Post-harvest technologies
M. Namjoo; M. Moradi; M. A. Nematollahi; H. Golbakhshi
Abstract
In this study, the air drying of cumin seeds was boosted by cold plasma pre-treatment (CPt) followed by high-power ultrasound waves (USp). To examine the impact of included effects, different CP exposure times (0, 15, and 30 s), sonication powers (0, 60, 120, and 180 W), and drying air temperatures (30, ...
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In this study, the air drying of cumin seeds was boosted by cold plasma pre-treatment (CPt) followed by high-power ultrasound waves (USp). To examine the impact of included effects, different CP exposure times (0, 15, and 30 s), sonication powers (0, 60, 120, and 180 W), and drying air temperatures (30, 35, and 40 ºC) were selected as input variables. A series of well-designed experiments were conducted to evaluate drying time, effective moisture diffusivity, and energy consumption, as well as color change and rupture force of dried seeds for each drying program. Numerical investigations can effectively bypass the challenges associated with experimental analysis. Therefore, the wavelet-based neural network (WNN), the multilayer perceptron neural network (MLPNN), and the radial-basis function neural network (RBFNN), as three well-known artificial neural networks models, were used to map the inputs and output data and the results were compared with the Multiple Quadratic Regression (MQR) analysis. According to the results, the WNN model with an average correlation coefficient of R2 > 0.92 for the train data set, and R2 > 0.83 for the test data set provided the most beneficial tool for evaluating the drying process of cumin seeds.
Modeling
M. Almaei; S. M. Nassiri; M. A. Nematollahi; D. Zare; M. Khorram
Abstract
IntroductionDrying shrimp is one of the storage methods that, while increasing the shelf life, leads to the production of a versatile product with various uses, from consumption as snacks to use as one of the main components of foods. Drying is preferred over other preservation methods because it offers ...
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IntroductionDrying shrimp is one of the storage methods that, while increasing the shelf life, leads to the production of a versatile product with various uses, from consumption as snacks to use as one of the main components of foods. Drying is preferred over other preservation methods because it offers numerous advantages, including extended shelf life, enhanced microbial stability, convenient consumption, reduced transportation costs, increased value, and product diversity.To accurately model these processes and thus obtain information on factors such as shelf life and energy consumption, it is necessary to determine the product’s initial and final temperatures, its geometry and dimensions, and its thermo-physical characteristics. Simulation of different drying processes requires accurate estimation of the effective moisture diffusion coefficient, which is highly dependent on temperature and humidity. Its dependence can be shown by an equation with an Arrhenius structure as an empirical function of humidity and temperature, or by considering the activation energy.It is necessary to have sufficient knowledge about heat and mass transfer characteristics, such as diffusion or penetration coefficient and the heat transfer coefficient to estimate the final temperature and drying time. This study investigated the drying process of peeled farmed shrimp (Litopenaeus vannamei) using a convective hot air dryer. Various parameters such as shrinkage and the effective moisture diffusion coefficient were examined.Materials and MethodsA drying device was built to conduct experimental studies on drying shrimp samples. The experiments were conducted on sliced shrimp meat samples at temperatures of 40, 50, and 60 degrees Celsius, with a constant air velocity of 1.5 m/s. The experimental drying models were based on diffusion theory. In these models, it is assumed that the resistance to moisture diffusion occurs from the outer layer of the food. In most cases, Fick's second law was used to describe the phenomenon of moisture penetration.The study used the standard method of immersion in toluene to measure volume changes in the samples. During the drying process, the volume of the samples was measured at 45-minute intervals, and their volume changes were calculated. To measure the moisture content of the samples, each test started by recording the initial weight of the samples using a digital scale with an accuracy of ±0.001 g. During the drying process, the samples were weighed each time their volume was measured.Shrinkage during the drying process is commonly modeled by