INTRODUCTION:

Nanoparticles have a particular propensity to lower their very high surface energy, which is the origin of their thermodynamic instability (Vimala, Samba Sivudu, Murali Mohan, Sreedhar, and Mohana Raju, 2009). Uncovered nanoparticles tend to stabilize themselves either by sorption of ions/molecules from the environment or by lowering the surface area through agglomeration. In order to avoid the later, nanoparticles have to be stabilized. The three conceptions of electrostatic, steric, and their combination electrosteric repulsive forces are generally available means for the prevention of agglomeration of nanoparticles.

The concept of stabilizing nanoparticles in viscous media, where the diffusion constants are low, is newly emerging still proven means of stabilizing nanoparticles. Polysaccharides being able to form a viscous environment for metal nanoparticles can play vital role in stabilizing nanosilver (NS) (Huang and Yang, 2004).

Development, characterization, and exploring applications of nanophase materials are all elementary to the anticipated nanoscience revolution. Within the last decade, researches on nanomaterials have magnified exponentially (Hosokawa, Nogi, Naito, and Yokoyama, 2012). Fundamentals of this development are truly based on the stabilization. Present work emphasized on the application of lemon seed mucilage for the stabilization of silver nanoparticles. No reports were found which have reported application of lemon seed in the nanotechnology/pharmaceutical arena. Mucilages are rich in polysaccharides which are usually natural polymers. Owing to the characteristics of polysaccharides, they tend to increase the viscosity of the aqueous medium. Present work hypothesized on the stabilization of NS by viscous medium formed by mucilage of lemon seed.

In present research article we reported the application of augmented simplex mixture design for extraction of lemon seed mucilage, which had been used to stabilize NS. This was the first attempt in pharmaceutical arena to explore lemon seed mucilage for stabilizing the NS.

MATERIALS AND METHODS:

Silver nitrate and ascorbic acid was procured from Sigma Aldrich. Lemon seeds were separated from the lemon fruits which were purchased from the local market. Lemon fruits were authenticated from the Botany department of Y.C. College of Science, Satara.

Experimental design:

Augmented simplex centroid design was used to study the influence of independent variables, extraction temperature, and extraction time and water seed ratio on the extraction yield (Y). The levels integrated for independent variables were decided on the results of precluding experiment, where experiment was conducted by soaking 1 gm of lemon seeds with 2 ml of water for 2hr. at 40ºC. Mucilage was the recrystallized using 95% alcohol and subsequently dried at room temperature, further kept in desiccators for final moisture removal. Augmented simplex centroid design was selected to recommend the model for the yield. Along with linear interactions, cubic and special cubic interactions were also observed in the evaluation of model. Therefore, the experimental data were fit into a second order polynomial equation with extended cubic interactions. The model proposed for response (Y) was,

Y = β 1X1+ β2X2+ β3X3+ β12X1X2 + β13X1X3+ β 23X2X3 + β123X1X2X3 Eq. 1

Where, Y is the extraction yield (dependent variable), the main (β1. β2, β3), interactions effects (β 12, Β13, β2 3, β 123).

Isolation and extraction of lemon seed mucilage:

Experimental design of 14 runs at different levels of independent variables (temperature 30 to 80 ºC, extraction time 1 to 8hr, and water/seed ratio 1:0.25 to 1:2 was used. pH 7 was maintained during experiment. Aqueous extraction technique was used to isolate mucilage from the seeds. Mucilage was extracted using distilled water. The pH of aqueous medium was adjusted to 7 with the help of 0.1 N NaOH/HCL. Seeds were mixed with distilled water and kept on magnetic stirrer for 4 hr at a constant temperature. Later, mucilage was separated from the thick solution using muslin cloth. Adhered mucilage of separated with sufficient amount of water. Mucilage was then recrystallized using 95% ethanol, subsequently which was dried in oven at 50°C for 2 hr. excess moisture was removed by keeping it in desiccator for 12 hr. Finally, the dried weight of extract of mucilage was recorded.

