Journal of Molecular Liquids 244 (2017) 279–284
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Journal of Molecular Liquids journal homepage: www.elsevier.com/locate/molliq
Application of Taguchi method to optimize garlic essential oil nanoemulsions Lebogang Katata-Seru a,b,⁎, Thabang C. Lebepe a, Oluwole Samuel Aremu a, Indra Bahadur a a b
Chemistry Department, Faculty of Agriculture, Science and Technology, North-West University, Mmabatho, Mafikeng 2735, South Africa Food Security and Safety Niche Area, Faculty of Agriculture, Science and Technology, North-West University, Mafikeng Campus, Mmabatho 2735, South Africa
a r t i c l e
i n f o
Article history: Received 30 July 2017 Received in revised form 2 September 2017 Accepted 3 September 2017 Available online 05 September 2017 Keywords: Antimicrobial growth promoters Essential oil Garlic Nanoemulsions Taguchi method
a b s t r a c t Essential oils have been recognised from both swine and poultry industries as an alternative to antimicrobial growth promoters as they pose a threat to animals and human health. Hence, the aim of this study was to develop garlic essential oil nanoemulsions (GEON) using Taguchi experimental design and emulsification method. Surfactant concentrations, mixing ratio, type of surfactant and stirring speed were selected as important factors influencing the droplet size and polydispersity index (PDI). The type of surfactant showed a greater effect on the droplet size and PDI during GEON preparation. The optimised nanoemulsion showed a droplet size, polydispersity index, good zeta potentials at 28.4 nm, 0.315 and 28.15 ± 1.1 mV, respectively. The compatibility of the garlic essential oil and Tween® 80 was ascertained by Fourier transform infrared spectroscopy. The presence of the important compounds of garlic in garlic essential oil nanoemulsions showed by gas chromatography-mass spectroscopy. Taguchi L-9 approach revealed to be an easy and useful tool to optimize various parameters investigated. Furthermore, the GEON was able to show antimicrobial activity improvement as an estimate to the garlic essential oil. The results of the study can be used further as a potential replacement for broiler growth performance in the near future. © 2017 Elsevier B.V. All rights reserved.
1. Introduction Antibiotics have been applied as growth promoters in animal feeds which were invented in the 1940s, where dried mycelia of Streptomyces aureofaciens were observed to improve animal's growth when fed to them [1]. The European commission banned the marketing and use of antimicrobial growth promoters (AGPs) in the feed using EC regulation No. 1831/2003 because some antibiotics led to the development of microbes resistant which are used to treat human and animal infections [1–3]. The impacts of the banning of the AGPs can be reduced if an adequate awareness is given to the execution of alternative disease prevention strategies and management factors. The alternatives to AGPs must have the same beneficial effects as AGPs, which include: increasing the antibacterial action that favours performance in different ways, lowering the incidence and severity of subclinical infections [4,5], minimising the microbial use of nutrients, lessing the amount of growth depressing metabolites produced by Gram-positive bacteria [6,7].
⁎ Corresponding author at: Food Security and Safety Niche Area, Faculty of Agriculture, Science and Technology, North-West University, Mafikeng Campus, Mmabatho 2735, South Africa. E-mail address:
[email protected] (L. Katata-Seru).
http://dx.doi.org/10.1016/j.molliq.2017.09.007 0167-7322/© 2017 Elsevier B.V. All rights reserved.
The use of essential oils (EOs) have gained more interest as promising AGPs substitutes and can be attested by various studies investigated in the poultry industry [5,8–17]. However the antimicrobial mechanism of essential oils is poorly understood due their lipophilic property and chemical structure. In contrast, the EOs has high volatility and some can be quickly decomposed by heat, humidity, light, or oxygen [18– 20]. Hence, many researchers have evaluated their enclosement in various colloidal systems such as microcapsules, microspheres, nanoemulsions as well as liposomes in order to reduce the volatility, improve an absorption mechanism and improve their bioefficacy [17–21]. Nanoemulsions have droplet size in the range of 10–500 nm [22,23]. They have shown more interest as delivery systems of functional lipophilic compounds (flavours, vitamins and antimicrobials) because of their benefits over other oil containing systems [24–27]. Studies have shown that garlic is one of the herbs most commonly used as a growth promoter [6]. It has been shown to inhibit the growth of a variety of microorganisms, like bacteria, fungi and viruses [7]. The factors that contribute to the bioactive components of garlic are sulphur-containing organic compounds known as dialkyl polysulphides that contain the antimicrobial activity that could be responsible for the growth promoting effect in broilers [6]. Garlic has been fabricated before by numerous researchers [28–35], but there is no record of garlic essential oil nanoemulsions intended for broiler growth performance.
