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A Review of New Methods for Extracting Oil from Plants to Enhance the Efficiency and Physicochemical Properties of the Extracted Oils
(MDPI AG, 2025-04-09)
Hamid Bakhshabadi
;
Mohammad Ganje
;
Mehdi Gharekhani
;
Toktam Mohammadi-Moghaddam
;
Cristina Aulestia
In general, there are three methods for extracting oil from various sources: mechanical, solvent, and pre-press-solvent. Each of these methods has its own advantages and disadvantages, with extraction efficiency depending on key factors such as the extraction technique, the properties of the plant component matrix, and the solvent used. Factors like temperature, pressure, and time also play a role. Researchers have consistently sought to replace or complement these methods to reduce residual oil in products. This study introduces new oil extraction methods that have gained attention in recent years, including the microwave, pulsed electric field, ultrasound, supercritical fluid, enzymatic, ohmic, and combined methods to enhance efficiency. The research demonstrates that these methods increase oil extraction efficiency and bioactive compound extraction from plant sources, resulting in improved oil quality. Most methods also reduce extraction time, offering researchers and industrialists a variety of options for their oil extraction needs. However, the study notes contradictions in the results, such as varying acidity levels in the oil, which may be attributed to raw materials and study conditions. In the end, it was determined that ultrasound, pulsed electric field, and enzyme methods can be used industrially to extract oil from olives, while supercritical fluid can be used to extract oil from certain seeds.
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Bread Staling Measurement Techniques: A Review
(United Scientific Group, 2024-05-31)
Toktam Mohammadi-Moghaddam
;
Mohammad Morshedi
;
Ramina Moalemzadeh Ansari
;
Amir Golmohammadi
;
Afsaneh Morshedi
The global production volume of wheat production is almost 785 million metric tons during 2023. Bread is a staple food produced with flour, water, or milk, with or without yeast. It is an important part of people’s worldwide people diet and provides their daily energy. One of the most significant problems in bread production and consumption is its staleness, which begins immediately after baking. Staling is divided into two categories: texture and microbial changes. Texture changes occur first due to moisture migration, followed by microbial changes. Ultimately, the aroma, flavor, and texture of bread become undesirable to consumers. There are many methods for evaluation staling: chemical, macroscopic, rheological, microscopic, structural features, and molecular features methods. All these methods are effective and can be used according to the facilities and conditions of the producers.
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Comparison of Sigmoid Logarithm and Hyperbolic Tangent Functions in Modeling the Oxidation Parameters of Soybean Oil Containing Extract of Black Plum Peels Natural Antioxidant
(United Scientific Group, 2024-09-06)
Toktam Mohammadi-Moghaddam
;
Mohaddeseh Kariminejad
;
Hamid Bakhshabadi
;
Elham Taghavi
;
Afsaneh Morshedi
To predict the oxidation parameters of soybean oil (SBO), we utilized five levels of black plum peel extraction (BPPE) antioxidant concentration (0, 400, 800, 1200, and 2000 ppm) and four levels of oil storage time (0, 8, 16, and 24 days) under accelerated oxidation conditions (temperature 60°C). We investigated the peroxide value (PV), thiobarbituric acid (TBA) value, acidity, conjugated diene (CD) content, and carbonyl value (CV). Artificial neural networks were employed using MATLAB software for prediction. Several feed-forward back-propagation networks with 2-6-5 topologies were examined, achieving correlation coefficients greater than 0.959 and mean square errors (MSE) < 0.009. The optimal model utilized a sigmoid logarithm activation function, a jumping learning pattern, and 1000 learning cycles. These models demonstrated high correlation coefficients (above 0.912) in predicting the oxidation process of SBO.
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Review of Some Thermal Methods in Drying and Roasting Processes
(United Scientific Group, 2024-09-18)
Toktam Mohammadi-Moghaddam
;
Mohammad Morshedi
;
Ramina Moalemzadeh Ansari
;
Afsaneh Morshedi
;
VALDES ALARCON, MARCOS EDUARDO
Thermal processing is a routine procedure in food science, with two important methods being drying and roasting. During thermal processing, simultane-ous heat and mass transfer occur, where the distribution of heat and humidity depends on effective diffusivity. Various methods exist for achieving this, each differing in efficiency and energy consumption. The conventional method of thermal processing involves hot air (HA) or convection, which typically requires sig-nificantly more energy and time (at least 25%). However, there are newer thermal processing methos based on radiation, each with their own advantages and disad-vantages. Nevertheless, all radiation-based methods generally consume less time and energy compared to the HA method. Different thermal processing methods have been studied and reviewed with regard to their energy consumption and effective diffusivity. In summary, while HA remains the routine method in indus-tries, it demands considerably more energy and time compared to radiation-based methods. Radiofrequency is a non-thermal method that can also be employed to enhance the efficiency of various processing techniques.
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The Effect of Pistachio Green Hull Extract on the Phenolic Compounds, Peroxide Value and Carbonyl Value of Salmon Oil Emulsion in Water
(United Scientific Group, 2024-09-03)
Ahmad Shakerardekani
;
Sara Banihashemi
;
Elham Taghavi
;
Afsaneh Morshedi
In this research, the extract of pistachio hull was used to delay the oxidation of fish oil emulsion in water. Total phenolic compounds, peroxide value and car-bonyl value of salmon oil was measured for 3 months storage. The total phenolic content of methanolic extract was 11.7 mg/g and the main components of meth-anolic extract included gallic acid, 4-hydroxybenzoic acid, protocatechuic acid and naringenin. In ethanolic extract, almost the same result was obtained. The lowest and highest peroxide value (0.6 and 51.3 meq/kg) and carbonyl number (0.007 and 0.41 μmol/g oil) were observed on day 0 and 90, respectively. Pistachio green hull extract delayed the oxidation rate and confirmed the antioxidant properties of phenolic compounds in the pistachio hull.
