained in 2.1% of sucrose concentration, 18 h of fermentation time, and 1.5 of liquid to solid ratio.In this study, total acidity increases with fermentation time, contrary to sucrose concentration and liquid to solid ratio.


### 3.4. Optimization of the Fermentation Conditions

Optimization of the Bsissa fermentation by LGG was carried out via a multiple response method called desirability (D) function to optimize different combinations of process parameters such as sucrose concentration, fermentation time, and liquid to solid ratio. The goal of optimization was to choose the best fermentation conditions that give us the higher biomass (log10⁡(LGG)>9±0.1) and free amino nitrogen (>13 ± 0.1) with a total acidity bigger than 6 μmol g−1 and lower than 7 μmol g−1. Figures 3(a), 3(b), and 3(c). show that desirability is higher when fermentation time is closer to 12 h (11-12 h), liquid to solid ratio closer to 1.2 (1.2–1.6), and sucrose concentration closer to 10.48% (8.4%–10.48%).Figure 3
Desirability fitted 2D surface that represent the effect of fermentation time and sucrose concentration (a); liquid to solid ratio and fermentation time (b); liquid to solid ratio and sucrose concentration (c), whenX1, X2, and X3 are 10.48 g (100 g DM)−1, 12 h, and 1.2(vw−1). X1: sucrose concentration g (100 g DM)−1; X2: fermentation time (h); X3: liquid to solid ratio (vw−1).
(a) (b) (c)Among all the optimum points, the best desirability value 88.4% was found in sucrose concentration of 10.48%, fermentation time of 12 h, and liquid to solid ratio of 1.2 (vw−1).Three test experiments were also carried out according to the optimum fermentation conditions. The result showed that the value of LGG growth, FAA content, and total acidity was closer to the values predicted earlier, with a low relative error (p<0.05), declaring the effectiveness of the RSM method to optimize the fermentation conditions of Bsissa.


### 3.5. Viability of LGG in Fermented Bsissa during Conservation

The Bsissa was fermented under the optimized conditions and then stored at 4°C. The viability of LGG in fermented Bsissa and the value of the pH and the total acidity over the refrigerated storage were monitored at 3-day intervals for 3 weeks. Figure4 shows that the number of LGG decreased significantly from 2.5 × 109 cfu g−1 (day 1) to 1.7 × 108 at day 21. Total viable count, coliforms, yeasts, and molds were not detected (<1 log10⁡(cfug-1)) during storage up to 21 days. Figure 5 showed the evolution of pH and total acidity during refrigerated storage of Bsissa. After 3 days of storage, the pH of the fermented Bsissa decreased from 4.3 to 4.1 and continues to decrease significantly (p<0.05) to 3.4 during the 21 days of refrigerated storage (average of 0.043 ΔpH day−1). The total acidity of the fermented Bsissa increased throughout 21 days of storage from 6.6 μmol/g to 10.23 μmol/g. Single factor ANOVA analysis showed that the pH and the total acidity changes were significant (p<0.05).Figure 4
Effect of storage time at 4°C on the viable LGG of fermented Bsissa.Figure 5
Effect of storage time on the pH (◆) and the total acidity (■) of fermented Bsissa.


## 3.1. Efficiency of the Bsissa Fermentation

During the fermentation of Bsissa under a liquid to solid ratio of 1.2 and sucrose concentration of 10.48 g (100 g DM)−1, the cell population increased rapidly from 7.87log10(cfug-1) to 9.33log10(cfug-1) after 18 h of fermentation and then remained constant until 48 h of fermentation (Figure 1(a)).Figure 1
Evolution ofLb. rhamnosus (a) and pH and total acidity (b) during fermentation of Bsissa.
(a) (b)Kinetics of pH changes during the fermentation period showed a significant (p<0.05) reduction in the pH from 5.5 to 4.9 after 18 h of fermentation. The pH showed a gradual reduction from 4.9 at 18 h to 4.63 at 48 h of fermentation (stationary phase). Hence, the total acidity increased significantly (p<0.05) from 4.5 μmol  g−1 up to 9.57 μmol  g−1 at the end of the fermentation (48 h) (Figure 1(b)).


## 3.2. Experimental Results of the BBD

The matrix design of the coded independent variables and experiment are shown in Table2. Each test was performed in duplicate and the central point was repeated five times (runs 13, 14, 15, 16, and 17). Results demonstrate that sucrose concentration, fermentation time, liquid to solid ratio, and their interactions have an effect on LGG growth and total acidity. In particular, the highest results of LGG growth (9.12log10(cfug-1)) and total acidity (8.2 μmol eq. lactic acid g−1) were obtained working with the highest fermentation time (18 h), an intermediate sucrose concentration (6.29%), and a lowest liquid to solid ratio (1.2). On the other hand, the maximum free amino nitrogen (13.7 mg g−1) was reached at the highest fermentation time (18 h), an intermediate liquid to solid ratio (1.5), and the lowest sucrose concentration (2.1%). For this reason, a simultaneous optimization of the three responses was considered to be necessary to select the best overall conditions for the process.