Determination of yield:

The mucilage obtained was weighed and yield was determined by the following equation (Nazir, Wani, and Masoodi, 2017):

Yield = Weight of extracted mucilage after drying/ Weight of lemon seeds taken for extraction* 100

Synthesis of NS using lemon seed mucilage as a stabilizing agent:

NS were synthesized with a completely novel method with the end objective of newer avenue for commercial way of synthesis. A newer approach was initiated with the inspiration originated from the scanty yield of NS reported by several researchers (Logeswari, Silambarasan, and Abraham, 2015; Prabhu and Poulose, 2012; Rai, Yadav, and Gade, 2009). In present investigation proportion of silver nitrate was raised up to 0.65%. Several reports mentioned 1 to 5 ml of 1mM of silver nitrate. Although some methods were reported with higher proportion of silver nitrate but the reported methods used organic solvents. We have synthesized NS using green method with aqueous solvent system. A completely novel method was developed in which, a freshly prepared aqueous solution of silver nitrate (0.65%) was used as a starting material. In another volumetric flask, 2% mucilage of lemon seed was prepared by stirring at 1000rpm for 20 mins, subsequently filtered to obtain a clear solution. Both solutions in equal proportion were mixed with the magnetic stirrer for 10mins at 100 RPM. To the mixture, 1ml of 0.1N sodium hydroxide(Singh, Sinha, and Mandal, 2009) was added slowly. Subsequently 0.5 ml of 2% ascorbic acid was added drop wise with a continuous agitation. Resulting solution was kept in a dark place for a couple of days and observed for color change. A UV-Visible spectrum between 600 to 200nm was recorded to confirm the synthesis of NS (Twu, Chen, and Shih, 2008). Synthesized NSs were suspended in an excess quantity of acetone and dispersion was heated to 40⁰C to evaporate the acetone. The yield was determined and resulting powder was kept in an air tight container away from light for further investigation. Prepared NS was characterized for UV-Visible spectroscopy, IR, TEM, particle size analysis and zeta potential.

RESULTS AND DISCUSSIONS:

Statistical analysis:

Design-Expert version 7.0.0 was used to predict the response surface methodology for the experimental data. Augmented simplex centroid design included 14 runs were conducted. The data obtained were fit in the model equation (1) for extraction yield (Y). The regression equation obtained was,

Y = +2.76X1+ 3.99X2 +3.31X3 +16.31X1X2 +16.45X1X3+ 5.82X2X3 -101.04X1X2X3 Eq. 2

Table 1: Experimental runs

Stanard	Run	Temperature (ºC)	Extraction time(hr)	Seed water ratio	Yield (gm)
1	1	1.000	0.000	0.000	1.44
9	2	0.167	0.167	0.667	2.7
5	3	0.000	0.500	0.500	2.2
8	4	0.167	0.667	0.167	2.3
2	5	0.500	0.500	0.000	3.1
3	6	0.500	0.000	0.500	3.3
12	7	0.000	1.000	0.000	2.1
7	8	0.667	0.167	0.167	2.5
14	9	0.500	0.500	0.000	3.2
10	10	0.333	0.333	0.333	2.5
6	11	0.000	0.000	1.000	3
11	12	1.000	0.000	0.000	1.4
4	13	0.000	1.000	0.000	2
13	14	0.000	0.000	1.000	3.1

Studentized residuals versus predicted values were observed for constant error. Influential values were checked from externally studentized residuals. Predicted values for yield were determined from the design model were shown in table 1. On comparing, the validity for each experimental run was determined. Box-Cox plot was also observed for power transformations. A standard deviation of 0.060 was observed for the model. Model adequacy was evaluated by determination of R2, adjusted R2, and predicted R2; values of 0.9950%, 0.9906, and 0.9694 were obtained for each respectively. Predicted R2, 0.9694 and adjusted R2, 0.9950 show reasonable agreement with a difference of less than 2%. ANOVA determined a mean value of 2.49%, and a PRESS value of 0.15. An insignificant lack of fit and a standard error of 0.010 further validate the model. Adequate precision of 44.056 indicates an adequate signal. Thus, it was implied that the model can be used to design space and also applied successfully.

Table 2: Analysis of variance table [Partial sum of squares - Type III

Source	Sum of Squares	df	Mean square	F value	p-value Prob > F
Model	4.99	6	0.83	229.95	< 0.0001	Significant
Linear Mixture	1.34	2	0.67	186.06	< 0.0001
AB	2.68	1	2.68	740.72	< 0.0001
AC	0.93	1	0.93	258.18	< 0.0001
BC	0.11	1	0.11	30.59	0.0009
ABC	0.35	1	0.35	96.70	< 0.0001
Residual	0.025	7	3.614E-003
Lack of fit	9.500E-003	3	3.167E-003	0.80	0.5544	Not significant
Pure Error	0.016	4	3.950E-003
Cor Total	5.01	13

Analysis of variance of variables and their interactions were presented in Table 2. The level of each coefficient measures its importance. Significance for every coefficient was analyzed by the P-value obtained in ANOVA. Values of P (P< 0.05) indicate the significance of terms. Lesser values for P indicate more coefficient significance.

