The potential of pulsed electromagnetic field-generated shock waves for reducing microbial load and improving homogenization in raw milk.

Milk is a highly nutritious food essential for human consumption. However, traditional thermal processing methods can reduce its nutritional value and cause unwanted changes. The use of shock waves produced by pulsed electromagnetic fields (PEMFs) has been explored as a means to reduce pathogenic microorganisms. The effect of shock wave treatment on microbial load and particle distribution in packaged fresh cow's milk was investigated. Additionally, the impact of shock wave treatment on Salmonella enterica counts in a bacterial suspension of phosphate-buffered saline (PBS) was evaluated, as this bacterium is a significant milkborne pathogen. Treatment with 1000 impulses from an electromagnetic shock wave generator resulted in a 0.7-log reduction in the total bacterial count of milk. In a separate experiment, a 300-impulse shock wave treatment applied to a Salmonella enterica suspension achieved a 3-log reduction in bacterial counts. Furthermore, shock wave treatment resulted in a decrease in milk particle size compared to untreated milk. Notably, the volume of milk used in this study aligns with commercially available packaged products, enhancing the experiment's industrial relevance. The use of PEMF to generate shock waves could provide a novel approach for future studies focused on reducing the microbial load of milk and improving its homogenization.

Prediction of focal image for solar parabolic dish concentrator with square facets-an analytical model.

Solar parabolic dish concentrator is one of the high-temperature applications of more than 400 °C for thermal and electrical power generation. In the solar parabolic dish concentrator, the arrangement of reflectors over the surface area is the significant factor for effective concentration of solar radiation. Also, focal image is one of the most influencing parameters in the design of receiver. Among the various reflectors, the square-shaped reflectors (facets) are comparatively effective in converging the incoming radiations to attain better focal image. In this regard, an attempt has been made to predict the focal image diameter of a solar parabolic dish concentrator with a square facet of different influencing parameters using a novel mathematical model. The influencing parameters considered for the study are aperture diameter, rim angle, and facet length of the dish concentrator. Using the model, the focal image dimension and aperture area of a solar parabolic dish concentrator with square facets can be predicted accurately for efficient design of a solar parabolic dish collector system. Finally, the model is validated with the experimentally obtained focal image diameter. The current model is in good agreement with the experimental value, with a deviation of 8.84%. Hence, the proposed model can be used for the design of parabolic dish systems.

Modeling for extraction of oil from walnut and sesame using batch flow cold press oil extraction system.

In this study, a batch flow oil extraction system was used for extraction of oil from walnut (Juglans regia L.) and Sesamum (Indicum sesame). Sample mass (g), applied pressure (MPa), and processing temperature of oil (°C) were selected as independent variables and oil extraction mass percentage and oil analysis as dependent variables. Response surface methodology was employed for conducting statistical analysis, modeling, and data optimization. The results revealed that the highest percentage of oil extraction for walnut was obtained at a pressure of 10.5 MPa, a temperature of 31.5°C, and a sample weight of 8 g, with a value of 25.36%. Also, the highest percentage of oil extraction for Sesamum was obtained at the pressure of 13.88 MPa, the temperature of 31.5°C, and a sample value of 20 g with a value of 22.4%. Optimal level of independent variables for walnut and sesame were 8.03 g, 10.41 MPa, and 27.37°C; 20 g, 13.88 MPa, and 27°C, respectively. In this optimum condition, the amount of sesame and walnut peroxide was 10 ± 0.03 and 1.9 ± 0.07 (meq O2/kg), respectively. Likewise, the amount of acid for sesame and walnut was 1.53 ± 0.05 and 0.06 ± 0.02 g/%, separately. Linoleic acid (42.7-51.15), oleic acid (38.6-24.03), palmitic acid (10.87-8.21), and stearic acid (5.5-3.39) were the most common fatty acid components in sesame and walnuts, respectively.

Prediction of power generation and rotor angular speed of a small wind turbine equipped to a controllable duct using artificial neural network and multiple linear regression.

