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Optimization of process conditions for developing yoghurt like probiotic product from peanut
Accepted Manuscript Optimization of process conditions for developing yoghurt like probiotic product from peanut Sangita Bansal, Manisha Mangal, Satish Kumar Sharma, Deep Narayan Yadav, Ram Kishor Gupta PII:
S0023-6438(16)30250-X
DOI:
10.1016/j.lwt.2016.04.059
Reference:
YFSTL 5447
To appear in:
LWT - Food Science and Technology
Received Date: 26 December 2015 Revised Date:
19 April 2016
Accepted Date: 29 April 2016
Please cite this article as: Bansal, S., Mangal, M., Sharma, S.K., Yadav, D.N., Gupta, R.K., Optimization of process conditions for developing yoghurt like probiotic product from peanut, LWT - Food Science and Technology (2016), doi: 10.1016/j.lwt.2016.04.059. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Optimization of Process Conditions for Developing Yoghurt like Probiotic Product from
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Peanut
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Short title: Process Conditions for Probiotic Peanut Yoghurt
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Sangita Bansal*, Manisha Mangal, Satish Kumar Sharma, Deep Narayan Yadav and Ram Kishor Gupta Division of Food Grains & Oilseed Processing, ICAR-Central Institute of Post-harvest
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Engineering & Technology, Ludhiana, 141 004, Punjab, India
Correspondence to: Dr. Sangita Bansal, Senior Scientist, Division of Food Grains & Oilseed
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Processing, ICAR-Central Institute of Post-harvest Engineering & Technology, P.O. PAU Campus, Ludhiana, 141 004, Punjab, India
Email: [email protected], [email protected] Phone: +91-161-2313165, Fax: +91-161-2308670
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Key words: Probiotic, Streptococcus, Peanut milk, Dairy alternative, Yoghurt
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Optimization of Process Conditions for Developing Yoghurt like Probiotic Product from
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Peanut Sangita Bansal*, Manisha Mangal, Satish Kumar Sharma, Deep Narayan Yadav and Ram Kishor Gupta FGOP Division, ICAR-CIPHET- Ludhiana
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Abstract
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Functional food market is dominated by dairy based probiotic products mainly yoghurt. There is
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need to develop dairy alternatives due to allergenic milk proteins, lactose and high cholesterol
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content. In this paper, efforts have been made to develop yoghurt like probiotic product from
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peanut milk utilizing single probiotic culture and without any supplements. The conditions were
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optimized utilizing response surface methodology by studying the individual and interactive
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effects of three process variables i.e. inoculum concentration, incubation temperature and time.
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Inoculum concentration of 1.9%, incubation temperature of 38°C and 12 h incubation time was
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found optimum for probiotic peanut yoghurt preparation.
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Key words: Probiotic, Streptococcus, Peanut milk, Dairy alternative, Yoghurt
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1.
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Probiotics are normally marketed as nutraceuticals in forms of capsules and powders or added to
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yogurt, which is most popular vehicle for incorporation of probiotic microorganisms. According
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to WHO 2006, Probiotics are defined as live microorganisms, which, when consumed in
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appropriate amounts (106cfu/ml), result in a health benefit to the host. Probiotics intake improves
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the intestinal microbial balance of the host and lowers the risk of gastro-intestinal diseases by
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stimulating the growth of beneficial microorganisms and reducing the amount of pathogens
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(Fuller, 1989; Cross, 2002; Chiang and Pan, 2012). Food is considered the more convenient way
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Introduction
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of delivering probiotics in daily diets as compared to capsules or powders. Dairy food products
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mainly yoghurts are ideal food matrix for delivering probiotics, owing to their high consumer
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acceptability and better viability of these organisms. But a number of factors like cholesterol
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content, allergy to milk proteins and lactose intolerance necessitate exploring other non-dairy
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alternatives. Several reports on development of probiotic foods from different matrices like
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cereals, oilseeds, fruits and vegetables etc. are available (Angelov et al., 2006; Bansal et al.,
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2014; Blandino et al., 2003). Attempts have also been made for developing yoghurt like
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probiotic products from non-dairy sources like soy milk utilizing single (Bansal et al., 2015) or
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mixed cultures (Farnworth et al. 2007; Ghorbania et al. 2012; Stijepic et al. 2013). Peanut milk
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(water extract of peanut) like soymilk, is a low-cost substitute for dairy milk for the developing
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countries. Peanut is a good source of protein, minerals essential fatty acids such as linoleic and
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oleic acids and antioxidant such as p-coumaric acid that may contribute to potential health
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benefits by their consumption (Duncan et al. 2006; Talcot et al. 2005;). Peanut milk is
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extensively used as a dairy alternative in India and other developing countries and by
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people/children who are lactose intolerant or allergic to milk proteins (Kouane et al., 2005). The
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current interest in peanut milk/ milk products is motivated by the fact that dairy and dairy
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products are always priced too high for the low income earners. Another factor, no less
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important, is the growing awareness of the nutritional benefits of vegetable proteins in low
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cholesterol diets by health conscious people (Kouane et al., 2005). Like soy products fermented
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with lactic acid bacteria, lactic acid fermented peanut milk/ curd (Giyarto et al., 2012; Isanga and
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Zhang 2009; Lee and Beuchat, 1991; Sunny-Roberts et al., 2004; Yadav et al., 2010) may act as
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a suitable carrier for probiotic to the host. The major challenge for development of non-dairy
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probiotic foods is the slow growth of probiotic bacteria on these substrates and less probiotic
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count. A product must contain at least 106cfu/ml viable probiotic bacteria to classify as
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probiotics. Non-dairy probiotics are generally produced using mixed cultures or additives/
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gelling agent, which further create problem in establishing exact probiotic count thus limiting its
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commercial production. Probiotic Soy yoghurts possess characteristic beany flavor. Therefore,
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present study was undertaken with the aim of developing a non-dairy probiotic product so as to
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cater to the needs of lactose intolerant and vegan consumers and a process for development of
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monoculture based probiotic peanut yoghurt was standardized utilizing response surface
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methodology.
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2.
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Materials & Methods
2.1. Preparation of Peanut Milk
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Preparation of peanut milk was done by using milk extractor. Peanuts were soaked in 0.5%
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NaHCO3 (1:3 kernels to 0.5% NaHCO3) for 16 to 18 hours as per method of Saio (1986). The
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soaked peanuts were then dehusked, washed with water and ground with hot water (1:6 kernels
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to water) in the grinder for 8 min. Pressure blanching of peanuts was done in autoclave at 121°C
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at 15psi for 3 to 5 mins. The grinded product is allowed to reach the deodorizer through the
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pressure exerted by gas in grinder. This deodorization aims at removing the peanut aroma from
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the milk. The slurry formed was sieved by muslin cloth to obtain the peanut milk.
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2.2. Culture Preparation
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Seven probiotic bacterial strains namely Lactobacillus brevis MTCC no. 1750, Lactobacillus
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casei MTCC no. 1423, Lactobacillus fermentum MTCC no. 903, Lactobacillus fermentum
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MTCC no. 1745, Lactobacillus plantarum MTCC no. 6160, Lactobacillus plantarum MTCC no.
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1407, and Streptococcus faecalis T110 (renamed as Enterococcus faecalis) were procured from
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IMTECH, Chandigarh and local market. The procured strains were received in the form of
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lyophilized cultures. The cultures were revived on MRS media (Himedia make). Pure cultures
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were maintained on MRS agar/broth at 37°C till further use. Two strains namely, Lactobacillus
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fermentum BBE4, Lactobacillus fermentum BBE5 isolated and characterized in our laboratory
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were also used for the experiments. Probiotic inoculum was prepared by inoculating active
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culture of probiotic bacteria in sterilized MRS broth. It was incubated at 37°C till OD 1 is
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achieved.
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2.3. Preparation of Peanut Yoghurt
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A preliminary trial was conducted utilizing the above mentioned probiotic cultures in order to
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screen the cultures that have the capability to ferment peanut milk in to set type yoghurt. For this
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active cultures (OD 1) grown overnight in MRS broth for about 16 hrs. at 37°C were taken. The
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peanut milk was warmed and inoculated with 1% of culture and incubated at 37°C for 10-16 hrs.
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Then on the basis of overall sensory rating results the best culture showing promising response
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was selected (Data not shown). Response surface methodology was applied to further optimize
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the fermentation conditions for probiotic peanut yoghurt development. Quadratic polynomial
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model was fitted to each response except firmness as per the equation given below:
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β X +
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β X +
β X X
(1)
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Where Y is the response, βo constant, βi the linear coefficient, βii the quadratic coefficient and βij
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the interaction coefficient. Xi and Xj are independent variables.
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2.3.1. Experimental design
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Twenty treatments were performed according to face central composite design with 3 factors and
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3 levels of each variable. The factors or independent variables of the design were inoculum
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concentration, incubation temperature and incubation time. Coded and actual levels of
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experimental design are given in table 1.
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2.3.2. Sensory quality
Sensory characteristics of yoghurt samples in terms of colour/ appearance, texture, flavor, odour
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and overall acceptability, on 9 point hedonic scale, were evaluated by a group of semi-trained
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panelists. Water was provided for mouth rinsing between evaluations of different samples to
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avoid the carryover effect of the aftertaste. 2.3.3. Physicochemical analysis
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In order to determine different responses to variables; inoculum concentration, incubation time
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and incubation temperature various physiochemical parameters of peanut yoghurt like acidity,
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syneresis, viscosity, firmness or texture, and probiotic count were analyzed. Titratable acidity
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was estimated using the method of AOAC (2000), by titration of sample with 0.1 N NaOH
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solution containing 1% phenolphthalein as an indicator. To determine synersis (ml/100ml or %),
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yoghurt samples were kept on filter paper over glass beaker for 16 h at 4 ºC to separate the water
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from yoghurt. The water was collected in measuring cylinder and % synersis was calculated as
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per the formula given below:
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Synersis = Volume of water collected after drainage x 100 Volume of yoghurt sample before drainage
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Viscosity was analyzed using rapid viscoanalyzer (Techmaster, Newport scientific, Australia).
