MATHEMATICALLY DESIGNED BIOPROCESS FOR RELEASE OF VALUE ADDED PRODUCTS WITH PHARMACEUTICAL APPLICATIONS FROM WASTES GENERATED FROM SPICES INDUSTRIESHTML Full Text
MATHEMATICALLY DESIGNED BIOPROCESS FOR RELEASE OF VALUE ADDED PRODUCTS WITH PHARMACEUTICAL APPLICATIONS FROM WASTES GENERATED FROM SPICES INDUSTRIES
Meemansha Singh and Siddharth Vats *
Institute of Biosciences and Technology, Shri Ram Swaroop Memorial University, Lucknow - 225003, Uttar Pradesh, India.
ABSTRACT: A mathematical model optimizing bio-physico-chemical pre-treatment of steam exploded Piper nigrum, and Syzygium aromaticum lignocellulosic biomass waste was developed. The model was developed using, RSM, involving central composite face-centered design (CCD) with six parameters, three levels and 40 runs, at 95% confidence level. Six parameters optimized were quantity of each enzyme (a) Cellulase (ml); (b) Xylanase (ml) for enzymatic actions at 50 ºC; (c) Incubation time of 2-15 days for which substrate were dipped in various solvent systems; (d) Volume of solvent systems used; (e) Time of incubation at given steam pressure for steam explosion; and (f) Steam pressure 10-15 Psi. Cellulase and xylanase enzymes used were with activity (3.563 IU/mL), (33.32 IU/mL) respectively. ANOVA was applied for validation of the predicted model at 95% of confidence level. The Base 10 log transformation was selected from the comparative study, and the model predicted 13.79 µmoles/mL, the release of polyphenols at 2 days of incubation of substrate with 10 ml of the solvent system, under 15.0 psi steam explosion pressure for 15 min, with the treatment of 1.00 ml of cellulose. The released polyphenols were tested against human pathogenic microbes (Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Micrococcus) and found to possess strong antimicrobial properties.
The steam explosion, RSM, Cellulase, Xylanase, Piper nigrum and Syzygium aromaticum
INTRODUCTION: History has witnessed a maximum number of loss to human life either by war or infectious diseases. With the domestication of animals, humans have made microbes to modify them genetically and morphologically and evolving to human hosts.
Microbes are evolving, and antibiotic resistance among microbes is one of the biggest challenges which have given a blow to all possible human medicine and drug system 1.
So, it’s become an urgent and highest priority to discover new medicines and new drugs with better efficacy and target specificity. Effective and cheap medicines can be made available to everyone if the overall cost of the process decreases while productivity increases. More than 25 percent of total drugs available in the market are made up of phytochemicals or plant’s derived substances 2. Phytochemicals like polyphenols have protective role against heart diseases, cancers and degenerative diseases 3, 4, 5. Poly-phenols include flavonols, flavanones, flavones, flavon-3-ols, iso-flavones, etc. Herbs and spices are an integral part of South Asian diet and are very rich in phytochemicals. Ayurveda the oldest known medicinal practice exploits the goodness of phytochemicals present in plants, herbs and spices 6, 7. In Indian traditional medicine system, Ayurveda, use of herbs and spices for health benefits includes the use of turmeric, ginger, cinnamon, basil, and mace, etc. 8 Phyto-chemicals obtained from spices can be a source to various drugs and medicines. Piper nigrum and Syzygium aromaticum lignocellulosic biomass wastes generated from industries associated with oil, and its derivative products can be used for the extraction of phytochemicals by employing bioprocess based techniques.
According to the report released by Spices Board of India, 37000 tonnes of pepper and 2060 tonnes of clove were produced in the year 14, 15 respectively. Even 1% waste of this huge amount would be a large quantity. This biomass can be exploited for the extraction of valuable phytochemicals. Like in other lignocellulosic biomass lignin provide a structural framework, which holds cellulose and hemicelluloses combined and embedded within it 9. To disturb this structural framework, pre-treatment of lignocellulosic biomass is must to ease the extraction of phytochemicals 10. Biological pre-treatment methods for Piper nigrum and Syzygium aromaticum lignocellulosic biomass wastes generated from industries is better than chemical and physical treatment methods, being eco-friendly, specific and producing fewer side products. Steam explosion based enzymatic pre-treatment process is significantly influenced by factors like steam pressure, the ratio at which each enzyme used and incubation time with solvent system, incubation time during the steam explosion, steam explosion pressure and solvent system volume.