## 3.3. Statistics

### 3.3.1. Application Response Surface Methodology to ViableLb. rhamnosus GG (Y1)

The second-order model describing viableLb. rhamnosus GG as a simultaneous function of sucrose concentration (X1), fermentation time (X2), and liquid to solid ratio (X3) is described by (3) after neglecting the statistically insignificant terms (p<0.05): (3)Y1=8.986-0.068X1+0.316X2-0.096X3-0.302X22-0.087X32-0.155X13-0.107X23±0.066,where Y1 is the viableLb.rhamnosus GG response, X13 is the interaction effect between sucrose concentration (X1) and liquid to solid ratio (X3), and X23 is the interaction effect between fermentation time (X2) and liquid to solid ratio (X3).The regression coefficients obtained to predict polynomial model for LGG growth are summarized in Table3. The significance of all regression coefficient was checked by means of Student’s test (variation of data about mean value) and p values (probability) (Table 3). We can see that X12 (sucrose concentration × sucrose concentration) and X12 (sucrose concentration × fermentation time) were found to be statistically insignificant (p>0.05). The goodness of fit of the model was examined by F-test and the determination coefficient R2. The analysis of variance (Table 4) showed that this elaborated regression model was highly significant (p<0.1%) as is evident from the Fisher F-test and has a very low probability value [(pmodel>F)<0.1%]. The value of 1 (>0.05) for lack of fit implies that it is not significant compared to the pure error and that the model equation was adequate for predicting viableLb. rhamnosus GG (log10⁡cfug-1, Y1). The fitness of the model was further confirmed by a satisfactory value of determination coefficient (R2), which was calculated to be 0.980 (Y1). Furthermore, the predicted responses of the final quadratic model, along with the corresponding values observed, are given in Table 2. The agreement between the predicted results of the model and the experimental data is very strong as shown by a high value of correlation coefficient, R2pred (0.968 (Y1)). The residuals were examined to check the adequacy of the model. The residuals were plotted against the predicted value. No unusual behavior was notified (horizontal band) [19], confirming the adequacy of the regression model. The effect of interaction of the three components on growth of LGG was tested by contour plots for all possible combinations of factors, keeping one factor constant at a time. The interactions between the variables can be inferred from the shapes of the contour plots [20]. Circular contour plots indicate that the interactions between the variables are negligible. In contrast, elliptical ones indicate the evidence of the interactions (Figure 2).Table 3
Coefficients by regression analysis and their significance values obtained by ANOVA.
Nomenclature of the coefficients ViableLb. rhamnosusGG (log10 cfu g−1, Y1) Free amino nitrogen content (mg g−1, Y2) Total acidity (µmol eq. lactic acid g−1, Y3) Coefficient Ecart-type t.exp. Signif. % Coefficient Ecart-type t.exp. Signif. % Coefficient Ecart-type t.exp. Signif. % b 0 8.986 0.029 304.93 ∗  ∗  ∗ 12.830 0.043 299.04 ∗  ∗  ∗ 6.920 0.117 59.30 ∗  ∗  ∗ b 1 −0.068 0.023 −2.90 ∗ −0.554 0.034 −16.33 ∗  ∗  ∗ −0.244 0.092 −2.64 ∗ b 2 0.316 0.023 13.57 ∗  ∗  ∗ −0.034 0.034 −1.00 35.5% 1.494 0.092 16.19 ∗  ∗  ∗ b 3 −0.096 0.023 −4.13 ∗  ∗ −0.528 0.034 −15.55 ∗  ∗  ∗ −0.225 0.092 −2.44 ∗ b 11 −0.039 0.032 −1.22 26.1% 0.118 0.047 2.51 ∗ −0.285 0.127 −2.24 5.8% b 22 −0.302 0.032 −9.40 ∗  ∗  ∗ −0.432 0.047 −9.25 ∗  ∗  ∗ 0.015 0.127 0.12 90.5% b 33 −0.087 0.032 −2.70 ∗ 0.140 0.047 2.99 ∗ −0.348 0.127 −2.73 ∗ b 12 −0.005 0.033 −0.15 87.8% −0.665 0.048 −13.86 ∗  ∗  ∗ 0.250 0.130 1.92 9.5% b 13 −0.155 0.033 −4.70 ∗  ∗ −0.158 0.048 −3.28 ∗ 0.188 0.130 1.44 19.2% b 23 −0.107 0.033 −3.26 ∗ −0.028 0.048 −0.57 58.9% 0.138 0.130 1.05 32.8% Test Student (t.exp.); ∗: p<5%; ∗∗: p<1%; ∗∗∗: p<0.1%.Table 4
Analysis of variance and regression analysis.
Source Sum of squares DF Mean squares F-value Signif. % ViableLb. rhamnosusGG (log10 cfu g−1, Y1) Model 1.4966 9 0.1663 38.2972 ∗  ∗  ∗ Residual 0.0304 7 0.0043 Lack of fit 0.0001 3 0.0000 0.0033 100.0% Pure error 0.0303 4 0.0076 Total 1 .5270 16 Free amino nitrogen content (mg g−1, Y2) Model 7.4485 9 0.8276 89.9226 ∗  ∗  ∗ Residual 0.0644 7 0.0092 Lack of fit 0.0000 3 0.0000 0.0005 100.0% Pure error 0.0644 4 0.0161 Total 7.5129 16 Total acidity (µmol eq. lactic acid g−1, Y3) Model 20.0954 9 2.2328 32.7892 ∗  ∗  ∗ Residual 0.4767 7 0.0681 Lack of fit 0.0169 3 0.0056 0.0489 98.4% Pure error 0.4598 4 0.1149 Total 20.5721 16 DF: degrees of freedom;F: variance ratio; ∗∗∗: P (probability) <0.1%.Figure 2
Response surface and contour plots that represent the effect of fermentation time and sucrose concentration (A); liquid to solid ratio and sucrose concentration (B); liquid to solid ratio and fermentation time (C) and their interaction on (1) viableLb. rhamnosus GG cells when X1, X2, and X3 are 6.29 g (100 g DM)−1, 11 h, and 1.5(vw−1); (2) free amino nitrogen content when X1, X2, and X3 are 6.29 g (100 g DM)−1, 11 h, and 1.5(vw−1); (3) total acidity when X1, X2, and X3 are 6.29 g (100 g DM)−1, 11 h, and 1.5(vw−1). X1: sucrose concentration g (100 g DM)−1; X2: fermentation time (h); X3: liquid to solid ratio (vw−1).Figure2(B1) showed that there was a significant decrease in LGG growth from 8.97log10⁡(cfug-1) to 8.66log10⁡(cfug-1), when liquid to solid ratio was between 1.5 (vw−1) and 1.8 (vw−1) and sucrose concentration was between 6.29% and 10.48%, which was corresponding to the extremely significant interaction of X1X3, shown in Table 4. However, the greater LGG values were shown for a liquid to solid ratio of [1.2;1.65] and for fermentation time between 11 h and 13 h (Figure 2(C1)). This interaction is, indeed, confirmed by the interaction X2X3 shown in Table 4.


