Optimization of subcritical water extraction for pectin extraction from cocoa pod husks using the response surface methodology.

This study optimized subcritical water extraction (SWE) conditions to maximize pectin yield from cocoa pod husk (CPH) and compared the characteristics of CPH pectin extracted through SWE with those of CPH pectin obtained through conventional extraction (CE) with citric acid. The Box-Behnken experimental design was employed to optimize SWE and examine the influence of process parameters, including temperature (100 °C-120 °C), extraction time (10-30 min), and solid:liquid ratio (SLR) (1:30-2:30 g/mL), on pectin yield. The maximum pectin yield of 6.58% was obtained under the optimal extraction conditions of 120 °C for 10 min with 1:15 g/mL SLR and closely corresponded with the predicted value of 7.29%. Compared with CE, SWE generated a higher yield and resulted in a higher degree of esterification, methoxyl content, and anhydrouronic acid value but a lower equivalent weight. The extracted pectin was pure, had low-methoxyl content, and similar melting and degradation temperatures.

Optimization of computational intelligence approach for the prediction of glutinous rice dehydration.

BACKGROUND: Five computational intelligence approaches, namely Gaussian process regression (GPR), artificial neural network (ANN), decision tree (DT), ensemble of trees (EoT) and support vector machine (SVM), were used to describe the evolution of moisture during the dehydration process of glutinous rice. The hyperparameters of the models were optimized with three strategies: Bayesian optimization, grid search and random search. To understand the parameters that facilitate intelligence model adaptation to the dehydration process, global sensitivity analysis (GSA) was used to compute the impact of the input variables on the model output. RESULT: The result shows that the optimum computational intelligence techniques include the 3-9-1 topology trained with Bayesian regulation function for ANN, Gaussian kernel function for SVM, Matérn covariance function combined with zero mean function for GPR, boosting method for EoT and 4 minimum leaf size for DT. GPR has the highest performance with R2 of 100% and 99.71% during calibration and testing of the model, respectively. GSA reveals that all the models significantly rely on the variation in time as the main factor that affects the model outputs. CONCLUSION: Therefore, the computational intelligence models, especially GPR, can be applied for an effective description of moisture evolution during small-scale and industrial dehydration of glutinous rice. © 2024 Society of Chemical Industry.

Valorization of green biomass Azolla pinnata fern: multi-parameter evaluation of processing conditions on protein extractability and their influence on the physicochemical, structural, techno-functional properties and protein quality.

BACKGROUND: This study determined the effect of processing conditions on protein extractability from Azolla pinnata fern, and their influence on the physicochemical, structural, techno-functional properties and protein quality. RESULTS: The protein extraction from A. pinnata fern was optimized through response surface methodology obtaining a maximum yield of 18.93% with a recovery rate of 73.66%. The A. pinnata fern protein concentrate (AFPC) had five protein bands with a molecular weight ranging from 17 to 56 kDa. AFPC contained high ß-sheet structure (36.61%), favouring its good thermal properties with three endothermic peaks at 54.28, 86.52 and 166.25 °C. The AFPC scored ≥ 1 for all essential amino acids, except for lysine and histidine. The AFPC exhibited exceptionally high techno-functional properties, particularly for water holding (5.46 g g-1 ) and fat absorption capacity (10.08 g g-1 ), and gelling properties (5% gelation concentration). The AFPC had high in vitro digestibility of 73%, signifying its high availability for human consumption. CONCLUSION: The underexploited A. pinnata fern is a potential source of edible protein, thus a promising nutraceutical or ingredient of functional and health-promoting foods. © 2022 Society of Chemical Industry.

Determination of the difference on color changes of watermelons by laser light backscattering imaging.

The potential of laser light backscattering imaging was investigated for monitoring color parameters of seeded and seedless watermelons during storage. Two watermelon cultivars were harvested and stored for 3 weeks with seven measuring storage days (0, 4, 8, 12, 15, 18, and 21). The color parameters of watermelons were monitored using the conventional colorimetric methods (L*, a*, b*, C*, H*, and ∆E*) and laser light backscattering imaging system. A laser diode emitting at 658 nm and 30 mW power was used as a light source to obtain the backscattering image. The backscattering images were evaluated by the extraction of backscattering parameters based on the mean pixel values. The results showed that a good color prediction was achieved by the seedless watermelon with the R2 are all above 0.900. Thus, the application of the laser light backscattering imaging can be used for evaluating the color parameters of watermelons during the storage period.

UVC dosage effects on the physico-chemical properties of lime (Citrus aurantifolia) juice.

Lime juice is in high demand due to a sour taste. Commercial thermal pasteurization extends juice shelf-life; however, fruit juice subjected to thermal pasteurization tends to change color and lose vitamin content. Lime juice was irradiated with ultraviolet-C (UVC) at dosages of 22.76, 30.19, and 44.24 mJ/cm2 to investigate effects on the physicochemical properties of lime juice. pH values of lime juice did not change while total soluble solids, turbidity, titratable acidity, sweetness, and color values of lime juice did change after UV treatments. Changes in quality index indicators were prominent at the highest UV dosage of 44.24 mJ/cm2. A low UVC dosage was effective for treatment of lime juice with minimal changes in juice properties.

Effects of post-drying methods on pomelo fruit peels.

Changes in physicochemical properties of moisture, ash, and fat contents, and color, due to freeze and oven post-drying treatments on flavedo, albedo, and lamella pomelo fruit peels were investigated. Physicochemical properties influence consumer acceptability and only a few studies are known. Pomelo peels were subjected to freeze drying and conventional drying at 60°C. Fresh pomelo peel was used as a control. Post-drying treatment changes in moisture, ash, and fat contents were observed, compared to controls. Minimal color changes were observed for freeze drying, compared with oven drying for flavedo, albedo, and lamella. Useful information for evaluation of drying treatments that can be used on pomelo peels is provided.

The Use of D-Optimal Mixture Design in Optimizing Development of Okara Tablet Formulation as a Dietary Supplement.

The usage of soy is increasing year by year. It increases the problem of financial crisis due to the limited sources of soybeans. Therefore, production of oral tablets containing the nutritious leftover of soymilk production, called okara, as the main ingredient was investigated. The okara tablets were produced using the direct compression method. The percentage of okara, guar gum, microcrystalline cellulose (Avicel PH-101), and maltodextrin influenced tablets' hardness and friability which are analyzed using a D-optimal mixture design. Composition of Avicel PH-101 had positive effects for both hardness and friability tests of the tablets. Maltodextrin and okara composition had a significant positive effect on tablets' hardness, but not on percentage of friability of tablets. However, guar gum had a negative effect on both physical tests. The optimum tablet formulation was obtained: 47.0% of okara, 2.0% of guar gum, 35.0% of Avicel PH-101, and 14.0% of maltodextrin.