Practically, optimizing “One variable at a time” approach disregards the complex interactions among parameters. Out of various new statistical optimization methods, RSM combines mathematical and statistical techniques for analyzing the problem with several independent variables having control on a dependent variable 11, 12. In the present study, optimization was done through stepwise experimental strategy. First, few wet lab experiments were conducted and based on them, screening of most significant factors was done and then optimization of significant components. A mathematical model has been generated with all possible relations among optimized factors to maximize polyphenols release.
MATERIALS AND METHODS:
Chemicals and Materials: All chemicals used in this study were of analytical grade and purchased from Himedia and S. D. Fine chemicals.
Enzyme Unit: Enzyme activity was calculated in units/mL which is defined as the amount of enzyme catalyzing the production of one-mole micromole of colored product per ml/min.
Piper nigrum and Syzygium aromaticum Biomass Waste and Steam Explosion: Piper nigrum and Syzygium aromaticum lignocellulosic biomass used were obtained from various small scale industries in and around Lucknow, producing pepper and clove oils. For pre-treatment of Piper nigrum and Syzygium aromaticum biomass waste was soaked with the different solvent system as mentioned in Table 1.
TABLE 1: USE OF DIFFERENT SOLVENT SYSTEMS FOR EXTRACT PREPARATION
|S. no.||Conical flask (100 ml)||Solute: Solvent (w/v; 5g:20 ml)||Solvent (v/v)||Solution system (w/v)|
|1.||A||Syzygium aromaticum||Ethanol (100%)||5g/20ml|
|2.||B||Syzygium aromaticum||DW (100%)||5g/20ml|
|3.||C||Syzygium aromaticum||Ethanol + DW(1:1)||5g/10ml:10ml|
|4||D||Piper nigrum||Ethanol (100%)||5g/20ml|
|5||E||Piper nigrum||DW (100%)||5g/20ml|
|6||F||Piper nigrum||Ethanol + DW (1:1)||5g/10ml:10ml|
This system was kept undisturbed for 2-15 days. This chemical time-based pre-treatment of Piper nigrum and Syzygium aromaticum was carried out to disturb its lignocellulosic structure and provide easy access to enzymes for biological pre-treatment. After this steam explosion was carried at 121 ºC temperature, 15 Psi, maintained for 8-10 min. Pre-treated solid cellulosic residues were collected and treated with enzymes, 0.5 g dry substrate / 15 ml of 100 mM sodium phosphate buffer pH 6-13, was taken and crude enzymes were added according to the values for hydrolysis 14, 15, 16 as suggested by RSM in a 100 ml flasks, incubated at 120 rpm for 12 h at 50 ºC 17 and filtered 18.
Experiment Description: 5 g Piper nigrum and Syzygium aromaticum wastes were taken in 250 ml Erlenmeyer flasks. To form mathematical model, it was necessary to perform few wet lab experiments, to pre-treat steam exploded Piper nigrum and Syzygium aromaticum with enzymes in different ratios for hydrolysis. The values suggested by RSM were obtained by setting RSM, CCD with replicated of factorial points of 1, and replicates of axial star point value as 1 and center points value 6 with K value >5 (alpha =1.56508), and 40 runs. A design was then suggested by the software
Design Matrix 10 (Stat-Ease, Minneapolis, MN), according to which practical values were set and total polyphenols values were calculated. 6 Factors namely A, B, C, D, E, F were used. Design Matrix with evaluation for Response Surface Quadratic Model. No aliases found for Quadratic Model. Aliases were calculated based on our response selection, taking into account missing data points, if necessary. The design had degree of freedom (df) evaluations for the model (27), residuals (12), lack of fit value (7) and pure error degree of freedom (5) where minimum valued recommended for df for lack of fit is 3 and, 4 for pure error. This ensures a valid lack of fit test. Fewer df will lead to a test that may not detect lack of fit. Data collected was then, used in the software, Design expert 10 (Stat-Ease, Minneapolis, MN), the range was filled in the software as shown in Table 2.1, to help Software to generate a model, which was used to perform wet lab experiments as shown in Table 2.2, and experimental values of polyphenols (PP) release was fed. Once the practical was performed for all set as per the model suggestion the value obtained was entered in the design layout the view.
