gupta2017 Development of fermented oat flour beverage as a potential probiotic vehicle

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Food Bioscience 20 (2017) 104–109

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Development of fermented oat flour beverage as a potential probiotic vehicle Mahak Gupta, Bijender Kumar Bajaj

MARK

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School of Biotechnology, University of Jammu, Jammu, India

A R T I C L E I N F O

A B S T R A C T

Keywords: Probiotics Lactobacillus plantarum M-13 Probiotic-fermented oat flour Avena sativa Honey

Dairy products have conventionally been used as carriers of probiotics. However, lactose intolerance, cholesterol, allergenic milk proteins, and the trend towards vegetarianism motivated the search for non-dairy products as potential probiotic carriers. Cereals may represent an excellent choice due to their high nutritional value and consumption all around the world. In the present study, an oat based fermented product ‘probiotic fermented oat flour’ (PFOF) was developed using a probiotic strain Lactobacillus plantarum M-13 and honey. The bacterial isolate L. plantarum M-13 has previously been characterized for several probiotic functional attributes. For PFOF development, process variables, i.e., concentrations of oat flour (8.0% w/v) and honey (3.0% w/v), and incubation time (48 h) were optimized based on a Box-Behnken design. Optimization enhanced the viable cell count of L. plantarum M-13 in PFOF from 14.4 log cfu/ml (unoptimized conditions) to 16.9 log cfu/ml, i.e. by 17.4%. With respect to linear terms, the variable incubation time had the most substantial positive influence on viable cell count of L. plantarum M-13, while with respect to interactive terms, the variables incubation time and honey had the maximum effect. Good viability of L. plantarum M-13 was observed in PFOF over a period of three wk of storage at room temperature and with refrigeration. Furthermore, sugar content decreased and lactic acid content increased during storage. The PFOF remained free of Enterobacteriaceae contamination, although fungal and yeast contaminants were found.

1. Introduction The interest in developing probiotics and/or prebiotics as dietary supplements is due to their potential to enhance the gut microbial composition and activities, and overall health (Rigo-Adrover et al., 2016). Fermented dairy products have so far been the predominant commercial carriers of probiotics, however, health concerns like lactose intolerance, allergies to milk proteins, cholesterol and saturated fatty acid content has prompted research on the development of non-dairy carriers of probiotics (Kumar, Vijayendra, & Reddy, 2015). Among various non-dairy options as potential probiotic vehicles, cereals offer many advantages, e.g., they are grown and consumed all over the world, and represent rich sources of energy, vitamins, and minerals. Besides, the presence of specific prebiotics, i.e., nondigestible carbohydrates (soluble fibers, oligosaccharides and resistant starches) in the cereals may stimulate the growth of probiotics and other beneficial gut bacteria (lactobacilli, bifidobacteria etc.), and help to maintain healthy gut conditions (Kumar et al., 2015). Furthermore, lactic acid bacteria (LAB) fermentation of cereals may enhance the bioavailability of several minerals, digestibility, and the organoleptic properties of foods

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(Enujiugha & Badejo, 2015). Probiotic fermented cereal grains like maize, sorghum, wheat, oat, millet, barley and rye are commonly used for preparing beverages, gruels and porridges (Kaur, Jha, Sabikhi, & Singh, 2014). Cereal based probiotic products have been developed previously like a probiotic wheat bread (Soukoulis et al., 2014), a probiotic oat flake beverage (Luana et al., 2014) and a probiotic ragi malt (VidyaLaxme, Rovetto, Grau, & Agrawal, 2014). Cereal based multiple probiotic beverages were produced by fermentation of oat, barley and malt substrates (Salmeron, Thomas, & Pandiella, 2014). Among various cereals as probiotic vehicles (Bernat, Chafer, Martinez, Garcia, & Chiralt, 2015; Luana et al., 2014; Salmeron et al., 2014) oat may be an apt choice due to its abundant functional properties. Oat (Avena sativa) is one of the important annual crops grown in temperate regions of the world. Oat is rich in health benefitting components like βglucan, dietary lipids, proteins, starch, and antioxidant phenolic compounds, and is known to have anticancerous and hypocholesterolaemic properties (Rasane, Jha, Kumar, & Sharma, 2015). In addition, availability of soluble fibers, both oligosaccharides and polysaccharide in oat have a prebiotic effect (Kaur et al., 2014). Despite this, fewer reports

Corresponding author. E-mail address: [email protected] (B.K. Bajaj).

http://dx.doi.org/10.1016/j.fbio.2017.08.007 Received 14 September 2016; Received in revised form 12 August 2017; Accepted 13 August 2017 Available online 12 September 2017 2212-4292/ © 2017 Elsevier Ltd. All rights reserved.