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The objective of this present study was to obtain optimised formulation of garlic essential oil nanoemulsions using oil in water nanoemulsion method, with lower droplet size as a possible replacement for antibiotics in animal feeds and an increased antimicrobial activity. Taguchi method was chosen because is easy to be adopted, applied without knowledge of statistics, saves time and money by reducing amount of chemicals used during the experiment. Taguchi experimental design combines mathematical and statistical techniques, which incorporates an empirical study and it has been previously applied to the development of pharmaceuticals. A standard orthogonal array L-9 was used to examine a four factors system at 3 levels.
Table 2 Taguchi experimental parameters and constant parameters for preparation of GEON. Trials Surfactant concentrations (%)
Oil-surfactant mixing ratios
Type of surfactants
Homogenizer speed (rpm)
1 2 3 4 5 6 7 8 9
1:4 1:8 1:24 1:4 1:8 1:24 1:4 1:8 1:24
Tween® 20 Tween® 80 Pluronic F68 Tween® 80 Pluronic F68 Tween® 20 Pluronic F68 Tween® 20 Tween® 80
10,000 15,000 20,000 20,000 10,000 15,000 15,000 20,000 1000
3 3 3 5 5 5 7 7 7
2. Material and methods 2.1. Materials Garlic essential oil was purchased from the Natural life Health store (Brooklyn, South Africa). Deionized water was obtained from a Milli-Q system (Millipore, Bedford, USA) for all experiments. Polysorbate 80 (Tween® 80), polysorbate 20 (Tween® 20), 95% absolute ethanol and poloxamer 188 (Pluronic® F68) were purchased from Sigma Aldrich (Johannesburg, South Africa). 2.2. Experimental design and optimization of garlic nanoemulsion Taguchi experimental method was used to study the effect of formulation variables in optimizing the preparation of GEON. A standard orthogonal array L-9 was used to examine a four factors system at 3 levels. Surfactant concentrations, mixing ratio, type of surfactant and stirring speed were selected as important factors affecting the droplet size and PDI of the GEON as illustrated in Table 1. The mean droplet size and PDI were taken as responses. Analysing of variance was used for statistical analysis of the results using software (Minitab 17.01), to investigate which factors had remarkable result on the response parameters, and the optimum conditions.
particles before analysis. All experiments were carried out in triplicate and the obtained data were expressed as the mean ± relative standard deviation. 2.5. Transmission electron microscopy analysis Transmission electron microscopy was carried out to visualize the shape and morphology of the GEON. Briefly, one drop of GEON was negatively stained with phosphotungstic acid and positioned on a copper grid. TEM micrographs were acquired by using a TEM (Tecnai-10, Phillips) with a tungsten source and operating at 80 kV. 2.6. Fourier transform infrared spectroscopy GEON, GEOs and Tween® 80 were analysed by FTIR spectra of liquid dispersion which was obtained using a FTIR system equipped with a germanium attenuated (Perkin Elmer Spectrum, Shelton, CT, USA) in the spectral region 4000 to 400 cm−1 using 1 cm−1 resolution. The samples were placed directly in the FTIR sample holder in direct contact with the total reflection accessory crystal and infrared spectra, in transmittance mode.
2.3. Preparation of nanoemulsion
2.7. Gas chromatography mass spectroscopy analysis
Nanoemulsion formulations were prepared using spontaneous emulsification by Bouchemal, et al. [27], with little alteration of parameters according to the composition presented in Table 2. Ethanol was used as a co-surfactant and kept constant in all trials. The nanoemulsions were prepared by mixing the co-surfactant mixture and oil with the surfactant before adding the required amount of water. After that the mixture was equilibrated using a high speed homogenizer for 2 min with different speeds. The solvent was removed, in order to receive the nanodroplets of oil which were dispersed in an aqueous solution of water and hydrophilic surfactant, by evaporation during 45 min under reduced pressure.
Gas chromatography-mass spectrometry analysis were performed on a gas chromatograph Varian 450-GC IT mass spectrometer equipped with a standard non-polar capillary column (20 m × 0.18 mm i.d., 0.18 μm film thickness). The identification of compounds from the extracts was made based on fragmentation patterns together with matching of the mass spectra which obtain from each sample and compared with those in the NIST Mass Spectral Library.
