POTENTIAL USE OF ULTRASOUND TO PRODUCE HIGH SOLIDS EMULSIONS

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1 POTENTIAL USE OF ULTRASOUND TO PRODUCE HIGH SOLIDS EMULSIONS L. Consoli 1a, G. F. Furtado 1b, R.L. Cunha 1c, M. D. Hubinger 1d 1 Department of Food Engineering School of Food Engineering University of Campinas Zip Code Campinas SP Brazil. Phone: Fax a larissa.consoli@gmail.com; b furtado.gf@gmail.com; c rosiane@unicamp.br; d mhub@unicamp.br RESUMO Utilizou-se ultrassom para obter emulsões cineticamente estáveis para posterior secagem em spray dryer. Foram avaliados tempo de sonicação de 3, 7 e 11 minutos nas amplitudes de potência de 50%, 75% e 100% (em relação à potência nominal do equipamento), calculando-se a densidade energética demandada em cada ensaio. As emulsões foram caracterizadas quanto a diâmetro médio e distribuição de tamanho das gotas, microscopia óptica, potencial zeta, índice de cremeação (IC) e comportamento reológico. Foram obtidas emulsões com distribuição de tamanho bimodal, com diâmetro D [3,2] entre 0,7 a 1,4 µm e IC entre 5% a 12%, sendo estes inversamente proporcionais às variáveis avaliadas, porém com aparente estabilização das propriedades na condição de 100% de amplitude de potência e 7 minutos de sonicação. O diâmetro D [3,2] mostrou dependência da densidade energética como uma função de potência. ABSTRACT Ultrasound was used to obtain kinetically stable emulsions for further spray drying. Sonication time of 3, 7 and 11 minutes were evaluated at power amplitudes of 50%, 75% and 100% (in relation to the nominal power of the equipment), where energy density required for each assay was calculated. Emulsions were characterized for droplets mean diameter and size distribution, optical microscopy, zeta potential, creaming index (CI) and rheological behavior. The products presented bimodal size distribution, with D [3,2] ranging from 0.7 to 1.4 µm and CI between 5% and 12%, being this parameters inversely proportional to the variables studied, but with an apparent stabilization after the treatment at 100% power amplitude at 7 min sonication. D [3,2] showed to depend of energy density as a power function. PALAVRAS-CHAVE: sonicação, óleo de palma, emulsificação por alta energia. KEYWORDS: sonication, palm oil, high energy emulsification. 1. INTRODUCTION In the last years, emulsion-based products have been seen not only as a part of food product, but also as potential delivery systems of active ingredients such as pharmaceutical drugs, nutraceuticals and bioactive compounds (McClements, 2015). Spray drying emulsions is an alternative to enhance their shelf life and also to improve transport and storage issues. Currently, many techniques to produce emulsions are known. The most frequently used are those that employ mechanical devices, such as high pressure homogenizers, rotor-stator mixers and ultrasound equipment. The last one, despite of the ability of providing many advantages in relation to process and product characteristics, is not considered a fully developed technique (Abbas et al., 2013). This work had as main goal evaluating the effect of ultrasound process parameters power amplitude and sonication time on high solid emulsions formation, in order to set the best condition to produce food emulsions for further spray drying.

2 2. MATERIAL AND METHODS 2.1. Material Aqueous phase of emulsions were composed of sodium caseinate (Alibra Ingredients - Campinas, SP, Brazil), maltodextrin MOR-REX 1910 (Dextrose Equivalent (DE) = 9-12) and Dried Glucose Syrup (DGS) MOR-REX 1930 (DE = 26-30), both supplied by Ingredion Brazil Industrial Ingredients Ltd. (Mogi-Guaçu, SP, Brazil). The oily phase was composed of palm oil (Cargill Foods Brazil - Itumbiara, GO, Brazil) and ethanol 95%. All other materials used in this work were of analytical grade EmulsionsPreparation Aqueous phase preparation: Emulsions had total solid concentration of 30 g/100 g, where the oily phase represents 15 g/100g of the total solids. Sodium caseinate, maltodextrin and DGS were individually solubilized in Milli-Q water containing 0.01% sodium azide, in the concentrations of 10.9, 37.9 and 37.9 g/100g, respectively. The solutions were stirred overnight at room temperature (~25 C). After this period, they were mixed with equal proportions of maltodextrin and DGS, until achieve a final protein/carbohydrate ratio of 1/5. The ph was then adjusted to 7.5 with NaOH 1 M. Coarse Emulsion: Ethanol 95% (0.4 g/100 g emulsion) was added to palm oil at 50 C. This oily phase was added to the aqueous mixture and the system was stirred at 4000 rpm for 2 min, using a rotorstator device (Silverson L5M-A Laboratory Mixer, Chesham, Buckinghamshire, UK). Ultrasound treatment: Coarse emulsion was completely transferred to a jacketed beaker connected to a thermostatic bath, in order to keep the temperature below 35 C in all assays. An ultrasonic processor Q700 (700W full power, 20 khz frequency - QSonica - Newton, CT, USA) was used. The probe (Ø=12.5 mm) was immersed 24 mm into the liquid and sonication was performed for 3, 7 and 11 min at power amplitudes of 50%, 75% and 100% of the equipment nominal power (700 W). These values were defined from preliminary trials. Assays were performed with 300 g (~285 ml) of emulsions. All assays were performed in duplicate Emulsions Characterization Emulsions droplet size and size distribution: A laser light scattering equipment (Mastersizer 2000, Malvern Instruments, Worcestershire, UK) was used to perform size measurements. Droplet mean diameter was expressed as the volume-surface mean diameter D [3,2] (Sauter mean diameter Equation 1). The Span was calculated from Equation 2. Each sample was analyzed in triplicate. D 3,2 = n id i 3 Span = D 0.9 D 0.1 D 0.5 n i D i 2 (1) Where n i is the number of droplets with diameter D i, and D 0.1, D 0.5 and D 0.9 represent the diameter of accumulated distribution of 10%, 50% and 90% of total droplets, respectively. Optical microscopy: Emulsions microstructure were visualized using an optical microscope Carl Zeiss Axio Scope A1 (Gottingen, Alemanha), with a total 1000x magnification. Images were acquired by the software Axio Vision Rel ζ-potential: 100 µl of each emulsion were diluted in 9.9 ml of Milli-Q water and measurements were performed in triplicate using a Zetasizer Nano Series (Malvern Instruments, Worcestershire, UK). (2)