Results from ANOVA showed, the yield was significantly influenced by temperature and water/seed ratio. Extraction time had a lesser significance; this may be due to the more hydrophilicity, rapid solubility (in water) of the lemon seed mucilage. All the interactions had a significant effect on extraction yield. Regression Eq. (2) can be used to make predictions about the response (Table 2). The coefficients are scaled to accommodate the units of each factor. To understand the relative impact of each factor, 3D response surface and contour curves (figure 2) were plotted which illustrate the interaction between all variables and help determining location of optimal conditions for better yield.

Table 3: Regression results for the special Cubic Model

Source	Result
Std. Dev.	0.060
Mean	2.49
C.V. %	2.42
PRESS	0.15
R-Squared	0.9950
Adj R-Squared	0.9906
Pred R-Squared	0.9694
Adeq Precision	44.056

Figure 2: Response surface and contour plot

Effect of temperature and time:

The effect of temperature and time, presented in Fig. 3 shows a strong interaction between temperature and time. An extraction yield of 2.1 g/100 g was obtained at a relatively low temperature (30ºC). Extraction yield considerably increased with increase in temperature from 30ºC to 50ºC. It can be inferred from Fig. 3 that yield is higher at 40ºC. Response surface shows that extraction yield increased to a maximum point and then decreased. Maximum yield of 3.1 g/100 g was obtained at 40ºC and started to decrease at and above 70ºC. Temperature set aside better diffusion of water into solid matrix of mucilage to solubilize the substances. As a consequence, the mucilage was effortlessly released and the extraction yield improved (Muñoz, Cobos, Diaz, and Aguilera, 2012). At elevated temperature (more than 60ºC) seeds turn into less sticky and mucilage discharge occurs(Campos, Dias Ruivo, da Silva Scapim, Madrona, and de C. Bergamasco, 2016) . However, above 60ºC, yield was found to be decreased, which may be due to degradation of polysaccharides leads to decline in the mucilage yield (Campos et al., 2016). Also, increasing the time of extraction was not having significant influence on the yield. This may be because of more hydrophilicity and more water solubility of the lemon seed mucilage (Capitani, Ixtaina, Nolasco, and Tomás, 2013). Still, extraction time, up to 2 hr influenced the efficiency of extraction and increases the yield. Later on, after 2 hr yield was found to be decreased. Liquid penetrates, dissolves and subsequently diffuses out the mucilage from seed pericarp. Mucilage of lemon seed was concentrated on the pericarp and hence less time of extraction was needed for effective extraction. Yield after 2 hr was decreased because of mutual effect of extraction time and temperature which was increased up to 45ºC. Trends in extraction yield showed an increasing tendency from 1 to 1.5 h and a decreasing trend was observed above 2 h. The mutual effect of temperature and time may be best explained by mass transfer effect, which causes the mucilage to disperse at a higher rate, showing a strong interaction between temperature and time(Felkai-Haddache et al., 2016; Rodríguez-González et al., 2014; Sepúlveda, Sáenz, Aliaga, and Aceituno, 2007). The effect of time was more pronounced at higher temperatures (40ºC) but extended extraction time might have caused changes in the polysaccharides structure and decreased the yield. A mutual effect of increase in temperature and extraction time led to a raise in the yield of mucilage. Highest extraction yield (3.2 g/100 g) of seed mucilage was obtained at a high temperature (40ºC) and short extraction time of 2 h. However, on increasing the temperature (above 40ºC) beyond a certain point of time (2 h) led to a decrease in the yield. This indicated that about 1.5 h is a sufficient time for mucilage extraction. Decrease in yield, after 2 h time occurs due to the hydrolysis of polysaccharides at higher temperature (Warren, 1996). Different other studies pertaining to optimization, reported a decrease in yield of bioactive compounds with an increase in temperature. The declining yield was a consequence of thermal degradation of bioactive compounds at elevated temperatures (Jouki, Mortazavi, Yazdi, and Koocheki, 2014).