### 3.3.2. Application Response Surface Methodology to Free Amino Nitrogen Content (Y2)

The second-order model describing free amino nitrogen (FAN) content as a simultaneous function of sucrose concentration (X1), fermentation time (X2), and liquid to solid ratio (X3) is described by (4)Y2=12.83-0.554X1-0.528X3+0.118X12-0.432X22+0.14X32-0.665X12-0.158X13±0.096,where Y2 is the free amino nitrogen content, X12 is the interaction between sucrose concentration (X1) and fermentation time (X2), and X13 is the interaction between sucrose concentration (X1) and liquid to solid ratio (X3).Figure2(A2) represents the FAN response surface versus the actual level of fermentation time and sucrose concentration. The results of the Fisher test for analysis of variance (Table 3) revealed that the regression is statically significant at 100% of confidence level. Moreover, the value of the determination coefficient (R2=0.991) points out the goodness of the regression, which can be used to explain 99.1% of the total variation in the response.We can see from Table3 that X2 (fermentation time) and X23 (fermentation time × liquid to solid ratio) had no significant effect on free amino nitrogen content (p>0.05). The linear term of the fermentation time seems to have no significant effect on the response, contrary to the quadratic term. This last increase is when the fermentation time is between 10 h and 12 h. Under 10 h and below 12 h of fermentation, FAN keeps decreasing.