2.4. Droplet size analysis and zeta-potential The mean droplet size and zeta-potential of nanoemulsions were determined by dynamic light scattering using Malvern Zetasizer Nano-series (Malvern Instruments, United Kingdom). Emulsions were filtered by using a PTFE 0.2 μL pore size membrane to remove possible dust Table 1 Taguchi L-9 experimental parameters and levels for preparation of GEON. Process parameters
Level 1
Level 2
Level 3
1
3
5
7
1:4 Tween® 20 10,000
1:8 Tween® 80 15,000
1:24 Pluronic® F68 20,000
2 3
Surfactant concentration (%) Oil-surfactant mixing ratios Type of surfactants
4
Homogenizer speed (rpm)
2.8. Antimicrobial activity for garlic essential oil and garlic essential oil nanoemulsions Antibiotic susceptibility tests were carried out on all E. coli O157 isolates to determine the resistant of the microbes using the paper disc diffusion method. Briefly isolates were grown on Nutrient agar at 37 °C for 18 to 24 h. Bacterial suspensions were prepared and aliquots of 100 μL were spread over Mueller Hinton agar. The 6 μm disks impregnated with garlic essential oil and GEON were placed on the surface of the inoculated agar plates and the plates were incubated at 37 °C for 18 to 24 h. After incubation, the essential oil and GEON inhibition zone diameters (IZD) were calculated and compared. 3. Results and discussion 3.1. The effect of formulation parameters on GEON droplet size and PDI The fabrication of GEO was done using the Taguchi design method. The investigated parameters were analysed for droplet size and PDI as shown in Fig. 1. The summary of results demonstrated that the
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Table 3 Mean S\N ratio for each level of the parameters for GEON droplet size and PDI. Factors
Droplet size
Surfactant concentration Oil-surfactant mixing ratio Type of surfactant Homogenizer
Fig. 1. The relationship between average droplet size and polydispersity index.
relationship between droplet size and PDI is not proportional to each other. The droplet sizes obtained ranged from 14.41 ± 0.907 to 336.5 ± 0.125 nm and PDI obtained from 0.321 to 0.924. The smallest average droplet sizes were obtained in trial 9, where 7% of Tween® 80 was used as a surfactant and the ratio of oil-surfactant was 1:24 with 10,000 rpm stirring speed. The smallest PDI was observed in trial 4 where 5% of Tween® 80 was used with 1:4 oil-surfactant mixing ratio and 20,000 rpm stirring speed. Tween® 80 is more effective in reducing the droplet size than Tween® 20, which is what was observed in their work, when they were formulating nanoemulsion Eucalyptus oil using Tween® 20 and Tween® 80 [29]. 3.2. The effect of formulation parameters on garlic essential oil nanoemulsion zeta potential The stable nanoemulsions were observed in trial 1, 5, 8, 4 and 2 in that order as illustrated in Fig. 2. The lowest zeta potential was obtained in trial 2 where 3% of Tween® 80 was used as a surfactant which indicated electrostatic repulsion between the particles due to lower zeta potential. The zeta potential showed the physical stability, which has been shown by respective lowest negative zeta potential according to Shah et al. [30]. Nanoemulsion exhibits a weak stability (agglomeration-flocculation) when the absolute value of zeta potential is below 30 mV, but when the absolute value is higher than 30 mV, nanoemulsions are assumed to be stable due to electrostatic repulsion [31]. In this study trial 2 showed to be more stable compared to other garlic nanoemulsions.