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Samples underwent controlled cooling from 43°C to 15°C as per the test configuration given
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below (Bennett et al., 2001):
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Table 1. Test configuration followed for RVA of yoghurt Type Temperature speed Speed Temperature End
Value (°C or RPM) 43 960 960 15 15
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Time (HH:MM:SS) 00:00:00 00:00:00 00:10:00 00:22:40 00:22:50
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Textural properties i.e. firmness and strength of the yoghurt samples were determined using
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Texture Analyzer(TA-HDi, Stable Micro System, UK)operated in the compression mode with
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settings viz. load cell force 5.0 kg, pretest speed 2 mm/s, test speed 2 mm/s, post-test speed 2
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mm/s, distance travel 10 mm with a 60o conical probe. 2.3.4. Microbiological Analysis
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For probiotic product development, the viability of probiotic bacteria is of prime importance.
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Total viable number of Streptococcus faecalis T110 on MRS agar was determined by serial
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dilution and standard plate count method. 2.4. Analysis of Data
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Response surface methodology (RSM) was adopted in experimental design and analysis (Khuri
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and Cornell, 1987). Multiple regression analysis was done to fit the model. Optimization of the
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polynomials thus fitted was done using the Design-Expert® software version 8. The constraints
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are set to get the coded value of variables between the lower and upper limit. Each goal was
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assigned with particular weight to adjust the desirability function. The response surfaces were
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plotted as a function of 2 variables while keeping the third one at optimum level.
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3.
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Peanut milk produced by the procedure mentioned in section 2.1 has protein content of 3.93%
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and fat content of 1.83%. A preliminary trial was conducted in order to screen the probiotic
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cultures that have the capability to ferment peanut milk into sensory acceptable set type yoghurt.
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On basis of overall sensory acceptability rating of 8.2, Streptococcus faecalis T110 was selected.
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Coded and actual values of independent variables along with the measured responses for all the
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20 treatments are given in table 1. The acidity of peanut yoghurt ranged between 0.1 - 0.26 and
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syneresis between 46 - 78 ml/100ml. Viscosity and firmness of peanut yoghurt ranged between
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32 to 52.5 cP and 0.027 to 0.715 N, respectively. The probiotic count was found to be log 6.2
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cfu/ml to log 7.7 cfu/ml. As compared to our previous results (Bansal et al., 2015) with probiotic
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soy yoghurt the acidity, viscosity and firmness is low whereas syneresis is high in probiotic
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peanut yoghurt.
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3.1. Diagnostic checking of the fitted models
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Results and Discussions
All main linear, quadratic and interactive effects were calculated for each model. The adequacy
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of the model was tested using F- ratio, coefficient of correlation and lack of fit test (Table 2). The
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quadratic models fitted for acidity, syneresis, viscosity and cell count and linear model for
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firmness. The correlation coefficients were very high ranging from 92.81% to 98.29% except in
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case of firmness where it was 27.16. The lack of fit tests were insignificant in all the cases which
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indicates that the models are adequately accurate to predict the acidity, syneresis, viscosity,
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firmness and probiotic cell count for any combination of independent factors in the ranges
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studied. This suggested that the obtained models can be used to determine the relative effect of
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the studied factors in order to find out the optimum parameter combinations for desirable
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responses and to predict the results for other conditions.
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3.2. RSM model for acidity
The F value for quadratic model of acidity was significant (P ≤ 0.01). All the three process
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variables i.e. incubation time, incubation temperature and inoculum concentration has significant
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(P ≤ 0.01) positive effect on acidity. The quadratic model for acidity can be expressed by the
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following equation.
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Acidity = +0.12958+ 0.014711A + 0.025728B + 0.035979 C - 0.005 A B - 0.0075AC - 0.01BC
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+0.009815A2 + 0.025725B2 + 0.022189C2
(2)
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Where A is the coded independent factor inoculum concentration, B is coded independent factor
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incubation temperature and C is coded independent factor incubation time.
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F-value of quadratic model for acidity was significant (P ≤ 0.01). The process variables i.e.
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incubation time and incubation temperature has significant (P ≤ 0.01) positive effect on acidity.
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Acidity significantly (P ≤ 0.01) increased with increasing inoculum concentration. Figure 1
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shows the combined effects of different variables on acidity. Consistent with the results of our
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previous study on probiotic soy yoghurt development (Bansal et al., 2015), there is a sharp
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increase in acidity as a function of incubation temperature and time (fig 1c).High metabolic
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activity due to high temperature may result in acid production and low pH (Wu et al., 2009).
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Unlike the other reports (Bitaraf et al., 2012; Kristo et al., 2003; Lee and Lucey, 2004) which
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indicate high inoculum concentration leads to high acid production, the effect of inoculum
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concentration on acidity was lower as compared to incubation time and temperature in the
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present study. 3.3. RSM model for syneresis
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Quadratic model was significantly (P ≤ 0.01) fitted to syneresis. Lack of fit was insignificant
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relative to pure error.
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Syneresis = +51.54 +1.68 A - 3.75 B + 6.88 C + 6.88 A B - 4.37 A C -1.37 B C + 9.08 A + 2
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1.65B + 1.65 C
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(3)
All three variables significantly affected the syneresis (Figure 2). Syneresis was minimum at
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medium inoculum concentration and it decreased initially with increasing inoculum
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concentration then increased with increasing inoculum concentration. Lee and Lucey (2004)
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have reported less syneresis with intermediate to high inoculum level. Syneresis increased
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significantly with increasing time and temperature. Although, this increase in syneresis was more
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as a function of incubation time in comparison to incubation temperature.
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RSM model for viscosity
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Quadratic model significantly (P ≤ 0.01) fitted to viscosity with high F value of 14.35.
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Significant (P ≤ 0.01) change was observed in viscosity with varying incubation temperature.
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The quadratic model for viscosity can be expressed by the following equation.
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Viscosity = +46.14834 -1.49907A - 5.48107B - 1.71974C - 1.7AB + 2.425A C + 0.45BC -
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2.92414A2 - 0.9796B2- 0.92656C2
(4)
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Viscosity increased gradually as function of time and inoculum concentration; however, it
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decreased slightly with increasing temperature (Figure 3). Incubation temperature affects the
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texture of yoghurt by affecting the growth of probiotic bacteria directly (Kristo et al., 2003). Page 10 of 18
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Decrease in viscosity with temperature may be due weaker gel structures as reported by Kristo et
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al., 2003 and Wu et al., 2009 that high fermentation temperature resulted in weaker gel
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structures. Few other reports suggest that high complex viscosity (Bitaraf et al., 2012) and
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enhanced rheology due to better gel strength (Skirver et al. 1993; Haque et al., 2001) can be
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achieved at higher temperature. 3.5.
RSM model for cell count
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Quadratic model fitted to viable cell count was significant (P ≤ 0.01) with high F value of 14.41.
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The quadratic model for cell count can be expressed by the following equation.
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Cell count = 7.500468 + 0.29389A - 0.1744 B + 0.134464 C - 0.0125AB + 0.0125AC +
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(5)
0.0625BC - 0.30358A2 - 0.2859B2 + 0.032297C2
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Inoculum concentration and incubation time are important factors in ensuring sufficient viable
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cell count in the fermented product (Lourens-Hattingh and Viljoen 2001; Khosravi-Darani et al.,
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2015). Viable cell count increased significantly (P ≤ 0.01) with increasing inoculum
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concentration and incubation time (Figure 4). However, the count increased initially with
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increasing temperature upto 40°C then it decreased. Optimal temperature for yogurt fermentation
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with standard cultures is usually 43°C; however, lower temperatures of about 37°C are optimum
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for growth of probiotic strains (Shortt, 1999).
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RSM model for firmness
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Linear model was best fitted to firmness but the model was insignificant.Though, lack of fit was
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insignificant relative to pure error. The linear model for firmness can be expressed by the
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following equation.
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Firmness = +0.414325 - 0.00819A + 0.102376B -.04445C
(6)
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Consistent with the report of probiotic soy yoghurt development (Bansal et al., 2015), the effect
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of incubation temperature was significant (P ≤ 0.01) on firmness in this case also. Firmness
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increased sharply with increase in temperature (Figure 5). Firmness decreased slightly with
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increasing concentration of inoculum. Other reports suggest medium inoculum concentrations
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resulted in higher firmness of yoghurt (Wu et al., 2009). 3.7.
Optimization of level of independent variables
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In order to optimize the level of independent variables, the responses i.e. acidity, syneresis,
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viscosity, firmness and cell count were assigned equal importance on the basis of their effect on
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quality and acceptability of yoghurt. The criterion used along with predicted and actual responses
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is given in Table 3. With the model, the optimized value for inoculation concentration was 1.9%,
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for incubation temperature, 38.25°C (38°C) and for incubation time 12h. Probiotic peanut
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yoghurt was developed as per the optimized process conditions. The actual measured responses
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were pretty close to the predicted values (Table 3). The acidity of peanut yoghurt was found to
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be 0.12 and syneresis between 45.5 ml/100ml. Titratable acidity of dairy is reported in the range
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of 0.5 to 1.0 % lactic acid (Ayar and Gurlin, 2014; Raju and Pal, 2014,), higher than the peanut
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yoghurt developed. However, titratable acidity of 0.38% has been reported for peanut milk
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fermented with Lactobacillus acidophilus SNP-2 (Giyarto et al., 2012). Viscosity and firmness
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of peanut yoghurt ranged between 52.5 cP and 0.442 N, respectively. The probiotic count was
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found to be log 7.5 cfu/ml.
