نشریه ماشین های کشاورزی
سال پنجم شماره 2 (پیاپی 10، نیمسال دوم 1394)

Iran is one of the major producers of almonds. According to the statistics released by FAO (2011), Iran with more than 110000 tons of almonds is the third in rank throughout the world. However, most Iranian almonds are presented as an unsorted and unpackaged product. Some producers sort their products by hand which is very time-consuming and labor-intensive. So, there is an essential need for suitable grading and packaging machines especially for the export of almond kernels.Grading, which is sometimes called sorting, is basically separating the material in different homogenous groups according to its specific characteristics like size, shape, color and on the basis of quality. Weighing is one of the best methods for grading agricultural products based on size, but due to its high cost and complexity of operations, usage of weigh size sorting machines is practically limited. So, sizing of most agricultural products is accomplished based on their dimensional attributes such as diameter, length, thickness or a combination of them. Field study shows that recently vibrating sizing machines are used for grading almond kernels. This type of sizing machine is huge, expensive, noisy and it consumes a lot of energy. Thus, the main objective of the present study was the design, development and evaluation of a new prototype of an almond kernel sizing machine. It is important that the machine could resolve defects of existing vibrating machines. It should provide efficient and cost effective sizing for a wide range of kernel sizes and shapes. Furthermore, it should be of simple construction and be able to accept manual feeding. Previously conducted experiments showed that the thickness of the kernel is the most appropriate dimension for its sizing. Among the different types of dimensional sizing machines, the divergent roller grader which grades the products based on their thickness is considered to be one of the simplest options. So, a divergent roller grader was developed and built in this research. The prototype consisted of two diverging rotating rollers which were made of mild steel with an outside diameter of 95 mm and a length of 700 mm. They were mounted to provide an adjustable slope towards the wide opening end. These roller beds were fixed on a box shaped frame of size 500×1000×1200 mm. The slope and counter-rotating action of the rollers encouraged the kernels to continue moving toward the end where the gap between the rollers was the widest. A tray was fixed at the feeding end of the machine for feeding the kernels. A provision was given to adjust the gap from a minimum to a maximum level. Based on the required activate torques of the rollers, an electric 74 W motor was selected to drive the machine. The power transmission mechanism consists of two pulleys 150 and 250 mm diameters and a V belt type A with a length of 1448 mm. The center distance of the pulleys is calculated to be 410 mm. Standard criterions of weighted sorting error index (C ̅_R), weighted sorting efficiencies index (EW) and operation capacity (Q) were used to evaluate the machine. Practical analysis showed that the machine’s performance is influenced mainly by the slope of the rollers, the rotation speed of the rollers, and the feeding rate of the product. In order to evaluate the performance of the prototype, a factorial experiment in a completely randomized design with three replications for each test was done. The performance evaluation was carried out for three levels of feeding rates (600, 1000, and 1400 kg 8h-1, three levels of slopes (2, 7, and 12 degree), and three rotation speeds of rollers (50, 80, and 110 rpm). Spreadsheet software MSTATC and SPSS were used to analyze the data and the Duncan's multiple range tests were used to compare the means. Analysis of variance showed that all three studied factors have significant effects on evaluating standard criterions of C ̅_R, EW, and Q at the 1% level of confidence. In this work, an increase in the slope of rollers led to a decrease in C ̅_R, whereas at the same time an increase in EW and Q was observed. It may be because at a higher level of slope the almond kernels slip more effectively on rollers surface. This condition restrains the aggregation of kernels on the first part of the gap between the rollers. So, they have enough time to drop through all of the gap. Experimental results show that as the feeding rate increases, C ̅_R and Q increase, whereas EW decreases. Based on the results of the experiments, with an increase of rotation speed of rollers from 50 to 110 rpm, the C ̅_R decreases up to %6.5, and EW decreases about %6. Study of interactions showed effects among which only the interaction of slope and rotation speed of rollers significantly affects all standard criterions. The results also showed that the operation capacity (Q) was significantly affected (P≤0.01) by the interaction effects between the feeding rate and the slope of rollers, and the feeding rate and the rotation speed of the rollers. The mechanical damage to almond kernels in the form of external damage such as cracks and scuffing was almost zero, which is a very important advantage of this machine in comparison with the other sizing machines. In this research, a divergent roller sizer was designed, developed and evaluated for almond kernels.The results showed that the best machine operation is obtainedat a feeding rate of 1000 kg 8h-1, slope of 9 degrees and rotation speed of 110 rpm. In this situation, the prototype could reach weighted sorting efficiencies index of 80% and operation capacity of 830 kg in an 8 hour work shift with weighed sorting error index of 23%.

From an economic viewpoint, tomato is considered as the second most valuable crop after potato. It is also preceded by the potato in terms of per capita consumption in the world. In 2008, the cultivation area used for the tomato as equal to 163,539 hectares in Iran and the production of it was equal to 5,887,715 tons with an average production of 117,887 tons in 4352 hectares in the provinces, respectively. Having high production volume and quality, costly hybrid seeds are currently used for the major planting areas of vegetable in Iran. Most of the used transplanted seedlings are 83%. Since the seeds are expensive, the percentage of seedlings and healthy and disease-free seeds should be used for maximized germination and be transferred to the fields of open space. Preparing seedlings in transplanting trays is a technology to respond to this need. Trays are covered with a layer of Peat and Miculite fertilizers. Then, one seed is manually placed in each cell after gauging and preparing a suitable field. However, manually placing seeds is time-consuming and requires hard labor. Sixteen working labors per hour are required for 15 × 7 cell in order to have 10200 seedlings grown in 100 trays. Due to lack of adequate labor, production capacity of greenhouses is reduced, especially in the farming season when finding labor for planting vegetable sprouts is laborious. Therefore, mechanizing tray seeding operations is essential to increase the capacity of the growing industry of greenhouses in Iran. Initially, the tomato seeds were examined in the laboratory. The most important parameters of the study included size, shape, weight, the speed of getting out of the tank and the minimum carrying speed. Then, a vacuum-based single seed picking unit was prepared to investigate the factors influencing the design, so that a single tomato seed can be harvested from the masses. The most important factors considered in the design and construction included: cost, ease of performance, portability, use of local equipment, the planter’s capacity as well as the style of picking single seeds (In Fig.1, the original scheme of the device is presented). The planter consists of several parts operating harmoniously to yield the desired results. These parts include a chassis and conveyor belt mechanism, primary and secondary fertilizer tanks, squashing unit, seed metering device and vibrating reservoir of the seed (The main text of modeling the device with SolidWorks software is shown in Fig.2). This device is designed in such a way that the position of the nozzle, the suction pressure, the height of removing seeds and the vibration frequency of the seeding tray are adjustable. Evaluation of the device was carried out by single seeding of tomato seeds in trays with 105 cells (7 × 15). Suction pressure and nozzle size were calculated for tomato seeds. Scaling distances were considered equal, based on the 30.5-mm intervals of the cells. Single seed picking efficiency of seeds was calculated by the system, as the single percentage of seeding and the total percentage of seeded cells. Seed consumption efficiency is the ratio of the total seeded cells to the total number of existing seeds in the cells. Seeding efficiency also refers to single, dual, and multiple harvested seeds. Furthermore, the device capacity is defined as the number of seeded tray cells per hour. In order to design and build a precise robot planter, an experiment including the designed planter and planting speed of workers in 10 repetitions was designed and implemented to estimate the seeding time and compare with automated and manual planting methods. Seedling trays with four replications were cultivated by the designed robot and the number of cultivated seeds per tray at each stage were correctly counted. After that, the spent planting time by a worker was determined with four replications. The planting rate of tomato seeds is different when comparing mechanized and manual methods. As it is known, the time required for cultivation in the mechanized method is at least one-tenth of the time required for cultivation in the conventional and manual method, which causes the planting rate to increase, and this robot is one of the components of cultivation in the mechanized method in cultivation and production of tomatoes. By assessing planting time using the mechanized method it was revealed that an average of 26.3 seconds is needed to fill a 7 × 15 centimeter tray of tomato seeds with 105 cells. The same planting procedure in the manual method takes an average of 357 seconds which is indicative of the high rate of the designed device. The planter capacity experimented using a seedling tray with the size of 15×7 cells, was calculated to be 17750 cells per hour showing that the suction pressure increases by a reduction in seed size. Thus, while working with small-sized seeds, fluctuations of the suction pressure must be carefully considered to be minimized and the seed being dual was only affected by the opening diameter. Therefore, the opening diameter should become the same in size in order to minimize the dual seed instances. In case of the tomato, the opening diameter had a great influence on the seeds being bulky. Manual planting takes a considerable time in comparison with the mechanized planting. Furthermore, using the designed device in addition to speeding up the planting process, caused regular and accurate cultivation of tomato seeds in order to produce seedlings. The results indicate that utilizing the device over time is highly economical for the major producers of tomatoes, and it is recommended to be used in agro-industry companies, and in the mechanized method of planting in large scales.

In conventional farming, the soil and crop are considered uniform in different locations of the farm and the fertilizers are applied according to the average of soil needs with an additional percentage for safety (Loghavi, 2003). Non-essential chemical fertilizers in the field have harmful effects and social, economic and environmental concerns will increase. Many fertilizers go into the surface waters and ground waters and cause poisoning and environmental pollution without being absorbed by the plants. In variable rate technology, the soil fertilizer needs a map of all parts of the farm which is prepared with the GIS system. This map is uploaded on the computer before variable rate fertilizer machine starts. The computer continually controls the fertilizing rate for each part of the farm using a fertilizing map and global positioning system. The purpose of this study is to construct and evaluate a map-based variable rate fertilizer system that can be installed on a common fertilizer in Iran to be used as a variable rate system. In common variable rate fertilizers, the rotational speed change of the distributor shaft is used to apply fertilizers. In this way, a DC motor is assembled on the main shaft of all distributors, which reduces the fertilizing accuracy. The reason for this is that there is no separation for units along the width of the fertilizer. Therefore, we used one DC motor for each distributor and another motor to rotate the agitator in the tank. System Set up: To design and select a suitable engine, the required torque for the rotation distributor shaft was measured by a torque meter and the amount of 2.1 Nm was acquired for that. With regard to the maximum rate of nitrogen fertilizer for land and tractor speed at the time of fertilizing, the order of 350 kg per hectare and 8 km per hour, the maximum distributor shaft speed and power required to rotate distributor shaft were calculated to be 55 rpm and 6.9 watts, respectively. The selected motor was rated 27.5 watts, 24 volts and 7.5 amperes (Since there were no 6.9 watts motors in the market, a more powerful motor was selected). According to the gear ratio and motor speed, the speed of the distributor shaft was adjustable in the range of 0 to 65 rpm. To determine the speed and position with respect to the direction, a central encoder (E50S8-600-6-L-5 model manufactured by Autonix Korea) was used on the ground wheel. The encoder had 600 pulses per revolution of the axis. Performance evaluation of the system: Performance evaluation of the system consists of two parts; static and moving tests. In static tests, the purpose was the determination of the fertilizer loss (in grams), due to changes in distributor speed as well as the accuracy of the electromechanical control system according to the command values sent to the device. Results of this part were used for the calibration of the device. In motion tests: In motion tests, the assessment of fertilizer loss was due to values set in a given situation and the accuracy of planted fertilizer in place (delay and acceleration) is reviewed. The delay is found by the determination of the distance that the fertilizer was placed after the desired location on the ground and the acceleration is found by the determination of the distance that the fertilizer is placed before the desired location on the ground. The distributor flow rate on F0 valve position was measured for different rotation speeds. The correlation (linear regression) between the planted fertilizer and rotation speed of distributor shaft (rpm) were 0.99 for y=71.636x+75.182. So, it can be deduced that these two parameters have a good linear correlation. The results achieved from diagrams and regression model were used in the programming of the system control unit. Thus, by reading the distributors motor speed, the amount of fertilizer can be calculated and the amount of used fertilizer according to the need of the farm in each part is controlled. The effect of plot length on the amount of fertilizing on 25% need level was not significant, but it was significant on 50% need level. This is due to stopping and starting fertilizer flow during the test, changes in motors speed and error of these on fertilizer output at a certain amount of fertilizing so that at the 25% need level, the error resulting from these factors had less share on the amount of plant fertilizer and the effect of plot length was not significant according to the system default. On the other hand, the effect of forward speed was significant on the 50% need level and insignificant on the 25% need level. In order to calculate the accuracy of the system, the error from the application amount of fertilizer was measured at different fertilizing rates. The correlation between the adjusted fertilizing rate and the measured fertilizing rate was 0.98 with regression model of y=1.0475x which shows the good accuracy of the system.