A response was chosen by clicking on the corresponding node under analysis. Six steps were performed. The first step was transformation where response node and transformation was chosen. As in our case, we have chosen base 10 Log, after comparing with other values of other statistical parameters. Fit summary data was obtained and used to evaluate models in step 2. Step three involves the choosing of the model order and desired terms from the list. After this, analysis of variance was performed based on which a mathematical model was developed based on results, showing coded and actual value equations.
Diagnostics of the model was the fifth step where model fit values and transformation choice was evaluated. In the lasts step, model graphs were obtained and analyzed for interpretation and evaluating the final model. To optimize the parameters, the software was then fed priority values for each factor and based on that; software predicted values for PP release at a different set of conditions.
TABLE 2.1: CODED AND ACTUAL VALUES OF PARAMETERS
Developing Matrix and Empirical Relationship: For evaluation software used was Design expert 10. Using response surface methodology, the six parameters of Incubation time, the volume of the solvent system, steam Explosion pressure, Psi time of incubation, the volume used of cellulase and xylanase enzymes. Representation of independent factors in quantitative form can be given as:
Y= Ø (x1, x2,...............xk) ± er (1)
Where, Y and x1, x2, x3......xk with k quantitative factors, er is a measure of experimental error. Ø represents response functions.
Representing the PP (Poly-phenol) released and the responses as functions of A, B, C, D, and E; PP= f (A, B, C, D, E, F)
The second order polynomial (regression) equation used to represent the response surface PP is:
Y= b0+∑bixi + ∑biix2i + ∑bijxixj + er (2)
TABLE 2.2: EXPERIMENTAL SETUP AS SUGGESTED BY SOFTWARE BASED ON RSM
|Std||Block||Run||Factor 1 A incubation
|Factor 2 B Volume (ml)||Factor 3 C Steam Expl. (Psi)||Factor 4
D: Psi Time (min)
5 E. Cellulose
|Factor 6 F Xylanase (ml)||Response 1 Total Poly -Phe mg/ml||O.D @405 nm|
PP released based on six factors, the selected polynomial could be expressed as:
b0 + b1(A) + b2(B)+ b3(C) + b4(D) + b5(E) + b6 (F)+ b11(A2) + b22(B2) + b33(C2) + b44(D2) + b55(E2) + b66(F2) + b12(AB) + b13(AC) + b14(AD) + b15(AE) + b16(AF) + b23(BC) + b24(BD) + b25(BE) + b26(BF) + b34(CD) + b35(CE) + b45(DE) (3)
Where, Intercept is A- Incubation, B- Volume, C-Steam Explosion, D- PsiTime, E- Cellulase, F-Xylanase.
Preparation of Microbial Culture and Plates for Test: Microbial culture of 106 colonies forming unit (CFU) for analysis was freshly prepared from stock solution. Muller Hinton broth (MHB) was sterilized and autoclaved. 15 g / 1000 ml of (MHB: DW) distilled water of MHB was used as a media for inoculation of pathogenic microbes. Media prepared had a pH 7.0 and post inoculation, incubated for 24 h at 28 ± 2 ºC @ 120 rpm in an incubator shaker. Plates were prepared of Muller Hinton agar (MHA) to check the antimicrobial activity of extracts.
Assay for Antimicrobial Activity of Against Gram Positive and Gram Negative Microbes: Modified Bauer-Kirby well diffusion method was employed 18, 19. Muller Hinton agar (MHA) plates made up of autoclaved MHA media and had bacteria swabbed (100 µl), were subjected to well preparation of 8 mm diameter size. These wells were then impregnated with 20, 30 50 µl of phytochemical extract. These plates were then incubated overnight at 28 ± 2 ºC, and the zone of inhibition around the well was measured. Large zones of inhibition around the disc indicated susceptibility of microbe toward the polyphenol extract. While, small zones of inhibition or no zones of inhibition were an indicator of resistive microbes. The method followed was according to the Clinical Laboratory standards Institute (CLSI) recommended.
RESULTS AND DISCUSSION:
Standardization of Moisture Content: Syzygium aromaticum and Piper nigrum waste in powdered form was taken, dried at room temperature 25 ± 5ºC, to prevent loss of valuable phytochemicals. The substrate was weighed at an interval of one hour as gap time where they were kept in plastic bags. The procedure was repeated until the weight was standardized as a measure of loss and gain of moisture content was uniform for each hour. The work was carried out with two sets (one was oven dried, and one was microwave dried) to find the average weight Table 3.