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Majority of the commercial probiotics food are based upon the formulations that uses
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dairy milk. Several research reports are there on development of probiotic soy yoghurts, but
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majority of them were prepared utilizing mixed cultures and supplementing milk solids, gelling
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agents (Garro et al., 2004, Kamaly, 1997, Karleskind et al., 1991, Tsangalis et al., 2003). Few Page 12 of 18
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reports on fermented peanut milk/ curd utilizing mixed cultures and milk solids are also available
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(Giyarto et al., 2012; Isanga and Zhang 2009; Lee and Beuchat, 1991; Sunny-Roberts et al.,
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2004; Yadav et al., 2010). But no report is available on monoculture based probiotic Peanut
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yoghurt development that is free from milk solids/ gelling agents/ additives. A process for
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preparation of probiotic peanut yoghurt using a single established probiotic culture Streptococcus
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faecalis T110 was optimized using RSM. The obtained model could be used to find out optimum
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parameters for any factor combianation and the process can be exploited for large scale
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production of probiotic Peanut yoghurt of consistent quality.
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4. Conclusion
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In the present study, fermentation conditions for preparing probiotic peanut yoghurt were
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optimized by successfully utilizing RSM for analyzing the individual and interactive effects of
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inoculum concentration, incubation temperature and incubation time on monoculture based
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probiotic peanut yoghurt. Inoculum concentration of 1.9%, incubation at 38°C for 12 h was
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found optimum for probiotic peanut yoghurt preparation. Isanga and Zhang (2009) have
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developed peanut milk yoghurt supplemented with skimmed milk powder and sucrose. The
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present report describes the development of probiotic peanut yoghurt without any
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supplementation and thus free from lactose. The process can be used to develop probiotic peanut
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yoghurt with consistent quality at commercial scale. The non-dairy yogurts developed in this
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report would have more noticeable benefits, for lactose intolerant people since they won’t be
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suffering from lactose maldigestion symptoms observed in dairy based yogurts.
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Acknowledgement
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This work was financially supported by ICAR-Central Institute of Post-Harvest Engineering &
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Technology (an ICAR Institute), Ludhiana (Project code IXX08214).
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References
2 3
Angelov, A., Gotcheva, V., Kuncheva, R., & Hrstozova, T. (2006). Development of a new oatbased probiotic drink. Int J Food Microbiol., 112, 75–80.
4 5
*AOAC (2000). Methods of Analysis. 17th edition. Washington DC. Association of Official Analytical Chemists.
6 7
Ayar, A., & Gurlin, E. (2014). Production and sensory, textural, physicochemical properties of flavored spreadable yogurt. Life Sci J., 11(4), 58-65.
8 9 10
Bansal, S., Mangal, M., Sharma, S.K., & Gupta, R.K. (2014). Non-dairy based Probiotics: a healthy treat for intestine. Critical Reviews in Food Science and Nutrition, DOI:10.1080/10408398.2013.790780.
11 12 13
Bansal,S., Mangal, M., Sharma, S.K., Yadav, D.N., & Gupta, R.K. (2015). Optimization of fermentation conditions for probiotic soy yoghurt using response surface methodology. J Food Processing Preservation, 39(6), 1809–1816.
14 15
Bennett, L., Harte, H., & Smithers, G. (2001). Dairy products processing in the RVA. RVA World, 19, 1-4.
16 17 18 19
Bitaraf, M.S., Khodaiyan, F., Mohammadifar, M.A., & Mousavi, S.M. (2012). Application of response surface methodology to improve fermentation time and rheological properties of probiotic yogurt containing Lactobacillus reuteri. Food and Bioprocess Technology, 5(4), 13941401.
20 21
Blandino, A., Al-Aseeri, M.E., Pandiella, S.S., Cantero, D., & Webb, C. (2003). Cereal-based fermented foods and beverages. Food Res Int., 36, 527–543.
22 23
Chiang, S.S., & Pan, T.M. (2012). Beneficial effects of Lactobacillus paracasei subsp. paracasei NTU 101 and its fermented products. Applied Microbiology and Biotechnology, 93(3), 903-916.
24 25 26
Cross, M.L. (2002). Microbes versus microbes: immune signals generated by probiotic lactobacilli and their role in protection against microbial pathogens. FEMS Immunol Med Microbiol. 34(4), 245-53.
27 28 29
Duncan, C.E., Gorbet, D.W., & Talcott, S.T. (2006). Phytochemical content and antioxidant capacity of water-soluble isolates from peanuts (Arachis hypogaea L.). Food Research International, 39, 898-904.
30 31 32
Farnworth, E.R., Mainville, I., Desjardins, M.P., Gardner, N., Fliss, I., & Champagne, C. (2007).Growth of probiotic bacteria and bifidobacteria in a soy yogurt formulation. International Journal of Food Microbiology, 116, 174-181.
33 34
Fuller, R. (1989). Probiotics in man and animals. The Journal of Applied Bacteriology, 66(5), 365–378.
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M AN U
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1
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Garro, M.S., De Valdez, G.F., & De Giori, G.S. (2004). Temperature effect on the biological activity of Bifidobacterium longum CRL 849 and Lactobacillus fermentum CRL 251 in pure and mixed cultures grown in soymilk. Food Microbiology, 21, 511–518.
4 5 6 7 8
Giyarto, Djaafar T.F., Rahayu E.S., & Utami, T. (2012). Fermentation of peanut milk by Lactobacillus acidophilus snp-2 for production of non-dairy probiotic drink Proceeding The 3rd International Conference of Indonesian Society for Lactic Acid Bacteria (3rd IC-ISLAB): Better Life with Lactic Acid Bacteria: Exploring Novel Functions of Lactic Acid Bacteria. Accessed on 18 dec 2015.
9 10
Ghorbania, A., Pourahmada, R., Fallahpourb, M., & Assadib, M.M. (2012). Production of probiotic soy yogurt. Annals of Biological Research, 3(6), 2750-2754.
11 12
Haque, A., Richardson, R.K., & Morris, E.R. (2001). Effect of fermentation temperature on the rheology of set and stirred yogurt. Food Hydrocolloids, 15, 593-602.
13 14
*Isanga, J., & Zhang, G. (2009). Production and evaluation of some physicochemical parameters of peanut milk yoghurt. LWT-Food Science and Technology, 42, 1132- 1138.
15 16
Kamaly, K.M. (1997). Bifidobacteria fermentation of soybean milk. Food Research International, 30, 675–682
17 18 19
Karleskind, D., Laye, I., Halpin, E., & Morr, C.V. (1991). Improving acid production in soybased yogurt by adding cheese whey proteins and mineral salts. Journal of Food Science, 56, 999-1001.
20 21
Khosravi-Darani, K., Taheri, P., & Ahmad, N. (2015). Effect of Process Variables on the Probiotic and Starter Culture Growth in Synbiotic Yogurt Beet. RRJFPDT, 3(2), 13-24.
22 23
Khuri, A.I., & Cornell, J.A. (1987). Response surfaces: designs and analysis (pp. 127-145). New York: Marcel Dekker.
24 25
Kouane, D., Zhang, G., & Chen, J. (2005). Peanut milk and peanut milk based products production. A review. Critical Reviews in Food Science and Nutrition, 45,405-423.
26 27 28
Kristo, E., Biliaderis, C.G., & Tzanetakis, N. (2003). Modelling of rheological, microbiological and acidification properties of a fermented milk product containing a probiotic strain of Lactobacillus paracasei. International Dairy J, 13,517-528.
29 30 31
Lee, C., & Beuchat, L.R. (1991). Changes in chemical composition and sensory qualities of peanut milk fermented with lactic acid bacteria. International J Food Microbiology, 13 (4), 273183.
32 33
Lee, W.J., & Lucey, J.A. (2004). Structure and physical properties of yogurt gels: effect of inoculation rate and incubation temperature. J Dairy Science, 87, 3153-3164.
34 35
Lourens-Hattingh, A., & Viljoen, B.C. (2001). Yogurt as probiotic carrier food. International Dairy Journal, 11, 1-17.
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Raju, N.P., & Pal, D. (2014) Effect of dietary fibers on physico-chemical, sensory and textural properties of Misti Dahi. J Food Sci Technol. 51(11), 3124–3133.
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Shortt, C. (1999). The probiotic century; historical and current perspectives. Trends in Food Science and Technology, 10, 411- 417.
5 6
Skriver, A., Roemer, H., & Qvist, K.B. (1993). Rheological characterization of stirred yoghurt viscometry. J. Texture Stud., 24,185-198.
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Stijepic, M., Glusac, J., Milosevic, D.D., & Mikulec, D.P. (2013).Physicochemical characteristics of soy probiotic yoghurt with inulin additon during the refrigerated storage.Romanian Biotechnological Letters,18(2), 8078-8085.
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Sunny-Roberts, E.O., Otulona, E.T., & Iwakun, B.T. (2004). An evaluation of some quality parameters of a laboratory-prepared fermented groundnut milk. European Food Research Technology, 218,452-455.
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Talcot, S.T., Passeretti, S., Duncan, C.E., & Gorbet, D.W. (2005). Polyphenolic content and sensory properties of normal and high oleic acid peanuts. Food Chemistry, 90, 379-388.
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Tsangalis, D., Ashton, J.F., McGill, A.E.J., & Shah,N.P. (2003). Biotransformation of isoflavones by bifidobacteria in fermented soymilk supplemented with D-glucose and Lcysteine. Journal of Food Science, 68, 623-631.