PDI
Mean S/N ratio
Mean S/N ratio
Level 1
Level 2 Level 3
Level 1 Level 2 Level 3
−45.5 −43.5
−43.0 −45.3
−42.25 −35.5 −41.0 −45.0
−37.5 8.623 −37.75 7.987
5.988 6.498
5.506 5.678
−49.0 −42.5
8.785 5.023
7.350 7.617
4.231 7.803
the quality of characteristics [27]. The smaller the better quality characteristic was used for average droplet size and the size distribution of nanoemulsions in this study. The optimal levels of the selected design parameters were used as the last step of Taguchi method to calculate by using the predicted ANOVA Eq. (1) and S/N ratio the-smaller-thebetter quality characteristic Eq. (2) taken from [36–39]. f ðxÞ ¼ f 0 þ
n X
f i ðxÞi − f m ðxÞ
where f(x) is the value of predicted S/N, f0 is the total mean S/N, fi(x)i is the mean S/N ratio at the optimal level, n is the number of the parameters affecting the quality characteristic, fm(x) is the grand average of performance. f ðxÞ ¼ −10 log x2
ð2Þ
where f(x) is the value of predicted S/N, and x is the estimated droplet size. The Table 3 illustrates the mean S/N ratio for each level of the parameters and the highest maximum-minimum values. It was found that the surfactant type had more effect on the droplet size and PDI of GEON formulation. The findings agree with the work done by Shahavi et al. [36], who have illustrated that droplet size and coalescence depends on the surfactant type since the method used is oil in water nanoemulsion, when they were preparing clove oil nanoemulsions [36]. Moreover, Figs. 3 and 4 showed the S/N graph response for droplet size and PDI agrees with Eq. (2) that the higher the S/N ratio, the smaller the variance of the droplet size around the desired value [39]. The L-9 Taguchi method predicted results of GEON as shown in Table 4 with predicted S/N ratio for droplet size of −23.173, was calculated using Eq. (1) and estimated droplet size was 14.41 nm calculated
3.3. Optimised formulation of GEON The optimal formulation conditions and parameters having a principal influence on the mean droplet size and size distribution were determined using the L-9 Taguchi experimental design. The desirable and undesirable conditions for the output characteristic were meant by Taguchi methods with the terms signal and noise (S/N), which reveals
Fig. 2. The effect of formulation parameters on garlic essential oil nanoemulsion zeta potential.
ð1Þ
i¼1
Fig. 3. Main effects plot for S/N ratios of GEON droplets size.
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Fig. 6. Transmission electron microscopy image of optimised GEON reported at 200× magnification.
Fig. 4. Main effects plot for S/N ratios of SN ratios of GEON PDI.
3.4. Fourier transform infrared spectrometry of GEON Table 4 Predicted and experimental results for GEON. Responds
Predicted Experimental
Droplets sizes mean (nm)
S/N ratio
PDI
S/N ratio
14.41 nm 28.41 ± 0.91 nm
−23.173 −29.069
0.233 0.315 ± 0.02
12.666 10.034
using Eq. (2). The predicted S/N ratio for PDI of GEON was 12.6663, with estimated PDI of 0.233, which was calculated similar to droplet size using Eqs. (1) and (2) respectively. The experimental results using the predicted optimal conditions for preparing GEON showed a good agreement with droplet size of 28.41 ± 0.91 nm and PDI of 0.315 ± 0.02. There was slight difference between the predicted and experimental droplet size and PDI. When we compare our results with work done by Shahavi et al. [36], who formulated clove nanoemulsions with droplet size range of 28.8 to 310.3 nm and PDI of 0.46 to 0.56, their results were almost similar but their PDI were higher than the obtained results, which showed improvement [32]. Sugumar et al. also prepared Eucalyptus oil nanoemulsion using Tween® 20 and 80, and obtained droplet size having the range size less than 70 nm, which was similar to the present work before impregnating them in chitosan film [29,37]. Fig. 5 demonstrated the intensity average distribution graph of the optimised GEON showing a monomodal distribution with a mean diameter of 28.41 ± 0.91 nm and PDI of 0.315 ± 0.02 with a zeta potential of −28.5 ± 1.15 mV. TEM image in Fig. 6 displayed a spherical morphology of the optimised GEON with different droplet sizes.
Fig. 5. Droplet Size distribution by intensity as function of droplet size of GEON.
The FTIR results showed the characteristic peaks for Tween® 80 peaks shown in Fig. 7A were covered in the GEON spectrum (Fig. 7C) due to the stretching vibration of garlic extract bands. The band 1325–1450 cm− 1 showed the S_O presence and 1675–1600 cm− 1 \\C\\C_C symmetric stretch which are present in garlic EO compounds as illustrated in Fig. 7B and C. The strong band around 3462 cm − 1 can be attributed to the O\\H stretching vibrations of GEON because nanoemulsion with in water. The increases in sizes of peaks in GEON spectra are due to the other excipients present in the formulation such as the surfactant [35,40].
3.5. GC–MS of GEON Fig. 8 show the GC–MS mass spectra analysis of the GEON which indicate the important constituents of garlic essential oil. Table 5 is a summary of the chemical constituents and the relative percentage of the total chromatogram area according to the total compounds of GEON. GC–MS analysis of GEON identified 4 constituents representing more than 99.5% of the total EO. The major components were Dimethyl disulphide (97.2%), Dimethyl sulphone (0.66%), 1, 2-Ethanedithiol (0.24%) and Dimethyl tetrasulphide (0.18%), which are mostly found in garlic [41].
Fig. 7. FTIR spectra of Tween® 80 surfactant A, garlic essential oil B, and GEON C.