TABLE 3: STANDARDIZATION OF MOISTURE CONTENT IN THE BIOMASS
|Sets**||Glass plates (g)||Powder and watch glass (g)||Dried with||Weight loss||Permissible limit|
|1||67.5464||86.4852 g||Oven||1.8 g||6.1% / 10%|
|2||65.0954||86.5815 g||Microwave||2.1 g||5% / 10%|
Central Composite Design: Co-efficient were obtained by applying central composite design, using the Design Expert Statistical software package (Stat-Ease, Minneapolis, MN), at 95% confidence level, significant coefficients were determined, used for finding final empirical relationships to estimate polyphenols (PP), and with equations showing empirical relationships for polyphenol (PP). In case of the mixture of design coded equations are determined first and then from this the actual equations, by replacing each term in coded equations with its coding formula:
Xcoded = Xactual - X̅ / [(Xhigh-Xlow)/2] (4)
While substituting in the quadratic term will generate the result in new quadratic coefficients and correction in the intercept.
TABLE 4: STATISTICAL DATA RELATED TO DIFFERENT TRANSFORMATION TO CHOOSE THE MOST SUITABLE TRANSFORMATION
|S. no.||Transform||Lack of fit P-value||Adjusted “R” square||Predicted “R” squared||F-value||Prob>F||Model||Lack of fit significant or not|
|1||None||< 0.0001||< 0.0001||0.5639||0.7319||0.3581||-3.7624||9.62||<0.0001||Quadratic||Sign.|
|3||Natural log||<0.0001||< 0.0001||0.6725||0.6943||0.5193||-2.4233||14.69||<0.0001||Quadratic||Sign.|
|4||Base 10 log||<0.0001||<0.0001||0.6725||0.6943||0.5193||-2.4233||14.69||<0.0001||Quadratic||Sign.|
|5||Inverse square root||<0.0001||<0.0001||0.6878||0.6121||0.5836||-2.6828||15.68||<0.0001||Quadratic||Sign.|
|9||Arc sine square root||--||--||--||--||--||--||--||--||--||--|
FIG. 1: Base Log 10 TRANSFORMATION
Choice of a Transformation: After comparing different statistical parameters as shown in Table 4 the most suitable transformation was chosen. Base 10 Log was chosen after analyzing the obtained data Fig. 1.
Final Equation in Terms of Coded Factors:
Log 10 (Total Poly Phenol) = + 1.00 + 0.012*A -4.507E - 003*B + 0.011*C - 4.512E - 003*D + 0.16*E + 0.15*F - 9.727E - 003*AB + 5.688E -003*AC + 5.104E - 003*AD - 2.951E -03*AE + 2.513E - 003*AF - 6.343E -004*BC + 0.010*BD + 0.010*BE + 0.016*BF - 0.012*CD + 0.012*CE -7.929E - 004*CF + 3.646E - 003*DE - 2.997E -003*DF + 0.083*EF + 0.037*A2 + 0.030*B2 + 0.048*C2 + 0.036*D2 + 5.029E003*E2 + 8.300E -003*F2 ......(6)
Preliminary one factorial wet lab experiments were perfomed to get the ranges, and it had been identified that parameters described in the Table 3 were chosen out of various parameters and were focussed to be optimised. Statistically model was evalueated by the F-test for analysis of variance (ANOVA) as shown in Table 5 and 6. The model F-value of 4.80 implies the model is significant. There is only a 0.33% chance that an F-value this large could occur due to noise. Values of "Prob> F" less than 0.0500 indicate model terms are significant. In this case E, F, EF is significant model terms. Values greater than 0.1000 indicate the model terms are not significant.
If there are many insignificant model terms (not counting those required to support hierarchy), the model reduction may improve your model. The "Lack of Fit F-value" of 174.02 implies the lack of fit is significant. There is only a 0.01% chance that a "Lack of Fit F-value" this large could occur due to noise. Significant lack of fit is bad- we want the model to fit.