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*Wu, S., Li, D., Li, S., Bhandari, B., Yang, B., Chen, X.D., & Mao, Z. (2009). Effects of incubation temperature, starter culture level and total solids content on the rheological properties of yogurt. International J of Food Engg., 5(2), 1556-3758.
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*Yadav, D.N., Singh, K.K., Bhowmik, S.N., & Patil, R.T. (2010). Development of peanut milk– based fermented curd. International J Food Science and Technology, 45, 2650-2658.
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LEGENDS TO TABLES Table 1: Coded and actual levels of independent variables A. inoculum concentration (% v/v), B. incubation temperature (oC) and C. incubation time (hrs.) used in central composite design along with measured responses
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Table 2: Design summary and estimated regression coefficients for dependent variables and their significance
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Table 3: Criteria for optimization for process conditions alongwith responses
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LEGENDS TO FIGURES
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Fig. 1. Response surface plot for acidity as a function of, a) incubation temperature and inoculum concentration at incubation time of 15 hrs, b) incubation time and inoculum concentration at incubation temperature of 40ºC and c) incubation time and incubation temperature at inoculum concentration of 2%
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Fig. 2. Response surface plot for synersis as a function of, a) incubation temperature and inoculum concentration at incubation time of 15 hrs, b) incubation time and inoculum concentration at incubation temperature of 40ºC and c) incubation time and incubation temperature at inoculum concentration of 2%
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Fig. 3. Response surface plot for viscosity as a function of, a) incubation temperature and inoculum concentration at incubation time of 15 hrs, b) incubation time and inoculum concentration at incubation temperature of 40ºC and c) incubation time and incubation temperature at inoculum concentration of 2%
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Fig. 4. Response surface plot for viable cell count as a function of, a) incubation temperature and inoculum concentration at incubation time of 15 hrs, b) incubation time and inoculum concentration at incubation temperature of 40ºC and c) incubation time and incubation temperature at inoculum concentration of 2%
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Fig. 5. Response surface plot for firmness as a function of incubation temperature and inoculum concentration at incubation time of 15 hrs
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Table 1: Coded and actual levels of independent variables A. inoculum concentration (% v/v), B. incubation temperature (oC) and C. incubation time (hrs.) used in central composite design along with measured responses A: Inoculum Concentration C A
B: Incubation Temperature C A
C: Incubation Time C A
Acidity
Syneres is (%)
1
-1
1
1
43
1
18
0.26
68
2
1
3
-1
37
1
18
0.24
60
3
-1
1
-1
37
-1
12
0.1
51
4
-1
1
1
43
-1
12
0.16
47
5
0
2
0
40
0
15
0.12
52 51
2
-1.68
34.95
0
15
0.15
1.68
3.68
0
40
0
15
0.18
8
1
3
1
43
1
18
0.24
9
0
2
0
40
0
15
0.14
10
0
2
1.68
45.05
0
11
0
2
0
40
0
12
1
3
-1
37
-1
13
-1
1
-1
37
1
14
-1.68
0.32
0
40
0
15
0
2
0
40
1.68
16 17 18
0 0 0
2 2 2
0 0 0
40 40 40
0 0 0
19
1
3
1
43
20
0
2
0
40
Cell count (log cfu/ml)
35
0.693
6.7
0.0453
7.4
52.5
0.2512
6.5
45
0.612
6.4
47.5
0.456
7.6
50
0.455
7.2
78
33.7
0.442
7.1
78
35
0.487
7.5
53
45
0.351
7.5
15
0.24
63
33.2
0.321
6.2
15
0.14
50
45
0.388
7.6
12
0.13
51
49.6
0.318
7.3
18
0.2
76
44
0.027
6.9
0.12
78
38.5
0.354
6.2
0.23
68
40
0.593
7.7
15 15 15
0.14 0.12 0.12
50 53 51
47.5 45 47.5
0.36 0.352 0.593
7.3 7.5 7.5
-1
12
0.21
76
32
0.473
6.8
-1.68
9.95
0.14
46
43.5
0.715
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Table 2: Design summary and estimated regression coefficients for dependent variables and their significance
Quadratic Significant Intercept 0.13 A 0.015** B 0.026** C 0.036** AB -0.005 AC -0.0075 BC -0.01 2 -0.0098 A 2 0.026** B 2 0.022** C 2 R (%) 94.22 Lack of Fit Insignificant **p <.01; *p <.05
Viscosity (cP) Firmness (N)
Quadratic Significant 51.54 1.68* 3.75** 6.88** 6.88** -4.38** -1.38 9.08** 1.65* 1.65* 98.29 Insignificant
Quadratic Significant 46.15 -1.499* -5.48** -1.72* -1.7 2.425* 0.45 -2.922** -0.98 -0.93 92.81 Insignificant
Linear Insignificant 0.414 -0.008 0.102* -0.044
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Synersis (%)
Cell Count (log cfu/ml) Quadratic Significant 7.50 0.29** -0.17** 0.13* -0.0125 0.0125 0.0625 -0.303** -0.29** 0.032 92.84 Insignificant
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Acidity (%)
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Factor
27.16 Insignificant
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Table 3: Criteria for optimization for process conditions alongwith responses
is in range is in range is in range minimize minimize maximize maximize is in range
1 37 12 0.1 46 32 0.4 6.2
3 43 18 0.26 78 52.5 0.715 7.7
Importance Solution 3 3 3 3 3 3 3 3
1.90% 38.25 °C 12.00 hrs. 0.101 43.78 50.33 0.4 7.41
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A:Ino Conc B:Temp C:Time Acidity Synersis Viscosity Firmness Cell count
Lower Upper Limit Limit
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HIGHLIGHTS The present paper describes the development of peanut based probiotic yoghurt that can be a dairy alternative.
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Developed product is free from lactose, cholesterol and milk proteins.
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Since single culture is used, the product of consistent quality could be obtained.
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The model developed utilizing RSM could be used to find out optimum parameters for any factor combianation.
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S0023-6438(16)30250-X
DOI:
10.1016/j.lwt.2016.04.059
Reference:
YFSTL 5447
To appear in:
LWT - Food Science and Technology
Received Date: 26 December 2015 Revised Date:
19 April 2016
Accepted Date: 29 April 2016
Please cite this article as: Bansal, S., Mangal, M., Sharma, S.K., Yadav, D.N., Gupta, R.K., Optimization of process conditions for developing yoghurt like probiotic product from peanut, LWT - Food Science and Technology (2016), doi: 10.1016/j.lwt.2016.04.059. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Optimization of Process Conditions for Developing Yoghurt like Probiotic Product from
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Peanut
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Short title: Process Conditions for Probiotic Peanut Yoghurt
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Sangita Bansal*, Manisha Mangal, Satish Kumar Sharma, Deep Narayan Yadav and Ram Kishor Gupta Division of Food Grains & Oilseed Processing, ICAR-Central Institute of Post-harvest
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Engineering & Technology, Ludhiana, 141 004, Punjab, India
Correspondence to: Dr. Sangita Bansal, Senior Scientist, Division of Food Grains & Oilseed
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Processing, ICAR-Central Institute of Post-harvest Engineering & Technology, P.O. PAU Campus, Ludhiana, 141 004, Punjab, India
Email: [email protected], [email protected] Phone: +91-161-2313165, Fax: +91-161-2308670
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Key words: Probiotic, Streptococcus, Peanut milk, Dairy alternative, Yoghurt
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Optimization of Process Conditions for Developing Yoghurt like Probiotic Product from
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Peanut Sangita Bansal*, Manisha Mangal, Satish Kumar Sharma, Deep Narayan Yadav and Ram Kishor Gupta FGOP Division, ICAR-CIPHET- Ludhiana
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Abstract
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Functional food market is dominated by dairy based probiotic products mainly yoghurt. There is
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need to develop dairy alternatives due to allergenic milk proteins, lactose and high cholesterol
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content. In this paper, efforts have been made to develop yoghurt like probiotic product from
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peanut milk utilizing single probiotic culture and without any supplements. The conditions were
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optimized utilizing response surface methodology by studying the individual and interactive
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effects of three process variables i.e. inoculum concentration, incubation temperature and time.
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Inoculum concentration of 1.9%, incubation temperature of 38°C and 12 h incubation time was
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found optimum for probiotic peanut yoghurt preparation.
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Key words: Probiotic, Streptococcus, Peanut milk, Dairy alternative, Yoghurt
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1.