### 3.3.3. Application Response Surface Methodology to Total Acidity (Y3)

The application of the response surface methodology to total acidity yielded the following regression equation:(5)Y3=6.92-0.244X1+1.494X2-0.225X3-0.348X32±0.261,where Y3 is total acidity response and X1, X2, and X3 are the coded value of sucrose concentration, fermentation time, and liquid to solid ratio, respectively.The coefficients ofX12 (sucrose concentration × sucrose concentration), X22 (fermentation time × fermentation time), X12 (sucrose concentration × fermentation time), X13 (sucrose concentration × liquid to solid ratio), and X23 (fermentation time × liquid to solid ratio) were found to be statistically insignificant (p>0.05). Besides, the analysis of variance reveals that this regression is statically significant at 98.4% confidence level. Besides R2=97.7% points out that only 2.3% of the total variation in the response is not explained by the model. The linear regression coefficient of fermentation time (X2) puts in evidence the positive effect of this parameter on the response, making the total acidity clearly growing with the fermentation time. The response surface to predict the total acidity within the region under investigation is shown in Figure 2(B3). The quadratic term of fermentation time is insignificant. The maximum total acidity (8.25 μmol g−1) was obtained in 2.1% of sucrose concentration, 18 h of fermentation time, and 1.5 of liquid to solid ratio.In this study, total acidity increases with fermentation time, contrary to sucrose concentration and liquid to solid ratio.


## 3.3.1. Application Response Surface Methodology to ViableLb. rhamnosus GG (Y1)

The second-order model describing viableLb. rhamnosus GG as a simultaneous function of sucrose concentration (X1), fermentation time (X2), and liquid to solid ratio (X3) is described by (3) after neglecting the statistically insignificant terms (p<0.05): (3)Y1=8.986-0.068X1+0.316X2-0.096X3-0.302X22-0.087X32-0.155X13-0.107X23±0.066,where Y1 is the viableLb.rhamnosus GG response, X13 is the interaction effect between sucrose concentration (X1) and liquid to solid ratio (X3), and X23 is the interaction effect between fermentation time (X2) and liquid to solid ratio (X3).The regression coefficients obtained to predict polynomial model for LGG growth are summarized in Table3. The significance of all regression coefficient was checked by means of Student’s test (variation of data about mean value) and p values (probability) (Table 3). We can see that X12 (sucrose concentration × sucrose concentration) and X12 (sucrose concentration × fermentation time) were found to be statistically insignificant (p>0.05). The goodness of fit of the model was examined by F-test and the determination coefficient R2. The analysis of variance (Table 4) showed that this elaborated regression model was highly significant (p<0.1%) as is evident from the Fisher F-test and has a very low probability value [(pmodel>F)<0.1%]. The value of 1 (>0.05) for lack of fit implies that it is not significant compared to the pure error and that the model equation was adequate for predicting viableLb. rhamnosus GG (log10⁡cfug-1, Y1). The fitness of the model was further confirmed by a satisfactory value of determination coefficient (R2), which was calculated to be 0.980 (Y1). Furthermore, the predicted responses of the final quadratic model, along with the corresponding values observed, are given in Table 2. The agreement between the predicted results of the model and the experimental data is very strong as shown by a high value of correlation coefficient, R2pred (0.968 (Y1)). The residuals were examined to check the adequacy of the model. The residuals were plotted against the predicted value. No unusual behavior was notified (horizontal band) [19], confirming the adequacy of the regression model. The effect of interaction of the three components on growth of LGG was tested by contour plots for all possible combinations of factors, keeping one factor constant at a time. The interactions between the variables can be inferred from the shapes of the contour plots [20]. Circular contour plots indicate that the interactions between the variables are negligible. In contrast, elliptical ones indicate the evidence of the interactions (Figure 2).Table 3
Coefficients by regression analysis and their significance values obtained by ANOVA.
Nomenclature of the coefficients ViableLb. rhamnosusGG (log10 cfu g−1, Y1) Free amino nitrogen content (mg g−1, Y2) Total acidity (µmol eq. lactic acid g−1, Y3) Coefficient Ecart-type t.exp. Signif. % Coefficient Ecart-type t.exp. Signif. % Coefficient Ecart-type t.exp. Signif. % b 0 8.986 0.029 304.93 ∗  ∗  ∗ 12.830 0.043 299.04 ∗  ∗  ∗ 6.920 0.117 59.30 ∗  ∗  ∗ b 1 −0.068 0.023 −2.90 ∗ −0.554 0.034 −16.33 ∗  ∗  ∗ −0.244 0.092 −2.64 ∗ b 2 0.316 0.023 13.57 ∗  ∗  ∗ −0.034 0.034 −1.00 35.5% 1.494 0.092 16.19 ∗  ∗  ∗ b 3 −0.096 0.023 −4.13 ∗  ∗ −0.528 0.034 −15.55 ∗  ∗  ∗ −0.225 0.092 −2.44 ∗ b 11 −0.039 0.032 −1.22 26.1% 0.118 0.047 2.51 ∗ −0.285 0.127 −2.24 5.8% b 22 −0.302 0.032 −9.40 ∗  ∗  ∗ −0.432 0.047 −9.25 ∗  ∗  ∗ 0.015 0.127 0.12 90.5% b 33 −0.087 0.032 −2.70 ∗ 0.140 0.047 2.99 ∗ −0.348 0.127 −2.73 ∗ b 12 −0.005 0.033 −0.15 87.8% −0.665 0.048 −13.86 ∗  ∗  ∗ 0.250 0.130 1.92 9.5% b 13 −0.155 0.033 −4.70 ∗  ∗ −0.158 0.048 −3.28 ∗ 0.188 0.130 1.44 19.2% b 23 −0.107 0.033 −3.26 ∗ −0.028 0.048 −0.57 58.9% 0.138 0.130 1.05 32.8% Test Student (t.exp.); ∗: p<5%; ∗∗: p<1%; ∗∗∗: p<0.1%.Table 4
Analysis of variance and regression analysis.
Source Sum of squares DF Mean squares F-value Signif. % ViableLb. rhamnosusGG (log10 cfu g−1, Y1) Model 1.4966 9 0.1663 38.2972 ∗  ∗  ∗ Residual 0.0304 7 0.0043 Lack of fit 0.0001 3 0.0000 0.0033 100.0% Pure error 0.0303 4 0.0076 Total 1 .5270 16 Free amino nitrogen content (mg g−1, Y2) Model 7.4485 9 0.8276 89.9226 ∗  ∗  ∗ Residual 0.0644 7 0.0092 Lack of fit 0.0000 3 0.0000 0.0005 100.0% Pure error 0.0644 4 0.0161 Total 7.5129 16 Total acidity (µmol eq. lactic acid g−1, Y3) Model 20.0954 9 2.2328 32.7892 ∗  ∗  ∗ Residual 0.4767 7 0.0681 Lack of fit 0.0169 3 0.0056 0.0489 98.4% Pure error 0.4598 4 0.1149 Total 20.5721 16 DF: degrees of freedom;F: variance ratio; ∗∗∗: P (probability) <0.1%.Figure 2
Response surface and contour plots that represent the effect of fermentation time and sucrose concentration (A); liquid to solid ratio and sucrose concentration (B); liquid to solid ratio and fermentation time (C) and their interaction on (1) viableLb. rhamnosus GG cells when X1, X2, and X3 are 6.29 g (100 g DM)−1, 11 h, and 1.5(vw−1); (2) free amino nitrogen content when X1, X2, and X3 are 6.29 g (100 g DM)−1, 11 h, and 1.5(vw−1); (3) total acidity when X1, X2, and X3 are 6.29 g (100 g DM)−1, 11 h, and 1.5(vw−1). X1: sucrose concentration g (100 g DM)−1; X2: fermentation time (h); X3: liquid to solid ratio (vw−1).Figure2(B1) showed that there was a significant decrease in LGG growth from 8.97log10⁡(cfug-1) to 8.66log10⁡(cfug-1), when liquid to solid ratio was between 1.5 (vw−1) and 1.8 (vw−1) and sucrose concentration was between 6.29% and 10.48%, which was corresponding to the extremely significant interaction of X1X3, shown in Table 4. However, the greater LGG values were shown for a liquid to solid ratio of [1.2;1.65] and for fermentation time between 11 h and 13 h (Figure 2(C1)). This interaction is, indeed, confirmed by the interaction X2X3 shown in Table 4.