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M. Gupta, B.K. Bajaj

2.2. Fermentation for production of ‘probiotic fermented oat flour’ PFOF

are available on usage of oat as a potential probiotic carrier (Gupta, Cox, & Ghannam, 2010; Bernat et al., 2015). Honey, a natural sweetener, contains several bioactive compounds such as vitamins, phenolics, flavonoids and fatty acids. Honey has potential biological activities such as antioxidant, immunomodulatory, antiproliferative and neurological properties (Muhammad et al., 2016). Additionally, honey has a prebiotic potential due to the presence of fructooligosaccharides. Thus, honey may be a suitable component of functional foods (Das et al., 2015). Statistical based optimization provides insight into process dynamics, and illustrates the complex interactions between the process variables, contrary to the conventional one-variable-at-a-time approach (Singh & Bajaj, 2016). Response surface methodology (RSM) based optimization has been used for development of new products and processes, and/or for the improvement of existing ones (Gupta, Sharma, Singh, Gupta, & Bajaj, 2015). The Box-Behnken design, a type of RSM is suitable for industrial research as it is an economical design, and requires only three levels for each factor (Tekindal, Bayrak, Ozkaya, & Genc, 2012). Various probiotic foods have been developed using statistical optimization (Selvamuthukumaran & Khanum, 2015). A probiotic cereal-based baby food was developed by fermentation with Lactobacillus casei and L. plantarum, using RSM (Rasane et al., 2015). Similarly, a process for production of probiotic oat milk was optimized using Lactobacillus reuteri and Streptococcus thermophilus as starter cultures (Bernat et al., 2015). Lactobacillus plantarum M-13 was previously isolated from kalarei, and characterized for functional attributes (Gupta, 2015; Gupta & Bajaj, 2017). Kalarei is a locally made fermented food product that is produced by fermentation of cow or buffalo milk with mixed cultures of lactic acid bacteria. It is a dense cheese that is usually consumed with bread after sauting and salting. Kalarei may be a suitable source for targeting novel probiotics. The isolate L. plantarum M-13 showed excellent survival under simulated gastrointestinal tract (GIT) conditions, and had several desired functional properties like adhesion ability, autoaggregation and coaggregation potential, extracellular enzyme producing ability, antibacterial activity and antibiotic susceptibility (Gupta, 2015; Gupta & Bajaj, 2017). Considering the need for non-dairy based probiotic products, the current study was done to develop probiotic fermented oat flour (PFOF) by using L. plantarum M-13, and honey. The fermented product PFOF was studied for the viability of L. plantarum M-13, and other biochemical properties.

