Post-harvest technologies
Z. Zangene Wandi; H. Javadikia; N. Aghili Nategh; L. Naderloo
Abstract
IntroductionThe use of corn oil in diets is due to its positive effects on cardiovascular and immune systems. Corn oil is composed of 99% triacylglycerol, with 59% unsaturated fatty acids and 13% saturated fatty acids. Of the unsaturated fatty acids, 24% contain a double bond. Because of this composition, ...
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IntroductionThe use of corn oil in diets is due to its positive effects on cardiovascular and immune systems. Corn oil is composed of 99% triacylglycerol, with 59% unsaturated fatty acids and 13% saturated fatty acids. Of the unsaturated fatty acids, 24% contain a double bond. Because of this composition, corn oil can be a good alternative to other oils high in saturated fatty acids, as it reduces blood cholesterol levels.This study employed an electrical nasal system to detect the amount of palm oil present in corn oil. The properties extracted from the signals obtained by the device were processed using principal component analysis, artificial neural networks, infusion, and response surface methods. The results were then compared to find the best method for detecting palm oil levels in corn oil.Materials and Methods The required palm oil was obtained from the Nazgol Oil Agro-industrial Plant, while the corn oil was obtained from natural lubrication centers. To prepare samples with different percentages of palm oil, 75 grams of palm oil and corn oil with the specified percentages were mixed and stored in special containers.In the electrical nose system, ten metal oxide semiconductor sensors (MOS) were used to collect output data. Pre-processing operations were performed on this data using RSM, ANFIS, PCA, and ANN methods to estimate the percentage of palm oil in corn oil. The Unscrambler V.9 software, Design Expert 8.07.1, and MATLAB R2013a were used to analyze the results.Results and DiscussionBased on the Score plot, PC-1 and PC-2 explain 53% and 25%, respectively, describing the variance between samples for a total of 78 data points. The analysis indicates that sensors 7 and 8 have minimal impact on the detection process and can be removed from the sensor array. When reducing the cost of the olfactory system's sensor array, sensor 6 plays a more significant role than other sensors in detecting corn oil with palm composition.According to the loading diagram of palm percentage in corn oil, the MQ6 sensor had the least effect in classifying different percentages of palm in corn oil and pattern identification. Out of all functional parameters (accuracy, sensitivity, and specificity), the RSM method is deemed more appropriate for determining the percentage of palm in corn oil.Regarding the separation of corn oil and palm oil by ANFIS, RSM, and ANN, the results in Table 3-1 indicate that the RSM method is better suited for classifying corn and palm oil.Conclusion In this study, we used an electronic multi-sensor system based on metal oxide sensors to analyze various aromatic compounds in different oil and palm samples and to detect the presence of palm. The system provided comparable information for classifying different samples of palm oils. Using PCA, ANN, ANFIS, and RSM methods, we evaluated the system's performance in differentiating and classifying various oil and palm samples.The results obtained from the loading diagrams for the detection of palm in corn oil indicated that the MQ6 sensor had the least impact on the detection process. Therefore, this sensor can be removed from the sensor array.Additionally, our analysis showed that using the RSM method is more effective in detecting different percentages of palm in corn oil. Overall, our study demonstrates the efficacy of the electronic multi-sensor system in analyzing different oil and palm samples and detecting the presence of palm.
A. Safrangian; L. Naderloo; H. Javadikia; M. Mostafaei; S. S. Mohtasebi
Abstract
Introduction Vibrations include a wide range of engineering sciences and discuss from different aspects. One of the aspects is related to various types of engines vibrations, which are often used as power sources in agriculture. The created vibrations can cause lack of comfort and reduce effective work ...