## 3.3.2. Application Response Surface Methodology to Free Amino Nitrogen Content (Y2)

The second-order model describing free amino nitrogen (FAN) content as a simultaneous function of sucrose concentration (X1), fermentation time (X2), and liquid to solid ratio (X3) is described by (4)Y2=12.83-0.554X1-0.528X3+0.118X12-0.432X22+0.14X32-0.665X12-0.158X13±0.096,where Y2 is the free amino nitrogen content, X12 is the interaction between sucrose concentration (X1) and fermentation time (X2), and X13 is the interaction between sucrose concentration (X1) and liquid to solid ratio (X3).Figure2(A2) represents the FAN response surface versus the actual level of fermentation time and sucrose concentration. The results of the Fisher test for analysis of variance (Table 3) revealed that the regression is statically significant at 100% of confidence level. Moreover, the value of the determination coefficient (R2=0.991) points out the goodness of the regression, which can be used to explain 99.1% of the total variation in the response.We can see from Table3 that X2 (fermentation time) and X23 (fermentation time × liquid to solid ratio) had no significant effect on free amino nitrogen content (p>0.05). The linear term of the fermentation time seems to have no significant effect on the response, contrary to the quadratic term. This last increase is when the fermentation time is between 10 h and 12 h. Under 10 h and below 12 h of fermentation, FAN keeps decreasing.


