This study examines the potential of applying computational intelligence modelling to describe the drying kinetics of persimmon fruit slices during vacuum drying (VD) and hot-air-drying (HAD) under different drying temperatures of 50 °C, 60 °C and 70 °C and samples thicknesses of 5 mm and 8 mm. Kinetic models were developed using selected thin layer models and computational intelligence methods including multi-layer feed-forward artificial neural network (ANN), support vector machine (SVM) and k-nearest neighbors (kNN). The statistical indicators of the coefficient of determination (R²) and root mean square error (RMSE) were used to evaluate the suitability of the models. The effective moisture diffusivity and activation energy varied between 1.417 × 10⁻⁹ m²/s and 1.925 × 10⁻⁸ m²/s and 34.1560 kJ/mol to 64.2895 kJ/mol, respectively. The thin-layer models illustrated that page and logarithmic model can adequately describe the drying kinetics of persimmon sliced samples with R² values (>0.9900) and lowest RMSE (<0.0200). The ANN, SVM and kNN models showed R² and RMSE values of 0.9994, 1.0000, 0.9327, 0.0124, 0.0004 and 0.1271, respectively. The validation results indicated good agreement between the predicted values obtained from the computational intelligence methods and the experimental moisture ratio data. Based on the study results, computational intelligence methods can reliably be used to describe the drying kinetics of persimmon fruit.

The effect of heating and freezing pretreatments on rapeseed oil yield and the volume of oil energy under uniaxial compression loading was investigated. Four separate experiments were carried out to achieve the study objective. The first and second experiments were performed to determine the compression parameters (deformation, mass of oil, oil yield, oil expression efficiency, energy, volume of oil and volume of oil energy). The third and fourth experiments identified the optimal factors (heating temperatures: 40, 60 and 80 °C, freezing temperatures: −2, −22 and −36 °C, heating times: 15, 30 and 45 min and speeds: 5, 10 and 15 mm/min) using the Box–Behnken design via the response surface methodology where the oil yield and volume of oil energy were the main responses. The optimal operating factors for obtaining a volume of oil energy of 0.0443 kJ/mL were a heating temperature of 40 °C, heating time of 45 min and speed of 15 mm/min. The volume of oil energy of 0.169 kJ/mL was reached at the optimal conditions of a freezing temperature of −36 °C, freezing time of 37.5 min and speed of 15 mm/min. The regression model established was adequate for predicting the volume of oil energy only under heating conditions.

The mechanical behavior of Ensete ventricosum fibers, expressed as the dependency of tension force in relation to the elongation, was determined for fibers with gauge length 50 mm and transformed into general linear mathematical model describing dependency of tension stress and strain. The average rupture force (10.88 ± 1.11) N, rupture stress (390.33 ± 21.96) MPa, rupture strain (0.021 ± 2 · 10^–5), and volume energy (3.39 ± 0.22) J m⁻³ were also determined at this conducted study. Using image analyses, it was determined that the cross section of Ensete ventricosum fiber has circle shape and its dimension was specified. From the study, it implies that Ensete ventricosum fiber, with respect to its mechanical behavior under tension loading having regard to its density and to the fact that it is environmentally friendly, biodegradable and recyclable, could be used as a perspective construction material of the future. Determined model of mechanical behavior could be applied as background for further research focused on the Ensete fiber application.

This present study investigated thin-layer drying characteristics of dried apple slices for a range of temperatures from 40 °C to 80 °C at a constant drying time of 10 h under infrared (IR) and hot air oven (OV) drying methods. The fresh apples were cut into a cylindrical size of thickness of 8.07 ± 0.05 mm and a diameter of 66.27 ± 3.13 mm. Fourteen thin-layer mathematical models available in the literature were used to predict the drying process. The goodness of fit of the drying models was assessed by the root mean square error (RMSE), chi-square (χ²), coefficient of determination (R²) and modelling efficiency (EF). The results showed that the lightness and greenness/redness of the dried sample, total colour change, chroma change, colour index, whiteness index, bulk density, final surface area and final volume significantly (p-value < 0.05) correlated with the drying temperature under IR. Under OV, however, only the final surface area and bulk density of the dried samples showed significant (p-value < 0.05) with the drying temperature. Shrinkage values for OV and IR methods showed both increasing and decreasing trends along with the drying temperatures. The Weibull distribution model proved most suitable for describing the drying processes based on the statistical validation metrics of the goodness of fit. In future studies, the combined effect of the above-mentioned drying methods and other drying techniques on apple slices among other agricultural products should be examined to obtain a better insight into the drying operations and quality improvement of the final product for preservation and consumer acceptability.

In this present study, an oil press was used to process 200 g each of sesame, pumpkin, flax, milk thistle, hemp and cumin oilseeds in order to evaluate the amount of oil yield, seedcake, sediments and material losses (oil and sediments). Sesame produced the highest oil yield at 30.60 ± 1.69%, followed by flax (27.73 ± 0.52%), hemp (20.31 ± 0.11%), milk thistle (14.46 ± 0.51%) and pumpkin (13.37 ± 0.35%). Cumin seeds produced the lowest oil yield at 3.46 ± 0.15%. The percentage of sediments in the oil, seedcake and material losses for sesame were 5.15 ± 0.09%, 60.99 ± 0.04% and 3.27 ± 1.56%. Sediments in the oil decreased over longer storage periods, thereby increasing the percentage oil yield. Pumpkin oil had the highest peroxide value at 18.45 ± 0.53 meq O₂/kg oil, an acid value of 11.21 ± 0.24 mg KOH/g oil, free fatty acid content of 5.60 ± 0.12 mg KOH/g oil and iodine value of 14.49 ± 0.16 g l/100 g. The univariate ANOVA of the quality parameters against the oilseed type was statistically significant (p-value < 0.05), except for the iodine value, which was not statistically significant (p-value > 0.05). Future studies should analyze the temperature generation, oil recovery efficiency, percentage of residual oil in the seedcake and specific energy consumption of different oilseeds processed using small-large scale presses.

The present study aims to estimate the maximum oil yield of hulled sunflower seed samples in a uniaxial process under a load of 40 kN and speed of 4 mm/min. The oil samples were assessed for their quality parameters and spectra curves within the wavelength range of 325–600 nm. The results show that heating temperatures in the range of 40 °C to 80 °C increased the oil output; however, a maximum oil yield of 48.869 ± 6.023% with a minimum energy of 533.709 ± 65.644 J at the fifth repeated pressing was obtained from the unheated sample compared to the heated samples. The peroxide values ranged from 6.898 ± 0.144 to 7.290 ± 0.507 meq O₂/kg, acid values from 1.043 ± 0.166 to 1.998 ± 0.276 mg KOH/g oil and free fatty acid values from 0.521 ± 0.083 to 0.999 ± 0.138 mg KOH/g oil, which were within the recommended quality threshold. There were significant spectral differences among the oil samples. A single absorbance peak was observed at 350 nm for all oil samples, indicating low levels of pigment molecules in the oil. The study revealed the need for repeated pressings to recover the considerable residual oil remaining in the seedcake after the first pressing.