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Probiotics are normally marketed as nutraceuticals in forms of capsules and powders or added to
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yogurt, which is most popular vehicle for incorporation of probiotic microorganisms. According
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to WHO 2006, Probiotics are defined as live microorganisms, which, when consumed in
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appropriate amounts (106cfu/ml), result in a health benefit to the host. Probiotics intake improves
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the intestinal microbial balance of the host and lowers the risk of gastro-intestinal diseases by
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stimulating the growth of beneficial microorganisms and reducing the amount of pathogens
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(Fuller, 1989; Cross, 2002; Chiang and Pan, 2012). Food is considered the more convenient way
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of delivering probiotics in daily diets as compared to capsules or powders. Dairy food products
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mainly yoghurts are ideal food matrix for delivering probiotics, owing to their high consumer
3
acceptability and better viability of these organisms. But a number of factors like cholesterol
4
content, allergy to milk proteins and lactose intolerance necessitate exploring other non-dairy
5
alternatives. Several reports on development of probiotic foods from different matrices like
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cereals, oilseeds, fruits and vegetables etc. are available (Angelov et al., 2006; Bansal et al.,
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2014; Blandino et al., 2003). Attempts have also been made for developing yoghurt like
8
probiotic products from non-dairy sources like soy milk utilizing single (Bansal et al., 2015) or
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mixed cultures (Farnworth et al. 2007; Ghorbania et al. 2012; Stijepic et al. 2013). Peanut milk
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(water extract of peanut) like soymilk, is a low-cost substitute for dairy milk for the developing
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countries. Peanut is a good source of protein, minerals essential fatty acids such as linoleic and
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oleic acids and antioxidant such as p-coumaric acid that may contribute to potential health
13
benefits by their consumption (Duncan et al. 2006; Talcot et al. 2005;). Peanut milk is
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extensively used as a dairy alternative in India and other developing countries and by
15
people/children who are lactose intolerant or allergic to milk proteins (Kouane et al., 2005). The
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current interest in peanut milk/ milk products is motivated by the fact that dairy and dairy
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products are always priced too high for the low income earners. Another factor, no less
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important, is the growing awareness of the nutritional benefits of vegetable proteins in low
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cholesterol diets by health conscious people (Kouane et al., 2005). Like soy products fermented
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with lactic acid bacteria, lactic acid fermented peanut milk/ curd (Giyarto et al., 2012; Isanga and
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Zhang 2009; Lee and Beuchat, 1991; Sunny-Roberts et al., 2004; Yadav et al., 2010) may act as
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a suitable carrier for probiotic to the host. The major challenge for development of non-dairy
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probiotic foods is the slow growth of probiotic bacteria on these substrates and less probiotic
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count. A product must contain at least 106cfu/ml viable probiotic bacteria to classify as
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probiotics. Non-dairy probiotics are generally produced using mixed cultures or additives/
3
gelling agent, which further create problem in establishing exact probiotic count thus limiting its
4
commercial production. Probiotic Soy yoghurts possess characteristic beany flavor. Therefore,
5
present study was undertaken with the aim of developing a non-dairy probiotic product so as to
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cater to the needs of lactose intolerant and vegan consumers and a process for development of
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monoculture based probiotic peanut yoghurt was standardized utilizing response surface
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methodology.
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Materials & Methods
2.1. Preparation of Peanut Milk
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Preparation of peanut milk was done by using milk extractor. Peanuts were soaked in 0.5%
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NaHCO3 (1:3 kernels to 0.5% NaHCO3) for 16 to 18 hours as per method of Saio (1986). The
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soaked peanuts were then dehusked, washed with water and ground with hot water (1:6 kernels
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to water) in the grinder for 8 min. Pressure blanching of peanuts was done in autoclave at 121°C
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at 15psi for 3 to 5 mins. The grinded product is allowed to reach the deodorizer through the
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pressure exerted by gas in grinder. This deodorization aims at removing the peanut aroma from
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the milk. The slurry formed was sieved by muslin cloth to obtain the peanut milk.
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2.2. Culture Preparation
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Seven probiotic bacterial strains namely Lactobacillus brevis MTCC no. 1750, Lactobacillus
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casei MTCC no. 1423, Lactobacillus fermentum MTCC no. 903, Lactobacillus fermentum
21
MTCC no. 1745, Lactobacillus plantarum MTCC no. 6160, Lactobacillus plantarum MTCC no.
22
1407, and Streptococcus faecalis T110 (renamed as Enterococcus faecalis) were procured from
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IMTECH, Chandigarh and local market. The procured strains were received in the form of
2
lyophilized cultures. The cultures were revived on MRS media (Himedia make). Pure cultures
3
were maintained on MRS agar/broth at 37°C till further use. Two strains namely, Lactobacillus
4
fermentum BBE4, Lactobacillus fermentum BBE5 isolated and characterized in our laboratory
5
were also used for the experiments. Probiotic inoculum was prepared by inoculating active
6
culture of probiotic bacteria in sterilized MRS broth. It was incubated at 37°C till OD 1 is
7
achieved.
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2.3. Preparation of Peanut Yoghurt
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A preliminary trial was conducted utilizing the above mentioned probiotic cultures in order to
10
screen the cultures that have the capability to ferment peanut milk in to set type yoghurt. For this
11
active cultures (OD 1) grown overnight in MRS broth for about 16 hrs. at 37°C were taken. The
12
peanut milk was warmed and inoculated with 1% of culture and incubated at 37°C for 10-16 hrs.
13
Then on the basis of overall sensory rating results the best culture showing promising response
14
was selected (Data not shown). Response surface methodology was applied to further optimize
15
the fermentation conditions for probiotic peanut yoghurt development. Quadratic polynomial
16
model was fitted to each response except firmness as per the equation given below:
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= +
β X +
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β X +
β X X
(1)
18
Where Y is the response, βo constant, βi the linear coefficient, βii the quadratic coefficient and βij
19
the interaction coefficient. Xi and Xj are independent variables.
20
2.3.1. Experimental design
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Twenty treatments were performed according to face central composite design with 3 factors and
2
3 levels of each variable. The factors or independent variables of the design were inoculum
3
concentration, incubation temperature and incubation time. Coded and actual levels of
4
experimental design are given in table 1.
5
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2.3.2. Sensory quality
Sensory characteristics of yoghurt samples in terms of colour/ appearance, texture, flavor, odour
7
and overall acceptability, on 9 point hedonic scale, were evaluated by a group of semi-trained
8
panelists. Water was provided for mouth rinsing between evaluations of different samples to
9
avoid the carryover effect of the aftertaste. 2.3.3. Physicochemical analysis
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In order to determine different responses to variables; inoculum concentration, incubation time
12
and incubation temperature various physiochemical parameters of peanut yoghurt like acidity,
13
syneresis, viscosity, firmness or texture, and probiotic count were analyzed. Titratable acidity
14
was estimated using the method of AOAC (2000), by titration of sample with 0.1 N NaOH
15
solution containing 1% phenolphthalein as an indicator. To determine synersis (ml/100ml or %),
16
yoghurt samples were kept on filter paper over glass beaker for 16 h at 4 ºC to separate the water
17
from yoghurt. The water was collected in measuring cylinder and % synersis was calculated as
18
per the formula given below:
19 20 21 22
Synersis = Volume of water collected after drainage x 100 Volume of yoghurt sample before drainage
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Viscosity was analyzed using rapid viscoanalyzer (Techmaster, Newport scientific, Australia).
2
Samples underwent controlled cooling from 43°C to 15°C as per the test configuration given
3
below (Bennett et al., 2001):
4
Table 1. Test configuration followed for RVA of yoghurt Type Temperature speed Speed Temperature End
Value (°C or RPM) 43 960 960 15 15
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Time (HH:MM:SS) 00:00:00 00:00:00 00:10:00 00:22:40 00:22:50
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Textural properties i.e. firmness and strength of the yoghurt samples were determined using
6
Texture Analyzer(TA-HDi, Stable Micro System, UK)operated in the compression mode with
7
settings viz. load cell force 5.0 kg, pretest speed 2 mm/s, test speed 2 mm/s, post-test speed 2
8
mm/s, distance travel 10 mm with a 60o conical probe. 2.3.4. Microbiological Analysis
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For probiotic product development, the viability of probiotic bacteria is of prime importance.
11
Total viable number of Streptococcus faecalis T110 on MRS agar was determined by serial
12
dilution and standard plate count method. 2.4. Analysis of Data
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Response surface methodology (RSM) was adopted in experimental design and analysis (Khuri
15
and Cornell, 1987). Multiple regression analysis was done to fit the model. Optimization of the
16
polynomials thus fitted was done using the Design-Expert® software version 8. The constraints
17
are set to get the coded value of variables between the lower and upper limit. Each goal was
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1
assigned with particular weight to adjust the desirability function. The response surfaces were
2
plotted as a function of 2 variables while keeping the third one at optimum level.
3
3.
4
Peanut milk produced by the procedure mentioned in section 2.1 has protein content of 3.93%
5
and fat content of 1.83%. A preliminary trial was conducted in order to screen the probiotic
6
cultures that have the capability to ferment peanut milk into sensory acceptable set type yoghurt.
7
On basis of overall sensory acceptability rating of 8.2, Streptococcus faecalis T110 was selected.
8
Coded and actual values of independent variables along with the measured responses for all the
9
20 treatments are given in table 1. The acidity of peanut yoghurt ranged between 0.1 - 0.26 and
10
syneresis between 46 - 78 ml/100ml. Viscosity and firmness of peanut yoghurt ranged between
11
32 to 52.5 cP and 0.027 to 0.715 N, respectively. The probiotic count was found to be log 6.2
12
cfu/ml to log 7.7 cfu/ml. As compared to our previous results (Bansal et al., 2015) with probiotic
13
soy yoghurt the acidity, viscosity and firmness is low whereas syneresis is high in probiotic
14
peanut yoghurt.
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3.1. Diagnostic checking of the fitted models
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Results and Discussions
All main linear, quadratic and interactive effects were calculated for each model. The adequacy
17
of the model was tested using F- ratio, coefficient of correlation and lack of fit test (Table 2). The
18
quadratic models fitted for acidity, syneresis, viscosity and cell count and linear model for
19
firmness. The correlation coefficients were very high ranging from 92.81% to 98.29% except in
20
case of firmness where it was 27.16. The lack of fit tests were insignificant in all the cases which
21
indicates that the models are adequately accurate to predict the acidity, syneresis, viscosity,
22
firmness and probiotic cell count for any combination of independent factors in the ranges
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studied. This suggested that the obtained models can be used to determine the relative effect of
2
the studied factors in order to find out the optimum parameter combinations for desirable
3
responses and to predict the results for other conditions.
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3.2. RSM model for acidity
The F value for quadratic model of acidity was significant (P ≤ 0.01). All the three process
6
variables i.e. incubation time, incubation temperature and inoculum concentration has significant
7
(P ≤ 0.01) positive effect on acidity. The quadratic model for acidity can be expressed by the
8
following equation.