3 Creaming index (CI): Immediately after preparation, 100 ml of each emulsion were transferred to cylindrical glass tubes (Ø=26 mm), sealed and kept at room temperature (~25 C) for 24 h. Phase separation was expressed as the ratio between the height of the superior phase (H) and the total height of liquid (H T ), as shown in Equation 3. CI = H H T (3) Rheological behavior: Emulsions flow curves were obtained using a cone-plate geometry (Ø= 60 mm) in a shear-controlled rheometer AR1500ex (TA Instruments, Elstree, UK). The analysis was done in the range between 0 and 1000 s -1, in 3 min, in a three-step sequence: up-down-up. The second up curve data was fitted to the Newtonian model (Equation 4) and to the Power Law (Equation 5). (4) n k. (5) in which σ is the shear stress(pa), ƞ is the viscosity (Pa.s), is the shear rate (s -1 ), k is the consistency index (Pa.s n ) and n is the behavior index (dimensionless) Energy Density Calculation The concept of energy density (ED) is applicable for the production of emulsions by mechanical devices. It relates the power introduced into the device and the volume flow rate of the fluid (Karbstein and Schubert, 1995). For ultrasound processors operating in batch, ED is calculated by Equation 6 (Jafari et al, 2007), which can also be used for rotor-stator devices, just by replacing t son by the stirring time used. The power, in this case, can be obtained by Equation 7. Ev, ult ( P tson) / V (6) Where P is the Power delivered to the system (W); t son is the sonication time and V is the volume of the fluid. P ( U i) (7) Where P is the power delivered to the system (W), U is the electric tension (V - volts) and i is the electric current (A - ampère) Statistical Analysis The data were statistically analyzed by Tukey test using the Statistic 12 software (Statsoft, Tulsa, Okla., USA). Differences between means were considered significant at a 95% confidence level (p 0.05). 3. RESULTS AND DISCUSSION 3.1. Emulsions droplet mean diameter, size distribution and microstructure Emulsions from all assays presented bimodal size distribution, independently on the power amplitude. However, this factor strongly affected on obtaining smaller droplets: in Figure 1, it is clear that, for the

4 same sonication time, the curves are shifted to the left when the power amplitude has increased. This fact is also demonstrated by the parameter D [3,2] (Figure 2A): at a fixed sonication time, the higher the power amplitude, the lower the D [3,2]. Sonication time affected D [3,2] in the same way. These observations show that emulsions characteristics are controlled by both the parameters. Figure 1. Size distribution diagrams and emulsions optical micrographs. (A) Coarse emulsion; Emulsions sonicated for 7 minutes with (B) 50%, (C) 75% and (D) 100% power amplitude. Emulsions sonicated for 7 or 11 min (100% power amplitude) showed similar mean diameters, which suggests that there is a limit of sonication time that will still promote droplet rupture at fixed power amplitude. Above this limit, the energy delivered to the system will be dissipated as heat. For power amplitudes lower than 100%, this limit is probably higher than 11 min. Figure 2B shows that the effect of sonication time was much stronger on the Span of emulsion droplet sizes than that of power amplitude. Long periods of sonication expose droplets to high amounts of energy, promoting not only droplet rupture, but also droplet collision and, thus, re-coalescence, that explains the larger variability in droplets size. Power amplitude did not affect the droplets polydispersity significantly. Figure 2. (A) Sauter mean diameter (D [3,2] ) and (B) Span of emulsions obtained by ultrasound process. Same letters represent results that are not significantly different (p 0.05). A B