## 3.3.3. Application Response Surface Methodology to Total Acidity (Y3)

The application of the response surface methodology to total acidity yielded the following regression equation:(5)Y3=6.92-0.244X1+1.494X2-0.225X3-0.348X32±0.261,where Y3 is total acidity response and X1, X2, and X3 are the coded value of sucrose concentration, fermentation time, and liquid to solid ratio, respectively.The coefficients ofX12 (sucrose concentration × sucrose concentration), X22 (fermentation time × fermentation time), X12 (sucrose concentration × fermentation time), X13 (sucrose concentration × liquid to solid ratio), and X23 (fermentation time × liquid to solid ratio) were found to be statistically insignificant (p>0.05). Besides, the analysis of variance reveals that this regression is statically significant at 98.4% confidence level. Besides R2=97.7% points out that only 2.3% of the total variation in the response is not explained by the model. The linear regression coefficient of fermentation time (X2) puts in evidence the positive effect of this parameter on the response, making the total acidity clearly growing with the fermentation time. The response surface to predict the total acidity within the region under investigation is shown in Figure 2(B3). The quadratic term of fermentation time is insignificant. The maximum total acidity (8.25 μmol g−1) was obtained in 2.1% of sucrose concentration, 18 h of fermentation time, and 1.5 of liquid to solid ratio.In this study, total acidity increases with fermentation time, contrary to sucrose concentration and liquid to solid ratio.


## 3.4. Optimization of the Fermentation Conditions

Optimization of the Bsissa fermentation by LGG was carried out via a multiple response method called desirability (D) function to optimize different combinations of process parameters such as sucrose concentration, fermentation time, and liquid to solid ratio. The goal of optimization was to choose the best fermentation conditions that give us the higher biomass (log10⁡(LGG)>9±0.1) and free amino nitrogen (>13 ± 0.1) with a total acidity bigger than 6 μmol g−1 and lower than 7 μmol g−1. Figures 3(a), 3(b), and 3(c). show that desirability is higher when fermentation time is closer to 12 h (11-12 h), liquid to solid ratio closer to 1.2 (1.2–1.6), and sucrose concentration closer to 10.48% (8.4%–10.48%).Figure 3
Desirability fitted 2D surface that represent the effect of fermentation time and sucrose concentration (a); liquid to solid ratio and fermentation time (b); liquid to solid ratio and sucrose concentration (c), whenX1, X2, and X3 are 10.48 g (100 g DM)−1, 12 h, and 1.2(vw−1). X1: sucrose concentration g (100 g DM)−1; X2: fermentation time (h); X3: liquid to solid ratio (vw−1).
(a) (b) (c)Among all the optimum points, the best desirability value 88.4% was found in sucrose concentration of 10.48%, fermentation time of 12 h, and liquid to solid ratio of 1.2 (vw−1).Three test experiments were also carried out according to the optimum fermentation conditions. The result showed that the value of LGG growth, FAA content, and total acidity was closer to the values predicted earlier, with a low relative error (p<0.05), declaring the effectiveness of the RSM method to optimize the fermentation conditions of Bsissa.


## 3.5. Viability of LGG in Fermented Bsissa during Conservation

The Bsissa was fermented under the optimized conditions and then stored at 4°C. The viability of LGG in fermented Bsissa and the value of the pH and the total acidity over the refrigerated storage were monitored at 3-day intervals for 3 weeks. Figure4 shows that the number of LGG decreased significantly from 2.5 × 109 cfu g−1 (day 1) to 1.7 × 108 at day 21. Total viable count, coliforms, yeasts, and molds were not detected (<1 log10⁡(cfug-1)) during storage up to 21 days. Figure 5 showed the evolution of pH and total acidity during refrigerated storage of Bsissa. After 3 days of storage, the pH of the fermented Bsissa decreased from 4.3 to 4.1 and continues to decrease significantly (p<0.05) to 3.4 during the 21 days of refrigerated storage (average of 0.043 ΔpH day−1). The total acidity of the fermented Bsissa increased throughout 21 days of storage from 6.6 μmol/g to 10.23 μmol/g. Single factor ANOVA analysis showed that the pH and the total acidity changes were significant (p<0.05).Figure 4
Effect of storage time at 4°C on the viable LGG of fermented Bsissa.Figure 5
Effect of storage time on the pH (◆) and the total acidity (■) of fermented Bsissa.