A suspension of oat flour was prepared in distilled water (8%, w/v), and sterilized. Honey was pasteurized at 90 °C for 20 min, and added aseptically (3%, w/v) into the oat flour suspension. An overnight grown culture of L. plantarum M-13 was inoculated (1%, v/v) into the oat flour suspension to get an initial cell count of 109/ml. The contents were fermented in 250 ml Erlenmeyer flasks at 37 °C with shaking (180 rpm). Samples were drawn at different time intervals, and examined for viability of the L. plantarum M-13 (standard plate count technique), titratable acidity (as lactic acid content), sugar content and pH. For viability analysis of the L. plantarum M-13, 1.0 ml sample of PFOF was subjected to vigorous vortex, and then serially diluted with 9.0 ml of sterile saline (0.1% NaCl, w/v). Then 0.1 ml of appropriately diluted PFOF sample was spread plated on MRS agar. The plates were incubated at 37 °C for 72 h. The colonies appeared on the plates were counted as colony forming units (cfu), and results were expressed as log cfu/ml. For measurement of other parameters of PFOF, i.e., titratable acidity (as lactic acid content), sugar content and pH, PFOF sample was centrifuged at 10,000 × g for 10 min (Eppendorf Centrifuge 5804 R, Hamburg, Germany), and supernatant was used for analysis. For the titratable acidity assay, 10.0 ml of centrifuged PFOF supernatant was titrated against 0.1 N NaOH using phenolphthalein as an indicator (pH 8.3). Titration was initiated by adding 2–3 drops of phenolphthalein to the sample, followed by drop wise addition of 0.1 N NaOH with continuous swirling. The appearance of a stable light pink color indicated the point of neutrality, i.e., the end point of the titration. The amount of NaOH used (titre) was recorded, and titratable acidity was expressed by using the following equation: 1.0 ml of 0.1 N NaOH = 0.0090 g of lactic acid. The total sugar content in PFOF was quantified by using the phenol sulphuric acid method (Dubois, Gilles, Hamilton, Rebers, & Smith, 1956). In a hot acidic medium glucose is dehydrated to hydroxymethyl furfural and forms a colored product with phenol that has an absorption maximum (λmax) at 490 nm (UV–VIS Spectrophotometer UV-1800, Shimadzu Corp., Kyoto, Japan). One ml of the appropriately diluted PFOF supernatant was mixed with 1.0 ml of phenol (5%, v/v), and then 5 ml of sulphuric acid (96%, v/v) was added. The contents were incubated at room temperature for 20 min, and then at 30 °C in a water bath for 30 min. The absorbance was measured at 490 nm. The amount of sugar in the sample was determined by using glucose as the standard. The pH of the PFOF sample was determined using a pH meter (Hanna Instruments, Woonsocket, RI, USA).

2. Materials and methods

2.3. RSM based optimization of variables for development of PFOF

2.1. Chemicals and raw materials, probiotic organism

Three process variables, i.e., amounts of oat flour and honey, and incubation time (time period of fermentation) were optimized using RSM (Design-Expert 6.0 software, Stat Ease, Inc., Minneapolis, MN, USA), for production of PFOF. The low and high values of the variables were used at three coded levels (−1, 0, +1) (Tables 1 and 2). The significance level (p-value) of each variable was determined using the Student's t-test with p < 0.05 indicating a statistically significant difference. A total of 17 experiments were carried out based on the design

All the chemicals used were of analytical grade and were obtained from Sigma-Aldrich Chemicals Ltd. (St. Louis, MO, USA), HiMedia Laboratories Ltd. (Mumbai, India), Ranbaxy Fine Chemicals Ltd. (Mumbai, India), Qualigens Fine Chemicals Ltd. (Mumbai, India), and Merck and Co. Inc. (White House Station, NJ, USA). Whole oat grains were obtained from a local grain market (Kanak Mandi, Jammu, India). In India oat is cultivated for fodder and grain purposes. The oat grains were washed, and dried at 40 °C in a hot air oven (Optics Technology, New Delhi, India) for 12 h, and then ground in a blender (Bajaj Electricals Ltd., Mumbai, India). The ground oat flour was sieved to get the particle size of less than 2 mm. The sieved oat flour was stored in an airtight container. Honey was purchased from a local horticulture farm in Jammu, where honey bees had access to mustard flowers. The probiotic organism used in the current study was L. plantarum M-13, an isolate from kalarei. For carrying out various experiments L. plantarum M-13 was grown in MRS broth for 18 h at 37 °C with shaking (180 rpm) to reach log phase (Andrabi, 2014; Andrabi, Bhat, Gupta, & Bajaj, 2016).

Table 1 Range of independent variables for Box-Behnken design based on RSM for production of ‘probiotic-fortified oat flour’ PFOF. Independent variable

Oat flour Honey Incubation time

105

Unit

%, w/v %, w/v h

Symbol

A B C

Coded level -1

0

+1

3 2 6

5 3 27

8 4 48

Food Bioscience 20 (2017) 104–109

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and 28 °C (PDA) for 24 h and 72 h, respectively, and then examined for the presence of contamination.