finding a relationship between shrinkage and moisture, using linear and non-linear models. In most cases, effective permeability is defined as a function of humidity and temperature. For this purpose, curve-fitting methods were employed to analyze the data collected from experimental tests. The appropriate function was extracted by incorporating the Arrhenius equation, which is applicable to most food items.Results and DiscussionBased on the results of statistical indices, the linear model was the best model for depicting the relationship between shrinkage changes versus moisture ratio changes among the various experimental models evaluated for shrinkage and drying kinetics. Similarly, the Weibull distribution demonstrated superior performance in expressing variations in moisture ratio over time. A moisture dependent experimental model was used to express the variations in the apparent density of shrimp, resulting in a computed range of 1017-1117 kg m-3. Furthermore, an Arrhenius equation was derived to express the effect of moisture content and temperature on the effective diffusion coefficient of shrimp. According to the results, the effective diffusion coefficient of shrimp exhibited variations ranging from 0.08 ×10-9 m2 s-1 to 7.39×10-9 m2 s-1. When deriving the effective diffusion coefficient, the impact of the number of terms in Fick's second law on the variation of the moisture ratio was studied. The findings revealed that increasing the number of terms beyond 100 did not significantly affect the model’s outputs.ConclusionThe linear model had the highest coefficient of determination (R2) among the evaluated shrinkage models, as well as the lowest root mean square error and sum of square error (SSE). This makes it the most optimal model for interpreting shrinkage at the tested temperature levels. The Weibull distribution experimental model proved to be the most suitable for expressing changes in the moisture ratio of shrimp meat slices over time within the evaluated temperature range. The Arrhenius model accurately predicts changes in the effective diffusion coefficient of shrimp slices with respect to temperature and moisture content within the tested temperature range.
M. Rahmatian; S. H. Karparvarfard; M. A. Nematollahi; A. Sharifi Malvajerdi
Abstract
All over the world, farmers choose different implements for tillage, which depend on crop type, soil type, the amount of plant residue from the previous crop, etc. Tillage implement selection is also affected by the availability of implements, power consumption, labor costs, and fund. In this research, ...
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All over the world, farmers choose different implements for tillage, which depend on crop type, soil type, the amount of plant residue from the previous crop, etc. Tillage implement selection is also affected by the availability of implements, power consumption, labor costs, and fund. In this research, the draft force, soil disturbance area, soil cone index, and fuel consumption were considered. The effects of rake angle, forward speed, and soil moisture content on the above-mentioned parameters were investigated. In this research, a comparison between the performance of a Fiber Reinforced Polymer (FRP) composite blade and a conventional steel blade was carried out. Tests were based on the split-split plot in a completely randomized design. The factors of soil moisture content, rake angle, and forward speed were included in three levels. Three levels for the soil moisture content (9.3, 13, 16.7 %), rake angle (20°, 30°, 40°), and forward speed (3, 5, 7 km.h-1), were considered. The FRP composite blade (on average in the desired range for variables) has reduced the draft force, fuel consumption, and soil cone index, 14.97%, 16.63%, and 35.08%, respectively, than the steel blade. Also, the soil disturbance area created by the FRP composite blade was 4.93% higher than the steel blade. Based on the results of this study, it is clear that the FRP composite blade has better performance rather than the conventional steel blade for the aforementioned test variables. The FRP composite is inexpensive than the steel, this leads to remarkable save money in the production of the FRP composite blade used in the chisel and combined tillage tools that is economical for the farmer and manufacturer.
Modeling
M. Rahmatian; R. Yeganeh; M. A. Nematollahi
Abstract
IntroductionTillage is a very important operation that influences the growth and productivity of agricultural products. It is necessary to introduce some conditions to improve soil physical properties, aeration, permeability and root development in tillage operations. However, in primary tillage, especially ...