Grading agricultural products always has a particular important position for submission to domestic and overseas markets. The grading causes more profitable product ranges and customer satisfaction. Grading treatment is carried out based on various parameters such as color, ripeness level, dimensions and weight. Product weight is one of the most effective parameters in grading operation. Egg weight is directly related to the smallness and coarseness of eggs. In egg grading, the largeness value is very important in marketing. This research aimed to design, fabricate and evaluate the egg weighing system based on its dielectric properties. To perform this research, the stages of work are divided into several sections including, design and construction of the hardware section, writing code for the software section to collect data, conducting nondestructive tests and data collection, analysis of obtained data using artificial intelligence, and giving the results of analysis for device calibration of the system as the software code. The large eggs as dielectric substances cause more increase in the capacity of the capacitive sensor. Furthermore, by derivation of a relation between capacity of capacitive sensor and egg weight, one can predict the weight of the sample. A prototype unit of weighing system was designed and fabricated. The designed unit was composed of a chassis, a voltage source, a sinusoidal signal generator, a voltage measurement unit, an AVR micro controller, a COM port, a capacitive sensor, and an LCD and a keyboard. Neural network technique was used for egg weight prediction. The designed net receives 16 voltage values at different frequencies as inputs and its output is the egg weight. In order to calibrate and evaluate the weighing unit, 150 fresh egg samples were provided on egg laying day from a local poultry farm. Experiments were divided into three groups. The experiments were carried out on egg-laying day, and the second and fourth day after laying. In this study, two networks were built and evaluated. In the first series, two-layer networks and in the second series, three-layer networks were developed. In the two-layer neural networks, the number of neurons in the hidden layer was changed from 2 to 10.According to the given results for two-layer networks, two layer networks with 10 neurons offer the best results (the highest R-value and minimum RMSE) and it can be chosen as the most effective two-layer network. Three-layer neural networks have been composed of two hidden layers. The number of neurons in the first hidden layer was 10 and in the second layer it was changed from 1 to 20. Between three-layer networks, the network with 7 neurons with the highest R-value and the lowest error is the most appropriate network. It is even more efficient than the two-layer network with 10 neurons. So, the most appropriate structure is 1-7-10-16 and it has been selected for calibration of the weighing device. To evaluate and assess the accuracy of the weighing machine, weights of 24 samples of fresh eggs were predicted and compared with the actual values obtained using a digital scale with the accuracy of 0.01 gr. The paired t-test has been used to compare the measured and predicted values and the Bland-Altman method has been used for charting the accordance between the measured and predicted values. Based on the findings, the difference between the measured and predicted values was observed up to 5.4 gr that is related to a very large sample. The mean absolute error is equal to 2.21 gr and the mean absolute percentage error is equal to 3.75 %. According to the findings, 95% of the actual and approximate matching range to compare the two weighing methods is between -5.3 gr and 3.36 gr. Thus, the dielectric technique may underestimate the egg weight up to 5.3 gr or it may overestimate it up to 3.36 gr more than the actual prediction. The best results were obtained with a 3 layers net having 10 and 7 neurons, respectively in the first and the second hidden layers with the highest R-value, 0.983 and the lowest error, 0.502. Therefore, this net was applied for egg weight prediction. To evaluate the device, the weights of 24 fresh eggs were estimated using the device and were compared with actual values and the maximum error was observed to be equal to 5.4 gr.

Barley is one of the most important grains with high digestible starch making it a main source of energy in human nutrition as well as in livestock rations formulation and feeding. Starch is the main part of barley grain and it has an inverse relation with its protein. It has a digestible foodstuff of 80 to 84 percent of its dry matter content. Barley as livestock foodstuff should be processed and it is done in several ways. A customary method for processing barley in dairy farms is its size reduction by milling (Hunt, 1996). An alternative method of barley processing is steam rolling. However, because of the high cost of steam generators a method of soaking with heating has been considered as an alternative method for steam rolling (Yang et al., 2000). The rate of moisture absorption by grains during the soaking process varies considerably and depends on the size of the grain, water temperature and the length of soaking. High temperature water soaking is an ordinary way to reduce the time duration for reaching a high rate of moisture absorption during the soaking process (Kashaninejad et al., 2009). Various studies have shown that these models have adequate accuracy in analyzing drying and moisture absorption processes for most agricultural products (Abu-Ghannam and McKenna, 1997). Some researchers have modeled beans moisture absorption behavior using 14 mathematical models and found that the Weibull model had the most conformity with variations in experimental data (Shafaei and Masoumi, 2014c). Observations made by researchers indicate that the moisture absorption process in various materials encompasses a primary phase with a fast rate and a second phase with a lower rate. The second phase in moisture absorption is called the relaxation phase. The main problem with all the mathematical and experimental models is the lack of the model’s ability to evaluate the rate of moisture absorption in the secondary phase. Artificial Neural Network (ANN) as an important artificial intelligent method comparable to human brain capabilities is applied to train and store data in the form of weighted networks (Dayhoff, 1990). This method has superiority to many ordinary statistical and model making methods. In comparison to linear regression models, ANN does not require placing estimated values around mean values and for this reason it retains actual variations in the data being analyzed. Prediction by using trained ANN enables the researchers to decrease or increase input and output variables.Therefore, it is possible to produce a multivariate model with an output even more than the objectives deemed necessary (Heristev, 1998). The goal of this research was to predict instant moisture content of three barley varieties (Reyhan3, Fajr and MB862) during the soaking process under three temperature levels (10, 20 and 45 ◦C) using two conventional ANN methods of multilayer perceptron (MLP) and radial basis function (RBF) in comparison with viscoelastic mathematical model and reporting the results. Barley varieties were collected from the Isfahan Province Agriculture Organization grain depository and were cleaned and the debris were separated before the experiments. The selected grains were sorted to three groups of small, medium and large grains sizes. To exclude the effect of grain size during moisture absorption, the medium size grains were used. The moisture content of the grains was determined based on the ASAE S352.2 DEC97 (ASAE, 1999) which were %8.23, %8.62 and %8.89 on a dry basis for Reyhan3, Fajr and MB862, respectively with no significant difference at %5 probability level (p>0.05). Experiments were conducted under three temperatures (10, 20 and 45 ◦C) in the refrigerator, at room temperature and in the oven, respectively for each variety. In each experiment, 10 medium size grains were selected randomly and weighed with an AND laboratory scale model Gf-400 (made in Japan) and placed in foam containers having 200 mg of distilled water. Grains were weighed after a predetermined period of elapsed time (5, 10, 15, 30, 60, 120, etc. minutes). The experiments were conducted with three replications and moisture absorption rates were determined by the equations presented by McWatters et al., 2002. The experiments were conducted on a time table based on which the time for the dissolving of grains was reached. In this case, the moisture content of the grains reaches the saturation point. According to equations presented by Peleg, as water density increases as much as 0.01 gram due to grains dissolving in water, the saturation point has been reached (Peleg, 1988). For this reason, distilled water density was measured and controlled before and after each experiment by a pycnometer. Neural network was designed according to the two methods of multi-layer perceptron (MLP) and radial basis function (RBF) with three neuron layers. The first layer, i.e. input layer, is independent variables of temperature and time.The second layer, i.e. hidden layers, is the networks hidden layer and the third layer, i.e. output layer, is the dependent variable of moisture content which was selected. In each case, the nonlinear reduced gradient, combined gradient and BFGS algorithm, and Trigonometric, Logarithmic, Gaussian, and Logical functions were used to train, test and evaluate the network. To evaluate the predicting viscoelastic model and the network, we used statistical indices maximum value of coefficient of determination (R2) and minimum value of mean square error (RMSE). Moisture absorption curves showed that as the temperature increases, moisture absorption rate increases as well. Higher equilibrium moisture levels are obtained in water with higher temperatures. This phenomenon is the result of increased moisture diffusion in grains due to higher temperature levels. Higher water temperatures causes grain internal material which is mainly starch to gelatinize and, thus, the internal tissues resistance to moisture absorption reduces (Ranjbari et al., 2011). The moisture absorption rate increases as immersion temperature and gelatinization temperature reach closer to each other. The results of this study showed that although viscoelastic mathematical model has an adequate accuracy for instant prediction of barley grain moisture content, it has a lower accuracy compared to intelligent models. On the other hand, among the two neural network methods, MLP method has a higher accuracy in predicting moisture content compared to RBF method. MLP obtained the best results for three varieties of barley because of back- propagation learning algorithm with BFGS algorithm and 2-4-1 network structure. According to the prediction of the best neural network which was selected, three-dimensional graphs of moisture content based on temperature and time variables, showed that with an increase in temperature and duration of immersion, moisture absorption increases for three varieties of barley.

Pistachio nut is one of the most delicious and nutritious nuts in the world and it is being used as a salted and roasted product or as an ingredient in snacks, ice cream, desserts, etc. (Maghsudi, 2010; Kashaninejad et al. 2006). Roasting is one of the most important food processes which provides useful attributes to the product. One of the objectives of nut roasting is to alter and significantly enhance the flavor, texture, color and appearance of the product (Ozdemir, 2001). In recent years, spectral imaging techniques (i.e. hyperspectral and multispectral imaging) have emerged as powerful tools for safequality inspection of various agricultural commodities (Gowen et al., 2007). The objectives of this study were to apply reflectance hyperspectral imaging for non-destructive determination of moisture content and hardness of pistachio kernels roasted in different conditions.

Dried O’hadi pistachio nuts were supplied from a local market in Mashhad. Pistachio nuts were soaked in 5L of 20% salt solution for 20min (Goktas Seyhan, 2003). For roasting process, three temperatures (90, 120 and 150°C), three times (20, 35 and 50 min) and three air velocities (0.5, 1.5 and 2.5 m s-1) were applied. The moisture content of pistachio kernels was measured in triplicate using oven drying (3 gr samples at 105 °C for 12 hours). Uniaxial compression test by a 35mm diameter plastic cylinder, was made on the pistachio kernels, which were mounted on a platform. Samples were compressed at a depth of 2mm and speed of 30 mm min-1. A hyperspectral imaging system in the Vis-NIR range (400-1000 nm) was employed. The spectral pre-processing techniques: first derivative and second derivative, median filter, Savitzkye-Golay, wavelet, multiplicative scatter correction (MSC) and standard normal variate transformation (SNV) were used. To make models at PLSR and ANN methods, ParLeS software and Matlab R2009a were used, respectively. The coefficient of determination (R2), the root mean square error of prediction (RMSEP) and the ratio of the standard deviation of the response variable to RMSEP (known as relative performance determinant (RPD)) were calculated.

Interpretation of hyperspectral data: The results showed that the spectra of the shell, the whole kernel and the internal part of the kernel have different patterns. The internal part of thekernel had 2 peaks at 630 nm and 690 nm, while the shell and the whole kernel had 1 peak at 670 nm and 720 nm, respectively and the peak of the whole kernel was sharper than that of the shell. The highest and lowest intensities were for the internal part of the kernel and the whole kernel, respectively. The spectral slope of the internal part is higher than that of the shell and the whole kernel at 500-700 nm. The effect of different pre-processing techniques and analysis on prediction of pistachio kernels properties: In the absence of pre-processing techniques, low correlation coefficients were observed for prediction of moisture content and hardness. However, with the use of pre-processing techniques, in some models, correlation coefficient and RPD increased and the RMSEP decreased. The results revealed that ANN models would predict moisture content and textural characteristics of roasted pistachio kernels better than PLSR models. Moisture content: ANN models can predict moisture content of roasted pistachio kernels better than PLSR models. In total, PLSR models showed low RPD and R2. For all samples, RPD was lower than 1.5, indicating that the developed models do not give an accurate prediction for moisture content. The best results with ANN method were achieved using a combination of SNV, wavelet and D1 for predicting moisture content with R2 =0.907 and RMSEP=0.179. Hardness: The results indicated that ANN models can predict the hardness better than PLSR models. The best results with PLSR models were achieved using a combination of SNV, wavelet and D1 with R2= 0.643, RMSEP=10.78, RDP= 1.48 and 2 PLSR factors. However, due to high RMSEP and low R2 and RPD, it can be mentioned that prediction of hardness values with ANN model was not sufficiently desirable. However it was better than the PLSR models. The best results with ANN models were achieved using a combination of SNV, wavelet and D2 with R2=0.876 and RMSEP=5.216.