Table 2 The experimental variables and their range for the Box-Behnken design of RSM. Study type: response surface

Initial design: Box-Behnken

2.5. Statistical analysis Experiments: 17 Response Y1

Name Log cfu/ml

Unit

Design model: quadratic

Factor A B C

Name Oats Honey Incubation time

Units % (w/v) % (w/v) h

Lower 3 2 6

All the experiments were performed in triplicates and the results were expressed as mean values ± standard deviation. The statistical analysis of the data was performed using the IBM SPSS software version 25. The data values of parameters between the wks were analysed using the repeated measure ANOVA, while data values of parameters within wk were analysed using paired T-test. The p value ≤ 0.05 was used to statistically validate the date.

Higher 8 4 48

3. Results and discussion

Table 3 Experimental and predicted response for growth (log cfu/ml) of L. plantarum M-13 using a Box-Behnken design. Run order

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 a

Experimental variablea

L. plantarum M-13, an isolate from kalarei, showed desirable functional probiotic attributes like adhesion and aggregation potential, enzyme producing ability, antibiotic susceptibility and antibacterial activity (Gupta, 2015; Gupta & Bajaj, 2017). In the current study L. plantarum M-13 was further investigated for its potential to produce PFOF, as a non-dairy carrier of probiotics.

Response (log cfu/ml)

A

B

C

Experimental

Predicted

5.0 5.0 8.0 2.0 2.0 5.0 5.0 5.0 5.0 5.0 2.0 8.0 5.0 2.0 8.0 8.0 5.0

3.0 4.0 2.0 3.0 4.0 3.0 3.0 3.0 2.0 2.0 2.0 3.0 4.0 3.0 4.0 3.0 3.0

27.0 48.0 27.0 48.0 27.0 27.0 27.0 27.0 48.0 6.0 27.0 48.0 6.0 6.0 27.0 6.0 27.0

15.5 15.6 15.4 15.7 15.5 15.4 15.8 15.2 15.7 15.4 15.1 16.0 14.5 15.4 15.3 15.4 15.5

15.2 15.6 15.3 15.2 15.3 15.3 15.8 15.3 15.5 15.3 15.2 16.1 14.8 15.3 15.2 15.3 15.5

3.1. Development of PFOF Oats are rich in health benefitting nutritional components like antioxidant phenolic compounds, β-glucan, proteins, starch, and dietary lipids, and are known to have anticancerous and hypocholesterolaemic properties. Therefore, oats due to their functional attributes may represent the best choice among cereals as a potential probiotic carrier (Enujiugha & Badejo, 2015; Salmeron et al., 2014). The food matrix intended for use as a probiotic vehicle must support high survival of probiotics for prolonged time periods. In our previous study (Gupta & Bajaj, 2017) high viability of L. plantarum M-13 (14.4 log cfu/ ml) was observed in PFOF (each w/v, oat flour 8%, and honey 3%) after 72 h of fermentation which substantiated the concept that PFOF may be a good food matrix that adequately supports the growth of probiotic organism (Gupta & Bajaj, 2017). This prompted us to optimize bioprocess for development of PFOF using design of experiments. The experiments were done to optimize the process variables for PFOF production by using a Box-Behnken design of response surface methodology (Table 3). Analysis of variance (ANOVA) was done to determine the significance of the model and the model terms (Table 4). The regression equation generated for the model was as follows:

(A: Oat flour, %w/v; B: Honey, %w/v, C: Incubation time, hours).

matrix (Table 3) and the respective response values (Y) were determined. The response values were the average values of three different experiments. Multiple regression analysis was used to analyze the data, and a polynomial equation was derived. The model was evaluated for analysis of variance (ANOVA). The analysis included the Fisher's Ftest (overall model significance), its associated probability p (F), correlation coefficient R, and determination coefficient R2. The response surface plots (three-dimensional plots) were evaluated to understand the interactions between the variables, and to determine the optimum level of each variable. The point prediction tool of the model was used for determining the optimal level of variables. Each variable was varied individually in the point prediction tool of the design software keeping others at constant level, until the maximum predicted response was achieved. Then a combination of the predicted values (optimum values) of the variables was used for executing the experiment for validation of the model.

Y = +15.50 + 0.067A − 0.089B + 3.75C + 0.068A2 − 0.25B2 + 0.058C2 + 1.69AB + 0.91AC + 2.37BC. Table 4 Results of ANOVA obtained for growth (log cfu/ml) of L. plantarum M-13 after using a Box-Behnken design.

