نشریه ماشین های کشاورزی
سال نهم شماره 1 (پیاپی 17، نیمسال اول 1398)

Harvesting is one of the most difficult steps in cabbage production that is usually a costly intensive operation. Cabbage harvesting is often done by human labors in Iran. According to customs administration’s statistics, more than 54000 tons of cabbages have been exported from Iran in 2015. Development of cabbage harvesting industry is necessary, because of the large cultivation area and the short available harvesting time. So far, a few studies have been done on cabbage mechanized harvesting in Iran. The harvesting machines can reduce harvesting time to one-eighth in comparison with manual harvesting. Design and manufacturing of a harvester unit suitable for small cabbage farms in Iran were conducted in the present study. So the paper was aimed to investigate the performance of the harvester at the different forward velocities, attack angles and distances between the plants. The proposed machine consists of two major units; the soil looser and the unit for pulling out, crops from the soil. In this machine, the blades loose the soil around the cabbage root after penetrating into the soil. Next, cabbage is pulled out from the soil by puller belts. The belts move contrary to forward speed direction and take crop to the backward of the machine. Mechanical and physical properties of the cabbages should be measured, because the harvester is directly in touch with the crop. These properties are firstly measured and then selection of the different components and machine manufacturing are done. Two narrow legs (tillage tools) equipped with one-side blade with attack angles of 20 and 25 degrees are used for losing the soil around the cabbage’s root. The force exerted on the blade was 5.47 kN. Finally, the harvesting force is estimated to be 164.8 N by using mechanical and physical properties of the cabbages. Experiments were conducted at the different forward velocity levels (2, 3.5 and 5 km h-1), attack angle of the blades at three levels (20, 25 and 30 degree) and the distance between the crops in two levels (40 and 60 cm) in a completely randomized design with three replications. The analysis of variance of the effect of different parameters on the harvested crop numbers showed, that the effects of forward velocity and attack angle on the number of harvested crops were significant in 5 percent probability. But distance between crops did not have significant effect on the number of harvested crops. Also the effects of interaction between forward velocity and attack angle, forward velocity and distance between crops, attack angle and distance between crops on the number of harvested crops were significant in 5 percent probability. According to the results, the number of harvested crops and machine performance were decreased by increasing forward velocity. Moreover, designed machine had the best performance (80 percent) at an attack angle of 25 degrees and forward velocity of 2 km h-1. The results showed, with increasing the forward speed from 2 to 5 km h-1 the harvest success decreased by 20 to 25 percent. Also, the harvesting quality did not change at the different distances between the plants. The highest machine capacity was more than 5300 plants per hour, which was observed at the forward velocity of 3.5 km h-1 and the attack angle of 25 degrees.

Nowadays, due to growth and development of the husbandry and its worthiness in providing human basic needs, affecting parameters such as costs, efficiency and fuel consumption is significantly important. So, increasing the efficiency of threshing machine could lead us to huge savings in energy. However using the conventional drums and concaves have some problems such as damaging seeds due to impact, complicated manufacturing technology and spending a lot of energy in separating process. Therefore in order to overcome above mentioned problems especially energy consumption, a new seed pod husker based on rubbing was designed, fabricated and tested in this research. Practical tests of this device were carried out on soybean which was harvested in a farm of Babolsar city. The experimental design was simple randomized complete design with three replications. The rotational speed of rollers and distance between rollers varied in three levels of 110, 170, and 210 rpm and 7, 8, and 9 mm for soybean. The measured parameters consisted of efficiency, separation and loss. For designing the seed pod husker, the required electric motor power and the torque for separating seeds from its pods were calculated. After reviewing the physical and mechanical characteristic of some seed pod crops specially, soybean, a seed pod husker was designed in SOLIDWORKS 2013 software. In order to facilitate seeds separation from the pod, it was preferred to use the right-round and left-round Archimedes screw on the rollers. According to the preliminary evaluations, it was considered to use a speed range of 110 to 210 rpm; it was because of that the speed lower than 110 rpm was not able to open pods and the speed higher than 210 rpm caused hyper movements of pods. Analysis of variance (ANOVA) and mean comparisons and interaction between the parameters were performed using the SPSS 22 software. The results indicated that the rollers were acceptable and sticking of pods were not seen. Results indicated that the efficiency of this device was increased with increasing the rotational speed and then was decreased. Increasing the rotational speed was led to increase separation. It is because of this fact that the performance of the husker’s component will be more powerful and crops suffer bigger impacts. The chart of device loss had a relatively upward slope. It could be due to a tougher collision between the seeds and the rollers. Increasing the roller distance, first decreased the efficiency of soybean and then increased that. The results indicated that separation efficiency decreased by increasing the distance. The reason for that was due to unavailable necessary force to separate the seed and pod. As the roller distance increased, the total losses of the device also increased. The reason for this was likely increasing in the movement of the seeds. The results of practical tests and qualitative observations showed that the device had sufficient resistance against the maximum torque produced by the crop. Influence of rotational speed of rollers and rollers clearance on the efficiency, separation and loss were significant for new fabricated seed pod husker (P<0.01). The capacity of the machine for soybean was 28.506 (kg hr-1). To achieve maximum efficiency, maximum separation and minimum loss for soybean, authors suggest using (9mm-170rpm), (7mm-210rpm) and (9mm-110rpm) compounds, respectively. Eventually, it is suggested to evaluate this machine for other seed pod crops and for other parameters such as germination percentage, electric conductivity and ergonomic issues such as noise and machine vibration. Of course, it is recommended to survey the impact of length of husking roller, shaft rotation method and thread types on measurement parameters.

