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Maximizing the yield of bioactive molecules extracted from plant materials requires the investigation of extraction process variables; therefore, in this research, a traditional aqueous solid–liquid extraction method was employed on two distinct grape pomace skin samples. The grape skin pomace represents a potentially valuable source of biologically active compounds, particularly polyphenols. Experiment 1 utilized ground grape pomace skin, whereas experiment 2 utilized grape pomace skin that had been both dried and ground beforehand. Employing a Box–Benkhen experimental design and response surface modeling in the Statistica 14.0 software package, this study evaluated the impact of temperature, extraction time, solid-to-liquid ratio (S/L), and mixing speed on extraction efficiency. The extracted compounds were assessed for both physical properties (conductivity, total dissolved solids, and pH) and chemical properties (total polyphenol content and antioxidant activity using 2,2-Diphenyl-1-picrylhydrazyl (DPPH) and ferric reducing antioxidant power (FRAP) assays). The optimization matrix design identified the specific conditions required to achieve the optimal physical and chemical properties of grape skin extract as follows: (i) for experiment 1, extraction time (t) = 15 min, temperature (T) = 80 °C, solid-to-liquid ratio (S/L) = 10 g/L, and mixing speed (rpm) = 500 1/min and (ii) for experiment 2, extraction time (t) = 15 min, temperature (T) = 80 °C, solid-to-liquid ratio (S/L) = 10 g/L, and mixing speed (rpm) = 375 1/min. Under optimal process conditions, 26.1284 mgGAE/gd.m. and 25.1024 mgGAE/gd.m., respectively, were obtained. These findings demonstrate the effectiveness of the optimization process in identifying precise extraction conditions that yield the optimal chemical properties of grape skin extracts. [ABSTRACT FROM AUTHOR]

The aim of this work was to analyze and compare the adsorption and desorption processes of carbohydrates (glucose as a model molecule), polyphenols (gallic acid as a model molecule), and proteins (bovine serum albumin, BSA as a model molecule) on alginate microcapsules. The adsorption and desorption processes were described by mathematical models (pseudo-first-order, pseudo-second-order, and Weber–Morris intraparticle diffusion model for adsorption, and first-order, Korsmeyer–Peppas, and the Higuchi model for desorption) in order to determine the dominant mechanisms responsible for both processes. By comparing the values of adsorption rate (k2) and initial adsorption rate (h0) based on the pseudo-first-order model, the lowest values were recorded for BSA (k1 = 0.124 ± 0.030 min−1), followed by glucose (k1 = 0.203 ± 0.041 min−1), while the model-obtained values for gallic acid were not considered significant at p < 0.05. For glucose and gallic acid, the limiting step of the adsorption process is the chemical sorption of substances, and the rate of adsorption does not depend on the adsorbate concentration, but depends on the capacity of the hydrogel adsorbent. Based on the desorption rates determined by the Korsmeyer–Peppas model (k), the highest values were recorded for gallic acid (k = 3.66236 ± 0.20776 g beads/mg gallic acid per min), followed by glucose (k = 2.55760 ± 0.16960 g beads/mg glucose per min) and BSA (k = 0.78881 ± 0.11872 g beads/mg BSA per min). The desorption process from alginate hydrogel microcapsules is characterized by the pseudo Fickian diffusion mechanism. [ABSTRACT FROM AUTHOR]

RSM and ANN were evaluated for prediction of physical and chemical properties of industrial hemp extracts prepared using MAE. The effects of liquid to solid ratio, ethanol content, extraction time, extraction temperature, and microwave power were analyzed. ANN had better prediction performance for both physical and chemical properties. Optimal conditions based on RSM were L/S = 30 mL/g, v/v = 25%, t = 25 min, T = 45°C and P = 600 W. Under those conditions, dynamic of the extraction process was analyzed using six kinetic models and showed that the extraction rate reached constant value after approximately 15 min. [ABSTRACT FROM AUTHOR]