2.4. Analysis of PFOF during 4 wk of storage The PFOF prepared under optimized conditions was evaluated for the cell viability, total sugar and lactic acid content, and changes in pH, over a period of 4 wk of storage at room temperature (25 °C) and with refrigeration (4 °C). Furthermore, the PFOF was monitored for contamination with members of Enterobacteriaceae, yeast and fungi. Eosine methylene blue (EMB) agar plates were used for determining contamination of PFOF by Enterobacteriaceae, while potato dextrose agar (PDA) plates were used for determining yeast/fungal contamination. An appropriately diluted sample of PFOF was spread plated on either of these medium plates. The plates were incubated at 37 °C (EMB agar) 106

Source

Sum of square

DF

Mean square

F value

Prob > F

Model A B C A2 B2 C2 AB AC BC Residual Lack of fit Pure error Cor total

1.26 0.036 0.063 0.67 0.018 0.26 0.014 0.068 0.020 0.13 0.45 0.24 0.20 1.71

9 1 1 1 1 1 1 1 1 1 7 3 4 16

0.14 0.036 0.063 0.67 0.018 0.26 0.014 0.068 0.020 0.13 0.064 0.081 0.051

32.20 0.57 0.98 10.41 0.28 4.00 0.22 1.06 0.31 2.08

0.0003 0.088 0.058 0.0007 0.069 0.085 0.069 0.001 0.638 0.091

1.55

0.331

Significant

Significant

Significant

Not significant

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Fig. 1. Response surface plots showing interaction between oat flour and honey (a), incubation time and oat flour (b), incubation time and honey (c), and perturbation plot (d).

on response as a stand-alone variable as well as in interactive terms. Validation of the statistical model was done by carrying out the experiments using the optimum values of the variables (oat flour 8% w/v, honey 2.89% w/v, and incubation time 48 h) determined based on point prediction tool. The actual experimental response (16.9 log cfu/ ml) was quite close to the predicted response (16.5 log cfu/ml), thus, substantiating the validity of the model. The statistical optimization of variables enhanced the viable cell count of L. plantarum M-13 in PFOF by 17%, i.e., 16.9 log cfu/ml under optimized conditions vs 14.4 log cfu/ml under unoptimized conditions. Statistical optimization has widely been used for the development of cereal based fermented food products. Optimization of variables like glucose, fructose, inulin and starter cultures (probiotic cultures L. reuteri and S. thermophilus) was done to produce a fermented oat-milk formulation. A survival of > 107 cfu/ml was reported for both the probiotic cultures (Bernat et al., 2015). Similarly, various variables like oil, xanthan, oat flour and storage time were optimized using RSM to produce a low-in-oil oat based salad dressing. A survival of 108 cfu/g was reported after 7.5 wk of refrigerated storage (Mantzouridou, Karousioti, & Kiosseoglou, 2013). Variables like wheat flour and wheat bran (from sprouted wheat), oat and stabilizers were optimized using response surface methodology to produce a probiotic beverage using Lactobacillus acidophilus NCDC-14 and L. acidophilus NCDC-14. The viable cell count of 10.4 log cfu/ml was attained after 8 h of fermentation (Sharma, Mridula, & Gupta, 2014).

The equation describes the variation in response Y (log cfu/ml) as a function of variables, i.e., oat flour (A), honey (B) and incubation time (C). The model F value and value of Prob > F indicated the significance of the model (Table 4). From the linear terms, incubation time (C) was found to have the most significant positive effect on response (log cfu/ ml), while for the squared terms oat flour (A) and incubation time (C) had positive effects on the response as shown in regression equation. Furthermore, the interactive effect of oat flour (A) and honey (B) was significant. The non-significant lack of fit value indicates the strength of the model. The low value of the coefficient of variation (CV 4.45) indicated the reliability of the experiments and a high degree of precision. The high value of the coefficient of determination R2 further substantiated the goodness of the fit of the model. The predicted R2 of 0.94 indicated good agreement between experimental and predicted responses. The value of the Adeq precision, i.e., signal to noise ratio of 6.71 indicated an adequate signal. The interactive effects of variables on the response were studied using response surface plots (Fig. 1). The interactive influence of incubation time and honey (1c) had the maximum effect on the response (cfu/ml of L. plantarum M-13), followed by oat flour and honey (1a), and incubation time and oat flour (1b). Perturbation plots (1d) show the increase or decrease in the response when the value of each variable is changed keeping other variables constant with respect to the chosen reference point. The reference point signifies the mid-value of the response and is set as zero by default. When the variable C (incubation time) was changed from the reference point it had the maximum positive effect on the response among all the variables. The variable A (oat flour) had a marginal positive effect while the variable B (honey) had an appreciable negative effect on the response. Thus, the incubation time (C) appeared to have a strong positive effect