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Introduction Vibrations include a wide range of engineering sciences and discuss from different aspects. One of the aspects is related to various types of engines vibrations, which are often used as power sources in agriculture. The created vibrations can cause lack of comfort and reduce effective work and have bad influence on the health and safety. One of the important parameters of the diesel engine that has the ability to create vibration and knocking is the type of fuel. In this study, the effects of different blends of biodiesel, bioethanol and diesel on the engine vibration were investigated. As a result, a blend of fuels such as synthetic fuel that creates less vibration engine can be identified and introduced. Materials and Methods In this study, canola oil and methanol alcohol with purity of 99.99% and the molar ratio of 6:1 and sodium hydroxide catalyst with 1% by weight of oil were used for biodiesel production. Reactor configurations include: maintaining the temperature at 50 ° C, the reaction time of 5 minutes and the intensity of mixing (8000 rpm), and pump flow, 0.83 liters per minute. A Massey Ferguson (MF) 285 tractor with single differential (2WD), built in 2012 at Tractor factory of Iran was used for the experiment. To measure the engine vibration signals, an oscillator with model of VM120 British MONITRAN was used. Vibration signals were measured at three levels of engine speed (2000, 1600, 1000 rpm) in three directions (X, Y, Z). The analysis performed by two methods in this study: statistical data analysis and data analysis using Adaptive neuro-fuzzy inference system (ANFIS). Statistical analysis of data: a factorial experiment of 10×3 based on completely randomized design with three replications was used in each direction of X, Y and Z that conducted separately. Data were compiled and analyzed by SPSS 19 software. Ten levels of fuel were including of biodiesel (5, 15 and 25%) and bioethanol (2, 4 and 6%), and diesel fuel. Data analysis by ANFIS: ANFIS is the combination of fuzzy systems and artificial neural network so that it has both benefits. This system is useful to solve the complex non-linear problems in agricultural engineering applications such as systems involved in the soil, plant and air. ANFIS by linguistic concepts can establish and inference non-linear relationship between inputs and outputs. In this research, modeling was generally performed by Toolbox of ANFIS and coding in MATLAB too. Five important and effective factors in modeling were optimized until the best ANFIS model is obtained. The five factors were: type of input fuzzy sets, the number of input fuzzy sets, fuzzy set of output, methods of optimization and the number of epochs. Results and Discussion Based on the total vibration acceleration values for different fuels in different rpm, pure diesel (B5E4D91) had the highest vibration and the lowest vibration was seen in the mixed fuel of B25E4D71. Based on the results, two combined fuel of (B25E2D73, B25E4D71) have the lowest vibration and highest amount of biodiesel fuel (25%). After them, three combined fuels of (B5E2D83, B5E4D81, and B5E6D79) have created more vibration and the lowest amount of biodiesel fuel in this study (5%) has created the greatest amount of vibration. With increasing engine speed, the number of combustion courses and piston shock per unit of time increases. As a result, the engine body vibration increases. The results are consistent with results from other researchers. Conclusion In this study, motor vibration of MF285 tractors, by replacing a portion of diesel fuel with biodiesel produced from canola oil and bioethanol, was investigated. In the beginning, necessary biodiesel fuel was produced by research reactor in biodiesel workshop, and then different percentages of diesel and bio-ethanol were mixed to biodiesel and ten combined fuels were created. Finally the effect of different fuel combinations and different engine rotational speeds on the tractor engine vibrations was studied based on a factorial randomized complete block design and then analyzed and modeled by ANFIS. The results showed that the vibration of pure diesel fuel had the highest vibration. Also, with increasing biodiesel fuel blends, the amount of vibration reduced significantly. Increase in engine speed had direct effect on increasing the amount of vibration. Also by increasing the percent of bioethanol from 0 to 4%, the amount of vibration was reduced then vibration value increased by raising the percent of bioethanol. After modeling and analyzing, our results showed that the best fuel in terms of having the lowest vibration motor was B25E4D71.
Modeling
A. Zareei; R. Farrokhi Teimourlou; L. Naderloo; M. H. Komarizade
Abstract
Introduction Spiral conveyors effectively carry solid masses as free or partly free flow of materials. They create good throughput and they are the perfect solution to solve the problems of transport, due to their simple structure, high efficiency and low maintenance costs. This study aims to investigate ...