The results of this study showed that employing pre-processing methods causesa decrease in prediction error and improves the quality of the models. ANN models could predict moisture content and hardness of roasted pistachio kernels better than the PLSR models.

Fast and accurate determination of geometrical properties of agricultural products has many applications in agricultural operations like planting, cultivating, harvesting and post-harvesting. Calculations related to storing, shipping and storage-coating materials as well as peeling time and surface-microbial concentrations are some applications of estimating product volume and surface area. Sphericity is also a parameter by which the shape differences between fruits, vegetables, grains and seeds can be quantified. This parameter is important in grading systems and inspecting rolling capability of agricultural products. Bayram presented a new dimensional method and equation to calculate the sphericity of certain shapesand some granular food materials (Bayram, 2005). Kumar and Mathew proposed atheoretically soundmethod for estimating the surface area of ellipsoidal food materials (Kumar and Mathew, 2003). Clayton et al. used non-linear regression models for calculation of apple surface area using the fruit mass or volume (Clayton et al., 1995). Humeida and Hobani predicted surface area and volume of pomegranates based on the weight and geometrical diametermean (Humeida and Hobani, 1993). Wang and Nguang designeda low cost sensor system to automatically compute the volume and surface area of axi-symmetricagricultural products such as eggs, lemons, limes and tamarillos (Wang and Nguang, 2007). The main objective of this study was to investigate the potential of Artificial Neural Network (ANN) technique as an alternative method to predict the volume, surface area and sphericity of pomegranates. The water displacement method (WDM) was used for measuring the actual volume of pomegranates. Also, the sphericity and surface area are computed by using analytical methods. In this study, the neural MLP models were designed based upon the three nominal diameters of pomegranatesas variable inputs, while the output model consisted of each of the three parameters including the volume, sphericity and surface area. Priorto any ANN training process, the data normalized over the range of [0, 1]. Fig. 1 shows a MLP with one hidden layer. In this study, back-propagation with declininglearning-rate factor (BDLRF) training algorithm was employed. The mean absolute percentage error (MAPE) and the coefficient of determinationof the linear regression line between the predicted values fromthe MLP model and the actual output were used to evaluate the performance of the model. The number of neurons in the hidden layerand also theoptimal values for the learning parameters η and αwere selected bytrial and error method. The bestresult was achieved with five neurons in the hidden layer. The results showed thatthe optimum modelof performance was obtained at constant momentum termequal to 0.8 and learning rate equal to 0.9. In this study, 300 epochs were selected as the starting points of the BDLRF. Some statistical characteristics of the actual values of volume were estimated by WDM, surface area was computed by equation (3) and sphericity of pomegranates was computed by equation (1) and the predicted values of them using the neural network method were shown in Table 1. The obtained results verified that the differences between theactual values and the estimated ones can be ignored. But, the predicted values of the volume using the MLP model in comparison with equation (2) are much closer to the actual values. Statistical comparisons of desired and predicted data and the corresponding p values are given in Table 2. The results showed that P-value was greater than 0.08 in all cases. Therefore, there was no significant difference between the statistical parameters. However, the P-value for equation 2 is much less than that of the MLP model. The results shown in Figures 2, 3 and 4 show that the coefficients of determination between actual and predicted data were greater than 0.9. Considering all the results in our study, the MLP model is more accurate than the WDM and analytical methods. In this paper, we first measure the actual volume of the pomegranate using WDM and equation (2). Also, assuming an elliptical fruit, the sphericity and surface area are computed analytically based on the three nominal diameters of a pomegranate. Finally, the results of achievements of the MLP designed revealed that the MLP model could be successfully applied to the prediction of thesphericity and surface area. Therefore, the MLP model can be a viable alternative to the analytical methods. However, this is possible only if there is a precise way to compute the three nominal diameters of pomegranates. In addition, according to the MAPE, the accuracy of the MLP model in prediction of volume of pomegranates was twicethe analytical method.

Apple is one of the most important horticultural crops of Iran. Its production in the country stands in the second place after citrus. Iran holds the fourth place in the world production of apples and gains a major share in the export of this product. Therefore, it is necessary to enhance the quantity and quality of the fruit in order to maintain and promote its position among the countries importing this product from Iran. Most of the mechanical damages to fruits and vegetables occur due to contact stresses under static, quasi-static and impact loading. To obtain stress distribution inside the fruit we can use finite element analysis. The aim of this study was to simulate the behavior of the apple as a viscoelastic body subjected to quasi-static loading and also to determine the failure criteria (maximum normal stress or shear stress) of apple flesh to estimate its susceptibility to mechanical bruising. In this study, Golab kohanz apple was used. Two samples were removed from each apple using a core sampler, one was used for uniaxial compression and the other was used for confined compression test using Instron universal tension and compression machine. Spherical indenter and parallel plate tests were performed in order to study apple susceptibility to bruising at four deformation levels (1, 2, 3 and 4 mm) and the bruise volume was then measured after 24 hours. Stress-strain curves were plotted and then, the elastic and viscoelastic properties were obtained. Then, by using the data obtained from apple properties, the apple was modeled in Abaqus software as spherical and cylindrical shapes with viscoelastic behavior subjected to quasi-static loadings. The normal stress distribution of the modeled apple in the shape of a cylindrical sample is shown in Fig. 4. The value of maximum normal stress was obtained (0.51 MPa) at the contact point of the loading plate with the sample. Experimental and modeled stress-strain curves are shown in Fig. 5. Up to the bio-yield point, the two curves are nearly matched; and beyond that point, there are some overestimations in the predicted stress values. The location and pattern of failure have often been used to explain the cause of failure in fruits. When specimens of fruit are subjected to a uniaxial compression, the failure often occurs the maximum shear stress plane. Failure patterns in the tested samples indicate that the failure occurs due to shear stresses. Another explanation that has been used by researchers for shear failure is the bruising position inside the fruit after loading. The position of bruising in most of the tested apples was a distance away from the apple surface (Fig. 7). According to the experiments results at the three deformation levels of 2, 3, and 4 mm, the maximum generated normal stress inside the apple was above the point of failure of the cylindrical samples. Based on the empirical results, the bruising was almost zero for the apples subjected to one or two mm deformation (Fig. 9a). The experimental value of the shear strength of the Golab kahanz apple was obtained to be 0.23 MPa. The maximum shear stress inside the modeled apple due to the two mm deformation was 0.195 MPa, which was lower than the shear strength of the apple. On the other hand, by applying three and four mm of deformation, the maximum shear stresses were obtained to be 0.24 and 0.26 MPa, respectively, indicating that the induced stress exceeded the shear strength of apple flesh; therefore, the bruising was observed in the flesh of these apples. The location of the maximum shear stress corresponds to the location of bruising in the tested samples as shown in Fig. 9b. According to the obtained results from the modeling in the finite element software, we can use this software in order to recognize and investigate the damages in agricultural products during different loading conditions (Harvesting, transportation, packaging and storage). In this work, Golab apple was considered as a viscoelastic material and its behavior under quasistatic loading was modeled using finite element method. Elastic, viscoelastic properties and shear strength of apple flesh were obtained and used in the simulation. Comparison of modeling and experimental results shows that the model simulates the behavior of apples during quasistatic loading well. The location of bruise occurrence in the flesh of tested apple and the location of maximum shear stress in the simulated apple was the same. Therefore, the maximum shear stress criterion can be used to estimate the susceptibility of apple varieties to internal bruising under quasistatic loading. Modeling of apple as a viscoelastic sphere in Abaqus software assuming constant bulk modulus could properly simulate apple behavior under quasistatic loading.

Tractors are considered as the main power generators in mechanized agriculture. Hence, the experts and engineers in tractor manufacturing of the country, are required to focus on developing and designing new features in tractor manufacturing. This must be, of course, paralleled with the economic aspects. Achieving this goal, Iran Tractor Manufactories Co., (ITMCO) has designed and developed tractors equipped with turbochargers. This has been performed on ITM800 & ITM485 models, according to world standards. The turbocharger system, with harnessing of lost energy in engine output fumes, compresses the air entering the engine and more air enters the cylinder. This will cause the engine to burn fuel more efficiently and thus produce more power.

This study has been carried out on ITM485 & ITM800 tractors (with turbocharger system) and ITM285 & ITM475 tractors (without turbocharger system) to assure the improvement of engine performance and compare them employing OECD world standards. Experiments were performed in the concrete runway of Tabriz Tractor Manufacturing Company. For experiments, a dynamometer was used to measure the traction force between two tractors, a measuring unit for fuel, a thermometer unit and a timer to measure the quantities of fuel consumption, drawbar force and power. For drawbar traction test, each of the tested tractors pulled the rear tractor in different gears and the dynamometer between these 2 tractors recorded the tractors traction force by data loggers. To measure tractors fuel consumption, a measuring unit of fuel (VDO - EDM 1404) was used that calculated the flow rate in the path of fuel from the fuel tank to the engine and the return path from the engine to the fuel tank and showed the quantity of fuel consumption in liters per hour digitally.

In comparison of traction power and force of tractors with turbochargers and without turbochargers in different gears, the results of variance analysis showed that the effect of tractor was significant. Traction power and force at tractors with turbochargers ITM485 and ITM800 and without turbocharger ITM475 have a significant difference in the level of one percent. Tukey post hoc test results also indicate that traction power and force in tractors with turbochargers ITM485 and ITM800 are significantly more than the tractor without turbocharger ITM475. The gear effect is also significant. Traction power and force in different gears have significant difference at the probability of one percent. Tukey post hoc test results indicate that power quantity is highest in the gears: (1+H, 2*H, 1*H, 3+L) and minimum in the gears: (1*L, 1+L, 2*L), (* Turtle and + Rabbit). But Tukey post hoc test results indicate that traction force quantity is highest in the gears: (1*L, 2*L, 1+L) and minimum in the gears: (2*H, 1+H). In the comparison of specific fuel consumption of tractors with turbochargers and without turbochargers in different gears, the results of variance analysis showed that the effect of tractor was significant. The amount of specific fuel consumption at tractors with turbochargers ITM485 and ITM800 and without turbocharger ITM475 has a significant difference in the level of one percent. Tukey post hoc test results also indicate that specific fuel consumption quantity in tractors with turbochargers ITM485 and ITM800 in the level of one percent is significantly less than the tractor without turbocharger ITM475. The gear effect is also significant. The specific fuel consumption quantity in different gears has significant difference at the probability of one percent. Tukey post hoc test results indicate that specific fuel consumption quantity is highest in the gears: (1*L, 1+L, 2*L) and minimum in the gears: (1+H, 2*H, 1*H).

The tests were performed on tractor drawbar traction. Results of variance analysis in this experiment on a concrete surface, indicated that the calculated traction power and force of ITM485 and ITM800 tractors (with turbocharger system) were higher than the ITM475 & ITM285 tractors (without turbocharger) and this difference was significant at the one percent level of probability. Meanwhile specific fuel consumption in the ITM485 and ITM800 tractors (with turbocharger system) was lower than that of the ITM475 & ITM285 tractors (without turbocharger) and this difference was significant at the one percent level of probability. This will lead to significant savings in fuel consumption.