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Fig. 8. GC–MS spectrum of disulphide dimethyl A, dimethyl sulphone B, 1,2-ethanedithiol C and dimethyl tetrasulphide D.
Table 5 GC–MS compounds of garlic essential oil nanoemulsion. No. CAS
Holder (%) Compounds
Formula
Molecular mass
1 2 3 4
97.2 0.66 0.24 0.18
C2H6S2 C2H6O2S C2H6S2 C2H6S4
94 94 94 158
624-92-0 67-71-0 540-63-6 5756-24-1
Dimethyl disulphide Dimethyl sulphone 1,2-Ethanedithiol Dimethyl tetrasulphide
3.6. Garlic essential oil and GEON antimicrobial activity test
difference. Further analysis is currently under way on the physicochemical characteristics such as stability, antioxidant and antibiotic studies, assessment of the in vitro and in vivo properties of GEON to determine the suitability for being used in broiler growth performance as possible animal feeds. Acknowledgements We would like to send our special gratitude to the Chemistry Department at North-West University for providing the research work facility, Food Security and Safety Niche Area and National Research Foundation in South Africa for their financial support.
Garlic Essential Oil Nanoemulsion exhibited a better inhibition levels against Escherichia coli than garlic essential oil as shown in Table 6 and Fig. 9. This is corresponds to the previously reported study using sunflower microemulsion [42].
4. Conclusion GEON was successfully prepared by spontaneous emulsification using high speed homogenizer method. The Taguchi L-9 approach showed quicker tool way to prepare GEON. In general 34 = 81 experiments were supported to be conducted. However, only 9 experiments in triplicate were done. The Tween®80 showed more effect on the droplet size and PDI for the preparation of GEON. The predicted optimised Taguchi method results and the experimental results had a small Table 6 Antibacterial activity of garlic essential oil and garlic essential oil nanoemulsions. No.
Name
Inhibition diameter measurement (mm)
1. 2.
Garlic essential oil Garlic essential oil nanoemulsion
13 ± 0.12 mm 15 ± 0.06 mm
Fig. 9. Photographic evidence of the antimicrobial inhibition of A) garlic essential oil, B) garlic essential oil nanoemulsions.
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References [1] J. Castanon, Poult. Sci. 86 (2007) 2466–2471. [2] G. Huyghebaert, R. Ducatelle, F. Van Immerseel, Vet. J. 187 (2011) 182–188. [3] B.V. Bonifácio, P.B. da Silva, M.A. dos Santos Ramos, K.M.S. Negri, T.M. Bauab, M. Chorilli, Int. J. Nanomedicine 9 (2014) 1–15. [4] B. George, C. Quarles, D. Fagerberg, Poult. Sci. 61 (1982) 447–450. [5] J. Brennan, J. Skinner, D. Barnum, J. Wilson, Poult. Sci. 82 (2003) 360–363. [6] S.D. Feighner, M.P. Dashkevicz, Appl. Environ. Microbiol. 53 (1987) 331–336. [7] A. Knarreborg, C. Lauridsen, R.M. Engberg, S.K. Jensen, J. Nutr. 134 (2004) 1487–1492. [8] S.B. Aji, K. Ignatius, Y. Asha'Adatu, J.B. Nuhu, A. Abdulkarim, U. Aliyu, M.B. Gambo, M.A. Ibrahim, H. Abubakar, M.M. Bukar, Res. J. Poult. Sci. 4 (2011) 22–27. [9] E. Demir, Ş. Sarica, M. Özcan, M. Sui Mez, Br. Poult. Sci. 44 (2003) 44–45. [10] F. Hernandez, J. Madrid, V. Garcia, J. Orengo, M. Megias, Poult. Sci. 83 (2004) 169–174. [11] G. Horton, M. Fennell, B. Prasad, Can. J. Anim. Sci. 71 (1991) 939–942. [12] I.A. Ibrahiem, T.A. Talib, F.F. Fathi, S.A. Awadalla, Y.I. Yousif, First Scientific Conference of Faculty of Veterinary Medicine, Benhar, 1–4 September 2004. [13] N. Landy, G. Ghalamkari, M. Toghyani, F. Moattar, J. Med. Plant Res. 5 (2011) 2332–2338. [14] N. Landy, G.H. Ghalamkari, M. Toghyant, Livest. Sci. 142 (2011). [15] A. Brenes, E. Roura, Anim. Feed Sci. Technol. 158 (2010) 1–14. [16] E. McCartney, Poult. Int. 41 (2002) 36–43. [17] W. Windisch, K. Schedle, C. Plitzner, A. Kroismayr, J. Anim. Sci. 86 (2008) E140–E148. [18] T. Nakatsu, A.T. Lupo, J.W. Chinn, R.K. Kang, Stud. Nat. Prod. Chem. 21 (2000) 571–631. [19] M. Sherry, C. Charcosset, H. Fessi, H. Greige-Gerges, J. Liposome Res. 23 (2013) 268–275. [20] A.R. Bilia, C. Guccione, B. Isacchi, C. Righeschi, F. Firenzuoli, M.C. Bergonzi, Evid. Based Complement. Alternat. Med. 2014 (2014). [21] F.C. Flores, R.F. Ribeiro, A.F. Ourique, C.M.B. Rolim, C.d.B.d. Silva, A.R. Pohlmann, R.C.R. Beck, S.S. Guterres, Quim Nova 34 (2011) 968–972.
