Journal of Researches in Mechanics of Agricultural Machinery

Abstract Saffron is one of the most critical and valuable medicinal plants. The lack of mechanized planting of saffron corm and the high costs of labour in the limited planting time is one of the problems in the cultivation of this medicinal plant. The present study aimed to construct and evaluate a machine that can plant saffron corms at the desired intervals without having the corms damaged. For this purpose, first, a five-row planter machine with the ability to plant 5 to 10 tons of saffron corms per hectare was designed and developed. Then, under field conditions, two container volumes (full and half full) and two planting velocities (3 and 6 km/h) were examined using different planting indices. In the machine's structure, a continuous flow spoon chain feeder was installed at the bottom of the corms container, and the corms were led to the furrowers by five outlet ducts. The results of the saffron corm planter evaluation performed in field conditions showed that the spoon chain feeder was suitable for efficiency. The measurement of planting traits showed that with increasing velocity and decreasing the container volume, the distribution uniformity of corms around the mean of the obtained distances and around the set distance, uniformity of corm depth and feed quality index decreased; but the none-planting and multiple-planting indices and coefficient of variation of intervals increase. This machine can be replaced by labour, and it is better to use it at a speed of 3 km/h and in a modified container.

Abstract Measuring the seed and fertilizer mass flow rate in drill delivery tubes is an essential tool for real-time monitoring of the application rates. In the present study, a non-contact capacitance measuring system was implemented to monitor the granular discharge rate in seed and fertilizer applicators. The set-up consisted of a fluted-roller feeding mechanism and the capacitance measuring system incorporated in the discharge tube. The set-up was mounted on a custom-built vibratory stand to simulate the field condition during the measurement. Then, triple super phosphate, wheat, and alfalfa granular discharge rates were measured over 30 s intervals in both static and dynamic conditions from 3.42±1.22 to 19.3±0.95 g/s in 5 rates, from 2.55±0.23 to 19.02±0.86 g/s in 8 rates, and from 0.42±0.02 to 1.6±0.08 g/s in 7 rates, respectively. The results revealed that the mass flow was effectively correlated with sensor signals for all examined materials. However, the capacitance sensor failed to measure the sudden change in mass flow rate synchronously with the digital scale. This phenomenon was predictable because it is attributed to the feature of a digital balance, which is always accompanied by an initial lag. Also, the results revealed that the vibrating stand had no effect on the sensor accuracy.

Abstract Lubricating parts to reduce friction and wear is one of the most important functions of engine oil. When engine oil is used, the color and viscosity of the engine oil changes during the operation of the car, and due to the increase in friction and the energy required to pump the oil, it causes an increase in fuel consumption. The purpose of this study is to investigate the detection of engine oil life based on the distance traveled with the help of smell, color and integrated data of color, smell and brix using two standard and zero-one methods. In this research, electronic nose devices, refractometer and colorimeter were used. Principal component analysis (PCA), linear discriminant analysis (LDA) and artificial neural network (ANN) were used to classify the data to detect kilometers, and partial least squares (PLS) and principal component regression (PCR) were used to predict the parameters. Brix and engine oil color changes were used. The main component analysis method of the results showed that in the score chart, engine oil life detection was done better based on color, and all the oil samples were well separated based on the distance traveled. Also, the LDA method for detecting the life of engine oil with different traveled kilometers for color data separated different classes with 96.36% accuracy. Based on the disturbance matrix obtained from the artificial neural network for the color data, the classification accuracy of engine oil with different distances traveled was 93.6%. LDA method showed better classification than PCA and ANN methods. The results showed that the PLS and PCR methods performed well in predicting Brix parameters and engine oil color change, but they did not perform well in predicting the mileage parameter. Using PCR and PLS models are more suitable for Brix and color change detection.