In recent years, production techniques and equipment have been developed for conservation tillage systems that have been adopted by many farmers. With proper management, overall yield averages for conventional and reduced tillage systems are nearly identical. Sometimes, field operations can be combined by connecting two or more implements. Much research has focused on either reducing or eliminating tillage operations to develop sustainable crop production methods. The greatest costs in farm operations are associated with tillage due to greater specific energy requirement in tillage and the high fuel costs. Combined operations reduce both fuel consumption and time and labor requirements by eliminating at least one individual trip over the field. Light tillage, spraying, or fertilizing operations can be combined with eitherprimary or secondary tillage or planting operations. The amount of fuel saved depends on the combined operations. Generally, light tillage, spraying, and fertilizing operations consume between 0.25 and 0.50 gallons of diesel fuel per acre. Fuel savings of 0.12 to 0.33 gallons per acre can usually be expected from combining operations. Eliminating one primary tillage operation and combining one light tillage, spraying, or fertilizing operation with another tillage or planting operation can usually save at least a gallon of diesel fuel per acre. Combining operations has the added benefit of reducing wheel traffic and compaction. To improve the tillage energy efficiency, implementing effective and agronomic strategies should be improved. Different tillage systems should be tested to determine the most energy efficient ones. Tillage helps seed growth and germination through providing appropriate conditions for soil to absorb sufficient temperature and humidity. Tillage is a time consuming and expensive procedure. With the application of agricultural operations, we can save considerable amounts of fuel, time and energyconsumption. Mankind has been tilling agricultural soils for thousands of years to loosen them, to improve their tilth for water use and plant growth and to cover pests. Tillage is a process of creating a desired final soil condition for seeds from some undesirable initial soil conditions through manipulation of soil with the purpose of increasing crop yield.The aim of conservation tillage is to improve soil structure. Considering the advantages of conservation tillage and less scientific research works on imported conservation tillage devices and those which are made inside the country, and considering the importance of tillage depth and speed in different tiller performance, this investigation was carried out. This investigation was carried out based on random blocks in the form of split plot experimental design. The main factor, tillage depth, (was 10 and 20cm at both levels) and the second factor istillage forward speed, (was 6, 8, 10, 12 km h-1 in four levels for Bostan-Abad and 8, 10, 12, 14 km h-1 for Hashtrood) with 4 repetitions. It was carried out by using complex tillager made in the Sazeh Keshte Bukan Company, which is mostly used in Eastern Azerbaijan and using Massey Ferguson 285 and 399tractors and its fuel consumptionwas studied. In this study, the effect of both factors on the feature of fuel consumption was examined. Regarding tillage speed effect for studies characteristic in Bostan-Abad at 1% probability level fuel consumption was effective. The effect of tillage depth has significance at 5% probability level on fuel consumption. The interaction effect of tillage speed and depth on fuel consumption was significant at probability level of 1%. In Hashtrood, the effect of tillage speed was significant on fuel consumption at probability level of 1%, and also tillage depth effect was significant on fuel consumption amount at probability of 1%. The interaction effect of tillage speed and depth on fuel consumption was significant at 1% level of probability. In this study, the effect of both factors on fuel consumptionwas examined. In Bostan-Abad and Hashtroud on the whole, the results indicated that with the increase in the speed of tillage, fuel consumption, was reduced per hectar.The speed of 10 kilometers per hour was the best for this implemented work. Also, with an increasing depth of tillage, the fuel consumption increased.Through an increase in tillage speed, fuel consumption mass reduced at unit level. Moreover, the optimum speed was concluded to be 10km per hour. The best tillage depth using this machine is 10cm.

Today, all kinds of vehicle engines work with fossil fuels. The limited fossil fuel resources and the negative effects of their consumption on the environment have led researchers to focus on clean, renewable and sustainable energy systems. In all of the fuels being considered as an alternativefor gasoline, methanol is one of the more promising ones and it has experienced major research and development. Methanol can be obtained from many sources, both fossil and renewable; these include coal, natural gas, food industry and municipal waste, wood and agricultural waste. In this study, the effect of using methanol–unleaded gasoline blends on engine performance characteristics has been experimentally investigated. The main objective of the study was to determine engine performance parameters using unleaded gasoline and methanol-unleaded gasoline blends at various engine speeds and loads, and finally achieving an optimal blend of unleaded gasoline and methanol. The experimental apparatus consists of an engine test bed with a hydraulic dynamometer which is coupled with a four cylinder, four-stroke, spark ignition engine that is equipped with the carbureted fuel system. The engine has a cylinder bore of 81.5 mm, a stroke of 82.5 mm, and a compression ratio of 7.5:1 with maximum power output of 41.8 kW. The engine speed was monitored continuously by a tachometer, and the engine torque was measured with a hydraulic dynamometer. Fuel consumption was measured by using a calibrated burette (50cc) and a stopwatch with an accuracy of 0.01s. In all tests, the cooling water temperature was kept at 82±3˚C. The test room temperature was kept at 29±3˚C during performing the tests. The experiments were performed with three replications. The factors in the experiments were four methanol- unleaded gasoline blends (M0, M10, M20 and M30) and six engine speeds (2000, 2500. 3000, 3500, 4000 and 4500 rpm). Methanol with a purity of 99.9% was used in the blends. All experiments were performed at 50% open throttle. Engine performance characteristics for fuel blends were compared with unleaded gasoline. The experimental results showed that adding methanol to unleaded gasoline increased brake torque and brake power in the M10 and decreased in the M30 compared to merely usingpure gasoline. Engine behavior when using M20 blend was similar to that of using pure gasoline (M0). The brake power and torque at engine speeds 2500, 3000, 3500 and 4000 rpm for M10 were increased by 5.42%, 7.76%, 14.89% and 16.78% compared to when these parameter relate to pure gasoline (M0), respectively, whereas the brake power and brake torque for M30 blend at engine speeds 2000, 2500, 3000, 3500, 4000 and 4500 rpm compared to when using pure gasoline was decreased by 6.91%, 8.1%, 6.23%, 5.29%, 4.59% and 14.27%, respectively. The experimental results showed that brake specific fuel consumption for M30 blend was increased at all engine speeds. The increase in specific fuel consumption values for this blend from 2000 - 4500 rpm were 17.78%, 16.38%, 13.06%, 10.99%, 14% and 19.11%, respectively. Also, the specific fuel consumption for the M20 was similar to the specific fuel consumption of pure gasoline. Comparing the brake specific fuel consumption of M10 to M0 fuel at 2500, 3000, 3500, 4000 and 4500 rpm this parameter was decreased by 1.9%, 6.03%, 8.91%, 13.85% and 5.55%, respectively. As the methanol content in the fuel blends increases, brake thermal efficiency also increases at all engine speeds and in all used fuels blends. The thermal efficiency at 2000, 2500, 3000, 3500, 4000 and 4500 rpm using M10 was increased by 3.73%, 8.12%, 12.43%, 15.57%, 22.34% and 12.01%, respectively in comparison to pure gasoline. These values for M20 were 4.14%, 7.82%, 10.12%, 13.37%, 18.94% and 13%, and for M30 were 2.69%, 3.89%, 6.35%, 8.01%, 5.12% and 0.78%. From the results of the study, the following conclusions can be deduced: 1- Using methanol as a fuel additive to unleaded gasoline causes an improvement in engine performance. 2- The largest increment in engine torque and brake power compared with M0 showed about 16.78% with M10 at 4000 rpm. 3- Minimum brake specific fuel consumption was obtained at 4000rpm with M10 fuel. 4- Thermal efficiency increased compared to the pure gasoline usage at all engine speeds and in all used fuel blends. The largest increment in brake thermal efficiency compared with M0 showed 22.34% with M20 at 4000 rpm. 5- The 10 vol. % methanol in fuel blend gave the best results for all measured parameters at all engine speeds.

Tire tractive parameters of the driving wheel are of the most substantial factors for the evaluation of the performance of agricultural tractors. Great tractive efficiency has called the attention of vehicle designers to attain economic efficiency owing to the minimization of fuel consumption. At terrain-tire interface, some soil physical-mechanical changes occur that lead to unwanted soil compaction. Of the influential parameters for the creation of soil compaction is the soil stresses formed owing to the wheeled vehicle trafficking. While the increase of tractive efficiency is desired, minimization of soil stresses should also be considered with the same importance to make a trade-off between the aforementioned parameters. There are numerous studies documented in the literature that deal with the measurement of soil stress/strain data due to the wheeled vehicle trafficking and also those works that address the correlation between the soil stress and soil compaction. It is recognized that in order to reduce soil compaction both at topsoil and subsoil levels, the soil stress at the soil-tire interface should be reduced. There are various parameters that affect the tractive efficiency and the soil stress creation such as wheel load, slip, tire inflation pressure, velocity, etc. On the other hand, the wheel is subjected to the torques and forces exerted to the vehicle and the vehicle dynamics are significantly affected by the soil-wheel interactions. Survey of the literature shows that numerous studies have focused on the evaluation of tractive efficiency both in field test and controlled conditions in laboratories with the intention of increasing tractive efficiency. The studies dedicated to the soil mechanical strength are more engaged with the approaches to minimize the soil stress propagation. The present study considers both factors and considers the most influential tire parameters such as wheel, velocity and slip to assess the relationship between traction and the soil vertical stress in a soil profile using a single-wheel tester and a soil bin facility. The soil bin in Department of Mechanical Engineering of Urmia University was used in this study. This soil bin is featured 24 m in length, 2 m in width and 1 m in depth including a single-wheel tester and the carriage. A chain system was used for the power transmission from the electromotor to the carriage. The carriage was able to move alongside the soil bin through four ball bearings which also hold the weight of the carriage. The utilized tire in the study was a 220/65R21 driving wheel. One load cell was situated vertically to measure the wheel load and four S-shaped load cells were horizontally situated between the single-wheel tester and the carriage to measure the traction force. An electric motor was used to empower the carriage while another electric motor was used to empower the wheel tester. The difference between the linear velocities of the carriage and the wheel-tester provided the desired levels of slip. A housing including four load cells situated at the distances of 12.5 cm was used to measure the soil vertical stress transmission in the soil profile. The system was buried at the desired depth in the path of wheel traversal. Under the aforesaid treatments, the experiments were undertaken with the purpose of simultaneous measurement of soil stress propagation and traction force and finally the correlation between these parameters. The results were analyzed using the statistical analysis at 1% significance level. The results showed that an increase in traction force leads to an increment of vertical soil stress. It was also recognized that the reduction in the velocity leads to the increase in soil stress which is due to the greater contact duration between the soil and the tire. Also, an increase in wheel load results in an increase of soil stress which has a linear correlation with the traction force. Furthermore, it was deduced that the increase in depth leads to a reduction of soil vertical stresses. The present study is aimed at investigating the effect of net traction force on the imposed vertical stress under the 220/65R21 driving wheel. Hence, velocity at three levels (i.e. 0.8, 1, 1.2 m s-1), wheel load at three levels (i.e. 2, 3, and 4 kN) and slippage at three levels (i.e. 8, 12, and 15%) were considered to obtain traction force and soil vertical stress at three depths of 0.1, 0.15 and 0.2 m. Experiments were carried out in the complete randomized block design with three replicates on clay loam soil at 12% moisture content. The vertical stress was measured using a manufactured soil stress transducer where the net traction was measured using four horizontally installed load cells between the tester rig and the carriage. A correlation was developed between soil stress and traction force. The results revealed that vertical stress increases with respect to increase of wheel load and slippage, whereas vertical stress decreases by increase in depth and velocity. Additionally, it was found that wheel load and slippage bring about increased traction force while velocity has no significant effect on traction force at 1% significance level. Finally, it was deduced that an increase of traction force results in an increase of vertical stress transmission.