[22] A. São Pedro, I. Santo, C. Silva, C. Detoni, E. Albuquerque, in: A. Méndez-Vilas (Ed.), Microbial Pathogens and Strategies for Combating Them, 2, Formatex Research Center Pulisher 2013, pp. 1364–1374. [23] C. Solans, P. Izquierdo, J. Nolla, N. Azemar, M. Garcia-Celma, Curr. Opin. Colloid Interface Sci. 10 (2005) 102–110. [24] O. Sonneville-Aubrun, J.T. Simonnet, F. L'Alloret, Adv. Colloid Interf. Sci. 108–109 (2004) 145–149. [25] J. Xue, Q. Zhong, J. Agric. Food Chem. 62 (2014) 9900–9907. [26] M.-J. Tsai, Y.-S. Fu, Y.-H. Lin, Y.-B. Huang, P.-C. Wu, PLoS One 9 (2014), e102850. [27] K. Bouchemal, S. Briançon, E. Perrier, H. Fessi, Int. J. Pharm. 280 (2004) 241–251. [28] J.D. Ilić, B.G. Nikolovski, I.S. Lončarević, J.S. Petrović, B.M. Bajac, M. Vučinić‐Vasić, J. Food. Process. Eng. (2016) http://dx.doi.org/10.1111/jfpe.12349. [29] D.Q. Luo, J.H. Guo, F.J. Wang, Z.X. Jin, X.L. Cheng, J.C. Zhu, C.Q. Peng, C. Zhang, J. Biomater. Sci. Polym. Ed. 20 (2009) 21–31. [30] N. Rai, A.K. Jain, J. Abraham, Int. J. Pharm. Res. Rev. 2 (2013) 12–24. [31] F.-L. Yang, X.-G. Li, F. Zhu, C.-L. Lei, J. Agric. Food Chem. 57 (2009) 10156–10162. [32] J. Wang, Y. Cao, B. Sun, C. Wang, Food Chem. 127 (2011) 1680–1685. [33] G. Von White, P. Kerscher, R.M. Brown, J.D. Morella, W. McAllister, D. Dean, C.L. Kitchens, J. Nanomater. 2012 (2012) 55. [34] H.M. Zheng, H.B. Li, D.W. Wang, D. Liu, J. Food Sci. 78 (2013) N1301–N1306. [35] K. Rajam, S. Rajendran, R. Saranya, J. Chem. 2013 (2013) 4. [36] M.H. Shahavi, M. Hosseini, M. Jahanshahi, R.L. Meyer, G.N. Darzi, Desalin. Water Treat. 57 (2016) 18379–18390. [37] B.M. Gopalsamy, B. Mondal, S. Ghosh, J. Sci. Ind. Res. 68 (2009) 686–695. [38] A. Bendell, J. Disney, W. Pridmore, Industries, Productivity, Improvement and Case Study, IFS Publication, UK, 1989. [39] L. Katata, L. Tshweu, S. Naidoo, L. Kalombo, H. Swai, J. Nanopart. Res. 14 (2012) 1–8. [40] J. Booyens, M.S. Thantsha, BMC Complement. Altern. Med. 14 (2014) 1–11. [41] D. Mnayer, A.-S. Fabiano-Tixier, E. Petitcolas, T. Hamieh, N. Nehme, C. Ferrant, X. Fernandez, F. Chemat, Molecules 19 (2014) 20034–20053. [42] C.H. Anjali, M. Dash, N. Chandrasekaran, A. Mukherjee, Int. J. Pharm. Sci. 2 (2010) 123–128.