Abstract In this research, the parameters and kinetics of drying red delicious apple slices were investigated in a dryer equipped with a heat pump at different temperatures (30, 40, 50, 60 and 70 ͦC) and air velocities (1, 1.5 and 2 m/s). Analysis of variance was used to determine the effects of temperature and air velocity on the parameters of color change, shrinkage and intensity of reabsorption. Five mathematical models were selected to describe and compare the drying kinetics of apple slices, and the coefficient of determination (R2), chi-square (χ2), and (RMSE) were used for evaluation. The results showed that the temperature and speed of drying air had a significant effect on the drying behavior of apple slices. Drying time decreased with increasing temperature and drying speed. Temperature and air velocity had little effect on the total color changes, shrinkage rate and intensity of reabsorption of dried apple slices. Among the mathematical models, the modified Page model with the lowest error and the highest coefficient of determination had the best fit. Moisture transfer from apple slices was described by applying the Fick's diffusion model. The effective diffusion coefficient (Deff) increased with increasing drying temperature and was obtained in the range of 2.32 ×10-10 to 5.18 × 10-10 m2/s. The effective temperature dependence was described by the Arrhenius equation and the activation energy for moisture diffusion in apple slices was determined to be 28.4 kJ/mol.

Abstract Hur al-Azim wetland in the southwest of Iran has become one of the major sources of air pollution in Khuzestan province in recent years due to widespread fires. Sustainable harvesting of this huge source of biomass and controlled combustion, in addition to reducing current pollution, can play an effective role in sustainable renewable energy production. Therefore, in this study, it is tried to estimate the amount of sustainable harvestable biomass from this wetland. In order to identify and estimate biomass amount, NDVI index was used in satellite images. Also, by visiting 30 points with different NDVI index, and harvesting biomass, yield per hectare was estimated. Also, the thermal characteristics of the reed plant were investigated for use in a biomass burning power plant. Based on the results of the estimation, approximately 3,500,000 tons of reeds can be harvested annually from the total of 33,712 hectares of reeds in the Iranian part of Hur al-Azim wetland, and according to the average biomass moisture (65%), the amount of dry biomass that can be harvested annually will be about 300 thousand tons, which is a very significant number. Also, according to the results, the calorific value of the reed plant (about 20 MJ/kg), the amount of ash, the composition of the ash, as well as the composition of the elements of the reed plant organs are comparable with reference energy plants, which makes it possible to use as a fuel in biomass power plants.

Abstract Disinfection of agricultural products as one of the main stages of processing agricultural products has been a very important issue in recent years. One of the new methods of disinfection with high efficiency and low operating costs and at the same time with minimal side effects is using liquid treated with plasma. Plasma-activated water (PAW) and its disinfecting effect on crops have previously been evaluated in a defined volume and for a predetermined amount of time in previous systems. In the current work the physical properties of continuously producing activated water with plasma were studied. The effect of different water sources including tap water (TW), distilled water (DiW), and deionized water (DeW), different water flow rates (0.5, 1, and 2 ml/min), and different sources of gases including air (Ai) and argon (Ar) as a cold-plasma micro jet was studied on physical properties of water at different times. As a result of plasma treatment, the oxidation-reduction potential (ORP), electrical conductivity (EC) significantly elevated while pH showed a significant reduction. There was a significant and positive correlation between ORP and EC, on the contrary pH had a significant and negative correlation with ORP and EC. Our findings showed that deionized water, argon gas, and 0.5 ml ml/min water flow rate are the best combination to produce PAW.

Abstract Drying is one of the most common methods of preserving agricultural products. It is very important to maintain the final quality of the product in the drying process. Changing the temperature parameter and humidity level of dryer air has a great impact on drying time and energy consumption. In this research, to compare the drying speed at different temperatures, a thermal dryer equipped with nano absorbent plates and closed air circulation and energy recovery was evaluated. So that the drying parts included: the product drying chamber, air communication pipes, air blowers, the chamber containing MOF nano absorbent materials, electric air heater and measurement and control systems. Experiments on mint leaves were compared at three temperature levels (40, 50 and 60 ºC) and in two open and closed air circulation methods. The results of the research showed that the drying time decreased with the increase in temperature and the drying time decreased by 50% under the conditions of using nano absorbent plates. Also, the lowest energy consumption was obtained in the conditions of using nano-absorbers at the rate of 161.92 W/h equal to 49% in reducing energy consumption. The changes in the total color index (ΔE) did not change much with the increase in temperature from 40 to 50 ºC, but from 50 to 60 ºC, the total color From 9.22 to 12.86 index increased, but there was not an obvious difference in the total color index between the two methods of using and not using nano absorbents.