3.2. Biochemical analysis of PFOF The PFOF prepared using the optimized conditions was analysed for various biochemical parameters. Analysis of PFOF after 48 h of fermentation showed that it had an acid and sugar content of 107

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Table 5 Viability of L. plantarum M-13 during storage at different temperatures and biochemical properties of PFOF. Time (wks)

Parameters studied# Survival (Log cfu/ml)

1 2 3 4

Acid production (g/100 ml)

pH

Total sugars (g/100 ml)

Room temperature (25 °C)

Refrigerated storage (4 °C)

Room temperature (25 °C)

Refrigerated storage (4 °C)

Room temperature (25 °C)

Refrigerated storage (4 °C)

Room temperature (25 °C)

Refrigerated storage (4 °C)

16.31 ± 0.02 a, e 16.11 ± 0.02b, e 16.09 ± 0.01c, e 0.00 ± 0.00d, e

16.26 ± 0.01a,e 16.02 ± 0.03b, e 15.90 ± 0.01c, e 13.89 ± 0.02d, e

1.32 ± 0.01a, f 1.44 ± 0.04b, f 1.48 ± 0.03c, f 2.16 ± 0.01d, f

0.90 ± 0.01a, f 0.94 ± 0.02b, f 1.26 ± 0.03c, f 1.74 ± 0.01d, f

3.8 ± 0.00a, G 3.0 ± 0.03b, g 3.0 ± 0.01c, g 2.0 ± 0.02d, g

4.0 ± 0.03a, G 3.9 ± 0.03b, g 3.9 ± 0.01c, g 3.8 ± 0.02d, g

0.45 ± 0.01a, H 0.38 ± 0.05b, H 0.32 ± 0.02c, H 0.05 ± 0.01d, H

0.47 ± 0.05a, H 0.46 ± 0.02b, H 0.30 ± 0.03c, H 0.05 ± 0.01d. H

# The statistical significance of the data is indicated by lower case alphabets (a, b, c, d, e, f, g, h) while the upper case alphabets represent the insignificance (A, B, C, D, E, F, G, H). First four letters (A, a - D, d) indicate the significance/ insignificance of data between the wks, while the next four alphabets (E, e- H, h) show the significance/ insignificance of the data within the wk.