Wind power is one of the most popular sources of renewable energies with an ideal extractable value that is limited to 0.593 known as the Betz-Joukowsky limit. As the generated power of wind machines is proportional to cubic wind speed, therefore it is logical that a small increment in wind speed will result in significant growth in generated power. Shrouding a wind turbine is an ordinary way to exceed the Betz limit, which accelerates the wind flow through the rotor plane. Several layouts of shrouds are developed by researchers. Recently an innovative controllable duct is developed by the authors of this work that can vary the shrouding angle, so its performance is different in each opening angle. As a wind tunnel investigation is heavily time-consuming and has a high cost, therefore just four different opening angles have been assessed. In this work, the performance of the turbine was predicted using multiple linear regression and an artificial neural network in a wide range of duct opening angles. For the turbine power generation and its rotor angular speed in different wind velocities and duct opening angles, regression and an ANN are suggested. The developed neural network model is found to possess better performance than the regression model for both turbine power curve and rotor speed estimation. This work revealed that in higher ranges of wind velocity, the turbine performance intensively will be a function of shrouding angle. This model can be used as a lookup table in controlling the turbines equipped with the proposed mechanism.

Enhancement of polyphenolic content extraction rate with maximal antioxidant activity from green tea leaves by cold plasma.

A dielectric barrier discharge (DBD) atmospheric cold plasma was evaluated as a tool to increase the extraction rate of total phenolic content (TPC) and antioxidant activity from green tea leaves. The effects of nitrogen DBD cold plasma on changes of color and surface morphology were investigated. Optimum conditions of cold plasma treatment (treatment time and generation power) were obtained by response surface methodology. After the nitrogen DBD cold plasma at 15 W of the generation power for 15 min, the TPC and antioxidant activity of green tea increased by 41.14% and 41.06%, respectively. The catechin also increased by 103.12%. The scanning electron microscopy results showed cell ablation and ruptures of the green tea leaf surface after nitrogen DBD cold plasma treatment. PRACTICAL APPLICATION: The developed DBD cold plasma source fed by nitrogen gas can be a suitable procedure for green and useful extraction of phenolic compounds from natural sources in the food industries.

Optimization of Biodiesel Production over Chicken Eggshell-Derived CaO Catalyst in a Continuous Centrifugal Contactor Separator.

Solid calcium oxide (CaO) catalyst was prepared via the calcination of chicken eggshells as an environmentally friendly waste resource and incorporated in a continuous centrifugal contactor separator (CCCS) for intensified biodiesel synthesis. Biodiesel or fatty acid methyl esters (FAME) were produced via the transesterification of sunflower oil (containing 5 wt % tetrahydrofuran as a cosolvent) with methanol under 60 °C and separated from the glycerol and catalyst phases continuously in the CCCS. The influence of reaction parameters on biodiesel production was well modeled by response surface methodology. At an oil flow rate of 9 mL/min, an alcohol to oil molar ratio of 11:1, and a weight hourly space time (defined as the catalyst weight over the oil mass flow rate) of 0.050 h, an optimized FAME yield of 83.2% with a productivity of 638 kgFAME/(m3 reactor·h) was achieved. CaO catalyst was reused without significant activity loss for at least four cycles.

An intelligent procedure for watermelon ripeness detection based on vibration signals.

In this paper, an efficient procedure for ripeness detection of watermelon was presented. A nondestructive method was used based on vibration response to determine the internal quality of watermelon. The responses of samples to vibration excitation were optically recorded by a Laser Doppler (LD) vibrometer. Vibration data was collected from watermelons of two qualities, namely, ripe and unripe. Vibration signals were transformed from time-domain to frequency-domain by fast Fourier transform (FFT). Twenty nine features were extracted from the FFT amplitude and phase angle of the vibration signals. K-nearest neighbor (KNN) analysis was applied as a classifier in decision-making stage. The experimental results showed that the usage of the FFT amplitude of the vibration signals gave the maximum classification accuracy. This method allowed identification at a 95.0 % level of efficiency. Hence, the proposed method can reliably detect watermelon ripeness.