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IntroductionTillage is a very important operation that influences the growth and productivity of agricultural products. It is necessary to introduce some conditions to improve soil physical properties, aeration, permeability and root development in tillage operations. However, in primary tillage, especially when moldboard ploughs are used, this may be time consuming and costly for researchers to use it in their research. Some researchers use physical experiments to perform the work, which the accuracy of the results is dependent on the measuring instruments precision. However, some other researchers use simulation and mathematical modeling to reduce the time and costs and increase the relative accuracy of the research results. Many studies have also shown that modeling the forces involved in tillage is a good way to estimate the performance of different tillage tools and improve their geometry. However, the key to success in numerical simulation of tillage operations is to simulate the exact instrumentation, based on the correct assumptions as well as the proper methods. The prediction of the forces involved in tillage tools has an important role in their design. Collecting data on the forces involved in tillage tool under different farm conditions is a time consuming and costly task. Therefore, the prediction of a tillage tool forces is very important for the designer and the user in order to achieve better performance of the tool. Materials and MethodsIn this study, a cylindrical moldboard made by Alpler Company in Turkey was used to simulate the moldboard. A measuring device was designed and constructed to measure the various points of the desired moldboard. Then, the spatial points obtained by the measuring device were presented to the SolidWorks 2016 software and the desired moldboard was modeled. The finite element method by Abacus 2016 was then used to simulate the interaction between soil and moldboard. Treatments used in simulated tillage operations included tillage depths (5, 10, 15, 20 and 25 cm) and forward speed (1, 1.5, 2, 2.5 and 3 millimeters per second). The independent variables were considered as tensile, vertical and lateral forces (Kilo newton). After simulating the tillage operations, tensile, vertical and lateral forces were obtained. These forces were modeled using response surface and artificial neural networks techniques. Then, the obtained models were compared using R2, RMSE and MRDM statistical indices and the best model was selected. Results and DiscussionWhen using the response surface method, the quadratic model was selected by using the maximum value of the statistical indices R2, R2a and R2p, among the linear, two-factor and quadratic models. Then, the significance of model variables was evaluated by using variance analysis. The forces were also modeled by using the neural network method. According to the fitting curves and statistical indices of R2, RMSE and MRDM for the tensile, vertical and lateral forces, it is revealed that both methods could well predict the forces but artificial neural network was more suitable than the response surface method. Moreover, by investigating the interactions of tillage treatments and forward speed on the forces in this research, it was observed that by increasing the depth of tillage and velocity, tensile, vertical and lateral forces were increased nonlinearly by 66.55%, 68.47%, and 64.76%, respectively. ConclusionRegarding all the results obtained from this study, it can be concluded that the developed models using the artificial neural network in this research was a good and powerful tool for predicting the forces involved in moldboard ploughs both in the field operations and in related studies. It is also recommended that the developed models in this study can be used to manage the tillage operations, such as selecting the proper tractor. However, it is also suggested that other affecting factors, such as moldboard angles, should be included in future models to increase the ability of the model to predict the forces involved in moldboard plows.
S. Zarei; M. Kasraei; M. A. Nematollahi
Abstract
Introduction Cereals as one of the most important sources of food plants could provide more than 70% of the food for the human population. Passing of water from the magnetic field is among approachable methods in order to reduce the total amount of water used for irrigation. Moreover, magnetized water ...
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Introduction Cereals as one of the most important sources of food plants could provide more than 70% of the food for the human population. Passing of water from the magnetic field is among approachable methods in order to reduce the total amount of water used for irrigation. Moreover, magnetized water is a new concept for increasing the water efficiency. Therefore, this study was aimed to investigate the effects of the magnetized water on some of features containing dry weight, germination velocity and percentage, length and weight vigor indices of five common wheat cultivars including Roshan, Sardari, Shiraz, Falat and Yavarus, to introduce the best cultivar considering the growth and germination indices as well as water and energy efficiency. Materials and Methods To perform this experiment, a device with a magnetic field of 500 millitesla was constructed to accommodate both the water path and the placement of seeds in the magnetic field. To perform the experiments, 10 seeds in 4-kg vases and 25 seeds in each Petri dish were cultivated in the greenhouse and laboratory, respectively. The experiments were carried out in the form of completely randomized factorial design. The factors are considered as the duration time of keeping the water in the magnetic field (three levels of 30, 60 and 120 minutes), the intensity of the magnetic field (three levels of 100, 150, and 200 millitesla), and five wheat cultivars (Roshan, Sardari, Shiraz, Falat and Yavarus) in three replications. Experiments related to the both of rate and percent of germination and for dry weight were performed at room temperature in the laboratory and greenhouse under controlled conditions, respectively. The measured data were analyzed using SAS software. The F test was used to determine the significant level of treatments. The comparison of the means was evaluated using LSD test. Results and Discussion The obtained results, showed that the effect of magnetic water on all growth and germination indices compared to control samples was significant. Under the 150 millitesla and 120 minutes treatment, the Yavarus, Roshan and Sardari cultivar had maximum dry weight, respectively. The Roshan cultivar had the maximum germination velocity at 100 and 150 millitesla and duration time of 30 minutes. Moreover, the maximum germination percentage was found in the Roshan cultivar, which did not have a significant difference with Yavarus cultivar. The Roshan cultivar in 200 millitesla field and duration time of 60 minutes, had the maximum percentage of length vigor index, which showed a significant difference with other averages. In general, Roshan and Sardari cultivars had more length vigor index than other cultivars. Sardari cultivar had maximum percentage of weight vigor index under 200 millitesla and 120 minutes duration time, which had no significant difference with the percentage of weight vigor index at the same field level and with duration time of 60 minutes. Conclusion According to the obtained results to achieve the maximum value of dry weight, it is better to use the Yavarus cultivar. It is recommended to use the Roshan cultivar with the lower level of magnetic field and duration time to attain the maximum value of the germination velocity and percentage. To get the maximum value of the length vigor index and the weight vigor index the Roshan and Sardari cultivars, and the Sardari cultivar with field of 200 milli Tesla and lower duration time are preferred.