Figure 3: Effect of temperature and extraction time

Effect of water/seed ratio and time:

The effect of water/seed ratio and time is shown in Fig. 3. Lowest extraction yield of 2.09 g/100 g was attained at water/seed ratio of 1:2 Increase in water/seed ratio up to 1:1.5 increased the yield to a certain maximum value of 2.1 g/100 g. Increase in time also showed increased extraction yield. Extraction time leads to an improved exposure of seeds to aqueous medium (Jouki et al., 2014). Fig. 3 shows increase in the yield. The response surface shows the effect of time was more marked at higher water/seed ratios. Extraction time influences the extraction efficiency. A significantly long extraction time has a positive effect on the yield of polysaccharides (Yaich et al., 2013). Response surface showed fairly linear interaction between water/seed ratio and time. Combined effect of increase in extraction time and water/seed ratio increased the yield. However, the graph predicted that yield increases steadily and slowly rather than a quick increase. Similar results were also found where a longer extraction time favored the polysaccharide production (Samavati and Manoochehrizade, 2013). Also, cress seeds showed alike outcome for extraction yield (Karazhiyan, Razavi, and Phillips, 2011). Yield of mucilage increased with increasing the water/seed ratio. This may be owing to the ease of use of more liquid that acts as a dynamic force to exude mucilage out of the seeds as the amount of water/seed ratio was increased (Koocheki, Mortazavi, Shahidi, Razavi, and Taherian, 2009). A greater mucilage yield water/seed ratio 1:1 showed an increase in mucilage yield. Enhancement in time also showed increased extraction yield. Extraction time directed to an increased exposure of seeds to aqueous medium (Jouki et al., 2014). Fig. 3 shows increase in the yield. The response surface shows the effect of time was more pronounced at higher water/seed ratios. Extraction time influences the extraction efficiency and selectivity of the fluid. An appreciably extended extraction time has an affirmative effect on the yield of polysaccharides (Lima Junior et al., 2013). Response surface shows somewhat linear interaction between water/seed ratio and time. Combined effect of increase in extraction time and water/seed ratio increased the yield. However, the graph predicted that yield increases steadily and slowly rather than a sharp increase. Alike results were also attained where a extended extraction time enhanced the polysaccharide yield from Malva sylvestris (Samavati and Manoochehrizade, 2013). Also, cress seeds demonstrated alike results for extraction yield (Karazhiyan et al., 2011). Yield of mucilage improved with raising the water/seed ratio. This may be owing to the availability of extra liquid that acts as a driving force to exude mucilage out of the seeds as the amount of water/seed ratio was improved (Koocheki et al., 2009). A better mucilage yield was as well reported from Alyssum homolocarpum and Opuntia spp. seeds as function of water ratio (Jouki et al., 2014).

Figure: 4 Effect of extraction time SW ratio when A is zero

Effect of temperature and water/seed ratio:

Effect of temperature (A) and water seed ratio (C) shown in figure 5. Results obtained showed slight co-relation of lesser significance. Response surface showed a increasing trend in yield. At water/seed ratio 1:0.25, at higher temperature showed decrease in yield. However, at a water/seed ratio 1:1 and an increase in temperature 40°C showed an increasing tendency. It can be revealed from Fig. 4, decreased water/seed ratios at higher temperatures, showed lesser yield. Water acts a driving force and optimum temperature (40ºC, in this case) allows better penetration of aqueous medium to increase yield (Campos et al., 2016; Jouki et al., 2014).

Figure 5: Effect of temperature S:W ratio when B is zero

Mucilage optimization:

Mathematical and graphical optimizations were used to establish the most favorable conditions. Optimum state was based on the highest extraction yield. An optimal state of 38°C, and water/seed ratio of 1:08 at 1hr 10 min was predicted by Design-Expert, with an extraction yield of 3.4 g. A graphical representation shown in figure 6 illustrates the optimal yield. The plot represents the best extraction conditions to obtain the highest extraction yield of lemon seed mucilage. Validation was carried out by performing empirical study at predicted optimal conditions, which revealed the yield 3.3 gm.