The stability of lavender, lemon balm, mint, sage, and thyme teas was investigated using in‐vitro simulation of the digestive system. Kinetics of changes in the total polyphenolic content (TPC) and the antioxidant activity during the in‐vitro trials were also evaluated. Results showed that TPC of mint teas decreases the fastest. Mathematical models for prediction of the TPC and the antioxidant activity of prepared teas based on UV–VIS and NIR spectra collected before, during, and after simulation showed that the best prediction was obtained for the wavelength ranges from 410 to 900 nm, 904 to 928 nm, and 1,399 to 1699 nm. It was concluded that the NIR can be used for calibration, validation, and classification of teas prepared from Lamiaceae plants. Practical applications: The bioactives' in‐vitro digestion process can successfully be characterized by chemical, spectroscopic, and mathematical analysis. Application of NIR spectroscopy, in combination with multivariate analysis, leads to a reduction of time, costs, and chemical consumption and gives reliable results that pharmaceutical, food, and chemical industries can benefit from. [ABSTRACT FROM AUTHOR]

The use of medicinal plants has been well documented for the past several decades. Plants from the Lavender genus are used for culinary purposes, but also as a part of herbal medicine, owing its benefits to essential oils and bioactive compounds. A detailed description of the extraction process dynamics is required to obtain the highest possible amount of bioactive compounds from lavender. In this study, a solid-liquid extraction of lavender flowers, using water as solvent, was performed. Total polyphenols, dry matter, conductivity, and total dissolved solids were determined in regular time intervals and experimental data was further used for mathematical modelling. Peleg's, Page's, and the logarithmic model were applied in order to describe the kinetics of bioactive compounds in lavender during solid-liquid extraction. The initial extraction rate and extraction capacity were determined for three different extraction temperatures; T = 40, 60, and 80 °C. The obtained results indicated that the initial extraction rate and the extraction capacity were the highest at T = 80°C. The adequacy of the applied mathematical models was estimated based on R2 and SRMSE values, which indicated that the most adequate model for solid-liquid extraction of lavender was the Peleg's model (R2 = 0.996, for total polyphenols at T = 40 ºC and R2 = 0.975 for dry matter at T = 60 °C, respectively) [ABSTRACT FROM AUTHOR]

Olive leaves are a rich source of polyphenols that have beneficial antihypertensive, hypocholesterolemic, cardioprotective, and anti-inflammatory effects. The aim of this study was to compare the efficiency of conventional extraction (CE), microwave-assisted extraction (MWE), and microwave–ultrasound-assisted extraction (MWUE) for the extraction of bioactive molecules from olive leaves using water as a solvent and to define the optimal extraction conditions for all three methods used. CE conditions (temperature, time, magnetic stirrer rotational rate and particle diameter) and MWE extraction and MWUE conditions (microwave power, time, particle diameter, and temperature) were optimized using response surface methodology (RSM) based on the Box–Behnken experimental design. The total polyphenol content and antioxidant activity of all prepared extracts was analyzed and compared. The results showed that MWUE provided the highest amount of total polyphenols (Total Polyphenolic Content (TPC) = 273.779 ± 4.968 mgGAE gd.m.−1) and the highest antioxidant activity, which was about 3.1 times higher than CE. Optimal extraction conditions were determined to be 80 °C, 15 min, 200 μm, and 750 min-1 for CE, 700 W, 7.5 min, 300 μm, and 80 °C for MWE, and 800 W, 5 min, 100 μm, and 60 °C for MWUE. Considering the maximum amount of total polyphenols extracted, the results suggest that MWUE is the most effective green extraction process that extracted the highest amount of polyphenols and could be used by the food industry for commercial exploitation of currently unprofitable plant bioactive sources. [ABSTRACT FROM AUTHOR]