5 3.2. Creaming Index(CI), Zeta Potential and Rheological Behavior Emulsions creaming refers to a gravitational separation due to the lower density of the disperse phase. In our work, CI of sonicated emulsions (Figure 3A) was more strongly affected by power amplitude than by sonication time. Power amplitude of 50% showed low effectiveness against creaming to all sonication times. The same observation is valid for 3 min sonication, at any power amplitude used. The lowest creaming index was reached for those emulsions with smallest droplet sizes (100% power amplitude, with 7 or 11 min of sonication). At 100% power amplitude, the use of sonication time higher than 7 min did not imply on significant reduction of CI. The ζ-potential of emulsions varied between to mv, with no significant difference among assays. The negative charge occurred mainly because of sodium caseinate, that is a protein negatively charged at ph 7.5 (~-50 mv data not shown), at which emulsions were prepared. The carbohydrates used also present negative charge at this ph, but it is very low compared to that of the protein. Systems with zeta potential between 30 and 60 mv (in modulus) are moderately stable due to electrostatic repulsion (Chuah et al., 2009). Since all emulsions here produced are in this range, it enhances the hypothesis that phase separation was more likely caused by gravitational separation. Rheological measurements revealed a typical Newtonian behavior for the emulsions prepared by rotorstator and ultrasound devices, when fitting both Newtonian model (R 2 ~0.9998) and Power Law (R 2 ~0.9999), with the behavior index n equal to The flow curves in Figure 3B also demonstrate the Newtonian behavior of the emulsions. The viscosity ranged between and mpa.s. These high values are a result of the high solids concentration, especially the carbohydrates (maltodextrin and DGS), which are 5-fold concentrated in relation to the protein. Higher sonication times and power amplitudes implied in increased viscosities. However, the order of magnitude is very close for all emulsions, and thus they did not present significant differences. Figure 3. (A) Creaming index obtained for sonicated emulsions after 24h of preparation. Same letters represent results that are not significantly different (p 0.05). (B) Flow curves obtained for emulsions produced from all assays. A B 3.3. The Effect of Energy Density on Emulsions Droplets Mean Diameter Figure 4 relates ED obtained for each assay to the respective D [3,2]. The ED delivered to the rotorstator device was about 40 times lower than that employed on the mildest condition on the ultrasound treatment (50% power amplitude, 3 min), and almost 300 times lower than the most drastic one (100% power amplitude, 11 min). As one of the two parameters was increased, the mean diameter D [3,2] was reduced, until apparently stabilize, confirming that it is possible to achieve emulsions with sub-micron droplets and low creaming index without using drastic process conditions. Logarithmic and power functions were fitted to data, and the later present the best correlation (R 2 =0.9931). This behavior is in accordance with that reported by Karbstein and Schubert (1995). The prediction of droplets mean diameter produced by mechanical devices is only one of the factors that make energy density an

6 important concept when producing emulsions. Besides that, it is also useful for the design, scaling-up and process control in emulsifying devices. Another application in which this concept may be very helpful is in the comparison of products properties of different mechanical emulsification processes (Schubert and Engel, 2004). Figure 4.Correlation between energy density and D [3,2], with logarithmic and power functions fitted to the data. 4. CONCLUSIONS Sonication was effective to produce sub-micron emulsions with high solids concentration. Both sonication time and power amplitude showed significant effects on emulsions properties. Emulsions sonicated at 100% power amplitude for 7 min presented low CI and D [3,2]. Since a longer sonication time did not reduce significantly droplet size or improved creaming, this condition was chosen for the continuity of the work. Inducing Maillard Reaction on this formulation is our purpose to achieve better emulsion stability using the process conditions selected. 5. ACKNOWLEDGEMENTS The authors are grateful to FAPESP (EMU 2009/ and2015/ ) for the financial support and CNPQ (140273/ and /2014-7) for the PhD fellowships. 6. REFERENCES Abbas, S., Hayat, K., Karangwa, E., Bashari, M., & Zhang, X. M. (2013). An Overview of Ultrasound-Assisted Food-Grade Nanoemulsions. Food Engineering Reviews, 5(3), Chuah, A. M., Kuroiwa, T., Ichikawa, S., Kobayashi, I., & Nakajima, M. (2009). Formation of Biocompatible Nanoparticles via the Self-Assembly of Chitosan and Modified Lecithin. Journal of Food Science, 74(1), N1-N8. Jafari, S. M., He, Y. H., & Bhandari, B. (2007). Production of sub-micron emulsions by ultrasound and microfluidization techniques. Journal of Food Engineering, 82(4), Karbstein, H., & Schubert, H. (1995). Developments in the continuous mechanical production of oilin-water macro-emulsions. Chemical Engineering and Processing, 34(3), McClements, D. J. (2015). Encapsulation, protection, and release of hydrophilic active components: Potential and limitations of colloidal delivery systems. Advances in Colloid and Interface Science, 219, Schubert, H., & Engel, R. (2004). Product and formulation engineering of emulsions. Chemical Engineering Research & Design, 82(A9),