Figure 6: Graphical illustration showing optimal conditions for the extraction of mucilage

Biosynthesis of silver nanoparticles:

Monodisperse silver nanoparticles were successfully synthesized using lemon seed extract. Digital images (for visual observations) of the synthesized NS were offered in Figure 7 and 8. First, there was a color change from transparent before the initiation of reaction to the yellow-brown depending on the composition of the reaction mixture (Landau, 1937). This indicated clearly the reduction of cationic silver to its metallic ion counterpart and the synthesis of NS. Reaction mixtures were not cloudy nor did they contain any precipitates, just colloidal (Mulfinger et al., 2007). This was a clear indication of formation of NS and was assumed to form stable colloidal dispersion (Guzmán, M.G., Dille, J., Godet, 2009). The development of the color from pale yellow to dark brown was related to the initial concentration of Silver nitrate, and, with increasing its amount, the colloid turned dark brown, evidencing the formation of NS at a higher concentration (Muzamil, Khalid, Aziz, and Abbas, 2014).

Figure 7 color change from transparent to pale yellow to dark brown

Figure 8 Color change to dark brown (supernatant is in completely colloidal state)

The reaction was completed after 2 days at ambient temperature in dark. The yield was >68% Therefore, the reaction was halted after 2 days and reaction mixture was kept in refrigerator at 6-8 degree Celsius.

UV- Spectroscopy

Surface Plasmon Resonance, SPR, band, because of collective oscillation of electrons at the surface of metallic silver, was observed in all the samples in the range of ~420–430 nm. This was the further evidence to prove synthesis of NS using lemon seed extract. With the increase in the concentration of AgNO₃ and extract, there was an increase in intensity of the SPR peak. This indicated more NS were formed with increasing Silver nitrate up to 0.65% w/v. The presence of a solitary SPR peak indicated the formation of spherical NS (Thomas et al., 2008). We observed no stable NS above an Ag: extract mass ratio of 1.0:1.5, indicating the minimum extract required for particle stability. The results of SPR were shown in figure 9.

Figure 9: SPR peaks of NS recorded at 426nm using CS extract at increasing concentration of Ag

Zeta potential:

Zeta potential analysis is a technique for determining the surface charge of nanoparticles in solution. Nanoparticles are naturally unstable in water by themselves, and are therefore need surface fuctionalization for optimum water stability. The purpose can be fulfilled by using molecules which must bind to the NP surface. Moreover they must be a hydrophilic moiety so that NP will be stable in water. The overall charge of the NP is the charge of the stabilizing moiety, a value that can be determined with zeta potential measurements (Hjelmeland, 2015).

When a charged NS is solubilized in an electrolyte solution, a cloud of co-ions and counterions immediately surrounds it. At the immediate surface of the NP, the local concentration of counterions is higher than the concentration of co-ions. A charged NP in an electrolyte solution has an electrical potential that drops with the distance from its surface.

In present investigation, zeta potential of the synthesized NS was found to be 30.71. Zeta potential is able to influence the pharmacokinetic properties of nanosystems in the body. Nanoparticles with positive zeta potential can better target various organs in the body. Moreover, can get absorbed effectively though various route of administration like skin, brain, ocular etc. (Honary and Zahir, 2013).

Figure 10 : Zeta potential of NS

Transmission electron microscopy:

TEM micrograph of NS was presented in Figure 11. The mean particle size was reported to be 20 ± 10 nm, which confirms ability of the method developed produce <30 nm NS. TEM results may prove the significance of present work and to our knowledge was the first reported illustration for the production of CS extract stabilized NS of <30 nm in size, produced in mass production.

CONCLUSION:

Response surface modeling for extraction of mucilage from lemon seed provides a way to understand the interdependence of extraction conditions on the yield. Results show that the effect of temperature and water/seed ratio has statistical significance in the extraction of mucilage. Second order polynomial model with extended special cubic interactions was obtained to predict the extraction yield of mucilage. Predicted and actual yield was found to be corresponding to each other, which validated the model applied. Using this mucilage, we also have demonstrated a simple and convenient process for preparing NS with narrow size distributions in the range of 20–50 nm. These NS could be easily prepared either as stable aqueous colloidal aqueous dispersion. The UV–Vis and TEM measurements indicated and confirmed formation of NS. We believe this method can be simply scaled up for the making of large volumes of silver nanoparticles, which should make them particularly well suited for industrial applications especially of pharmaceutical drug delivery sector.

ACKNOWLEDGEMENTS:

The author thanks the Gourishankar Education Society and Satara College of Pharmacy for providing all the research facilities and support to carry out research process.

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Received on 06.01.2019 Accepted on 29.01.2019

Asian J. Pharm. Tech. 2019; 9 (1):31-39

DOI: 10.5958/2231-5713.2019.00007.2