Highlights • Extraction of five medicinal plants was investigated. • The Taguchi method was used to optimize the extraction conditions. • Total polyphenolic content and antioxidant activity can be predicted. • Nonlinear models can be used for prediction of bioactives in herbal extracts. • Piecewise linear regression models confirmed their dominance in quantification. Abstract Optimizing the extraction methods of bioactive compounds are of great interest for research and development in the food and pharmaceutical industries. This study investigated five medicinal plants: lavender (Lavandula x hybrida L.), lemon balm (Melissa officinalis L.), mint (Metha piperita L.), sage (Salvia officinalis L.), and thyme (Thymus serpyllum L.), with the focus on the extraction conditions and analysis of the total polyphenolic content, antioxidant activity, conductivity and extraction yield. In order to optimise the extraction conditions the Taguchi method was used. Nonlinear and piecewise linear regression models were developed for prediction of physical and chemical properties of medicinal plant extracts based on experimental process conditions. For extracts of all five medicinal plants the expected total polyphenolic content and the antioxidant activity can be predicted with high determination coefficients r2 > 0.9) by piecewise linear regression models, while the prediction of conductivity and extraction yield resulted with determination coefficients slightly under 0.9, which is still highly acceptable considering that the models present the prediction for all five plants. Proposed nonlinear models can be used as qualitative models in relation of the prediction of bioactive compounds, while the piecewise linear regression models confirmed they dominance in the quantification models. [ABSTRACT FROM AUTHOR]

Antioxidants derived from plants are widely used in dietary supplements and have been investigated for the prevention of diseases such as cancer, coronary heart disease and altitude sickness. In order to obtain the highest possible amount of bioactive compounds from plant material, effective extraction procedures are required. One of the most widely used extraction techniques which requires no toxic chemicals is solid-liquid extraction. Mathematical modelling of solid–liquid extraction processes is an important engineering tool in the design process in order to reduce energy, time and chemical reagents consumption. In agreement with that, the aim of this paper was determination of the best suited kinetic model for description of the solid-liquid extraction of bioactive compounds from Asteraceae family plants. In this study, four most common representatives of Asteraceae family were chosen as subjects: camomile ( Matricaria recutita L.), dandelion ( Taraxacum officinale Web.), marigold ( Calendula officinalis ) and yarrow ( Achillea millefolium L.). Initial extraction rate, extraction capacity, activation energy, Gibbs energy, enthalpy and entropy were determined for all of the four analysed plants. The highest extraction efficiency of total polyphenols content, antioxidants and extraction yield were achieved at the highest extraction temperature of T = 80 °C for all four plants used in this study. Obtained results for activation enthalpies indicated that the extraction processes were endothermic and Gibbs free energy of activation indicated that they were endergonic and not spontaneous. [ABSTRACT FROM AUTHOR]

[Display omitted] • Physical and chemical properties of dried root vegetables were predicted by ANN. • Near-infrared (NIR) spectra were recorded for all samples. • PCA analysis showed specific grouping of samples in two clusters. • NIR and ANN can be used for description of dried root vegetable properties. Artificial neural networks (ANN) were developed for prediction of total dissolved solids, polyphenol content and antioxidant capacity of root vegetables (celery, fennel, carrot, yellow carrot, purple carrot and parsley) extracts prepared from the (i) fresh vegetables, (ii) vegetables dried conventionally at 50 °C and 70 °C, and (iii) the lyophilised vegetables. Two types of solvents were used: organic solvents (acetone mixtures and methanol mixtures) and water. Near-infrared (NIR) spectra were recorded for all samples. Principal Component Analysis (PCA) of the pre-treated spectra using Savitzky-Golay smoothing showed specific grouping of samples in two clusters (1st: extracts prepared using methanol mixtures and water as the solvents; 2nd: extracts prepared using acetone mixtures as the solvents) for all four types of extracts. Furthermore, obtained results showed that the developed ANN models can reliably be used for prediction of total dissolved solids, polyphenol content and antioxidant capacity of dried root vegetable extracts in relation to the recorded NIR spectra. [ABSTRACT FROM AUTHOR]