2.1. Raw Materials and Sample Preparation

Ranjit raw rice variety and Ahu Kalogoria grain cultivar were considered in this study and purchased from local farmers of Goalpara district, Assam, NER, India. Ahu Kalogoria paddy germinated and sundried according to the method described by Veluppillai et al. [14]. The breakdown of germinated part and the husk is done in dheki, and the separation of the husk and germinated part from rice is done. The rice is then powdered into flour and are kept for the further fermentation process. The Ranjit raw rice was cooked for 10 min in induction using a 1:2 ratio of water. After cooking, it is kept to cool down.

2.2. Optimization of Process Conditions for Fermented Rice Product Production

A Box-Behnken central fractional factorial design was used to optimize the process conditions, viz., temperature, time, and initial pH in order to the enrichment of nutrition in pachoiwere observed and the responses chosen were carbohydrate, fats and proteins. To achieve the initial pH for optimization, lactic acid and sodium bicarbonate were used. Finally, for the optimization purpose, the same protocol was followed as indicated in natural fermentation with the only exception where the beaker was covered with aluminum foil. For pachoi preparation 100 g of Ranjit rice (cooked) was taken then 5 g of flour, 0.5 g of salt, and 7 g of sugar were thoroughly combined. Next, 30 mL of water was used to immerse 8 g of husk with germinated roots and shoots for 30 min, after which the mixture was filtered. 3 mL of pasteurized liquid milk Amul Taza (bought from the local market in the Goalpara district of Assam, NER, India) were added to the mixture along with the filtered water. Following complete mixing, the mixture was placed in a 500 mL beaker, covered with aluminum, and allowed to ferment in the incubator in different temperatures, time, and different pH. Then, amount of carbohydrates, fats, and proteins, was measured.

2.3. Protein Analysis

The Kjeldahl method can be used to convert the total nitrogen content into the total protein content. The conversion factor is 6.25 [15].

2.4. Carbohydrate Analysis

Carbohydrate analysis was carried out using the phenol sulphuric acid method by Guo et al. [16] with little modification. In this method, D-glucose was used as a standard solution. 500 mg sample was taken in 5 mL of 2.5 N HCL and heated in the water bath for 3 h then make up the volume up to 50 mL with distilled water. Standard was taken in five test tubes in different concentrations and 5% phenol, then 96% sulphuric acid was added. Different test tubes with different samples were taken, followed by the addition of phenol and sulfuric acid. Absorbance was taken in 490 nm using spectrophotometer, and the graph was prepared. From the graph, carbohydrate concentration in the sample was calculated.

2.5. Determination of Fat

Lipid content was estimated by extracting the sample with petroleum ether in Soxhlet apparatus for 8 h, and the amount of lipid was determined after the removal of petroleum ether [17]. The W₁ is the weight of the flask (initial weight). W₂ is the weight of the flask after evaporation of the ether, i.e., the final weight.

Fat% = W₂–W₁/sample weight × 100

2.6. Experimental Design and Statistical Analysis

RSM was used to find the optimum condition for the production of fermented pachoi. A Box-Behnken design with three factors and three levels was chosen to evaluate the combined effect of three independent variables, i.e., fermentation temperature, fermentation Time, and initial pH, coded as A, B, and C, respectively. After preliminary fermentation trials, the upper and lower limits for the independent variables were established. Temperature, time, and pH levels are 25–30°C, 6–24 h, and 4–7, respectively. Three levels of each variable were chosen, and 12 fermenting trials [Table 1] were performed for the evaluation of the optimized condition. A statistical tool (Design-Expert Version 7.0) was used to perform the computations, which included the choice of experimental points, randomization, analysis of variance (ANOVA), fitting of the models, and graphical displays. ANOVA was performed on the data to find variations across formulations that were statistically significant (P < 0.05).

Table 1: Experimental design for preparation of pachoi.

2.7. Production of Pachoi by Natural Fermentation

About 100 g of cooked Ranjit rice was mixed well with 5 g of flour, 0.5 g of salt, and 7 g of sugar. Then, 8 g of husk with germinating roots and shoots were soaked in 30 mL of water for 30 min and filtered it. The filtered water was added to the mixture along with 3 mL of pasteurized liquid milk purchased from the local market of Goalpara district, Assam, NER, India. After mixing it thoroughly, the mixture was transferred into a beaker (500 mL), covered by the Petri plate, kept for fermentation, and carbohydrate, fats, proteins, and alcohol were estimated. fat, carbohydrates, and proteins are estimated using the method explained in the subsection of method and materials section.