lactic acid as their major end product. The amount of acid produced not only exerts a profound effect on the viability of probiotic bacteria in a food matrix but influences the functional and organoleptic characteristics of food which in turn may influence the consumers’ acceptability of the product. Similar to the current study, a novel cereal based probiotic product showed an increase in titratable acidity from 0.09% to 0.18% (w/w) after 30 days of storage with refrigerated conditions (Gautam & Sharma, 2014). Likewise, titratable acidity of a probiotic whey-pineapple beverage increased from 0.54% to 0.89% (w/v), after 28 days of storage at ambient temperature (Shukla, Jha, & Admassu, 2013). All the stored PFOF samples showed a pH reduction. An inverse relationship was observed between the amount of acid produced and pH of stored PFOF samples (Table 5). The pH reduction was more prominent for room temperature stored samples (pH decreased from initial 3.8 to 2.0) than the refrigerated ones (pH decreased from initial 4.0 to 3.8). The minimal pH reduction of samples stored under refrigerated conditions was attributed to the low metabolic activity of the probiotic, and hence low acid production. A probiotic Prunus mume puree had a final pH of 3.0 from an initial of 3.5 after 10 days of storage at room temperature (Yu et al., 2015). However, insignificant changes in pH (from an initial of 5.5 to 5.7) were observed for a probiotic cheese like product over a period of 4 wk (Cichosz, Aljewicz, & Nalepa, 2014). The sugar content of PFOF decreased with storage time (Table 5). The total sugar decreased from an initial value of 0.45 to 0.05% w/v, and from 0.47% to 0.056% w/v, for samples stored at room temperature and with refrigeration, respectively. So there was almost complete utilization of PFOF sugars by L. plantarum M-13. Coda, Lanera, Trani, Gobbetti, and Cagno (2012) developed a yogurt like beverage containing a mixture of cereals, soy and grape must, using two strains of L. plantarum and observed that sugar level was decreased by 90–92% of that of initial value after 4 wk of storage. Similar to the current study, Yu et al. (2015) observed a decrease in the total sugar content of a probiotic Prunus mume puree, from an initial of 0.1 to 0.066% after 10 days of storage at room temperature. Similarly, decreased carbohydrate content from an initial of 20% to 11.5% (w/v) was observed in a pomegranate and vanilla fortified synbiotic yogurt beverage after 9 wk of storage (Walsh, Cheng, & Guo, 2014). PFOF must be investigated further for in-depth nutritional, sensory, organoleptic characteristics, and overall appeal of the product. Attempts may be made to enhance nutritional value and shelf life of PFOF. Lactic acid bacteria may synthesize several vitamins, exopolysaccharides, enzymes, antioxidant, antimicrobial, and cholesterol lowering substances which may contribute towards enhanced functional attributes of foods. Sensory properties of foods like color, flavour, aroma, texture, rheological properties, consistency etc. of PFOF also needs further investigation.

0.45 ± 0.02% w/v, and 0.85 ± 0.21% w/v, respectively, and pH at 4.1 ± 0.2. There was no contamination with fungi, yeast and Enterobacteriaceae in PFOF after 48 h of fermentation. Luana et al. (2014) developed a probiotic oat flakes yogurt using L. plantarum LP09, and reported the viable count, titratable acidity, pH and sugar content, respectively, of 6.5 × 108 cfu/ml, approximately 2.4%, w/v, 4.2% and 29.7% (w/v), after 12 h of fermentation. A probiotic walnut beverage was developed using kefir grains, and the viable cell counts of lactococci, lactobacilli and yeast in the fermented beverage were 8.2 × 107, 1.1 × 108and 1.0 × 106 cfu/ml, respectively. The titratable acidity and pH of the beverage, respectively, were 0.65% w/v, and 4.16, after 12 h of fermentation (Cui, Chen, Wang, & Han, 2013). 3.3. Analysis of PFOF during storage Analysis of PFOF after storage at room temperature and refrigerated conditions for different time intervals showed that there was an excellent survival of L. plantarum M-13 for three wk (Table 5). However, after the 4th wk, viability of L. plantarum M-13 was completely lost in the PFOF samples stored at room temperature, while a moderate decrease in the cell count (3.0 log cfu/ml) was observed for the refrigerated samples. The complete inhibition of L. plantarum M-13 in PFOF samples stored at room temperature after the 4th wk could be ascribed to high acid production, and the accompanying pH reduction. Low pH might have been detrimental for survival of L. plantarum M-13. However, L. plantarum M-13 seemed to have low metabolic activity in refrigerated samples, and hence relatively less acid production and pH reduction was observed. Therefore, good viability of L. plantarum M-13 was seen even after the 4th wk of refrigerated storage. Lactobacillus acidophilus and Bifidobacterium animalis had viability of 6.8 and 8 log cfu/g, respectively, in a soy based probiotic product after 21 days of storage at 4 °C (Matias, Bedani, Castro, & Saad, 2014). However, two probiotic Lactobacillus rhamnosus strains showed a viability of over 10 log cfu/g in a chestnut based probiotic mousse during 3 months at 15 °C (Romano et al., 2014). Similarly, a probiotic ice-cream made from goat milk showed a viability of 107 to 108 cfu/g for probiotic cultures up to 52 wk of storage at –20 °C (Ranadheera, Evans, Adams, & Baines, 2013). Thus, survival of probiotics varies due presumably to the make-up of the supporting matrix, and the details of the storage conditions along with the characteristics of the probiotic microorganism. Analysis of PFOF samples showed that lactic acid content increased with prolonged storage, and higher amounts of acid were produced at room temperature than at refrigerated conditions (Table 5). Lactic acid content increased from 1.32% to 2.16% w/v, at room temperature, and from 0.90% to 1.74% w/v, with refrigeration, after 4 wk. Elevated lactic acid production at room temperature is attributed to higher metabolic activity of L. plantarum M-13 at room temperature. Probiotic bacteria are either homo or hetero-fermentative in nature, and produce 108

