The moisture content of a powder is a parameter crucial to be controlled in order to produce stable products with a long shelf life. Inferential control is the best solution to control the moisture content due to difficulty in measuring this variable online. In this study, fundamental and empirical approaches were used in designing the nonlinear model-based inferential control of moisture content of coconut milk powder that was produced from co-current spray dryer. A one-dimensional model with integration of reaction engineering approach (REA) model was used to represent the dynamic of the spray drying process. The empirical approach, i.e., nonlinear autoregressive with exogenous input (NARX) and neural network, was used to allow fast and accurate prediction of output response in inferential control. Minimal offset (<0.0003 kg/kg) of the responses at various set points indicate high accuracy of the neural network estimator. The nonlinear model-based inferential control was able to provide stable control response at wider process operating conditions and acceptable disturbance rejection. Nevertheless, the performance of the controller depends on the tuning rules used.
In the present study, ultrasound-assisted extraction of crude oil from winter melon seeds was investigated through response surface methodology (RSM). Process variables were power level (25-75%), temperature (45-55 °C) and sonication time (20-40 min). It was found that all process variables have significant (p < 0.05) effects on the response variable. A central composite design (CCD) was used to determine the optimum process conditions. Optimal conditions were identified as 65% power level, 52 °C temperature and 36 min sonication time for maximum crude yield (108.62 mg-extract/g-dried matter). The antioxidant activity, total phenolic content and fatty acid composition of extract obtained under optimized conditions were determined and compared with those of oil obtained by the Soxhlet method. It was found that crude extract yield (CEY) of ultrasound-assisted extraction was lower than that of the Soxhlet method, whereas antioxidant activity and total phenolic content of the extract obtained by ultrasound-assisted extraction were clearly higher than those of the Soxhlet extract. Furthermore, both extracts were rich in unsaturated fatty acids. The major fatty acids of the both extracts were linoleic acid and oleic acid.
In the present study, supercritical carbon dioxide (SC-CO(2)) extraction of seed oil from winter melon (Benincasa hispida) was investigated. The effects of process variables namely pressure (150-300 bar), temperature (40-50 °C) and dynamic extraction time (60-120 min) on crude extraction yield (CEY) were studied through response surface methodology (RSM). The SC-CO(2) extraction process was modified using ethanol (99.9%) as co-solvent. Perturbation plot revealed the significant effect of all process variables on the CEY. A central composite design (CCD) was used to optimize the process conditions to achieve maximum CEY. The optimum conditions were 244 bar pressure, 46 °C temperature and 97 min dynamic extraction time. Under these optimal conditions, the CEY was predicted to be 176.30 mg-extract/g-dried sample. The validation experiment results agreed with the predicted value. The antioxidant activity and fatty acid composition of crude oil obtained under optimized conditions were determined and compared with published results using Soxhlet extraction (SE) and ultrasound assisted extraction (UAE). It was found that the antioxidant activity of the extract obtained by SC-CO(2) extraction was strongly higher than those obtained by SE and UAE. Identification of fatty acid composition using gas chromatography (GC) showed that all the extracts were rich in unsaturated fatty acids with the most being linoleic acid. In contrast, the amount of saturated fatty acids extracted by SE was higher than that extracted under optimized SC-CO(2) extraction conditions.
The present study is aimed to prepare κ-carrageenan microparticles for the encapsulation of model drug, coenzyme Q10 (CoQ10). A face-centered central composite design was employed to study the effects of three different formulation variables (κ-carrageenan, emulsifier, and oil). The powder yield was found inversely affected by the κ-carrageenan and oil concentration. The encapsulation efficiency was maximized in the region of the middle level κ-carrageenan concentration, the high level emulsifier concentration, and the low level oil concentration. The emulsifier concentration was the most influential variable on the particle size of powder. The optimal formulation was reported as 0.91% (w/v) κ-carrageenan concentration, 0.64% (w/v) emulsifier, and 1.0% (w/w) oil. Both differential scanning colorimeter and X-ray diffraction analyses proved that incorporation of CoQ10 into κ- carrageenan microcapsules resulted in amorphous powder with significantly (p<0.05) higher water solubility compared to pure CoQ10 and physical mixture in the crystalline form.
The optimization of pink guava was executed using central composite face-centred design to optimize the spray drying parameters of inlet temperature, maltodextrin concentration (MDC) and feed flow (FF). The experimental results were significantly (p<0.01) fitted into second-order polynomial models to describe and predict the response quality in terms of the final moisture, particle size and lycopene with R2 of 0.9749, 0.9616, and 0.9505, respectively. The final moisture content significantly (p<0.01) decreased with increasing inlet temperature and MDC, whereas the particle size increased. In contrast, the lycopene content significantly (p<0.01) decreased with the higher temperature and increased with increasing MDC. However, according to multiple response optimization, the optimum conditions of 150°C inlet temperature, 17.12% (w/v) MDC and 350 mL/h FF-predicted 3.10% moisture content, 11.23 μm particle size and 58.71 mg/100 g lycopene content. The experimental observation satisfied the predicted model within the acceptable range of the responses.
Subcritical water hydrolysis process for sugar recovery from leftover croissants (LC) and leftover doughnuts (LD) was optimised using response surface methodology with three process parameters as dependent variables and sugar yield as the response. The process parameters: temperature (160-200 °C), time (5-15 min), and solid loading (10-50%), on the sugar yield were investigated. For the LC sample, the optimised process conditions were determined to be: 200 °C, 6.17 min, and 10% solid loading producing an 80% hydrolysis yield of 466.11 ± 0.67 mg/g. Comparatively, the LD sample optimisation parameters were: 200 °C, 5 min, and 10% solid loading producing a 76.18% hydrolysis yield of 394.34 ± 0.33 mg/g. The sugar extracts were further characterise; which through scanning electron microscopy revealed the LC had most starch granules rupture during hydrolysis, while Fourier-transform infrared spectroscopy detected the presence of monosaccharides and oligosaccharides for both LC and LD. 5-hydroxymethylfurfural (5-HMF), a sugar degradation by-product, was also detected with 39.16 ± 0.61 and 20.59 ± 0.81 mg/g for the LC and LD, respectively, at optimal conditions.
