Plant gum exudate, such as gum arabic, is extensively used in a variety of industrial applications due to their emulsification, microencapsulation and stabilisation properties. The present study is aimed to investigate the effect of particle size on the proximate composition, the density and the physicochemical properties of the gum arabic powder. The classification of particle size based on the mean diameter (d50) ranged between 30 to 800 µm. Based on the proximate composition results, the coarse (414 µm) and very coarse (790 µm) particles yielded a similar moisture content of 13.8%, which was higher than that of the commercial gum (11.1%). Meanwhile, the medium coarse (208 µm) particles contain higher fiber content (97.9%) as compared to other particle sizes. The bulk and tapped density of the gum were significantly affected by the particle size. Water activity analysis indicated that the gum arabic is microbiologically safe, as it has poor condition or environment for microbial growth. From the hygroscopicity analysis, it was found that the very fine (37 µm) particles obtained the highest hygroscopicity value of 40%. The swelling index of medium coarse (208 µm) particles was closed to that of the commercial gum. The emulsion capacity (EC) and emulsion stability (ES) analyses observed that the very coarse (790 µm) and very fine (37 µm) particles recorded the highest EC and ES values of 93% and 89%, respectively. The glass transition temperature was not significantly affected by the particle size. The colour analysis indicated that the commercial gum is lighter (71.4) than the other particle sizes. Meanwhile, the very fine (37 µm) and fine (85 µm) particles exhibited similar redness (a*) value with that of the commercial gum, with a value recorded at 3.7. The morphology analysis observed that the gum exhibited irregular shape with rough granule surfaces. The present work revealed that coarse (208 to 414 µm) particles showed better characteristics compared to that of the commercial gum arabic that is available in the market.

Arabic gum is derived from the exudation of stems and branches of Acacia senegal L. and it is widely used as a food additive. The application of Arabic gum as a functional food ingredient is significantly increasing. However, there is limited information on the effects of particle size on the handling and processing of Arabic gum in the industry. Therefore, a study was performed to determine the effects of particle size on the physical properties of Arabic gum powder. The physical properties measured were density, flowability, and dissolution characteristics. In this work, the powders were classified based on their mean diameter (d50) that ranged between 20 and 1,000 μm. The very fine powder exhibited poor flowing properties and long dissolution time, with a Hausner ratio of 1.24 ± 0.1 and dissolution time of 2,821.0 ± 76.0 s. However, the coarse powder had excellent flowing properties and shorter dissolution time, with a Hausner ratio of 1.13 ± 0.02 and dissolution time of 531.5 ± 70.5 s. The results indicated a significant impact of particle size on the cohesivity and solubility of powder, where smaller particle size tended to decrease flowability and increase the dissolution time of the powder. Practical applications This paper studies the characterization of Arabic gum at various particle sizes. The physical properties measured were density, flowability, and dissolution of Arabic gum powder. The results of this study indicate that particle size had significantly affected the powder properties. This knowledge is very important, as Arabic gum is widely used as a food ingredient; this might affect the overall product properties. The outcomes are also beneficial to the industry prior to selecting the specific particle size for the designing and processing of products. Therefore, the results on flowability and dissolution properties of Arabic gum powder can be used as guidance for the development of food product.

This current study focuses on the modelling and optimization of supercritical fluid extraction of Quercus infectoria galls oil. In this case, response surface methodology (RSM) and artificial neural network (ANN) were applied for the modelling and prediction of extraction yield of galls oil. A 17-run Box-Behnken Design (BBD) was employed to statistically optimize the process parameters of SC-CO2 extraction of Quercus infectoria galls at a condition as follows: pressure (5000, 6000, 7000 Psi), temperature (40, 50, 60°C) and extraction time (30, 45, 60 min). The maximum yield of the extracted oil is1.12 % and the optimum conditions are at an extraction pressure of 5574 Psi; extraction temperature of 75°C and extraction time of 54 min. Under the optimal conditions, the experimental results agree with the predicted values obtained through analysis of variance (ANOVA). This indicates a successful response surface methodology and highly satisfactory goodness of fit of the model used. The analysis of experimental design for process optimization results demonstrates that temperature and extraction time are the main parameters that influence the oil extraction of Quercus infectoria.