Mulch tillage system is an intermediate system which covers some of disadvantages of no tillage and conventional tillage systems. In farms in which tillage is done with a chisel plow, runoff and soil erosion have a less important relation to moldboard and disk plow and naturally absorption of rainfall will be developed. Thus, the mulch tillage system is an appropriate alternative to conventional tillage and no tillage (Backingham and Pauli, 1993). The unwanted vibration in machinery and industry mainly processes most harmful factors, for example: bearing wear, cracking and loosening joints. And noise is produced in electrical systems by creating a short circuit (Wok, 2011). Self-induced and induced vibration are used in tillage systems. Induced vibration is created by energy consumption and self-induced vibration is created by collision among the blades and soil at the shank (Soeharsono and Setiawan, 2010). A study by Mohammadi-gol et al. (2005) was conducted. It was found that on the disk plow, plant residues maintained on the soil are more than that of moldboard plow. 99% frequency and amplitude, speed and rack angle of blade directly affect soil inversion and indirectly affect preservation of crop residue on the soil. The effect of vibration frequency and rack angle of blade to reduce the tensile strength is also clear. Moreover, in contrast to previous studies when speed progressing is less than (λ), not only the relative speed (λ), but also frequency can reduce the tensile strength (Beiranvand and Shahgoli, 2010; Awad-Allah et al., 2009). Therefore, aim of this study was to determine the effect of vibration and the speed of tillage on soil parameters and drawbar power in using electric power. To perform this test, three different modes of vibration (fixed, variable and induced vibration) and two levels of speed in real terms at a depth of 20 cm were used for farming. The test was performed with a split plot and randomized complete block design and three replications, and the fixed factors were: the depth of tillage: 20 cm, soil moisture: 16 to 17 percent and rack angle: 15 degrees; and the variable factors were the rate of progress in both 4.5 and 7.5 kilometers per hour and six levels of frequency, 1 fixed (zero) 2 variables (self-induced), 3 (positive19) and 4 (negative19), 5 (positive37) and 6 (negative37) Hz were performed. An electric generator was used to create vibration power. The equation (1) was used to calculate the vibration power: (1) Where P: Electric power (W), V: voltage (V), I: current (amps) and Ǿ: phase angle (degrees) between the voltage and current. After the calculation, the required power of 19 Hz was calculated to be 0.6, and the required power of 37Hz, was calculated to be 0.75 kilowatts, respectively. The sample of mean weighted diameter, after tillage in each plot, was about 10 kg soil (0 to 20 cm depth) with 3 replicates and through the equation (2), mean weight diameter was calculated as follows: (2) Where MWD: Mean weight diameter (cm), Xi: Two Elk consecutive mean diameters (cm) and Wi: weight ratio of the soil remaining on the sieve to the total weight of the sample. In order to calculate the specific energy tension due to the width of tillage (28 Cm), equation (3) was used. (3) Where E: tensile special energy in kilojoules per square meter, P1: drawbar pulling power required in kW, P2: the vibration according to equation (1) based on kilowatt, T: tillage time in one square meter per second. According to analysis of variance (Table 2) interaction effects of frequency and speed to keep the residue are significant at 1%, and this situation was shown well in Fig.2 Therefore, in practice, with increasing frequency in both induction and self-induction vibration, the tillage blades created a groove at the soil surface with less turmoil, and this would maintain the maximum residue on the surface of the soil. As is clear from Fig.3, treatment of the frequency of 37+ (code 5) in both the first and second average forward speed is highest in remaining residue with 85% and 74%, respectively (Liu and Chen, 2010) and (Awad-Allah et al., 2009). By applying induced vibrations, a significant reduction in tensile strength occurs, because it reduces the time to deal with the blade of soil tillage and soil fractures with blows of the blade. It is clear that vibration reduces slip and real wheel speed is progressing, and following it, the increase in tensile strength occurs and it should not be considered due to the in efficiency of vibration tillage, since vibration may increase the depth of tillage, with the same vertical force component (Sahaya et al., 2009). Specific energy (plus drawbar and vibration) are shown in Figure.5 and the lowest energy consumption in both the first and the second speeds was on treatment of frequency +19, being 18.9 kJ m and 23.2 kJ m to first and second speeds, respectively. In general, both factors (vibration and speed) affected tillage parameters and energy consumption and induced vibration caused by the system of unequal mass and electrical power properties was very easy to change phase vibration and transfer of power. This study was designed because of the significant effects on the important parameters of quality by vibration frequency of tillage and different frequencies to control the way in which tillage parameters are controlled. We can take it as a precision tillage that introduced variable control rate of percent residue on the soil, clod mean weight diameter that is suitable for the cultivation combined with reduced energy consumption.

In recent years, production techniques and equipment have been developed for conservation of tillage systems that have been adopted by many farmers. With proper management, overall yield averages for conventional and reduced tillage systems are nearly identical. Sometimes, field operations can be combined by connecting two or more implements. Combined operations reduce both fuel consumption, and time and labor requirements by eliminating at least one individual trip over the field. Light tillage, spraying, or fertilizing operations can be combined with either primary or secondary tillage or planting operations. Tillage helps seed growth and germination through providing appropriate conditions for soil to absorb sufficient temperature and humidity. Moreover, it helps easier development of root through reducing soil penetration resistance. Tillage is a time-consuming and expensive procedure. With the application of agricultural operations, we can save substantial amounts of fuel, time and energy consumption. Conservation tillage loosens the soil without turning, but by remaining the plant left overs, stems and roots. Bulk density reflects the soil’s ability to function for structural support, water and solute movement, and soil aeration. Bulk densities above thresholds indicate impaired function. Bulk density is also used to convert between weight and volume of soil. It is used to express soil physical, chemical and biological measurements on a volumetric basis for soil quality assessment and comparisons between management systems. This increases the validity of comparisons by removing the error associated with differences in soil density at the time of sampling. The aim of conservation tillage is to fix the soil structure. This investigation was carried out considering the advantages of conservation tillage and less scientific research works on imported conservation tillage devices and those which are made inside the country, besides the importance of tillage depth and speed in different tiller performance. This investigation was carried out based on random blocks in the form of split plot experimental design. The main factor, tillage depth, (was 10 and 20cm at both levels) and the second factor, tillage speed, (was 6, 8, 10, 12 km h-1 in four levels for Bostan-Abad and 8,10,12,14 km h-1 for Hashtrood) with four repetitions. It was carried out using complex tillage made in Sazeh Keshte Bukan Company, which is mostly used in Eastern Azerbaijanand using Massey Ferguson 285 and 399 tractors in Bostab-Abad and Hashtrood, respectively. In this investigation, the characteristics of soil bulk density were studied in two sampling depths of 7 and 17 centimeters. Bulk density is an indicator of soil compaction. It is calculated as the dry weight of soil divided by its volume. This volume includes the volume of soil particles and the volume of pores among soil particles. Bulk density is typically expressed in g cm-3. In this study, the effect of both factors on the feature of the soil bulk density at the sampling depth of 5-10 and 15-20 cm was examined. In Bostan-Abad, regarding tillage speed effect for studies characteristics at 1% probability level on soil bulk density was effective. The effect of tillage depth on the soil bulk density was significant at 5% probability level. The interaction effect of tillage speed and depth on soil bulk density was significant at probability level of 1%. Regarding sampling depth effect, the soil bulk density was significant at 5% probability level, respectively. In Hashtrood, the effect of tillage speed on soil bulk density at probability level of 1%, and also tillage depth effect on soil bulk density was significant at 5% level of probability. The interaction effect of tillage speed and depth on soil bulk density was significant at 5% level of probability. Regarding the depth of sampling it was significant on soil bulk density at probability level of 1%. Through an increase in tillage speed, soil bulk density reduces at unit level. In this study, the effect of both factors on the feature of the soil bulk density in the sampling depth of 5-10 and 15-20 cm was examined. In Bostan-Abad and Hashtroud, on the whole, the results indicated that the increase in the speed of tillage, soil bulk density, was reduced and the speed of 10 kilometers per hour was the best for this to implement work. Also, with an increasing depth of tillage, the bulk density increased. Through an increase in tillage speed, soil bulk density reduced at unit level. Moreover, the optimum speed was concluded 10km per hour. Through an increase in tillage depth, bulk density and soil humidity increase accordingly. The best tillage depth using this machine is 10cm.

Nowadays the number of motor vehicles in large and small cities is growing. Increasing the number of motor vehicles leads to serious increase of the amount of environmental pollution and daily fuel consumption. Motor vehicle emissions that are known as the most air polluting emissions cause 50-90 percent of air pollution. With large increasd in the number of motor vehicles and their emissions todays, many researchers have investigated engine optimization in order to reduce emissions of motor vehicles. But due to the lack of affordable changes in the physical structure of the engine, it is not possible to create major changes in the amount of engine exhaust. Hence, in order to improve engine performance and reduce emissions, a lot of research has been carried out on changes in the fuel and engine inlet air. So, in this study a new method has been proposed and tested in order to detect changes in the charactristics of emissions. So, the effects of enriched nitrous oxide gas on the exhaust emissions of a spark-injection engine were investigated. In this way, a certain amount of Nitrous Oxide (N2O) gas was mixed with the engine inlet air (with concentration of 0, 4, 8, 12 and 16 percent) and it was injected to the engine. Then its effect was studied on emission parameters at various engine rotational speeds. Then, by using genetic algorithm, the optimal values of N2O concentration and engine rotational speed were determined to reach the minimum emission parameters. To measure the engine emission parameters including CO, CO2, HC and NOx, the expriments were conducted after preparing a system to inject inlet air with different percentages of N2O into an Otto engine (model: M13NI). In this study, the randomized complete block design was used to investigate the effect of N2O concentration (five levels) and engine rotational speed (three levels) on exhauste emission parameters. Each expriment was replicated 9 times. For statistical analysis, Duncan’s multiple range test and multivariate analysis of variance were performed by using SPSS Software. Also, each factor was modeled by polynomial equations and the obtained models were optimized in three dimensions by genetic algorithm method in MATLAB Software. After optimization ofeach emission parameter in the same time by multi-objective optimization regression, separately, and determination of the best value of N2O concentration in the inlet air andthe engine rotational speed, the optimizations were compared in order to obtain the minimum value of emission parameters. The experimental results indicated that by increasing N2O concentration in the inlet air of motor vehicle engine, the amounts of CO and HC were significantly decreased and the amounts of CO2 and NOx were significantly increased. Also, the results of this study showed that increasing the engine rotational speed at the same time with increasing the N2O concentration caused a significant decrease in the amounts of CO, CO2, HC and NOx. The optimal amount of N2O concentration and engine rotational speed by genetic algorithm method were obtained to be14.545 % and 3184 rpm, respectively. The main conclusions obtained from this research are listed below: - The amount of N2O concentration in the engine fuelis the decisive factor for decreasing emissions. - By increasing N2O concentration in the inlet air of motor vehicle engine, the amounts of CO and HC were significantly decreased and the amounts of CO2 and NOx were significantly increased. - By increasing the engine rotational speed and N2O concentration, the amounts of CO, CO2, HC and NOx were decreased. - The optimal amount of N2O concentration and engine rotational speed were obtained to be 14.545 % and 3184 rpm, respectivelyby using the genetic algorithm method. For these values, based on regression models, concentration of CO and CO2, were obtained to be 0.056% and 12.5%, respectively. - The concentration of N2O and the optimum rotational speed of engine for CO gas were obtained to be 10.562% and 3749 rpm. - The concentration of N2O and the optimum rotational speed of the engine for CO2 gas were found to be 0% and 2847 rpm, respectively. - The concentration of N2O and optimum rotational speed of engine for HC werefound to be 12.71% and 3750 rpm, respectively. - The concentration of N2O and optimum rotational speed of engine for NOx werefound to be 0% and 4300 rpm, respectively.

In order to improve the use of pesticides and pesticide consumption and prevent environmental pollution, manufactures and scientists have considered two major trends. The first major trend is improving techniques that are practical and effective use of small quantities of chemicals to reduce the negative effect of residues of pesticides. The use of new methods usually requires investment and cost. The second major trend is changing the parts that are more important to reform the sprayer components in order to reduce pollution, mainly by including engineering controls, and design and construction of appropriate nozzles. The optimization can be done with the least expensive pesticide. Nozzle is a device for spraying the solution in the form of particles with a certain pattern. Tip of a nozzle is placed in the nozzle’s body and has many different types. The main factors in choosing tips include: material, pattern of distribution, spray angle and the amount of the solution. The spray tip may be made of aluminum, brass, nylon, stainless steel, ceramic or other materials. Nanocomposites are composites that contain at least one component with dimensions in the nanometer range between 1 to 100 nm. This material is suitable as an alternative to overcome the limitations that exist with integrated microcomposites. The aim of this study was the construction and evaluation of a sprayer nozzle with ceramic nanocomposites with good shelf life and optimum performance. This research was supported by the Agricultural Engineering Research Institute and Nanotechnology Committee of the Ministry of Agriculture. The operations of this study were as follows: 1- Preparing of materials, including alumina powder and stabilized zirconia powder with yttrium. 2- Design and manufacture of molds. 3- Preparation of the samples pressing operations. 4- Zintering of samples to achieve high density. 5- Tests to determine the quality of the products. In order to prepare nanocomposite powder mixed with stabilized zirconia alumina, the ratio of 10/90 percent by volume of the powder was poured into the mill for three hours and it was stirred in the mixer. Pressing is placing the powder into a mold, and applying pressure to achieve the desired density. In this study, pressing device with 30 tons was manually used and powder sample in the amount of one gram was placed in a semi-cylindrical small hollow. After making a few samples and determining the optimal pressure and time of pressing in action, samples were manufactured under 90 kg cm-2 pressure at 20 seconds. A high temperature furnace model F3L-1720 was used for zintering. Samples were put into the furnace after forming by a single-axis press. Temperature the of furnace was raised up 1650°C at a rate of 10 degrees per minute and then the samples were exposed for one hour in order for the heat to be evenly applied in all the body of the nozzle. Finally, a hollow cone spray pattern fan nozzle with a major diameter of 15 mm and an inner diameter of 2 mm was built. Equipment for analyzing used in this study included: X-Ray Diffraction device (XRD), Scanning Electron Microscope (SEM). The flow rate output was measured at a pressure of 2 bar in the period of 0-50 hours at 1, 2, 3, 4, 5, 8, 10, 15, 20, 25, 30, 40 and 50 hours. XRD analysis of nano-composite stabilizer in the presence of yttria- zirconia- alumina toughness with (Al2O3-ZrO2-Y2O3), yttria stabilized zirconia (ZrO2-Y2O3) and alumina indicates respective phases. For the samples made with better properties, it should be uniformly distributed within it. To evaluate the uniformity, SEM-Mapping test samples were made. The results showed that the distribution of Y, Zr, Al in nanocomposite (Al2O3-ZrO2-Y2O3) is almost uniform. The results of changes in the level of output over time showed that the rate of flow in composite (Al2O3-ZrO2-Y2O3) nozzle versus ceramic conventional (Al2O3) nozzle after 50 hours of testing under static condition, flow rate was decreased to 30- 35 percent. Nozzles are one of the most important terminal parts in sprayers and are used to spread the liquid evenly at a certain flow rate. Addinga nanomaterial ceramic structure as a new solution was effective. By paying attention to reduce the use of chemicals and protection of the resource bases, a correct approach to the development of agricultural mechanization equipment that are essential components should be a priorityas a low-cost solution.