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Introduction Spiral conveyors effectively carry solid masses as free or partly free flow of materials. They create good throughput and they are the perfect solution to solve the problems of transport, due to their simple structure, high efficiency and low maintenance costs. This study aims to investigate the performance characteristics of conveyors as function of auger diameter, rotational speed and handling inclination angle. The performance characteristic was investigated according to volumetric efficiency. In another words, the purpose of this study was obtaining a suitable model for volumetric efficiency changes of steep auger to transfer agricultural products. Three different diameters of auger, five levels of rotational speed and three slope angles were used to investigate the effects of changes in these parameters on volumetric efficiency of auger. The used method is novel in this area and the results show that performance by ANFIS models is much better than common statistical models. Materials and Methods The experiments were conducted in Department of Mechanical Engineering of Agricultural Machinery in Urmia University. In this study, SAYOS cultivar of wheat was used. This cultivar of wheat had hard seeds and the humidity was 12% (based on wet). Before testing, all foreign material was separated from the wheat such as stone, dust, plant residues and green seeds. Bulk density of wheat was 790 kg m-3. The auger shaft of the spiral conveyor was received its rotational force through belt and electric motor and its rotation leading to transfer the product to the output. In this study, three conveyors at diameters of 13, 17.5, and 22.5 cm, five levels of rotational speed at 100, 200, 300, 400, and 500 rpm and three handling angles of 10, 20, and 30º were tested. Adaptive Nero-fuzzy inference system (ANFIS) is the combination of fuzzy systems and artificial neural network, so it has both benefits. This system is useful to solve the complex non-linear problems in agricultural engineering applications. ANFIS by linguistic concepts can establish and inference non-linear relationship between inputs and outputs. In this research, generally modeling was performed by using toolbox of ANFIS and coding in MATLAB software. Five important and effective factors in modeling were optimized until the best ANFIS model was obtained. The five factors were: type of fuzzy sets for inputs, number of fuzzy sets for inputs, type of fuzzy set for output, method of optimization and number of epochs. The statistical model was done by using SPSS and in the multivariate regression method. In multivariate linear regression in statistical model, the independent variables were auger blade diameter, rotational speed and the angle of slope of the auger and dependent variable was volumetric efficiency. The factorial test in randomized complete block design was conducted for variance analysis of volumetric efficiency. Mean Comparison of volumetric efficiency in different levels of factors was performed using Duncan' test in 5% level. Conclusion In this study, volumetric efficiency of spiral conveyors was investigated as a function of auger blade diameter, auger rotational speed and slope of transfer. The performance was measured in terms of volumetric efficiency using ANFIS and statistical models with SPSS. The results showed that: Volumetric efficiency almost decreased by increasing of rotational speed, for all three conveyors. Maximum volumetric efficiency in all three spiral conveyors was in the speed range of 100 to 200 rpm. Volumetric efficiency significantly reduced in all three spiral conveyors by increasing in rotational speed and slope of transferring in spiral conveyors. Effect of spiral conveyor diameter on the volumetric efficiency in product transferring was irregular and no specific process is appeared. The correlation coefficient between the actual and predicted values was obtained as 0.98 in ANFIS model and 0.94 in multivariate linear regression with SPSS which showed the ANFIS model was more accurate than statistical model. Comparison between performances of spiral conveyor to transfer the seeds of wheat, with results by other researchers that has been reported for spiral conveyors with the same slope to transfer of corn kernels, was found that the angle effect on volumetric efficiency is quite significant. Therefore, it proves that performances of spiral conveyor are impressed by characteristics of transition material considerably. The maximum volumetric efficiency was corresponded in rotational speed of 100 rpm, inclination angle of 10º, and blade diameter of 17.5 cm that it was approximately 29.11%.