## 4. Discussion

Since Bsissa has been traditionally consumed as a nonfermented beverage, carrying preliminary experiments was essential to test the fermentability of the cereal-mix byLactobacillus rhamnosus GG. After 18 h of fermentation, the viable cell counts were well above the suggested minimum limit of 7.7log10⁡(cfug-1) for a probiotic product to confer a therapeutic effect based on a 100 g daily dose [21]. The LGG strain used in the present study showed good growth in Bsissa. This aromatized cereal medium was appropriate for growth of LGG because it provides all the required nutrients. This could be attributed to the presence of considerable amounts of glucose in carob [22] and wheat [23]. Kocková and Valík [24] showed thatLb. rhamnosus GG was able to grow in cereal, pseudocereal, and leguminous substrates (buckwheat, dark buckwheat, barley, oat, soya, and chickpea, in combination with oat) with only a small content of residual water (from 48.8% to 79.8%), unlike in porridges or beverages (95%). The growth of LGG was lower in cereal and pseudocereal in comparison to porridges and beverages due probably to the lower water content.Application of probiotic cultures in cereal products, such as Bsissa, represents a great challenge. The formulation of the new probiotic Bsissa requires several factors to be considered such as final viable cells in the product, total acidity, and viability of probiotic during conservation. In this study, the main parameters of the fermentation, sucrose concentration g (100 g DM)−1, fermentation time (h), and liquid to solid ratio (vw−1), were optimized by using a Box-Behnken design at constant temperature 30°C.Results showed that the sucrose concentration poorly affects the LGG growth, contrary to fermentation time, which had the higher significant effect on cell growth. No interaction was revealed between the two variables, which correspond properly to the insignificant interaction (87.8%) (Table4). However, the interaction between sucrose concentration (from 6.29 to 10.48%) and liquid to solid ratio (from 1.5 to 1.8) leads to a decrease in LGG from 8.97log10⁡(cfug-1) to 8.66log10⁡(cfug-1). Liquid to solid ratio under 1.5 had no effect on LGG growth. The greater LGG values were shown for a liquid to solid ratio of [1.2;1.65] and for a fermentation time between 11 h and 13 h. After 13 h of fermentation, LGG shows a slight decrease, especially when the liquid to solid ratio is higher than 1.35. LGG growth shows a greater result when fermentation time and liquid to solid ratio have an opposite code sign, corresponding to fermentation time of [11;15] and liquid to solid ratio of [1.2;1.5]. This interaction is, indeed, confirmed by the interaction X2X3 shown in Table 4.Thus, maximum LGG was found when liquid to solid ratio was in the center point of the experimental design. Similar results were reported by Chen [25], who found that negative effect on the bacterial growth was shown when liquid to solid ratio was too low or too high. In fact, a poor liquid to solid ratio gave a little medium to satisfy microorganism growth; however, high amount created free medium and decreased the porosity of the liquid film on the surface and oxygen transfer needed for the growth of microorganisms.In our study, when sucrose concentration is 6.28 g (100 g DM)−1 and liquid to solid ratio is 1.5 (vw−1), LGG increased from 7log10⁡(cfug-1) to 8.99log10⁡(cfug-1) after 11 h of fermentation at 30°C.The cell numbers increased by1.99log10⁡(cfug-1) at the center point of the experiment. Comparable results were reported by Kocková et al. [26] and Kocková and Valík [24] during the fermentation of cereals (rye, barley, oat, and millet), pseudocereals (amaranth, buckwheat, and dark buckwheat), and legumes (soya and chickpea) substrates. The cell numbers increase greater than 2log10⁡(cfug-1) (7.40–8.80log10⁡(cfug-1)) after 10 h of fermentation at 37°C. Other studies reported that higher fermentation time was needed to obtain a similar result. Maize porridge with malted barley addition was fermented by LGG at 37°C and needed 24 h to increase probiotic cells by only 1.2log10⁡(cfug-1) [27]. Similar results were found during the lactic fermentation of the cashew apple juice (16 h) [28] and the mare’s milk (24 h) [29]. It has been suggested that the fermentation time and the final probiotic biomass is a function of the probiotic strain and the food matrix. The LGG growth in this study reached 9log10⁡(cfug-1) after 11 h of fermentation. The same amount of lactic bacteria was obtained in Togwa after 20 h of fermentation [30] and in York cabbage after 24 h [31]. In other studies, final lactic acid growth in food matrix was found to be 8log10⁡(cfug-1) such as cereal-based probiotic beverages (oats, barley, and malt substrates) [32]. The effect of sucrose concentration on lactic bacteria was controversial. In fact, sucrose did not support the good growth of theLb. Plantarum [33]. However, it supported the growth of theLb. casei in probiotic roselle juice [34]. Chan-Blanco et al. [35] and Nancib et al. [36] found thatL. casei subsp. rhamnosus is unable to consume the sucrose in an appropriate period of time. It uses firstly glucose as a carbon source, followed by fructose [37].FAN increased when the