Nowadays, the tractor mounted boom sprayer is used in many agricultural fields. These sprayers have many advantages compared to other sprayers, but in Iran, their field efficiency is much lower than that of the developed countries, because the tank volume and consumption of pesticides per hectare is often so highthat spraying per hectare takesa long time for handling the solutions and transporting the sprayers. Also spray droplet size is ordinarily high and its distribution is unknot uniform. So, often spraying and dropping top parts of plants on the earth is inevitable. According to studies carried out in the country during the years 2005-2008 in the agricultural research centers in several provinces such as Khuzestan, four types of sprayers including tractor mounted sprayer, atomizer, microner, and electrostatic atomizer were studied and some of the results obtained include the following. From the point of view of percentage of crash crop, tractor mounted sprayer has the highest percentage, but microner sprayer had the lowest. From the point of view of the solution of consumption amount and spraying cost per hectare, the operation of the tractor mounted sprayer and electrostatic sprayer had the highest and the lowest ranks, respectively. Atomizer sprayer had the highest effect on the percentage amount of weed control, but it requires a high amount of water consumption, high drift and low operation (Safari and Lovaimi, 2010). The experiment was carried out during 2012-2013 in the field of agricultural research located in the Mollasani city located 20 km near Ahvaz. In this study, tractor mounted spinning disk sprayer (mounted microner sprayer) was evaluated in comparison with conventional boom sprayer on weeds control. The treatments included medium (3500 rpm) and low (2000 rpm) speed rotation disk sprayer and two types of nozzle in conventional boom sprayer. One of them was an Italian tee jet nozzle and the other one was flowage nozzle and they were compared with control treatment. Experiment design was Randomized Completed blocks Design (RCBD) with seven replications. Parameters such as spraying quality, diameter, volume mean diameter and numerical mean of droplets, spray quality factor, the percentage of crash crop, weeds dry weight and number, percentage of weed control and the drift were measured. The results were compared with a control treatment. For comparative tests between the sprayers, the measured parameters were compared with each other using SAS software. Volume mean diameter and numerical mean diameter in tractor mounted microner sprayer with medium and low speed rotation disk treatment and also tractor mounted boom sprayer with Italian fan nozzle treatment were metered 162.5, 461 and 635.5 micron, and 138.5, 355 and 452.5 micron, respectively. Volume mean diameter related to numerical mean diameter was obtained to be 1.17 and 1.3 for tractor mounted microner sprayer with medium and low levels of speed rotation disk, and 1.4 for tractor mounted boom sprayer with Italian fan nozzle, respectively. Whenever the spray quality coefficient is closer to one, the spray quality is better. So microner sprayer treatment with 1.17 coefficient has the best spray quality. The results about weeds control numbers showed all treatments had significant difference with control treat in 1% levels (Table 3). Evaluating all treatment results showed the flowage nozzle with 22.57 weeds number and 27.26 g. weeds dry weight had significant difference with other treatments in 1% levels that was the best operation (Table 4). In comparison of sprayers’ technical evaluation, all treatments had significant difference in 1% levels, so the flowage nozzle with 191.66 l.ha solution consumption and microner treatment with medium speed rotation disk with 44.38 l.ha solution consumption were the most and the least treatments. And they have significant difference in 1% levels (Table 5). The most percent of crop loss belonged to sprayer boom tractor with flowage nozzle (27.03%) and the least belonged to microner boom sprayer tractor (6%). The most percent of drift belonged to microner boom sprayer tractor with medium speed of rotation disk (76.19%) and the least belonged to sprayer boom tractor with flowage nozzle (23.81%). The best spraying quality (1.17) was for microner with medium rotation disk treat (Table 6). Performance of a sprayers mostly depends upon the working of its nozzle. In this research, two different sprayers with three typical nozzles were used to control wheat crop weeds. In general, the tractor sprayer of microner (40 million Rials) is more expensive than the typical boom sprayer, and because most farmers owntractor mounted boom sprayers the most convenient and least expensive method is to use Italian fan nozzle (standard) due to lower cost and higher performance. However, there are many effectiveness parameters to select a suitable sprayer for the field. But on the bases of the sprayer's technological specifications, weed control parameters, economical parameters and etc., technical methods such as Analytical Hierarchy Process (AHP) or other ones are proposed to choose the better sprayer for pesticide applications.

Encountering soil from the viewpoint of management and product manufacturing has always been considered important, and an attempt is always made hat the tools and contrasting methods of soil be designed in such a way that itself prevents, as much as possible, the destructive consequences or energy waste that include economical or environmental limitations. Enhancing the soil encountering methods, quality reformation, and its related equipment, requires performing reliable tests in actual soil conditions. Considering the complexity and variety of variables in soil and machine contrast, this is a hard task. Hence, the numeral simulations are the key of all optimizations that illustrate efficient models by removing the costly farm tests and reducing research time. Tire is one of the main factors engaged with soil, and it is one of those tools that are discussable in both farms, and software environments. Despite the complexities in soil behavior, and tire geometry, modeling, tire movement on the soil has been the researchers’ objective from the past. A non-linear finite element (FE) model of the interaction of a non-driving tire with soil surface was developed to investigate the influence of the forward speed, tire inflation pressure and vertical load on rolling resistance using ABAQUS/Explicit code. In this research numerical and experimental tests were done under different conditions in order to estimate tire rolling resistance. In numerical tests, the soil part was simulated as a one-layer viscous-elastic material with a Drucker-Prager model by considering realistic soil properties. These properties included elastic and plastic properties which were obtained in the soil laboratory using relevant tests. The soil samples were prepared from the soil which was inside the soil bin. The same soil was utilized in experimental tests. Finite strain hyper elasticity model is developed to model nearly incompressible rubber materials for the tire. Tire model consisted of three components: tread, rubber and ring. Using a soil bin and one wheel tester with their related equipment, experimental tests were carried out in the workstation of mechanics of bio system engineering department of the Urmia University. This system includes various sections such as soil storage in dimensions of 22×2×1 meter, tools carrier or tracker, soil processing equipment, dynamic system, evaluation tools and controlling systems. In order to launch the collection and supply required power for wheel carrier, an industrial three phase electromotor with 22 kW (30 hp) was used. Both numerical and experimental tests were done at three levels of wheel dynamic load (1, 2, 3, 4 and 5) kN, tire inflation pressure (100, 200 and 300) kPa and four levels of speed (0.25, 0.45, 0.65, 0.9 and 1.15) m s-1 to obtain the rolling resistance of the tire. In order to evaluate the performance of final non driving tire-soil model to estimate the rolling resistance, numerical results were compared with preliminary experimental data obtained from the soil-bin tests. The comparison showed reasonably good agreement between the computed and measured general pattern of the rolling resistance at the tire-soil interface under different speeds, vertical loads and inflation pressures. In both tests, a specified relation was not seen between tire velocity and its rolling resistance, as it was not seen in empirical models such as Wismar and Luce. Correlation coefficient between experimental and numerical data, in the minimum and maximum value of tire inflation pressure was computed to be 0.06 and 0.016 percent, respectively. The amount of tire rolling resistance significantly increased with increase of tire vertical load. Correlation coefficient between experimental and numerical data, in the minimum and maximum vertical loads was computed to be 80 and 87 percent, respectively. Gent and Walter obtained the same results. The tire inflation pressure and rolling resistance variables had inverse relation to each other in both numerical and experimental tests. Correlation coefficient between experimental and numerical data was computed to be 97 and 73 percent in the minimum and maximum tire inflation pressure, respectively. The gradient of changes in tire inflation pressure - rolling resistance diagram was less in numerical tests. This was because of differences between real properties and the properties entered into the software. To conclude, in this investigation a new 3D tire-soil model was simulated which has specific features. The experimental results showed that the numerical data of estimation of non-driven tire rolling resistance were reliable. In both tests, the effect of changes in tire forward speed on rolling resistance was not significant.The amount of the tire rolling resistance significantly increased with increasing tire vertical load. Changes in tire inflation pressure and rolling resistance had an inverse relation with each other in both numerical and experimental tests. The slope of rolling resistance - inflation pressure diagram in numerical tests was less than the same diagram in the experimental tests.

Golestan province is one of Northern provinces in Iran. The area under cultivation of agricultural products in this province is 724.697 hectares, of which about 694.618 hectares are used for farm products (AJMDC, 2011). Cotton as one of oilseed is a potential feedstock for biodiesel production (Ahmad et al., 2011). In the study of energy consumption and greenhouse gas emissions for cotton production in Alborz province, results showed that the total energy input was 31.237 MJ ha-1. Energy efficiency and energy productivity were 1.85 and 0.11, respectively, and greenhouse gas emissions of cotton production in Alborz province were 1195.25 kg CO2eq ha-1 (Pishgar-Komleh et al., 2012). Another study on energy analysis, greenhouse gas emissions and economic analysis of agricultural production was performed in Northern Iran (AghaAlikhani et al., 2013; Royan et al., 2012; Pishgar-Komleh et al., 2011; Mohammadi et al., 2010; Taheri-Garavand et al., 2010). The aims of this study were to determine the energy flow, greenhouse gas emissions and economic analysis of cotton production in the Golestan province and also to determine the effect of energy inputs on cotton yield. This research was conducted during 2011-2012 in three areas including Gorgan, Aq’qala and Gonbad in the Golestan province. The primary data were collected from the rice producers through a field survey with the help of a structured questionnaire. The number of subjects were studied by the Cochran formula (Snedecor and Cochran, 1980). Accordingly, 43 cotton producers were determined. In this study, eight energy inputs including seed, labor, machinery, diesel fuel, chemical fertilizers, chemicals, water for irrigation and farmyard manure for cotton production system were considered as independent variables. The outputs of the system including lint and seed were considered as dependent variable. Energy indices including energy efficiency, energy productivity, specific energy and net energy were calculated. In this study, the effect of energy inputs on yield was estimated using the Cobb-Douglas function. In order to determine the sensitivity of energy inputs in the production of cotton in the Golestan province, the marginal physical productivity method was applied. Greenhouse gas emissions, inputs of agricultural machinery, fuel, chemical fertilizers, chemicals and farmyard manure in cotton production in the Golestan province were calculated by the coefficients of each of these inputs. For economic evaluation of cotton production in the Golestan province, the variable costs, fixed and total production per unit area were considered. Economic indices of total production value, gross income, net income, economic productivity and benefit to cost ratio were estimated. Data analysis was performed using JMP8 software. Cotton yield in the Golestan province was about 2650 kg ha-1. Average cotton yield in the Alborz province was reported to be 3430 kg ha-1 (Pishgar-Komleh et al., 2012). In this study, diesel fuel had the highest energy consumer among other inputs like the other studies that have been done on energy crop production in Iran. Labor energy input with energy consumption of 2413 MJ ha-1, is known to be the fourth high-energy input in cotton production in the Golestan province. However, in many studies in Iran, this input was accounted to be less than one percent of the energy consumption in the production of agricultural products (Saeedi et al., 2013; Khoshnevisan et al., 2013; Mobtaker et al., 2012; Mobtaker et al., 2010). Chemical energy input with 1036 MJ ha-1, was allocated as 3.6% of energy consumption in the cotton production in the region. Seed energy input was the lowest energy among the other inputs in cotton production in the Golestan province. The results revealed that the total energy inputs for cotton production in the Golestan province was 28.898 MJ ha-1. The average energy efficiency for cotton production in the Golestan province was obtained to be 1.58. Energy productivity for cotton production in the Golestan province was calculated to be 0.092. From the results of Cobb-Douglas function to determine the relationship between energy input and yield of cotton in Golestan province, the effects of human labor, diesel fuel, water for irrigation, chemical fertilizers and farmyard manure inputs on the yield were positive, and the effects of agriculture machinery and chemicals inputs on cotton yield were negative. Greenhouse gas emission from diesel fuel input hadthe highest value of 646.23 kg CO2eq ha-1 with a 45.2 percent share. Farmyard manure with 23.5 percent of greenhouse emissions was identified as the second largest input in greenhouse gas emissions in cotton production. Variable costs, fixed and total cotton production in the Golestan province were calculated to be 3042429, 851880 and 3894309 Toman ha-1, respectively. Benefit to cost ratio for the cotton production in the Golestan province was calculated as 1.16. The results of this study showed that the energy efficiency for cotton production in the Golestan province was less than the energy efficiency for cotton production in the Alborz province, Hatay province of Turkey, and canola, soybean and sunflower production in the Golestan province. Also, the energy efficiency of cotton production was less than that of cotton production in Antalya Turkey and canola in the Mazandaran province. The highest share of energy consumption and greenhouse gas emissions belonged to diesel fuel with the share of 45.6 and 45.2 percent, respectively. However, this input accounted for 2.7 percent of variable costs.