Food Bioscience 20 (2017) 104–109

M. Gupta, B.K. Bajaj

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3.4. Analysis of PFOF for Enterobacteriaceae, fungi and yeast contamination During storage, budding yeast appeared in both samples stored at room temperature and with refrigeration during the first wk. By the end of the second wk fungal contaminations were observed in both samples. By the fourth wk, the room temperature samples were completely contaminated with fungi and yeast, and so were samples stored with refrigeration but the microbial load (yeast and fungi) was lower in refrigerated samples. However, no contamination with Enterobacteriaceae was observed even after 4 wk for either of the samples. This might be due to the acidic conditions found in the samples which were not amiable for the growth of bacteria. Coda et al. (2012) detected yeasts but no contamination of Enterobacteriaceae in various probiotic cereal products (rice, oat, soy and an emmar-based yogurt-like beverage) after storage. Similarly, Gautam and Sharma (2014) observed no contamination with mesophilic aerobic bacteria, yeast and molds in a novel cereal based probiotic product. 4. Conclusion It may be concluded from the current study that the PFOF due to its potential capability to support the growth and survival of probiotic microorganism, may potentially be developed as an appropriate nondairy carrier for probiotics. Statistical optimization is a powerful, economic and rapid means for process development. Conflict of interest statement The authors declare no conflict of interest, i.e., scientific, financial or otherwise. Acknowledgements Dr. Bijender Kumar Bajaj gratefully acknowledges VLIR-UOS (Government of Belgium) for ‘Short Research Stay Scholarship’ (SRSScholarship) at the Department of Bioscience Engineering, University of Antwerp, Antwerpen, Belgium; Department of Science and Technology (Government of India), for granting Research Project (Ref. SR/SO/BB66/2007), and Department of Biotechnology (DBT), Government of India, for financial support. Authors thank Dr. Parmil Kumar, Associate Professor, Department of Statistics, University of Jammu, for statistical analysis of data, and the Director, School of Biotechnology, University of Jammu, Jammu, for laboratory facilities for undertaking probiotics research. References Andrabi, S. T. (2014). Probiotic attributes of isolated lactic acid bacteria for probiotic-fortification of fruit juices and soymilk (M.Phil. Biotechnology thesis)Jammu, India: University of Jammu. Andrabi, S. T., Bhat, B., Gupta, M., & Bajaj, B. K. (2016). Phytase-producing potential and other functional attributes of lactic acid bacteria isolates for prospective probiotic applications. Probiotics and Antimicrobial Proteins, 8, 121–129. Bernat, N., Chafer, M., Martinez, G. C., Garcia, R. J., & Chiralt, A. (2015). Optimisation of oat milk formulation to obtain fermented derivatives by using probiotic Lactobacillus reuteri microorganisms. Food Science Technology International, 21, 145–157. Cichosz, G., Aljewicz, M., & Nalepa, B. (2014). Viability of the Lactobacillus rhamnosus hn001probiotic strain in Swiss-and Dutch-type cheese and cheese-like products. Journal of Food Science, 79, 1181–1188. Coda, R., Lanera, A., Trani, A., Gobbetti, M., & Cagno, R. D. (2012). Yogurt-like beverages made of a mixture of cereals, soy and grape must: Microbiology, texture, nutritional and sensory properties. International Journal of Food Microbiology, 155, 120–127. Cui, X. H., Chen, S. J., Wang, Y., & Han, J. R. (2013). Fermentation conditions of walnut milk beverage inoculated with kefir grains. LWT-Food Science and Technology, 50, 349–352. Das, A., Datta, S., Mukherjee, S., Bose, S., Ghosh, S., & Dhar, P. (2015). Evaluation of antioxidative, antibacterial and probiotic growth stimulatory activities of Sesamum

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