9
Acidity = +0.12958+ 0.014711A + 0.025728B + 0.035979 C - 0.005 A B - 0.0075AC - 0.01BC
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+0.009815A2 + 0.025725B2 + 0.022189C2
(2)
11
Where A is the coded independent factor inoculum concentration, B is coded independent factor
12
incubation temperature and C is coded independent factor incubation time.
13
F-value of quadratic model for acidity was significant (P ≤ 0.01). The process variables i.e.
14
incubation time and incubation temperature has significant (P ≤ 0.01) positive effect on acidity.
15
Acidity significantly (P ≤ 0.01) increased with increasing inoculum concentration. Figure 1
16
shows the combined effects of different variables on acidity. Consistent with the results of our
17
previous study on probiotic soy yoghurt development (Bansal et al., 2015), there is a sharp
18
increase in acidity as a function of incubation temperature and time (fig 1c).High metabolic
19
activity due to high temperature may result in acid production and low pH (Wu et al., 2009).
20
Unlike the other reports (Bitaraf et al., 2012; Kristo et al., 2003; Lee and Lucey, 2004) which
21
indicate high inoculum concentration leads to high acid production, the effect of inoculum
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1
concentration on acidity was lower as compared to incubation time and temperature in the
2
present study. 3.3. RSM model for syneresis
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3
Quadratic model was significantly (P ≤ 0.01) fitted to syneresis. Lack of fit was insignificant
5
relative to pure error.
6
Syneresis = +51.54 +1.68 A - 3.75 B + 6.88 C + 6.88 A B - 4.37 A C -1.37 B C + 9.08 A + 2
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4
2
1.65B + 1.65 C
7
2
(3)
All three variables significantly affected the syneresis (Figure 2). Syneresis was minimum at
9
medium inoculum concentration and it decreased initially with increasing inoculum
10
concentration then increased with increasing inoculum concentration. Lee and Lucey (2004)
11
have reported less syneresis with intermediate to high inoculum level. Syneresis increased
12
significantly with increasing time and temperature. Although, this increase in syneresis was more
13
as a function of incubation time in comparison to incubation temperature.
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3.4.
RSM model for viscosity
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Quadratic model significantly (P ≤ 0.01) fitted to viscosity with high F value of 14.35.
16
Significant (P ≤ 0.01) change was observed in viscosity with varying incubation temperature.
17
The quadratic model for viscosity can be expressed by the following equation.
18
Viscosity = +46.14834 -1.49907A - 5.48107B - 1.71974C - 1.7AB + 2.425A C + 0.45BC -
19
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15
2.92414A2 - 0.9796B2- 0.92656C2
(4)
20
Viscosity increased gradually as function of time and inoculum concentration; however, it
21
decreased slightly with increasing temperature (Figure 3). Incubation temperature affects the
22
texture of yoghurt by affecting the growth of probiotic bacteria directly (Kristo et al., 2003). Page 10 of 18
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Decrease in viscosity with temperature may be due weaker gel structures as reported by Kristo et
2
al., 2003 and Wu et al., 2009 that high fermentation temperature resulted in weaker gel
3
structures. Few other reports suggest that high complex viscosity (Bitaraf et al., 2012) and
4
enhanced rheology due to better gel strength (Skirver et al. 1993; Haque et al., 2001) can be
5
achieved at higher temperature. 3.5.
RSM model for cell count
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Quadratic model fitted to viable cell count was significant (P ≤ 0.01) with high F value of 14.41.
8
The quadratic model for cell count can be expressed by the following equation.
9
Cell count = 7.500468 + 0.29389A - 0.1744 B + 0.134464 C - 0.0125AB + 0.0125AC +
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(5)
0.0625BC - 0.30358A2 - 0.2859B2 + 0.032297C2
11
Inoculum concentration and incubation time are important factors in ensuring sufficient viable
12
cell count in the fermented product (Lourens-Hattingh and Viljoen 2001; Khosravi-Darani et al.,
13
2015). Viable cell count increased significantly (P ≤ 0.01) with increasing inoculum
14
concentration and incubation time (Figure 4). However, the count increased initially with
15
increasing temperature upto 40°C then it decreased. Optimal temperature for yogurt fermentation
16
with standard cultures is usually 43°C; however, lower temperatures of about 37°C are optimum
17
for growth of probiotic strains (Shortt, 1999).
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3.6.
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RSM model for firmness
19
Linear model was best fitted to firmness but the model was insignificant.Though, lack of fit was
20
insignificant relative to pure error. The linear model for firmness can be expressed by the
21
following equation.
22
Firmness = +0.414325 - 0.00819A + 0.102376B -.04445C
(6)
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Consistent with the report of probiotic soy yoghurt development (Bansal et al., 2015), the effect
2
of incubation temperature was significant (P ≤ 0.01) on firmness in this case also. Firmness
3
increased sharply with increase in temperature (Figure 5). Firmness decreased slightly with
4
increasing concentration of inoculum. Other reports suggest medium inoculum concentrations
5
resulted in higher firmness of yoghurt (Wu et al., 2009). 3.7.
Optimization of level of independent variables
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In order to optimize the level of independent variables, the responses i.e. acidity, syneresis,
8
viscosity, firmness and cell count were assigned equal importance on the basis of their effect on
9
quality and acceptability of yoghurt. The criterion used along with predicted and actual responses
10
is given in Table 3. With the model, the optimized value for inoculation concentration was 1.9%,
11
for incubation temperature, 38.25°C (38°C) and for incubation time 12h. Probiotic peanut
12
yoghurt was developed as per the optimized process conditions. The actual measured responses
13
were pretty close to the predicted values (Table 3). The acidity of peanut yoghurt was found to
14
be 0.12 and syneresis between 45.5 ml/100ml. Titratable acidity of dairy is reported in the range
15
of 0.5 to 1.0 % lactic acid (Ayar and Gurlin, 2014; Raju and Pal, 2014,), higher than the peanut
16
yoghurt developed. However, titratable acidity of 0.38% has been reported for peanut milk
17
fermented with Lactobacillus acidophilus SNP-2 (Giyarto et al., 2012). Viscosity and firmness
18
of peanut yoghurt ranged between 52.5 cP and 0.442 N, respectively. The probiotic count was
19
found to be log 7.5 cfu/ml.
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Majority of the commercial probiotics food are based upon the formulations that uses
21
dairy milk. Several research reports are there on development of probiotic soy yoghurts, but
22
majority of them were prepared utilizing mixed cultures and supplementing milk solids, gelling
23
agents (Garro et al., 2004, Kamaly, 1997, Karleskind et al., 1991, Tsangalis et al., 2003). Few Page 12 of 18
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reports on fermented peanut milk/ curd utilizing mixed cultures and milk solids are also available
2
(Giyarto et al., 2012; Isanga and Zhang 2009; Lee and Beuchat, 1991; Sunny-Roberts et al.,
3
2004; Yadav et al., 2010). But no report is available on monoculture based probiotic Peanut
4
yoghurt development that is free from milk solids/ gelling agents/ additives. A process for
5
preparation of probiotic peanut yoghurt using a single established probiotic culture Streptococcus
6
faecalis T110 was optimized using RSM. The obtained model could be used to find out optimum
7
parameters for any factor combianation and the process can be exploited for large scale
8
production of probiotic Peanut yoghurt of consistent quality.
9
4. Conclusion
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In the present study, fermentation conditions for preparing probiotic peanut yoghurt were
11
optimized by successfully utilizing RSM for analyzing the individual and interactive effects of
12
inoculum concentration, incubation temperature and incubation time on monoculture based
13
probiotic peanut yoghurt. Inoculum concentration of 1.9%, incubation at 38°C for 12 h was
14
found optimum for probiotic peanut yoghurt preparation. Isanga and Zhang (2009) have
15
developed peanut milk yoghurt supplemented with skimmed milk powder and sucrose. The
16
present report describes the development of probiotic peanut yoghurt without any
17
supplementation and thus free from lactose. The process can be used to develop probiotic peanut
18
yoghurt with consistent quality at commercial scale. The non-dairy yogurts developed in this
19
report would have more noticeable benefits, for lactose intolerant people since they won’t be
20
suffering from lactose maldigestion symptoms observed in dairy based yogurts.
21
Acknowledgement
22
This work was financially supported by ICAR-Central Institute of Post-Harvest Engineering &
23
Technology (an ICAR Institute), Ludhiana (Project code IXX08214).
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References
2 3
Angelov, A., Gotcheva, V., Kuncheva, R., & Hrstozova, T. (2006). Development of a new oatbased probiotic drink. Int J Food Microbiol., 112, 75–80.
4 5
*AOAC (2000). Methods of Analysis. 17th edition. Washington DC. Association of Official Analytical Chemists.
6 7
Ayar, A., & Gurlin, E. (2014). Production and sensory, textural, physicochemical properties of flavored spreadable yogurt. Life Sci J., 11(4), 58-65.
8 9 10
Bansal, S., Mangal, M., Sharma, S.K., & Gupta, R.K. (2014). Non-dairy based Probiotics: a healthy treat for intestine. Critical Reviews in Food Science and Nutrition, DOI:10.1080/10408398.2013.790780.
11 12 13
Bansal,S., Mangal, M., Sharma, S.K., Yadav, D.N., & Gupta, R.K. (2015). Optimization of fermentation conditions for probiotic soy yoghurt using response surface methodology. J Food Processing Preservation, 39(6), 1809–1816.
14 15
Bennett, L., Harte, H., & Smithers, G. (2001). Dairy products processing in the RVA. RVA World, 19, 1-4.