The performance of agricultural machines depends on the reliability of the equipment used, the maintenance efficiency, the operation process, the technical expertise of workers, etc. As the size and complexity of agricultural equipment continue to increase, the implications of equipment failure become even more critical. Machine failure probability is (1-R) and R is machine reliability (Vafaei et al., 2010). Moreover, system reliability is the probability that an item will perform a required function without failure under stated conditions for a stated period of time (Billinton and Allan, 1992). Therefore, we must be able to create an appropriate compromise between maintenance methods and acceptable reliability levels. Precision failure data gathering in a farm is a worthwhile work, because these can represent a good estimate of machine reliability combining the effects of machine loading, surrounding effects and incorrect repair and maintenance. Each machine based on its work conditions, parts combinationand manufacturing process follows a failures distribution function depending on the environment where the machine work and the machine’s specifications (Meeker and Escobar, 1998). General failures distributions for contiguous data are normal, log-normal, exponential and Weibull (Shirmohamadi, 2002). Each machine can represent proportionate behavior with these functions in short or long time. The study area was the Hakim Farabi agro-industry Company located 35 kilometers south of Ahvaz in Iran. Arable lands of this company are located in 31 to 31°10 N latitude and 45 to 48°36 E longitudes. The region has dry and warm climate. A total of 24 Austoft 7000 sugarcane chopper harvester are being used in the company. Cane harvesters were divided into 3 group consisting of old, middle aged and new. From each group, one machine was chosen. Data from maintenance reports of harvesters which have been recorded within 400 hours were used. Usually, two methods are usedfor machine reliability modeling. The first is Pareto analysis and the second is statistical modeling of failure distributions (Barabadi and Kumar, 2007). For failures distribution modeling data need to be found, that are independent and identically (iid) distributed or not. For this, trend test and serial correlation tests are used. If the data has a trend, those are not iid and its parameters are computed from the power law process. For the data that does not havea trend, serial correlation testare performed. If the correlation coefficient is less than 0.05 the data is not iid. Therefore, its parameters reach via branching poison process or other similar methods; if the correlation coefficient is more than 0.05, the data are iid. Therefore, the classical statistical methods will be used for reliability modeling. Trend test results are compared with statistical parameter. A test for serial correlation was also done by plotting the ith TBF against the (i-1)th TBF, i ¼ 1; 2;. .. ; n: If the plotted points are randomly scattered without any pattern, it can be interpreted that there is no correlation in general among the TBFs data and the data is independent. To continue, one must choose as the best fit distribution for TBF data. Few tests can be used for best fit distribution that include chi squared test and Kolmogorov–Smirnov (K-S) test. Chi squared test is not valid when the data are less than 50. Therefore, when the TBF data are less than 50, K-S test must be used. Hence, the K-S test can be used for each TBF data numbers. When the failure distribution has been determined, the reliability model may be computed by equation (2). Results of trend analysis for TBF data of sugarcane harvester machines showed that the calculated statistics U for all machines was more than chi squared value that was extracted fromthe chi square table with 2 (n-1) degrees of freedom and 5 percent level of significance. Hence, it is possible that all of the machines’ TBF data will have identically and independent distributions. For validating this hypothesis, correlation testwas performed on TBF data that verified prior results. Then, Kolmogorov- Simonov test was done on TBF data. Results showed that all three machines followed Weibull 3 parameters function, but the shape parameter was different for them. The analysis showed the shape parameter for old, middle aged and new cane harvesters was 1.5, 1.42 and 1.35, respectively. In order to control and reduce failures and to plan and schedule the harvester operations in optimum time, machine reliability must be known. In this paper, three sugarcane harvesters were studied individually. From the trend analysis and serial correlation, it is seen thatthe assumption of identically and being independently distributed was valid for all machines’ TBF data of sugarcane chopper harvesters.

Different models of tractors have been imported from foreign countries or assembled in Iran for many years. Consistency of foreign manufactured products with native specifications and the improvement of locally manufactured tractors are important problems that must be considered. Moreover, tractor dimensions, sitting space and some other important factors such as the ability of Iranian users to operate them must be taken into consideration. In this study, we surveyed the proper proportion of tractors dimension, location of control tools and driver’s work space, with Iranian users’ anthropometric data of drivers from five provinces. Human factors are of paramount importance in developing farm machinery given that these machines will often be operated by persons with minimum skills. Therefore, farm machinery should be made simple to operate and as free from hazards as possible. Firstly, the anthropometric data for 250 users 20-60 years old was calculated. The drivers were selected randomly. Then the specifications of 4 tractors including: Ferguson 285, Ferguson 399, Valtra and New Holland were compared with the anthropometric data of user in 5th and 95th percentile value and their adaptation was studied. Anthropometric Data of subjects consisted of: standing height, full hand length, popliteal length, seat pan width, seat pan depth, elbow height, seat back support height, hand pan width, hand grip and full-leg length. Getting on the tractor is the first contact of an operator with a tractor. In assessing the suitability of the provision made for getting on the tractor, an experiment was arranged in which operators tried to get on 3 tractors. The mode of getting on the tractors, the agony on the operator’s face, the muscular reactions and individual opinion on the difficulties or comfort while undertaking the task were observed and recorded. The specifications of tractors compared with Anthropometric Data were measured, whiles the tractors were positioned on a level ground for measurements after the tires had been ganged. These specifications were tractor height, steering wheel height, footrest height, foot set height; tractor seat geometry as seat pan width, seat pan depth and seat pan support height; steering geometry as distance of steering wheel from seat reference point, steering wheel radius, steering wheel thickness, steering wheel inclination to the horizontal and seat reach adjustment; levers and pedals distance from seat reference point as gear lever, parking brake lever, hydraulic control lever, clutch pedal, accelerator pedal, brake pedal, front panel, workspace width and workspace length. The experiment that was conducted with operators attempting to get on the tractors indicated that tractor steps heights were higher than the desirable limit. Therefore, based on the ideas of the researcher and tractors drivers, getting on all tractors is difficult. With an increase in the number of steps or a decrease in their heights, the desirable condition can be created. Seat depth of new Holland and Valtra tractors were great for drivers in the 5th percentile value. A variable thickness pad can solve this problem. Results of studies indicated that Seat depth of Massey Ferguson 285 and 399 was shorter than driver’s leg length of 95th percentile value. To solve the problem an increase of 10 centimeters to pad height of these tractors was suggested. Seat pad of tractors were short for drivers in the 95th percentile value. Distance of steering wheel from seat reference point (SRP) in Massey Ferguson 285 and Valtra was further than drivers hand length in the 5th percentile value. Therefore, the drivers hand is short for driver’s good operation. Surveys indicated that drivers had problems for gear lever access in Massey Ferguson 399. Therefore, for good access on gear lever we must increase seat stroke range by 5-10 centimeters. The record available from Meteorological Organization indicated that air temperature and rain throughout the year in the study area is between 20 to 40degrees Celsius and 100to 300mm change. Valtra and New Holland tractors having a driver cabs with heating and cooling equipment have the ideal space for the performance of their driver. Massey Ferguson 285 tractor does not have any driver cab and Roll Over Protection Structure (ROPS). This research was conducted in five provinces of Iran to assess ergonomics of some commonly and new used tractors in Iran containing Ferguson 285, Ferguson 399, Valtra and New Holland. As there was no data base with required details, data was collected directly by personal contact with tractor users. A questionnaire was filled out for each person and anthropometric data was calculated in all provinces for 250 users 20-60 year old that were selected at random. Then relevant specifications of 4 tractors were measured and compared with the relevant anthropometric data of users in the 5th and 95th percentile value and their adaptation was studied. The results indicated that tractor steps, Seat depth, distance of steering wheel and distance of some levers and pedals from seat reference point should be amended.