fermentation time is between 10 h and 12 h. Under 10 h and below 12 h of fermentation, FAN keeps decreasing. Similar results were described by [38]. They found that FAN content increased during the lag phase and at the end of fermentation of malt media byLb. acidophilus. In fact, the increase in FAN concentration during the lag phase is probably due to the hydrolysis of intracellular proteins. However, the increase in FAN concentration towards the end of incubation signaled the initiation of the disintegration of intracellular proteins, which was probably the very first step of cell autolysis. At the end of fermentation FAN concentration decreased linearly, even throughout the stationary phase to provide maintenance energy for the cells [10, 38].Total acidity increases with fermentation time, contrary to sucrose concentration and liquid to solid ratio. Reference [39] studied the effect of sucrose concentration on lactic acid production. The productivity of lactic acid byLactobacillus casei subspecies rhamnosus decreases with the high sugar concentration probably owing to substrate inhibition, the osmotic pressure, the low water activity, and the accumulation of toxic byproducts (e.g., high concentration of LA) especially after a long fermentation time [39]. However, in probiotic roselle juice fermented byLactobacillus plantarum andLactobacillus casei, the addition of sucrose (7 and 14%) at the beginning of fermentation increased the amount of titrable acidity by at least two times (more than 1.1% lactic acid) after 48 h of fermentation to reach a pH inferior to 3.5 [34]. This result was also confirmed by Costa et al. [40] during pineapple juice (86% sucrose) fermentation. It has been suggested that lactic acid production reduced the pH. At low pH value sucrose hydrolysis is enhanced. Then, when sucrose concentration increases, the acidity of the final product increases too.This study proves that decreasing liquid to solid ratio increased total acidity. Reference [41] found that maximum glutamic acid production byBrevibacterium was at maximum experimental moisture content (85–90%) due to homogeneous distribution of the nutrients. However, when the liquid to solid ratio is over 90%, the support may form clumps and affect negatively the bacterial growth [25].The Bsissa was fermented under the optimized conditions calculated by the experimental design (Section3.4). After 21 days of refrigerated storage, this fermented cereal food showed a high viability of LGG. In fact, the counts ofLb. rhamnosus remained viable above the minimum effective dose for therapeutic cultures of 106 cfu g−1 [42]. This result indicates that LGG is capable of surviving under highly acidic conditions during storage at 4°C. High survival rates of LGG in fermented products during storage under refrigerated conditions have been reported in earlier studies. Klu et al. [43] and Randazzo et al. [44] reported high survival of LGG (>6 logs) in peanut butter after 48 weeks of storage. The final pH after 21 days of storage in the Bsissa was 3.34, which is similar to the results (pH between 3.4 and 4.4) reported by Helland et al. [27] during the fermentation of a cereal based product.In this study, the viability of a probiotic strainLactobacillus rhamnosus GG was tested on a traditional nonfermented Tunisian aromatized cereal: “Bsissa.” A Box-Behnken design with the RSM was successfully applied to the optimization of the fermentation conditions of the Bsissa. Quadratic models were elaborated to describe the relationship between the LGG growth (Y1), the free amino nitrogen production (Y2), and the total acidity (Y3) and the fermentation time, the solid to liquid ratio, and the sucrose concentration. Among all the optimum points, the best desirability value (88.4%) was found in sucrose concentration of 10.48%, fermentation time of 12 h and liquid to solid ratio of 1.2 (vw−1). Under these conditions, LGG, free amino nitrogen content, and total acidity were, respectively, 9.1log10⁡(cfug-1), 12.95 mg g−1, and 6.46 μmol g−1. The Bsissa was fermented under these optimal conditions and the viability of LGG was high (>6 log10⁡(cfug-1)) during 21 days of storage. This study shows a new possibility to make an acceptable fermented product based mainly on cereals, leguminous plants, spices, and aromatics, which are suitable substrates that can support the high probiotic viability during cold storage for 21 days.The amount of free amino nitrogen was investigated in the nonfermented and the fermented Bsissa under the optimized condition. These values were 13.11 mg/g and 13.42 mg/g, respectively. Thus, the fermentation improved the nutritive value of the Bsissa by increasing the amount of free amino nitrogen. In addition, it was an efficient way to extend the shelf life of the Bsissa by the combination of the heat treatment and the fermentation. In conclusion, the fermentation contributed to improve the nutritive value of the final product and to formulate a new probiotic cereal meal with original aroma, different from the traditional mix. This kind of study can facilitate the development of new, fermented, nondairy, nutritionally well-balanced food products.



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*Source: 1742143-2017-01-18.xml*