2.8. Estimation of Alcohol Content

Quantitative estimation of ethanol was performed using the potassium dichromate method [18]. 10–50 μL of absolute alcohol was taken in different test tubes as standard then the volume was made up to 500 μL by adding distilled water. 30 μL of test samples (juice) was taken and the volume makeup to 500 μL by adding distilled water. 1 mL of potassium dichromate reagent was added in each test tube, and then 2 mL of NaOH solution was added in each test tube and incubated at 50°C for 30 min. After incubation absorbance was measured at 600 nm wavelength by spectrophotometer. Moreover, a graph was drawn for the calculation of the ethanol quantity.

2.9. Determination of Total Phenolic Content (TPC)

Folin ciocalteu (FC) was used to estimate the TPC described by Dewanto et al. [19]. Each extract 120 μL was taken and followed by 2.5 mL of FC reagent (10%) added, and in between 8 min, 2 mL of sodium carbonate (Na₂CO₃ [7.5%]) was mixed. The samples were vortexed immediately and incubated in the dark for 30 min at 40 °C. Using a Shimadzu ultraviolet (UV)-1800 spectrometer (Shimadzu Inc., Kyoto, Japan), the absorbance of the blue color was measured at 760 nm. The TPC was reported as mg of gallic acid equivalents (GAE)/100 g of sample dry weight, using gallic acid as the standard (DW).

2.10. Determination of Flavonoid content (TFC)

The method of Khatun et al. [18] with little modification was used. Crude extract sample preparation in 1 mg/mL methanol stock. A sample of 200 microliters was taken from stock. Make up the volume up to 1 mL in all the test tubes with methanol. Followed by the addition of 0.5 mL of 5% NaNO₂ and 0.5 mL of 10% AlCl₃. After 5 min of reaction, 2 mL of NaOH (4%) solution was added and incubated at room temperature for 15 min and read the absorbance at 510 nm using a UV-VIS spectrophotometer. Quercetin is used as a standard solution. Blank preparation using methanol (1 mL) and all chemicals except the sample solution. Moreover, the total flavonoid content result is expressed using the graph as quercetin equivalent mg/100 g.

2.11. Determination of Antioxidant Activity by DPPH Method

This method was described by Dewanto et al. [19] with some modifications. DPPH gives strong absorbance at 517 nm (deep violet color) due to its unpaired electron. When this radical pairs off in the presence of a free radical scavenger, the absorption vanishes, resulting in decoloration or yellowish color. 200-μL sample extract and make up the volume up to 1 mL with methanol, and control as 1 mL methanol and 3 mL DPPH (0.004%).

DPPH scavenged% = A_con–A_test/A_con × 100

A_con–is the absorbance of the control reaction

A_test–is the absorbance of the test sample.

2.12. Determination of Total plate count (TPC)

A widely used technique for assessing microbial levels in food is the TPC method, which measures the population of viable bacteria. In this process, 25 mL of a well-blended food sample is mixed with 225 mL of sterile water in a flask to form a uniform suspension. From this mixture, 1 mL is taken and added to 9 mL of sterile water in a test tube, then thoroughly mixed using a vortex mixer. This dilution is labeled as 10^–1. The serial dilution process continues similarly, with each subsequent dilution clearly marked.

From each dilution level, 1 mL of the sample is dispensed into sterile Petri dishes. Then, 15 mL of nutrient agar, previously cooled to 45°C, is poured into each dish. The mixture is gently swirled to ensure uniform dispersion of microorganisms throughout the medium and is allowed to solidify. Once solidified, the plates are incubated upside-down at 37°C for 24–48 h to facilitate bacterial growth. After incubation, only those plates showing 30–300 colonies are selected for enumeration, as this range provides statistically reliable data and avoids errors due to excessive or insufficient colony numbers. Finally, the number of colony-forming units (CFU) per gram or milliliter of the food sample is calculated from the colony counts, providing a quantitative measure of microbial contamination [20].

log₁₀ CFU/g = log₁₀ (Number of colonies/volume plated × dilution factor).

3.1. Modeling of Experimental Data

Three-dimensional response surface plots were produced to elucidate the relationships between the responses and the experimental levels of each independent variable. The optimum level of each variable for maximum nutritional content was resolved using the response optimizer tool of the software. The following quadratic equation based on linear coefficients of independent variables calculates the optimal point of the given model.