The common method used for juice pasteurization is the thermal method since thermal methods contribute highly to inactivating microbes. However, applying high temperatures would lead to inefficient effects on nutrition and food value. Such effects may include vitamin loss, nutritional flavor loss, non-enzyme browning, and protein reshaping (Kuldiloke, 2002). In order to decrease the adverse effects of the thermal pasteurization method, other methods capable of inactivation of microorganisms can be applied. In doing so, non-thermal methods including pasteurization using high hydrostatic pressure processing (HPP), electrical fields, and ultrasound waves are of interest (Chen and Tseng, 1996). The reason for diminishing microbial count in the presence of ultrasonic waves could be due to the burst of very tiny bubbles developed by ultrasounds which expand quickly and burst in a short time. Due to this burst, special temperature and pressure conditions are developed which could initiate or intensify several physical and/or chemical reactions. The aim of this study is to evaluate the non-thermal ultrasonic method and its effective factors on the E.coli bacteria of sour cherry. In order to supply uniform ultrasonic waves, a 1000 W electric generator (Model MPI, Switzerland) working at 20±1 kHz frequency was used. The aim of this study is to evaluate the non-thermal ultrasonic method and its effective factors on the E.coli bacteria of sour cherry. For this purpose, a certain amount of sour cherry fruit was purchased from local markets. First, the fruits were washed, cleaned and cored. The prepared fruits were then dewatered using an electric juicer. In order to separate pulp suspensions and tissue components, the extracted juice was poured into a centrifuge with the speed of 6000 rpm for 20 min. For complete separation of the remaining suspended particles, the transparent portion of the extract was passed through a Whatman filter paper using a vacuum pump (Mehmandoost et al., 2011). Afterwards, the samples were poured into a reactor with diameter and height of 80 and 50 mm, respectively. It is necessary to mention that the dimensions of the reactor were optimized during pretests. Probe design: One of the most common types of horns used for ultrasonic machining technologies is step type horn (Naď, 2010). For obtaining the governing equations on deformation along the step type horn in steady state conditions, Eq. (1) was used. In the solution of the mentioned differential equation, the answers are divided into two subsets and each of the answers is obtained considering the boundary conditions (Hosseinzadeh et al., 2013): (1) c^2.[(∂S/∂x)/(S(x)).(∂u(x,t))/∂x+(∂^2 u(x,t))/〖∂x〗^2]=(∂^2 u(x,t))/〖∂t〗^2 From Eq. (1), it can be concluded that: (2) u(x,t)=(A cos⁡〖ωx/c〗+B sin⁡〖ωx/c)(C cos⁡〖ωt+D sin⁡ωt 〗 〗)The boundary conditions for Eq. (2) are written as follows: (3) {■(a) (∂u(x))/∂x=0,x=0@b) (∂u(x))/∂x=0,x=l@c) u(0)=u_in)} One of the most important parts in probe design is preventing stress concentration in locations in which the area changes. To avoid this problem, the displacement in this section must be equal to zero (Hosseinzadeh et al., 2013). For obtaining the probe length, the displacement equation and the l1 parameter are used:σ=-E.u_in.ω/c.sin⁡〖(ω.x)/c〗 (4) In order to determine the maximum axial stress in step type probe, Eq. (3) and (4) are derived and set equal to zero. Therefore, the maximum stress will be equal to:σ_max=π.E.u_in/l (5) Optimization and Modeling using Response Surface Response surface methodology (RSM) has an important application in the design, development and formulation of new products, as well as in the improvement of existing product designs. It defines the effect of the independent variables, alone or in combination, on processes. In addition, to analyzing the effects of the independent variables, this experimental methodology generates a mathematical model which describes the chemical or biochemical processes (Anjum et al., 1997, Halim et al., 2009). In order to obtain the optimum value, Eq. (1) will be used: (6) Y_i=β_0+∑▒〖β_i X_i+∑▒〖β_ij X_i X_j+〗〗 ∑▒〖β_ij X_i^2 〗+εwhere, β0, βj, βij, βjj are regression coefficients for intercept, linear, interaction and quadratic coefficients, respectively, while Xi and Xj are coded independent variables and ε is the error. For this purpose, four factors of ultrasonic power (200 to 600 W), wave exposure time (5 to 15 min), probe diameter (20 to 40 mm), and probe penetration depth in sour cherry juice container (0 to 40 mm) were selected. First, the probes with the desired diameters were designed using the related formulas by using CAD-CAM. Surface Method (RSM) indicated that the quadratic model with 0.96 coefficient of friction, standard error of 1545.3, and coefficient of variation of 14% is the best model for estimating the number of E.coli bacteria among the different studied treatments. The results showed that with increasing probe diameter and probe depth, the destructive effects of ultrasonic wave increase. It was also revealed that as the probe diameter and penetration depth increase, the destructive effect of ultrasonic wave is initially increased and then follows by a decreasing trend. With the increasing power of ultrasonic, ultrasonic intensity increases and leads to reducing number of E.coli in sour cherry juice. The increase in time of treatment with ultrasonic causes a decrease in the number of E.coli in sour cherry juice. This is due to the fact that the increase of ultrasonic exposure time leads to the increase of sonic stream in reactor and results in higher contributions of ultrasonic waves to E.coli. Finally, the examined variables were optimized by RSM and the values of ultrasonic power, waves exposing time, probe diameter, and probe penetration depth were obtained as 600 W, 15 min, 35.31 mm, 20.83 mm, respectively. Considering the mentioned values, the amount of E.coli bacteria reduction was estimated to be 1.97 logarithmic period. 1. Increasing probe diameter and probe depth increasesthe destructive effect of ultrasonic wave. 2. The examined variables were optimized by RSM and the values of ultrasonic power, waves exposure time, probe diameter, and probe penetration depth were obtained as 600W, 15 min, 35.31 mm, 20.83 mm, respectively. Considering the optimum values, the amount of E.coli bacteria reduction was estimated to be 1.97 logarithmic period. 3. With the increasing power of ultrasonic waves, ultrasonic intensity increases and leads to a reduction of the number of E.coli in sour cherry juice. 4. The increase in time of treatment with ultrasonic causesa decrease in the number of E.coli in sour cherry juice.

There are several sources of noise in an industrial and agriculture environment. Machines with rotating or reciprocating engines are sound-producing sources. Also, the audio signal can be analyzed to discover how well a machine operates. Diesel engines complex noise SPL and sound frequency content both strongly depend on fuel combustion, which produces the so-called combustion noise. Actually, the unpleasant sound signature of diesel engines is due to the harsh and irregular self-ignition of the fuel. Therefore, being able to extract combustion noise from the overall noise would be of prime interest. This would allow engineers to relate the sound quality back to the combustion parameters. The residual noise produced by various sources, is referred to as mechanical noise. Since diesel engine noise radiation is associated with the operators’ and pedestrians’ discomfort, more and more attention to being paid to it. The main sources of noise generation in a diesel engine are exhaust system, mechanical processes such as valve train and combustion that prevail over the other two. In the present work, experimental tests were conducted on a single cylinder diesel engine in order to investigate the combustion noise radiation during stationary state for various diesel and biodiesel fuel blends.

The engine used in the current study is an ASHTAD DF120-RA70 that is a single cylinder 4 stroke water cooled diesel engine and its nominal power is 7.5 hp at 2200 rpm. The experiment has been done at three positions (Left ear of operator, 1.5 and 7.5 meter away from exhaust) based on ISO-5131 and SAE-J1174 standards. For engine speed measurement the detector Lurton 2364 was utilized with a measurement accuracy of 0.001 rpm. To obtain the highest accuracy, contact mode of detector was used. The engine noise was measured by HT157 sound level meter and was digitalized and saved with Sound View software. HT157 uses alow impedance, capacitor microphone with a unidirectional pattern whose size, sensitivity and frequency range are 1/2", 50 mV Pa-1 and 10 Hz to 20 kHz with a flat extrusion, respectively. Choosing the combination of fuel was carried out according to experiments that have been done before determining engine operation parameters.

Fuel type has a direct effect on the quality of the IC engine's combustion phenomenon. One of the most important quality parameters that can be fluctuated by fuel type is engine noise. The fuel type has a direct effect on internal fuel ignition engines and affects the quality of fuel ignition. One of the effects of ignition quality is the sound of the engine that is very important in terms of both the health and evaluation of engine performance. Two-wheel tractors are of the most important tools used in agriculture. In addition to agricultural work, they have applications in rural areas as power generators. No research has been carried out so far in Iran on the sound of two-wheel tractors fuelled with diesel and biodiesel fuels. Therefore, the sound of the ignition of biodiesel and diesel mixtures in four stroke, single cylinder, two wheel diesel tractors manufactured by Ashtad Company was studied. The purpose of this study is to analyze the noise parameters of a diesel engine using B0, B5, B10, B15, B20, B25 and B30 biodiesel–diesel blends. Biodiesel was produced from waste oil and blended with net diesel fuel to evaluate the Power tiller's engine noise parameters. This study was carried out at a stationary position and at three positions such as driver's left ear position (DLEP), 1.5 meter (1.5 MAFE) and 7.5 meters (7.5 MAFE) away from the exhaust at 6 engine speeds (1200, 1400, 1600, 1800, 2000 & 2200 rpm). Statistical analysis and frequency analysis were used to analyze sound of the engine. The results showed that the sound pressure levels of the engine for B10 fuel have the least amount of noise level of the sound pressure. However, this fuel has no significant difference at 1% level with B00, B05 and B15 fuel. At the A weight level, that matches the structure of the human ear, and there is no difference between the sound pressure levels of ignition. Sound pressure level increased with increasing engine speed and the difference is significant at the 1% level. With increasing speed engine, noise levels increased up to 7.8 dB. Average sound pressure level was 83.76 dB at the driver's ear position (79.3 dBA), at 1.5 meters away from exhaust it was 85 dB (80.9 dBA) and at 7.5 meters away from exhaust it was 79.5 dB (72.4 dBA). The results proved that the lowest and highest sound pressure levels (SPL) of power tiller take place at B10, and B30, respectively. The SPL increased by 7.8 dB for increasing engine speed from 1200 to 2200 rpm. The test results showed that the average SPL at DLEP was 4.3 dB higher than 7.5 MAFE position.

B10 has minimum sound pressure level (SPL), but its difference with B00 (DIESEL FUEL), B05 and B15 is not significant in 1% error level. Considering the NOISH standard, the operator can work with a machine for 8 hours. In DLPE position, the most overcome frequency is 315 Hz for all blends that resulted from exhaustion and combustion. B10 has a minimum SPL at this peak point significantly lower than other blends. For the used engine in this experiment, by optimizing muffler design it is possible to reduce SPL of engine in this frequency peak point.

Drying process of agricultural products, fruits and vegetables are highly energy demanding and hence are the most expensive postharvest operation. Nowadays, the application of control systems in different area of science and engineering plays a key role and is considered as the important and inseparable parts of any industrial process. The review of literature indicates that enormous efforts have been donefor the intelligent control of solar driers and in this regard some simulation models are used through computer programming. However, because of the effect of air velocity on the inlet air temperature in dryers, efforts have been made to control the fan speed based ont he temperature of the absorber plate in this study, and the behavior of this system was compared with an ordinary dryer without such a control system. In this study, acabinet type solar dryer with forced convection and 5kg capacity of fresh herbs was used. The dryer was equipped with a fan in the outlet chamber (the chimney) for creating air flow through the dryer. For the purpose of research methods and automatic control of fan speed and for adjusting the temperature of the drying inlet air, a control system consisting of a series of temperature and humidity sensors and a microcontroller was designed. To evaluatethe effect of the system with fan speed control on the uniformity of air temperature in the drying chamber and hence the trend of drying process in the solar dryer, the dryer has been used with two different modes: with and without the control of fan speed, each in twodays (to minimize the errors) of almost the same ambient temperature. The ambient air temperature during the four days of experiments was obtained from the regional Meteorological Office. Some fresh mint plants (Mentha longifolia) directly harvested from the farm in the morning of the experiment days were used as the drying materials. Each experimental run continued for 9 hours, startingat 8:00 am and terminating at 17:00. To determine the moisture content for the purpose of observing and recording the drying process, the drying materials were sampled with one hour time step. The moisture contentwas determinedin the laboratory using the well- known method of oven drying which is presented elsewhere. Since the ambient air temperature during the four days of experimental runs was almost the same, the effect of ambient air temperature on the drying process was ignored. Considering the dryer inlet air temperature charts obtained in this study (Fig. 2 and Fig. 3), it can be concluded that for those tests using the fan speed control system, the outlet air temperature of the collector during drying period associated with very little variations, is compared with the no control mode runs. At the beginning of the day and also during the hours at the end of the day, due to a decrease in the temperature of the absorber plate compared to the middle of theday, the fan speed is reduced as air passes slowly through the absorber plate and hence the temperature rises. But in the middle of the day, with increasing the temperature of absorber plate, the speed of the fan is increased to provide sufficient airflow and to prevent the absorber plate from warming up. Inexperiments without fan speed control, the fan works with no limitation, and the temperature of the inlet air was changed with the temperature change in the absorber plate. The fan speed control system in addition to lowering the temperature changes in the outlet air, also increased the average outlet temperature about 3C, compared to the dryer without such a control system. During the twodays of experiments, the average ambient air temperature was 28C and at the sametime the outlet air temperature was 40.6 and 40.8C, respectively. In twodays of no control system, the average temperature of the ambient air was 28.5 and 28C and at the sametime the outlet air temperature was 38 and 37.8C, respectively. The results showed that with fan speed control mode the variation of inlet air temperature of the drying chamber was more limited and remained within the range of 39 to 42 and 40 to 42°C during the two experimental days, respectively. However, without fan speed control, the system exhibited a wider variation of inlet drying air temperature and limited within the range of 33 to 44 and 32 to 43°C. Furthermore, with fan speed control in a solar dryer, along with more uniformity in moisture content, the drying rate may speed up and with further decrease in final moisture content up to 8%, when compared to a system with no fan speed control. The average temperatures of the outlet air of collector in two days with fan speed control system, were 40.6 and 40.8°C while in the system without the fan speed control, were 38 and 37.8, respectively. This clearly indicates that the system control could increase the temperature of the collector outlet. The dryer was also able to control the fan speed during the 9hours of drying mint with initial moisture content of 85% (w.b) and to reduce it to about 24.5 and 25.5%, during the two experimental days, respectively. While the corresponding values without the use of a control system were 33.5 and 33.5%, respectively. In other words, in the experiments with the use of control system, the final moisture content was about 8% lower than the moisture content of materials dried without such a system. Furthermore, the control system reduces the volume of air required by the system and hence speeds up the drying process.