H. Javadikia; Y. Nosrati; M. Mostafaei; L. Naderloo; M. Tabatabaei
Abstract
Introduction Biofuels are considered as one of the largest sources of renewable fuels or replacement of fossil fuels. Combustion of plant-based fuels is the indirect use of solar energy. Biofuels significantly have less pollution than other fossil fuels and can easily generate from residual plant material. ...
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Introduction Biofuels are considered as one of the largest sources of renewable fuels or replacement of fossil fuels. Combustion of plant-based fuels is the indirect use of solar energy. Biofuels significantly have less pollution than other fossil fuels and can easily generate from residual plant material. Waste and residues of foods and wastewater can also be a good source for biofuel production. Transesterification method (one of biodiesel production methods) is the most common forms to produce mono-alkyl esters from vegetable oil and animal fats. The procedure aims are reduction the oil viscosity during the reaction between triglycerides and alcohol in the presence of a catalyst or without it. In this study, the method of transesterification with alkaline catalysts is used that it is the most common and most commercial biodiesel production method. In this study, configurations of made hydrodynamic cavitation reactor were studied to measure biodiesel fuel quality and enhanced device performance with optimum condition. The Design Expert software and response surface methodology were used to get this purpose. Materials and Methods Transesterification method was used in this study. The procedure aims were reduction of the oil viscosity during the reaction between triglycerides and alcohol in the presence of a catalyst or without it. Materials needed in the production of biodiesel transesterification method include: vegetable oil, alcohol and catalysts. The used oil in the production of biodiesel was sunflower oil, which was used 0.6 liters per each test in the production process base on titration method. Methanol with purity of 99.8 percent and the molar ratio of 6:1 to oil was used based on titration equation and according to the results of other researchers. The used catalyst in continuous production process was high-purity sodium hydroxide (99%) that it is one of alkaline catalysts. Weight of hydroxide was 1% of the used oil weight in the reaction. Response surface methodology: Three important settings of reactor were considered to optimize reactor performance, which include: inlet flow to reactor, reactor rotational speed and the fluid cycle time in the system. Each set was considered at three levels. The factorial design was used to the analysis without any repeat, there will be 27 situations that because of the cost of analysis per sample by GC, practically not possible to do it. Therefore, response surface methodology was used by Design Expert software. In the other words, after defining the number of variables and their boundaries, software determined the number of necessary tests and the value of the relevant variables. Results and Discussion Three parameters include the inlet flow to reactor, reactor rotational speed and the fluid cycle time in the system were considered as input variables and performance of reactor as outcome in analyzing of extracted data from the reactor and GC by Design Expert software. The results of tests and optimization by software indicated that in 3.51 minutes as retention time of the raw material of biodiesel fuel in the system, the method of transesterification reaction had more than 88% Methyl ester and this represents an improvement in reaction time of biodiesel production. This method has very low retention time rather than biodiesel fuel production in conventional batch reactors that it takes 20 minutes to more than one hour. Conclusion According to the researches, efficiency of biodiesel fuel production in hydrodynamic cavitation reactors is higher than ultrasonic reactors so in this study, the settings of hydrodynamic reactor were investigated so that the settings were optimized in production of biodiesel fuel. Sunflower oil was used in this research. The molar ratio of Methanol to oil was 6 to 1 and sodium hydroxide as a catalyst was used. Three important settings of reactor were considered which include: inlet flow to reactor, reactor rotational speed and the fluid cycle time in the system. The results were analyzed by gas chromatography. The results showed that at 8447 rpm of reactor speed, inlet flow of reactor at 0.86 liters per minute and 1.02 minute of circulation time, the best performance of reactor were created. The flash point, kinematic viscosity and density of biodiesel in this study were 172 °C, 2.4 square millimeters per second and 861 kg per cubic meter, respectively. Maximum and minimum performances of hydrodynamic cavitation reactor in biodiesel production were 6.19 and 1.13 mg kJ-1, respectively.