X = C₀ + A* + B* + C* + AB* + AC* + BC* + A2* + B2* + C2*

Where A is Temperature, B is Time and C is pH.

3.2. Fat Content

The fat content range is between the range of 0.91–1.43%, as shown in [Table 1]. R² value of 0.89 indicates 89% of the goodness of fit. [Figure 1] shows that the points are close to the fitted line, indicating good fit [Figure 2] indicates the 3D surface of the fat content. The ANOVA data for the fat content is tabulated in Table 2.

Figure 1: Scatter plot of predicted value versus actual value of fat content from response surface methodology design. [Click here to view]

Figure 2: 3D surface graphical representation of fat content. [Click here to view]

Table 2: Analysis of variance table for fat content.

3.3. Carbohydrate Content

Carbohydrates are in the range of 39.3–74.25% as shown in [Table 1]. [Figure 3] shows that the points are not close to the fitted line that indicating there is average fit [Figure 4] indicates the 3D surface of the carbohydrate content. The ANOVA data for the carbohydrate content are tabulated in Table 3.

Figure 3: Scatter plot of predicted value versus actual value of carbohydrate content from response surface methodology design. [Click here to view]

Table 3: Analysis of variance table for carbohydrate content.

3.4. Protein Content

The protein content estimated by the Kjeldahl method and the protein range was 9.02–13.32%, as shown in [Table 1]. R² value of 0.91 indicates 91% of the goodness of fit. [Figure 5] shows that the points were close to the fitted line indicating a good fit. [Figure 6] indicates the 3D surface of the protein content. The ANOVA data for the protein content are tabulated in Table 4.

Figure 5: Scatter plot of predicted value versus actual value of protein content from response surface methodology design. [Click here to view]

Figure 6: 3D surface graphical representation of protein content. [Click here to view]

Table 4: Analysis of variance table for protein content.

After considering all the 3 responses; the sample with 1.32904% fat, carbohydrate of 51.7548%, and protein of 13.1355% was selected as the best sample with a desirability score of 0.686, as shown in Table 5. With a protein content of 13%, it can be claimed as highly nutritious for human health. Figure 7 shows the 3D surface graphical representation of desirability. According to Prakash Tamang et al. [21], during the fermentation procedure, the metabolic activity of bacteria produces a significant quantity of free amino acids. The amount of protein is directly correlated with the density of fermentative bacteria. Increased microbial growth results in higher protein content and nutritional content of the product altered by microbial density.

Table 5: Best sample based on maximum carbohydrate, protein, fat.

Figure 7: 3D surface graphical representation of desirability. [Click here to view]

Table 6 mentioned above indicates that there is little difference between the actual and observed values of fat, protein, and carbohydrates in relation to the values predicted by the software.

Table 6: Predicted versus observed value of carbohydrate, fat and protein in pachoi.

3.5. Fat, Carbohydrate, Protein and Alcohol Content of Natural Fermented Rice Product FP (N)

The pH of pachoi was dropped after 24 h of fermentation, from 5.9 to roughly 4.1. It has been documented that various fermented foods experience a pH drop during cereal fermentation. Lactic acid bacteria use the free sugars in cereal fermentation to make lactic acid, which causes the reduction of pH. pH fall increases the activity of microbial enzymes, which gives extra benefits of fermented meals. Furthermore, meals with low pH helps to preserve food by delaying the growth of several other potentially dangerous microbes [21-23]. The total carbohydrate content was analyzed using phenol sulfuric method. The carbohydrates content found in naturally fermented pachoi was 32.9%. Depending on the type of rice and herbs used in various fermented foods, the quantity of carbohydrates varies [24]. The total protein content of pachoi was analyzed by using the Kjeldahl method and found to be 12.4%. Protein content of traditional Indian fermented breakfast idli and dosa was found as 7.2 ± 1.10 g and 6.6 ± 0.25 g, respectively, and significantly less than pachoi [25]. However, according to the study of Krishnamoorthy et al. [25], no such change was found in the protein content of fermented rice product idli and non-fermented rice product Khaman.