16 17 18 19
Bitaraf, M.S., Khodaiyan, F., Mohammadifar, M.A., & Mousavi, S.M. (2012). Application of response surface methodology to improve fermentation time and rheological properties of probiotic yogurt containing Lactobacillus reuteri. Food and Bioprocess Technology, 5(4), 13941401.
20 21
Blandino, A., Al-Aseeri, M.E., Pandiella, S.S., Cantero, D., & Webb, C. (2003). Cereal-based fermented foods and beverages. Food Res Int., 36, 527–543.
22 23
Chiang, S.S., & Pan, T.M. (2012). Beneficial effects of Lactobacillus paracasei subsp. paracasei NTU 101 and its fermented products. Applied Microbiology and Biotechnology, 93(3), 903-916.
24 25 26
Cross, M.L. (2002). Microbes versus microbes: immune signals generated by probiotic lactobacilli and their role in protection against microbial pathogens. FEMS Immunol Med Microbiol. 34(4), 245-53.
27 28 29
Duncan, C.E., Gorbet, D.W., & Talcott, S.T. (2006). Phytochemical content and antioxidant capacity of water-soluble isolates from peanuts (Arachis hypogaea L.). Food Research International, 39, 898-904.
30 31 32
Farnworth, E.R., Mainville, I., Desjardins, M.P., Gardner, N., Fliss, I., & Champagne, C. (2007).Growth of probiotic bacteria and bifidobacteria in a soy yogurt formulation. International Journal of Food Microbiology, 116, 174-181.
33 34
Fuller, R. (1989). Probiotics in man and animals. The Journal of Applied Bacteriology, 66(5), 365–378.
AC C
EP
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M AN U
SC
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1
Page 14 of 18
ACCEPTED MANUSCRIPT
Garro, M.S., De Valdez, G.F., & De Giori, G.S. (2004). Temperature effect on the biological activity of Bifidobacterium longum CRL 849 and Lactobacillus fermentum CRL 251 in pure and mixed cultures grown in soymilk. Food Microbiology, 21, 511–518.
4 5 6 7 8
Giyarto, Djaafar T.F., Rahayu E.S., & Utami, T. (2012). Fermentation of peanut milk by Lactobacillus acidophilus snp-2 for production of non-dairy probiotic drink Proceeding The 3rd International Conference of Indonesian Society for Lactic Acid Bacteria (3rd IC-ISLAB): Better Life with Lactic Acid Bacteria: Exploring Novel Functions of Lactic Acid Bacteria. Accessed on 18 dec 2015.
9 10
Ghorbania, A., Pourahmada, R., Fallahpourb, M., & Assadib, M.M. (2012). Production of probiotic soy yogurt. Annals of Biological Research, 3(6), 2750-2754.
11 12
Haque, A., Richardson, R.K., & Morris, E.R. (2001). Effect of fermentation temperature on the rheology of set and stirred yogurt. Food Hydrocolloids, 15, 593-602.
13 14
*Isanga, J., & Zhang, G. (2009). Production and evaluation of some physicochemical parameters of peanut milk yoghurt. LWT-Food Science and Technology, 42, 1132- 1138.
15 16
Kamaly, K.M. (1997). Bifidobacteria fermentation of soybean milk. Food Research International, 30, 675–682
17 18 19
Karleskind, D., Laye, I., Halpin, E., & Morr, C.V. (1991). Improving acid production in soybased yogurt by adding cheese whey proteins and mineral salts. Journal of Food Science, 56, 999-1001.
20 21
Khosravi-Darani, K., Taheri, P., & Ahmad, N. (2015). Effect of Process Variables on the Probiotic and Starter Culture Growth in Synbiotic Yogurt Beet. RRJFPDT, 3(2), 13-24.
22 23
Khuri, A.I., & Cornell, J.A. (1987). Response surfaces: designs and analysis (pp. 127-145). New York: Marcel Dekker.
24 25
Kouane, D., Zhang, G., & Chen, J. (2005). Peanut milk and peanut milk based products production. A review. Critical Reviews in Food Science and Nutrition, 45,405-423.
26 27 28
Kristo, E., Biliaderis, C.G., & Tzanetakis, N. (2003). Modelling of rheological, microbiological and acidification properties of a fermented milk product containing a probiotic strain of Lactobacillus paracasei. International Dairy J, 13,517-528.
29 30 31
Lee, C., & Beuchat, L.R. (1991). Changes in chemical composition and sensory qualities of peanut milk fermented with lactic acid bacteria. International J Food Microbiology, 13 (4), 273183.
32 33
Lee, W.J., & Lucey, J.A. (2004). Structure and physical properties of yogurt gels: effect of inoculation rate and incubation temperature. J Dairy Science, 87, 3153-3164.
34 35
Lourens-Hattingh, A., & Viljoen, B.C. (2001). Yogurt as probiotic carrier food. International Dairy Journal, 11, 1-17.
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Page 15 of 18
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Raju, N.P., & Pal, D. (2014) Effect of dietary fibers on physico-chemical, sensory and textural properties of Misti Dahi. J Food Sci Technol. 51(11), 3124–3133.
3 4
Shortt, C. (1999). The probiotic century; historical and current perspectives. Trends in Food Science and Technology, 10, 411- 417.
5 6
Skriver, A., Roemer, H., & Qvist, K.B. (1993). Rheological characterization of stirred yoghurt viscometry. J. Texture Stud., 24,185-198.
7 8 9
Stijepic, M., Glusac, J., Milosevic, D.D., & Mikulec, D.P. (2013).Physicochemical characteristics of soy probiotic yoghurt with inulin additon during the refrigerated storage.Romanian Biotechnological Letters,18(2), 8078-8085.
10 11 12
Sunny-Roberts, E.O., Otulona, E.T., & Iwakun, B.T. (2004). An evaluation of some quality parameters of a laboratory-prepared fermented groundnut milk. European Food Research Technology, 218,452-455.
13 14
Talcot, S.T., Passeretti, S., Duncan, C.E., & Gorbet, D.W. (2005). Polyphenolic content and sensory properties of normal and high oleic acid peanuts. Food Chemistry, 90, 379-388.
15 16 17
Tsangalis, D., Ashton, J.F., McGill, A.E.J., & Shah,N.P. (2003). Biotransformation of isoflavones by bifidobacteria in fermented soymilk supplemented with D-glucose and Lcysteine. Journal of Food Science, 68, 623-631.
18 19 20
*Wu, S., Li, D., Li, S., Bhandari, B., Yang, B., Chen, X.D., & Mao, Z. (2009). Effects of incubation temperature, starter culture level and total solids content on the rheological properties of yogurt. International J of Food Engg., 5(2), 1556-3758.
21 22
*Yadav, D.N., Singh, K.K., Bhowmik, S.N., & Patil, R.T. (2010). Development of peanut milk– based fermented curd. International J Food Science and Technology, 45, 2650-2658.