A. Nourmohamadi-Moghadami; D. Zare; Sh. Kamfiroozi; A. A. Jafari; M. A. Nematollahi; R. Kamali
Abstract
Introduction During filling a silo, granular material containing a range of particle sizes, the fine material accumulates under the filling point. The inclined surface of stationary bed particle which is formed in silos during filling process acts similar to a sieve through which the smaller particle ...
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Introduction During filling a silo, granular material containing a range of particle sizes, the fine material accumulates under the filling point. The inclined surface of stationary bed particle which is formed in silos during filling process acts similar to a sieve through which the smaller particle fall. This effect is called sifting. As a result of the mentioned effect, much finer particles form a vertical cylindrical zone of high concentration at the silo center. For optimal design in industrial process such as aeration of stored products in silos, filling silos, and wherever granular materials are handled, it is necessary to survey the distribution of the fine materials depending on product and process properties. The objectives of present study were: (a) To study fine change as affected by substantial parameters, (b) To model fine changes at different conditions in silos. Materials and Methods In the present study, an experimental setup consist of a main container, elevator, trapezoidal container and experimental silo was designed and built. Fine content was defined by BCFM (broken corn and foreign material). By applying a new approach, sampling was performed in a radial and vertical direction. The position of each sampling point was determined with a scaled distance from center (R) and from bottom (Z). Local BCFM (BCL) was defined as the value of BCFM in each sampling point. Influential parameters namely, initial BCFM (BCI), volume flow rate (Q) and fill pipe diameter (DF) were considered as treatments. Non-linear regression technique was applied on the experimental data to predict the distribution pattern of fines into the pilot-scale silo. The most appropriate model in a try and error procedure was selected based on highest value of R2 and least value of χ2, RMSE and MRDM. Results and Discussion According to the results of ANOVA, it was found that the effects of all parameters were significant at 5% probability. BCL decreased nonlinearly with a concave down decreasing trend along radial direction due to sifting effect. As a result, most amount of fines remained in the sections closer to the center of the silo. Fine distribution became more uniform with decreasing Z and increasing BCI and DF. Also, the distribution of fine became more uniform with increasing Q. BCL was a nonlinear function of R and a linear function of Z, BCI, Q and DF. Although including more and complex terms increased the model complexity but in the present study considering BCL as an exponential function of R and as an implicit function of Z and R (ZR) improved the quality of the model significantly. The values of 0.94, 1.14, 1.06, 11.39 for R2, χ2, RMSE and MRDM, respectively, gave the best model. The results showed, considerable accumulation of fines occurred at the center of the silo which increased with increase of level of Z. Also, low concentration of fine occurred at the periphery of the silo especially at higher levels of Z. It means that maximum non-uniformity of fine distribution occurred at higher levels of Z. Conclusion The present study investigated distribution of fines during filling affected by main parameters namely, initial BCFM, volume flow rate and fill pipe diameter in a pilot scale silo. A new procedure was developed for measuring the fine material along radial and vertical directions. Distribution of fine was modeled using a developed equation considering the effects of main parameters. The results showed that distribution of fine becomes more uniform with decreasing height and increasing initial BCFM, volume flow rate and fill pipe diameter.