TABLE 5: ANOVA FOR RESPONSE SURFACE QUADRATIC MODEL (ANALYSIS OF VARIANCE TABLE [PARTIAL SUM OF SQUARES - TYPE III])
|Lack of Fit||0.16||7||0.023||174.02||< 0.0001||Significant|
TABLE 6: STATISTICAL DATA
|C.V. %||10.46||Pred R-Squared||-1.8072|
|-2 Log Likelihood||-106.58||BIC||-3.29|
A negative "Pred R-Squared" implies that the overall mean a better predictor of your response than the current model. "Adeq Precision" measures the signal to noise ratio. A ratio greater than 4 is desirable. This ratio of 8.321 indicates an adequate signal. This model can be used to navigate the design space.
Final Equation in Terms of Actual Factors:
Log 10 (Total Poly Phenol) = + 2.71928 - 0.015292 * Incubation - 0.045202 * Volume -0.17738 * Steam Explosion - 0.064210 * Psi Time - 0.070795 * Cellulase + 0.029204 * Xylanase -2.99295E - 004 * Incubation * Volume + 3.50050E -004 * Incubation * Steam Explosion + 2.24374E -004 * Incubation * Psi Time - 9.08104E – 004 * Incubation * Cellulase + 7.73276E - 004* Incubation * Xylanase - 5.07464E – 005 * Volume * Steam Explosion + 5.96364E - 004 * Volume * Psi Time + 4.13134E - 003 * Volume * Cellulase + 6.29789E - 003 * Volume * Xylanase - 1.33166E -003 * Steam Explosion * Psi Time + 9.61954E - 003 * Steam Explosion * Cellulase - 6.34284E - 004 * Steam Explosion * Xylanase + 2.08330E -003 * Psi Time * Cellulase - 1.71270E - 003 * Psi Time * Xylanase + 0.33024 * Cellulase * Xyla-nase + 8.66754E-004 * Incubation 2 + 1.18022E-003* Volume2 + 7.62332E - 003* Steam Explo-sion 2 + 2.97953E - 003 *Psi Time2 + 0.020116 * Cellulase2 +0.033201* Xylanase2 ....(7)
Effect of Enzyme on the Structure of Piper nigrum and Syzygium aromaticum lignocellulosic Biomass Waste: After optimizing the parameter for enzymatic pretreatment, strucutral change in the Piper nigrum and Syzygium aromaticum lignocellulosic biomass waste were studied and change in size was noted, and this change in the structure of the biomass might be one reason for enhanced release of polyphenols after pre-treatment. Disturbance in the crystallinity of the lignocellulosic biomass makes them more prone to enzymatic hydrolysis. Crystallinity of biomass influences the hydrolysis 20.
Steam explosion and then further enzymatic treatment of Piper nigrum and Syzygium aromaticum lignocellulosic biomass by disrupting inters and intra hydrogen bonding of cellulose fibrils 21 can be the reason for enhanced polyphenol release. Other reason could be amorphous sites on lignin which because of steam explosion got disturbed and enzyme were prevented from being getting bonded to lignin, instead of attacking the cellulose and increasing their efficiency 22.
Synergistic Antimicrobial Activity of Extract Prepared: All the extracts prepared were tested for antimicrobial activity against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Micrococcus. The results obtained are listed in Table 7.
Need of Polyphenol in Combating the Diseases: Pathogens and diseases have affected human and its live stocks since ages. The ultimate source of drugs is medicinal plants and herbs which are abundant. Antibiotics are losing their edge in the fight against diseases and pathogens. Many antibiotic resistance microbes like vancomycin-resistant Enterococcus (VRE), PRSA, MRSA, quilone, and ciprofloxacin resistance P. Aeruginosa (QCPRA) pose a challenge to our well being. Many foodborne pathogens such as E. coli, Salmonella, and Campylobacter responsible for diarrhea and gastroenteritis have resistance towards antibiotics. The stem of Fadogia agrestis showed the presence of saponins, steroids, terpenoids, flavonoids, tannins, anthraquinone, glycosides and alkaloids. Extract demonstrated antibacterial activity against S. aureus, S. spp. B. subtilis and E. coli 2. A diet rich in phytochemicals may decrease the chances of deadly diseases like heart diseases & cancers 5.
Vegetables, berries and fruits, and beverages are good sources of flavonoids and are associated with reducing the risks of no. of diseases, flavonoids have shown their effects on immune system both in-vitro as well as in-vivo 23. Polyphenols of low molecular weight and are having three-ring structures and are of various types based on the different substitutions 23. Flavonoids play a number of important roles in plants as antimicrobials, antioxidant, attractors, light receptors, and many other biological activities 24. And the main possible mechanism is their antioxidant activity.