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Application of Artificial Neural Networks for Predicting Cooking Dynamics in Industrial Sesame Seed Oil Extraction
(United Scientific Group, 2024-10-01)
Hamid Bakhshabadi
;
Alireza Ghodsvali
;
Abolfazl Bojmehrani
;
Mohammad Ganje
;
Toktam Mohammadi-Moghaddam
Sesame seeds are a significant source of vegetable oil and were among the earliest grains used for oil extraction. In this study, aimed at designing an industrial-scale process for extracting oil from sesame seeds, we investigated three cooking temperatures (75°C, 90°C, and 105°C) and three different moisture contents of the seeds leaving the cooking pot (4.5%, 5.5%, and 6.5%). The study focused on several responses: the oil content of the pressed cake, the quantity of extracted oil, the protein and moisture contents of the resulting meal, and the percentage of insoluble fine particles in the extracted oil. To predict these responses, an artificial neural network (ANN) model was employed. Among the various backpropagation feedforward networks with different topologies studied, the configuration with 2 input nodes, 5 hidden nodes in one layer, and 5 output nodes was selected based on its high correlation coefficient (R² = 0.997) and low mean squared error (MSE = 0.0002). The sigmoid hyperbolic tangent activation function was used, and the Levenberg-Marquardt learning algorithm with 1000 learning cycles was identified as the optimal neural model. The selected optimized models demonstrated high R² ≥ 0.97 during the evaluation of their results.
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Use of Mono-diglyceride Emulsifier and Carotin Vegetable Oil to Prevent Oil Separation from the Texture of New Pistachio Halva Product: A Short Article
(United Scientific Group, 2024-08-14)
Ahmad Shakerardekani
;
Fahimeh Kordi
;
Afsaneh Morshedi
Separation of oil is one of the most important problems of pistachio halva. In this study, carotino oil (0, 1.5, and 3%) and monodiglyceride (0, 1, and 2%) were used to reduce oil separation from pistachio halva texture. The control halva, and the halva containing 2% monodiglyceride showed the highest and lowest oil separation for 8 weeks storage, respectively. The highest and lowest sensory evaluation score were obtained by halva containing 1% monodiglyceride and control halva, respectively. The control halva and halva containing 2% monodiglyceride had the highest and lowest peroxide values during the 2 months of storage, respectively. There was no significant difference between the use of 1% or 2% monodiglycer-ide. The amount of monodiglyceride used affects the amount of pistachio paste needed. If 1% emulsifier is used, no need to use carotino oil. The oil separation can be prevented up to 60% in pistachio halva, contains 1% monodiglyceride. Re-ducing the separation of oil from the product improves its texture and appearance and reduces its oil oxidation.
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A Simple Overview in Magnetic Resonance Imaging Application in Evaluation of Food Quantity and Quality Aspects
(United Scientific Group, 2024-10-03)
Toktam Mohammadi-Moghaddam
;
Mohammad Morshedi
;
Afsaneh Morshedi
;
VALDES ALARCON, MARCOS EDUARDO
Magnetic resonance imaging (MRI) has been a professional method in medical diagnostics for many years. Recently, considering the increase in population, preparing healthy food is a worldwide challenge. Hypothesis and implementation of MRI in research of food is approximately new. MRI is considered as a green, noninvasive, low cost, rapid, and nondestructive experimental method for investigating food processing. This method could be used in a short time while its results are suitable to apply in different industries even in online monitoring. Utilizing MRI techniques enhances the capacity to quantify basic processes such as gelation, crystallization, drying, dehydration, freezing, diffusion, and flow that occur in food products. This technology equips food scientists with a robust tool in the physicochemical properties study of food systems or specified food components and assessing them throughout diverse processes. This technique has some disadvantages in some process conditions too.
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Modeling and Optimization of the Osmotic Dehydration of Cantaloupe
(United Scientific Group, 2024-10-09)
Hamid Bakhshabadi
;
Mohammad Ganje
;
Masoumeh Moghimi
;
Alireza Ghodsvali
;
Toktam Mohammadi-Moghaddam
In current research, the optimization of osmotic dehydration of cantaloupe pieces aimed to maximize water loss (WL) and minimize moisture reabsorption using artificial neural network (ANN). The effects of three parameters were studied: osmotic solution temperature (40-60°C), immersion time (40-240 min), and solution concentration (40-60°Brix), employing central composite design (CCD). Various parameters including WL, solid gain (SG), reduction in WL to SG ratio, and reduction in sample weight were analyzed. The results indicated that the optimal conditions for osmotic dehydration were achieved with a solution temperature of 60°C, immersion time of 85.71 min, and solution concentration of 40% sucrose (sugar). Under these conditions, the following parameters were observed: WL of 3.79%, SG of 43.74%, WL to SG ratio of 14.48, and sample weight reduction of 47.71%. Furthermore, results from the ANN revealed that a network structure with one hidden layer comprising 5 nodes (3-5-4 network with 3 inputs, 5 nodes in the hidden layer, and 4 outputs) provided the most accurate predictions. This network achieved correlation coefficients (R2) of 0.999 and root mean squared error (RMSE) of 0.000039, demonstrating high reliability and precision in predicting the selected responses.

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