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LEGENDS TO TABLES Table 1: Coded and actual levels of independent variables A. inoculum concentration (% v/v), B. incubation temperature (oC) and C. incubation time (hrs.) used in central composite design along with measured responses
4 5
Table 2: Design summary and estimated regression coefficients for dependent variables and their significance
6
Table 3: Criteria for optimization for process conditions alongwith responses
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LEGENDS TO FIGURES
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Fig. 1. Response surface plot for acidity as a function of, a) incubation temperature and inoculum concentration at incubation time of 15 hrs, b) incubation time and inoculum concentration at incubation temperature of 40ºC and c) incubation time and incubation temperature at inoculum concentration of 2%
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Fig. 2. Response surface plot for synersis as a function of, a) incubation temperature and inoculum concentration at incubation time of 15 hrs, b) incubation time and inoculum concentration at incubation temperature of 40ºC and c) incubation time and incubation temperature at inoculum concentration of 2%
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Fig. 3. Response surface plot for viscosity as a function of, a) incubation temperature and inoculum concentration at incubation time of 15 hrs, b) incubation time and inoculum concentration at incubation temperature of 40ºC and c) incubation time and incubation temperature at inoculum concentration of 2%
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Fig. 4. Response surface plot for viable cell count as a function of, a) incubation temperature and inoculum concentration at incubation time of 15 hrs, b) incubation time and inoculum concentration at incubation temperature of 40ºC and c) incubation time and incubation temperature at inoculum concentration of 2%
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Fig. 5. Response surface plot for firmness as a function of incubation temperature and inoculum concentration at incubation time of 15 hrs
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Table 1: Coded and actual levels of independent variables A. inoculum concentration (% v/v), B. incubation temperature (oC) and C. incubation time (hrs.) used in central composite design along with measured responses A: Inoculum Concentration C A
B: Incubation Temperature C A
C: Incubation Time C A
Acidity
Syneres is (%)
1
-1
1
1
43
1
18
0.26
68
2
1
3
-1
37
1
18
0.24
60
3
-1
1
-1
37
-1
12
0.1
51
4
-1
1
1
43
-1
12
0.16
47
5
0
2
0
40
0
15
0.12
52 51
2
-1.68
34.95
0
15
0.15
1.68
3.68
0
40
0
15
0.18
8
1
3
1
43
1
18
0.24
9
0
2
0
40
0
15
0.14
10
0
2
1.68
45.05
0
11
0
2
0
40
0
12
1
3
-1
37
-1
13
-1
1
-1
37
1
14
-1.68
0.32
0
40
0
15
0
2
0
40
1.68
16 17 18
0 0 0
2 2 2
0 0 0
40 40 40
0 0 0
19
1
3
1
43
20
0
2
0
40
Cell count (log cfu/ml)
35
0.693
6.7
0.0453
7.4
52.5
0.2512
6.5
45
0.612
6.4
47.5
0.456
7.6
50
0.455
7.2
78
33.7
0.442
7.1
78
35
0.487
7.5
53
45
0.351
7.5
15
0.24
63
33.2
0.321
6.2
15
0.14
50
45
0.388
7.6
12
0.13
51
49.6
0.318
7.3
18
0.2
76
44
0.027
6.9
0.12
78
38.5
0.354
6.2
0.23
68
40
0.593
7.7
15 15 15
0.14 0.12 0.12
50 53 51
47.5 45 47.5
0.36 0.352 0.593
7.3 7.5 7.5
-1
12
0.21
76
32
0.473
6.8
-1.68
9.95
0.14
46
43.5
0.715
7.5
TE D
15
20.05
EP
C coded level, A actual level
AC C
Firmness N
47.5
SC
0
7
M AN U
6
Viscosity (cP)
RI PT
Run
ACCEPTED MANUSCRIPT
Table 2: Design summary and estimated regression coefficients for dependent variables and their significance
Quadratic Significant Intercept 0.13 A 0.015** B 0.026** C 0.036** AB -0.005 AC -0.0075 BC -0.01 2 -0.0098 A 2 0.026** B 2 0.022** C 2 R (%) 94.22 Lack of Fit Insignificant **p <.01; *p <.05
Viscosity (cP) Firmness (N)
Quadratic Significant 51.54 1.68* 3.75** 6.88** 6.88** -4.38** -1.38 9.08** 1.65* 1.65* 98.29 Insignificant
Quadratic Significant 46.15 -1.499* -5.48** -1.72* -1.7 2.425* 0.45 -2.922** -0.98 -0.93 92.81 Insignificant
Linear Insignificant 0.414 -0.008 0.102* -0.044
AC C
EP
TE D
M AN U
Model
Synersis (%)
Cell Count (log cfu/ml) Quadratic Significant 7.50 0.29** -0.17** 0.13* -0.0125 0.0125 0.0625 -0.303** -0.29** 0.032 92.84 Insignificant
RI PT
Acidity (%)
SC
Factor
27.16 Insignificant
ACCEPTED MANUSCRIPT
Table 3: Criteria for optimization for process conditions alongwith responses
is in range is in range is in range minimize minimize maximize maximize is in range
1 37 12 0.1 46 32 0.4 6.2
3 43 18 0.26 78 52.5 0.715 7.7
Importance Solution 3 3 3 3 3 3 3 3
1.90% 38.25 °C 12.00 hrs. 0.101 43.78 50.33 0.4 7.41
TE D EP AC C
Actual response value ---0.12 45.5 52.5 0.442 7.5
RI PT
A:Ino Conc B:Temp C:Time Acidity Synersis Viscosity Firmness Cell count
Lower Upper Limit Limit
SC
Goal
M AN U
Constraints
ACCEPTED MANUSCRIPT
(a)
(b)
Design-Expert® Software Factor Coding: Actual Acidity Design points above predicted value Design points below predicted value 0.26
(c)
Design-Expert® Software Factor Coding: Actual Acidity Design points above predicted value Design points below predicted value 0.26 0.1
0.22
0.2 0.18
0.16
0.14 0.12 0.1
0.14 0.12 0.1
43.00
3.00 42.00 40.00
B: Temperature
18.00
3.00
1.50
38.00 37.00 1.00
15.00
C: Time
12.00 1.00
M AN U TE D EP AC C
40.00
14.00
A: Inoculum
43.00
42.00
41.00
15.00
C: Time
SC
Fig. 1
1.50
13.00
18.00
16.00
2.00 14.00
A: Inoculum
0.12
17.00
2.50
16.00
2.00 39.00
0.14
0.1
17.00
2.50
41.00
0.16
RI PT
A c id ity
A c id ity
0.22
Actual Factor A: Inoculum = 2.00
0.18
0.16
0.24
X1 = B: Temperature X2 = C: Time
0.2
Actual Factor B: Temperature = 40.00
0.18
0.1
0.22
X1 = A: Inoculum X2 = C: Time
0.2
Actual Factor C: Time = 15.00
A c id ity
0.1 X1 = A: Inoculum X2 = B: Temperature
Design-Expert® Software Factor Coding: Actual Acidity Design points above predicted value Design points below predicted value 0.26
39.00
13.00
38.00
12.00 37.00
B: Temperature
ACCEPTED MANUSCRIPT
(a)
(b)
Design-Expert® Software Factor Coding: Actual Synersis Design points above predicted value Design points below predicted value 78
(c) Design-Expert® Software Factor Coding: Actual Synersis Design points above predicted value Design points below predicted value 78
Design-Expert® Software Factor Coding: Actual Synersis Design points above predicted value Design points below predicted value 78
46
46
75
X1 = A: Inoculum X2 = B: Temperature
70
X1 = A: Inoculum X2 = C: Time
65
Actual Factor B: Temperature = 40.00
46
75
80
70
X1 = B: Temperature X2 = C: Time
65
Actual Factor A: Inoculum = 2.00
70
55 50 45
60
60 55 50
43.00
3.00 42.00
2.50
41.00 40.00
B: Temperature
18.00
3.00 17.00
1.50
38.00 37.00 1.00
2.50
16.00 15.00
2.00 39.00
A: Inoculum
50
40
45
C: Time
14.00
1.50
13.00 12.00 1.00
18.00
17.00
16.00
A: Inoculum
C: Time
M AN U TE D EP AC C
43.00 42.00
41.00
15.00
SC
Fig. 2
2.00
RI PT
S y n e rs is
S y n e rs is
60
S y n e r s is
Actual Factor C: Time = 15.00
40.00
14.00
39.00
13.00
38.00
12.00 37.00
B: Temperature
ACCEPTED MANUSCRIPT
(a)
(b)
Design-Expert® Software Factor Coding: Actual Viscosity Design points above predicted value Design points below predicted value 52.5
(c) Design-Expert® Software Factor Coding: Actual Viscosity Design points above predicted value Design points below predicted value 52.5
Design-Expert® Software Factor Coding: Actual Viscosity Design points above predicted value Design points below predicted value 52.5
32
32
32
X1 = A: Inoculum X2 = C: Time
Actual Factor A: Inoculum = 2.00
50
45
50 45
45
40 35 30
40 35 30
3.00
18.00
3.00
43.00
17.00
2.50 16.00 2.00 14.00
1.50 13.00
30
18.00
2.00
12.00 1.00
1.50 38.00 37.00 1.00
A: Inoculum
C: Time
M AN U TE D EP AC C
39.00
38.00
13.00
12.00 37.00
SC
Fig. 3
40.00
15.00
14.00
39.00
B: Temperature
43.00
42.00
41.00
16.00
40.00
A: Inoculum
35
17.00
2.50 41.00
15.00
C: Time
42.00
40
RI PT
V is c o s ity
V is c o s ity
55
55 Actual Factor C: Time = 15.00
50
V is c o s ity
Actual Factor B: Temperature = 40.00
X1 = B: Temperature X2 = C: Time
X1 = A: Inoculum X2 = B: Temperature
55
B: Temperature
ACCEPTED MANUSCRIPT
(b)
Design-Expert® Software Factor Coding: Actual cell count Design points above predicted value Design points below predicted value 7.7
(c) Design-Expert® Software Factor Coding: Actual cell count Design points above predicted value Design points below predicted value 7.7
Design-Expert® Software Factor Coding: Actual cell count Design points above predicted value Design points below predicted value 7.7
6.2
6.2
6.2
cell count = 7.3 Std # 19 Run # 16 X1 = A: Inoculum = 2.00 X2 = B: Temperature = 40.00
7.8
Actual Factor C: Time = 15.00
X1 = B: Temperature X2 = C: Time
X1 = A: Inoculum X2 = C: Time
Actual Factor A: Inoculum = 2.00
Actual Factor B: Temperature = 40.00
7.6 7.2 7 3.00
6.8 6.6 6.4
2.50
c e ll c o u n t
c e ll c o u n t
7.4
7.8
7.8 7.6 7.4 7.2 7 6.8 6.6 6.4
7.6 7.4
c e ll c o u n t
(a)
43.00 42.00
7.2 7 3.00
6.8 6.6 6.4
2.50
41.00 18.00
41.00
1.50
40.00
40.00
17.00
A: Inoculum
42.00
16.00
39.00
15.00
38.00 13.00
38.00 37.00 1.00
C: Time
B: Temperature
1.50
14.00
12.00 1.00
C: Time
M AN U TE D EP AC C
16.00
13.00
12.00 37.00
SC
Fig. 4
A: Inoculum
17.00
15.00
14.00
39.00
2.00
18.00
B: Temperature
RI PT
2.00
43.00
ACCEPTED MANUSCRIPT
Design-Expert® Software Factor Coding: Actual firmness Design points above predicted value Design points below predicted value 0.715 0.027
0.6
X1 = A: Inoculum X2 = B: Temperature
0.55
Actual Factor C: Time = 15.00
0.5
0.4 0.35 0.3
43.00
3.00 42.00
2.50
41.00 40.00 39.00
1.50
38.00 37.00 1.00
A: Inoculum
SC
B: Temperature
2.00
RI PT
firm n e s s
0.45
AC C
EP
TE D
M AN U
Fig. 5
ACCEPTED MANUSCRIPT
HIGHLIGHTS The present paper describes the development of peanut based probiotic yoghurt that can be a dairy alternative.
2.
Developed product is free from lactose, cholesterol and milk proteins.
3.
Since single culture is used, the product of consistent quality could be obtained.
4.
The model developed utilizing RSM could be used to find out optimum parameters for any factor combianation.
AC C
EP
TE D
M AN U
SC
RI PT
1.