TABLE 7: ANTIMICROBIAL ACTIVITY OF EXTRACT PREPARED UNDER DIFFERENT SET OF CONDITIONS
Where A, B, C, and D are Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa and Micro coccus. 8P.N.= 8 min steam explosion treated Piper nigrum, 15P.N. = 15 min steam explosion treated Piper nigrum, where as S.A. stands for Sygium arromaticum, D.W. distilled water E = ethanol
Antioxidants are evolved as an important part of natural defense mechanism among living organisms 25. These are the molecules which scavenge the free radicals species and inhibit the chain reactions which can damage vital molecules of living organisms. Intake of flavonols and flavones can reduce the chances of heart disease like myocardial infarction and strokes. Methods to increase the production of phytochemicals can be done by understanding the phytochemical pathway genes, which lead to the synthesis of these compounds in fruits and other vegetables. Biochemical and molecular techniques can be used to enhance the productions. Isoflavones are the subclass of flavonoids and are scarcely distributed in nature.
The objective of using RSM CCD design was to optimize the hydrolysis conditions for enhancing the release of phytochemicals like polyphenol. One parameter at one time, based optimization cannot study the combined effect of all variables. There have been various studies for optimization of reducing sugar released and bioethanol production from lignocellulosic wastes. And pre-treatment of lignocellulosic materials is must to remove lignin and disturb the crystallinity of hemicellulose 22. Numbers of pre-treatment methods have been introduced including physical, chemical and biological, which are used either singularly or in different combinations. Sindhu et al., 2012 studied surfactant assisted acid pre-treatment of sugarcane tops for bioethanol production with the help of Box-Benkhen Design and 0.798 g/g sugarcane tops, reducing sugar were obtained 26.
Similarly RSM based statistical tool was used for optimizing enzymatic hydrolysis of alkaline pretreated peroxide wheat straw, by Qi et al., (2009) 27, where they noted conditions like cellulase loading (40.00 FPU/g), substrate concentration 22.00 g/L, surfactant concentration 6.676 g/L with hydrolysis time of 72 h. Use of acid, chemicals, and surfactant affects environment & lead to the production of more inhibitors, while the use of a large amount of water at pre, during and post-treatment can add to cost and make it more energy consuming 22. Presence of various phytochemicals in Piper nigrum and Syzygium aromaticum if purified can be used in pharma industries also which can turn waste in to gold. This model predicted satisfactory the minimum use of chemicals and wastage of energy with the production of value-added producers from agricultural wastes also give it an edge over other process.
CONCLUSION: From this investigation, the following important conclusions were derived:
- An empirical relation among different parameters (Where, Intercept is A-Incubation, B-Volume, C-Steam Explosion, D-PsiTime, E-Cellulase, F-Xylanase) was developed to predict the polyphenols release, at 95% confidence level, incorporating central composite design (CCD), design mode was quadratic, based on response surface study.
- The Base 10 Log transformation was selected from the comparative study, and the model predicted 13.79 µmoles/mL, the release of polyphenols at 2 days of incubation of substrate with 10 ml of the solvent system, under 15.0 Psi steam explosion pressure for 15 min, with the treatment of 1.00 ml of cellulose.
- The released polyphenols were tested against human pathogenic microbes (Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Micrococcus) and had shown antimicrobial activity against them.
ACKNOWLEDGEMENT: The authors gratefully acknowledge the SRMU, Lucknow for providing all the necessary help and support.
CONFLICT OF INTEREST: The authors declared no competing interests.
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How to cite this article:
Singh M and Vats S: Mathematically designed bioprocess for release of value added products with pharmaceutical applications from wastes generated from spices industries. Int J Pharm Sci & Res 2019; 10(1): 130-38. doi: 10.13040/IJPSR.0975-8232.10(1).130-38.
All © 2013 are reserved by International Journal of Pharmaceutical Sciences and Research. This Journal licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
M. Singh and S. Vats *
Institute of Biosciences and Technology, Shri Ram Swaroop Memorial University, Lucknow, Uttar Pradesh, India.
04 May 2018
06 July 2018
22 November 2018
01 January 2019