During filling a silo, granular material containing a range of particle sizes, the fine material accumulates under the filling point. The inclined surface of stationary bed particle which is formed in silos during filling process acts similar to a sieve through which the smaller particle fall. This effect is called sifting. As a result of the mentioned effect, much finer particles form a vertical cylindrical zone of high concentration at the silo center. For optimal design in industrial process such as aeration of stored products in silos, filling silos, and wherever granular materials are handled, it is necessary to survey the distribution of the fine materials depending on product and process properties. The objectives of present study were: (a) To study fine change as affected by substantial parameters, (b) To model fine changes at different conditions in silos. In the present study, an experimental setup consist of a main container, elevator, trapezoidal container and experimental silo was designed and built. Fine content was defined by BCFM (broken corn and foreign material). By applying a new approach, sampling was performed in a radial and vertical direction. The position of each sampling point was determined with a scaled distance from center (R) and from bottom (Z). Local BCFM (BCL) was defined as the value of BCFM in each sampling point. Influential parameters namely, initial BCFM (BCI), volume flow rate (Q) and fill pipe diameter (DF) were considered as treatments. Non-linear regression technique was applied on the experimental data to predict the distribution pattern of fines into the pilot-scale silo. The most appropriate model in a try and error procedure was selected based on highest value of R2 and least value of χ2, RMSE and MRDM. According to the results of ANOVA, it was found that the effects of all parameters were significant at 5% probability. BCL decreased nonlinearly with a concave down decreasing trend along radial direction due to sifting effect. As a result, most amount of fines remained in the sections closer to the center of the silo. Fine distribution became more uniform with decreasing Z and increasing BCI and DF. Also, the distribution of fine became more uniform with increasing Q. BCL was a nonlinear function of R and a linear function of Z, BCI, Q and DF. Although including more and complex terms increased the model complexity but in the present study considering BCL as an exponential function of R and as an implicit function of Z and R (ZR) improved the quality of the model significantly. The values of 0.94, 1.14, 1.06, 11.39 for R2, χ2, RMSE and MRDM, respectively, gave the best model. The results showed, considerable accumulation of fines occurred at the center of the silo which increased with increase of level of Z. Also, low concentration of fine occurred at the periphery of the silo especially at higher levels of Z. It means that maximum non-uniformity of fine distribution occurred at higher levels of Z. The present study investigated distribution of fines during filling affected by main parameters namely, initial BCFM, volume flow rate and fill pipe diameter in a pilot scale silo. A new procedure was developed for measuring the fine material along radial and vertical directions. Distribution of fine was modeled using a developed equation considering the effects of main parameters. The results showed that distribution of fine becomes more uniform with decreasing height and increasing initial BCFM, volume flow rate and fill pipe diameter.

Long drying time and high energy consumption are the big problems in paddy drying using conventional batch type dryer. Besides, non-uniformity occurs in paddy rice dried and low milling quality. Paddy is over dried in lower layers and broken kernel chance increased in milling process. Using of a new pattern for warm air causes to better air passing through the paddy bulk and uniformity of drying. Computational fluid dynamics (CFD) is a good method for modeling of air passing in dryers in order to find better air condition in paddy drying process. The aim of this research was investigation on common and porch patterns applied for air entrance to paddy bulk in a dryer in order to optimize air channel conditions in a conventional paddy dryer. In this study, optimization of air flow was investigated in a batch type paddy dryer using computational fluid dynamics (CFD). Two patterns as conventional and porch (reverse V type) patterns were applied for air entrance to paddy bulk in the dryer as conventional and porch (reverse V type) patterns. Experimental examination were done using a laboratory batch type dryer with chargeable air flow pattern in 50 °C for drying paddy (Tarom-Hashmei Var.). Numerical simulation of air velocity and pressure drop in porous media of paddy in the dryer was achieved by employing computational fluid dynamics method and Fluent software. Air velocity pattern and temperature changes in bulk of paddy were investigated in different time of solution including 20, 100, 1000, 1800, 3600 and 7200 seconds for both patterns. Considering air flow and temperature as constant, the results showed the porch type pattern has better performance than the conventional pattern for air passing in the dryer. The velocity vortex was higher in all parts of the channel in the porch scheme. Air velocity uniformed decreased from beginning to end area in the conventional pattern, but in the porch type pattern, air velocity was more in the end of the duct than beginning area. Pressure drop was about 10 percent in the conventional pattern than porch pattern. At the end of the air channel, this variation inversed due to contact of the air with the end wall and pressure drop in this part of the chamber of porch scheme was higher than the conventional one. Improvement of air flow in paddy occurred in low and middle layers in the porch type pattern and there was no difference between two air passing patterns in top layers. Validation of modeling showed that temperature disturbance of the porch model was more uniform than the conventional model and difference between temperatures of model and experiments was about 2 to 3 °C. The research concluded that using of the porch type pattern had better performance than the conventional pattern for air passing in the dryer but it is needs to more supplementary research to find the best height and angle in the paddy dryer. Porch type pattern causes to more speed and uniformity of air among of paddy than the conventional pattern. This improvement observed in low and middle layers of the paddy bulk. Validation of temperature data showed that the difference between experimental and modeled data was 4 to 6 percent and this difference was higher in the conventional pattern than the porch pattern. According to the results of this research, Porch pattern can be recommended to use in the conventional batch type dryer.

