In this work, the objective is to utilize avocado seed extract as a cheap alternative source of active compounds and was successfully encapsulated using gum arabic by spray drying as an antioxidant and antimicrobial agent. First, the active compounds were extracted from avocado seed using solvent n-hexane and followed by solvent separation using rotary vacuum evaporator. Next, gum arabic as the encapsulation agent was added to avocado seed extract to form an emulsion, then spray-dried with drying air at a temperature of 140 °C. The mass ratio of avocado seed was varied at extract: gum arabic of 5:5, 5:10, 5:15, and 5:20. Then, the particle morphology, yield, moisture content, encapsulation efficiency, loading capacity, chemical groups, antioxidant activity, and antibacterial ability were analyzed to investigate the performance of the encapsulation particles. Among the ranges studied, the extract–gum arabic with a mass ratio of 5:10 exhibited the best properties of yield powder, loading capacity, and encapsulation efficiency at 49.78%, 3.43%, and 7.33%, respectively. The encapsulated particles have smooth surface, crackless, lower indentation, and a single-core encapsulation structure with an average diameter of 4.60 μm. Besides, the stability of antioxidant activity decreased by 2.36%, from 94.82% to 92.46% for four weeks of storage. They also performed antimicrobial activity against E. coli and S. aureus, which were maintained after seven days. Meanwhile for avocado seed extract only, the unencapsulated stability of antioxidant activity has continually decrease from 91.58% to 84.05% and performed no antimicrobial activity against E. coli after seven days.
Drying air inlet temperature is one of the critical variables in the microencapsulation process by spray drying. However, when spray drying is carried out at inappropriate drying air inlet temperature, it can impact the particle produced. This study presents a simulation of spray drying from a mathematical model was developed to determine the effect of drying air inlet temperature on moisture content, particle diameter, particle density, and drying air outlet temperature in the microencapsulation process of avocado seeds oil as core materials and gum arabic as wall materials. For this aim, the mathematical model was developed then simulated using a matrix laboratory (Matlab) computer program with Euler numerical method for drying air inlet temperatures of 160, 180, and 200 °C. The selected model was validated with Cotabarren’s experimental results indicating the model was acceptable. The particles’ moisture contents predicted from simulation results are 1.170, 1.049, and 0.933 kg water/kg solid for 160, 180, and 200 °C, respectively. On the other hand, the predicted particle diameters are 29.73, 29.49, and 29.23 urn for 160, 180, and 200 °C, respectively. The predicted particle densities are 1215.72, 1225.21, and 1233.25 kg/m3 for 160, 180, and 200 °C, respectively. The prediction of drying air outlet temperatures was 39.76, 41.94, and 43.89 °C for inlet air temperatures of 160, 180, and 200 °C, respectively. The proposed models’ simulation results show that the higher temperatures caused lower particle moisture content, smaller particle diameter, and higher particle density. Also, the outlet drying air temperatures were always the same as the outlet particle temperatures.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.