The fat content of the naturally fermented rice sample was estimated at 1.1%. According to the study of Rajalakshmi and Vanaja [26], traditional Indian breakfast idli and dosa were prepared by using rice and millet mix separately through overnight fermentation. Experimental results revealed that fat content in rice-based idli and millet mix idli were 0.84 ± 0.35 g and 5.2 ± 0.28 g, respectively. However, the fat content in rice-based dosa and millet mix dosa was 1.96 ± 0.26 g and 9.8 ± 0.10g, respectively. According to the study of Hannah and Jyoti [27], the fat content of selroti, an ethnic fermented food, was increased after fermentation.

The total alcohol content estimated in pachoi was found to be 1.3% v/v. Alcohol is produced during the fermentation process due to microbial activity. There is a variation in alcohol concentration during the fermentation. According to the study of Ghosh et al. [28], the total alcohol content of the rice beer chuwak in Tripura was found to be 26–35% v/v.

3.6. Phenolic, Flavonoid, and DPPH Radical Scavenging Activity of two samples, FP (L) and FP (N)

The TPC of FP (L) and FP (N) is 563.66 ± 1.15 and 579 ± 1.15 (mg GAE/100 g). The total flavonoid content and DPPH Radical Scavenging content of both FP (L) and FP (N) are 467 ± 1, 478.66 ± 1.15 (mg QE/100 g) and 68.33 ± 1.52, 71.33 ± 0.57% respectively [Table 7]. According to Saharan et al. [29], phenolic and antioxidant content increases during fermentation this could be because of the important role that enzymes (including glucosidase, xylanase, and amylase) play in the breakdown of insoluble bound phenolics during fermentation. In rice, 46.98 ± 1.02 μM/g GAE was noted, and on the 5^th day of incubation, TPC increased up to eight or nine times more during fermentation. Antioxidant phenol compounds are created throughout the process of fermentation by microbes via a secondary metabolic process or are liberated from the matrix of the substrate by extracellular enzymatic action [30]. According to Ghosh et al. [28] 63.42 mg GAE/g total phenol and total Flavonoids 45.36 mg QE/g was observed in Haria a rice fermented food. The fermented rice had a significantly greater number of flavonoids and phenolics. One explanation for this could be that the strain’s production of microbial enzymes and acids helped to liberate the flavonoids and phenolics from their complex in dietary fiber and into a form that was easily soluble. On the 4^th day of fermentation, the rice-fermented food had a significant level of free radical scavenging activity. It is associated with fermented rice that has greater levels of flavonoids and phenolics [31]. Ghosh et al. [28] discovered that Haria had 82.54% antioxidant activity against DPPH free radicals.

Table 7: Phenolic, flavonoid and DPPH radical scavenging activity of two sample FP (L) and FP (N).

3.7. TPC of Two Samples FP (L) and FP (N)

The TPC at the initial stage, i.e., 0 h of fermentation, is 2.07 and 1.02 in FP (N) and FP (L) and then increases after 24 h of fermentation, as shown in Figure 8. The rise in TPC observed during rice fermentation is a typical and predictable outcome, indicating the expansion of microbial populations due to the presence of abundant nutrients and favorable environmental factors. This microbial activity significantly contributes to altering the sensory qualities-such as the consistency, taste, and shelf life-of the resulting fermented product. According to the study of [32], there is a considerable increase in microbial counts during traditional rice fermentation processes. As microorganisms break down the nutrients found in rice, they alter the surrounding environment-producing factors such as a mildly acidic pH, higher carbon dioxide levels, and various metabolic substances-that support the expansion of a wide range of microbial species, especially in the initial phases of fermentation. The starting ingredients, such as rice and water, naturally contain indigenous microorganisms. When fermentation begins, these native microbes become active, utilizing available resources and reproducing quickly, particularly when there are no chemical preservatives or antimicrobial agents present to restrict their growth [33]. When examining other traditional rice-based fermented drinks, clear variations in the levels of total bacterial populations were evident. For example, Haria, a customary fermented rice drink from West Bengal, showed a markedly elevated count of aerobic bacteria at the initial phase of fermentation, measuring 10.51 log₁₀ CFU/g. These aerobic microorganisms remained predominant throughout the early fermentation period, sustaining their high numbers until the 3^rd day [34]. On the other hand, Xaj Pani, a traditional starter used for rice wine preparation in Assam, showed a relatively reduced count of aerobic mesophilic bacteria, with values between 1.2 and 3.1 log₁₀ CFU/g [35].

Figure 8: Total plate count of FP (n) and FP (l). [Click here to view]

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