Baking temperature and time are among the conditions for producing good quality cakes. The aim of this study was to investigate the effects of baking temperature and time on the volume expansion, moisture content, and texture of moist cakes baked in either an air fryer or a convection oven. The cakes were baked under different conditions: (1) baking temperature of 150 °C, 160 °C, and 170 °C for both air fryer and convection oven and (2) baking time of 25, 30, 35 min for air fryer and 35, 40, 45 min for convection oven. Baking temperature and time were found to have a significant (p
Seed mucilages are potential sources of natural polysaccharides. They are biodegradable, biocompatible, sustainable, renewable, and safe for human consumption. Due to the desirable physicochemical and functional properties (e.g. gelling, thickening, stabilizing, and emulsifying), seed mucilages have attracted extensive attention from researchers for utilization as a promising material for the development of advanced carrier systems. Seed mucilages have been utilized as natural polymers to improve the properties of various carrier systems (e.g. complex coacervates, beads, nanofibers, and gels) and for the delivery of diverse hydrophilic and lipophilic compounds (e.g. vitamins, essential oils, antioxidants, probiotics, and antimicrobial agents) to achieve enhanced stability, bioavailability, bioactivity of the encapsulated molecules, and improved quality attributes of food products. This review highlights the recent progress in seed mucilage-based carrier systems for food and nutraceutical applications. The main contents include (1) sources, extraction methods, and physicochemical and functional characteristics of seed mucilages, (2) application of seed mucilages for the development of advanced carrier systems, (3) major issues associated with carrier fabrication, and (4) mechanisms of carrier development, latest improvements in carrier formulation, carrier efficiency in the delivery of bioactive agents, and application in food and nutraceuticals. Furthermore, major challenges and future perspectives of seed mucilage-based carriers for a commercial application are discussed.
Jackfruit is one of the major fruits cultivated in many Asian countries. Jackfruit seeds are generally disposed of into the environment, which causes an environmental concern that leads to biowaste accumulation. The seeds have excellent nutritional value, such as carbohydrates, protein, fats, minerals, and bioactive compounds. Bioactive compounds, such as phenolic, can be recovered from jackfruit seeds that could add value to the food and pharmaceutical industry. Thus, this study focused on utilizing subcritical water to extract the phenolic compounds from jackfruit seeds and correlate them with antioxidant activity (AA). The extraction of phenolic compounds was studied at different temperatures and extraction times. The highest total phenolic compounds (TPC) and AA were obtained by treating the jackfruit seed powder at 210 °C, 30 min, and 15% solid loading under subcritical water extraction (SWE) with 1.84 mg GAE/100 g (TPC) and 86% (AA). High correlation between the extracted TPC and AA of the jackfruit seed extracts was obtained (R2 = 0.96), indicating a significant positive relationship between TPC and AA. A higher amount of TPC was obtained via SWE as compared to Soxhlet extraction (1 h:0.53 mg GAE/100 g and 4 h:1.20 mg GAE/100 g). More pores were detected on the surface of the sample treated by SWE than using Soxhlet extraction. Thus, jackfruit seed extracts can be potentially beneficial in the fortification of fermented dairy or meat products.
Single-screw extrusion of a fibrous-structured meat analog from soy proteins added with low-grade oyster mushroom was successful. Satisfactory extrudates were obtained at a barrel temperature of 140 °C, screw speed range of 100-160 rpm, and oyster mushroom addition at 0%, 7.5%, and 15% via factorial experiments. Single-screw extrusion equipped with a slit die successfully produced expanded oyster mushroom-soy protein extrudates. However, the increase in the oyster mushroom content significantly decreased (p ≤ 0.05) the expansion ratio of the extrudate from 1.26 to 0.98. This result indicated that adding more oyster mushroom restrained the expansion ratio. The extrudates had a medium density range (max of 1393.70 ± 6.30 kg/m3). By adding oyster mushroom, the extrudates attained a higher moisture content (range = 34.77% to 37.93%) compared with the extrudates containing the protein mixture only (range = 26.99% to 32.33%). The increase in screw speed and oyster mushroom significantly increased (p ≤ 0.05) the water absorption index. The increase in the texturization index was significantly influenced (p ≤ 0.05) by oyster mushroom addition rather than the screw speed. A defined fibrous structure supported the high texturization index and small shape of air cells observed in the extrudates.
Spray drying techniques are one of the methods to preserve and extend the shelf-life of coconut milk. The objective of this research was to create a particle swarm optimization-enhanced artificial neural network (PSO-ANN) that could predict the coconut milk spray drying process. The parameters for PSO tuning were selected as the number of particles and acceleration constant, respectively, for both global and personal best using a 2k factorial design. The optimal PSO settings were recorded as global best, C1 = 4.0; personal best, C2 = 0; and number of particles = 100. When comparing different types of spray drying models, PSO-ANN had an MSE value of 0.077, GA-ANN had an MSE of 0.033, while ANN had an MSE of 0.082. Sensitivity analysis was conducted on all three models to evaluate the significance level of each parameter on the model, and it was discovered that inlet temperature had the most significant influence on the model performance. In conclusion, the PSO-ANN was found to be more effective than ANN but less effective than GA-ANN in predicting the quality of coconut milk powder.