Abstract Plum is one of the nutritious and popular fruits in Iran. Depending on the quality of the fresh fruit before harvesting and the drying process, different quality grades of this fruit are produced as dried plums. In this research, a computer vision system and machine learning algorithms were used to classify dried plums into three different quality grades. Different color, shape, and texture features were extracted from the images of dried plum samples, and were used separately and in combination with each other for developing classification algorithms of Multilayer Perceptron (MLP) neural networks, Support Vector Machine (SVM), Linear Discrimination Analysis (LDA) and Decision Tree (DT). In order to reduce the number of features and to extract more important features, the Correlation-based Feature Selection (CFS) method was used. Results showed that the combination of different image-extracted features increases the classification accuracy, compared to individual color, shape, or texture features. In this regard, the Random Forest (RF) DT model using the combination of image features and CFS feature selection algorithm had the highest classification accuracy in the training and evaluation stages. The values of Root Mean Squared Error (RMSE) and accuracy of this model were obtained equal to 0.1958 and 93.75% in the training stage, and equal to 0.2110 and 91.67% in the evaluation phase, respectively. Considering these performance parameters and the nature of machine vision systems, the results of this research can be used to develop an accurate, fast, and inexpensive system for the quality grading of dried plums.

Abstract The present study was conducted to investigate the possibility of using compressed natural gas fuel in compression ignition engines without the use of ignition system. For this purpose, a four-cylinder compression-ignition engine with the possibility of using compressed natural gas as the main fuel and diesel fuel as the igniter was used. Performance tests and emission of pollutants were performed at the Engine Research Center of Tabriz Motor Manufacturers Company. All performance and pollution tests were performed after 10 minutes of operation in the engine room and the tests were performed in five levels of rotational speed of 1200, 1400, 1600, 1800 and 2000 rpm and in two modes of single diesel fuel and dual fuel mode (combined fuel) was performed in three replications. The maximum output torque of the engine in single diesel mode was 360 N.m at a rotational speed of 1400 rpm and the maximum output torque of this engine in the combined fuel mode was 334 N.m at a rotational speed of 1600 rpm, which showed that the combined fuel mode had 26 N.m of torque reduction. In addition, with increasing the rotational speed of the engine, the amount of diesel fuel consumption also increased. According to the results of pollution tests, at indicated rotational speed of 2000 rpm, the amount of NOX, HC, CO2 and CO pollutants in the combined system was 20, 53, 16 and 86% more than diesel fuel, respectively, and the variables O2 and soot at indicated rotational speed of 2000 rpm, the combined system was 51% and 69% lower than diesel fuel, respectively. Therefore, by using a hybrid system, there is no significant reduction in engine production capacity and this system can be proposed as an alternative to existing systems, although compared to diesel fuel, hybrid fuel produced more pollutants.

Abstract In this study, the possibility of using solar energy for recycling food waste in the West Azarbaijan region was investigated. The method of waste distillation was assumed as the basis for the work, and a system for distillation of wastewater was developed using heating from a solar collector. In the design of the machine, another source of energy was not required to flow into the system. The machine was equipped with an electric element for water heating to perform preliminary tests and performance evaluation. Tests were made to estimate the capacity of the machine in four levels of input wastewater temperature (representing four levels of ambient temperature in different seasons) as well as three levels of thermal evaporation of water. The results indicate increased distillation performance by increasing the initial temperature of the wastewater and also increasing the thermal power of the device. By matching the radiation conditions in the studied area, based on the weather data and test results of the device with the electric element, the distillation capacity of the machine was estimated for the months of the year. According to the research, the maximum distillation capacity of the machine is projected to be about 50 liters in July. The annual capacity of the device is estimated at around 10,000 liters, which is remarkable considering the importance of environmental wastewater treatment as well as the economic benefits of using the free energy of the sun.