Olive is one of the plants, that has been cultivated for long in Iran. The average extracted oil is about 65 kg per tree. Four to five kg olives give approximately one liter oil. Olive harvesting problem, is one of the obstacles to development cultivation in Golestan province. Concurrency olive harvesting time with a number of field crops, seasonal precipitation and a lack of the workers are some limitations for development of this fields. Investigative study of the alternative methods instead of the traditional can be desirable strategy for cultivation development of this product. But gardeners are not eager to use this equipment due to lack of harvesting machine. With regard to the afore-mentioned items, the objective of this study was to determine the appropriate method, the optimal time and interaction effect of the two afore-mentioned factors on the measured traits in order to damage reduction during harvesting time. This research was conducted with the two factors, i) date of harvesting and ii) harvesting method. In this regard, harvesting operation carried out at the three dates including; i) 19 December, ii) 3 January and iii) 18 January in 2015. At the three afore-mentioned harvesting dates; olives were harvested with the three methods including; i) traditional (hitting with the long wood by worker), ii) manual comb and iii) motorize pneumatic comb shaker. The measured traits during operations before and during the harvesting time were the abscission naturally percentage, at the start and the end of the harvest, amount of harvesting (harvested fruit percentage), the remaining fruits percentage on the tree, damaged fruits percentage and damaged fruit index. The experimental design carried out in this research was a split plot based on the randomized complete block design, with three replications. The main plots attributed to olive harvesting time at three levels. The sub-plots attributed to types of olive harvesting method at three levels. After sampling and data collection, the data were set in the Excel software. The obtained data analyzed by using SAS software. Analysis of variance (ANOVA) and comparison of means extracted from the output of analysis of the data with a probability level of 5%. Interaction effect of harvesting time and harvesting method on maturity index was significant at 1% level (Table 1). The lowest and highest value of maturity index occurred at the time of 19 December and 18 January (2.28 and 4.07), respectively. The effect of harvesting time on naturally abscission percent was significant at the 5% level. The lowest (1.16) and highest (2.21) naturally abscission attributed at the time of 18 December and 18 January, respectively.
The effect of harvesting method on the percentage of the remaining fruits on the tree was significant at the 1% level. The lowest (2.71%) and the highest (5.89 %) value of the remaining fruits occurred in the manually comb and traditional methods, respectively.
The effect of harvesting method on the amount of remaining fruit on the tree per kg of harvesting was significant at the 1% level. The highest (62.86 gr) and the lowest (27.92 gr) value of this trait yielded in the traditional and manually methods, respectively.
Interaction effect of the harvesting time × harvesting method on the damaged fruits was significant at 1% level. The highest and the lowest values of the damaged fruits took place in 19 December and in the traditional and the manual comb methods, respectively.
The effect of harvesting time on abscission leaf percent was significant at the 1% level. The highest value of 13.2% and the lowest value of 4.47% occurred in 18 January and 19 December, respectively.
Interaction effect of harvesting time and harvesting method on the damaged fruits index, was significant at the 1% level in 18 January. The highest (1.002) and the lowest (0.424) yielded in traditional and manually comb methods, respectively. The results showed that in order to percentage of remaining fruits on the tree, remaining amount on the tree per kg, damaged fruit and damaging fruit index, the best method of olive harvesting is the manually comb method. The lowest percentage of leaves abscission naturally occurred on 19 December. The Lowest percentage of leaf abscission was on 18 January. So the best of olive harvesting method (variety Koroneiky) in the study area, the use of manual comb with maturity index 3.58 is suggested.

The texture of fresh fruit is determined by the structural and mechanical properties of tissue. It depends on climate, maturity, variety and postharvest condition. During ripening, due to loss of turgor, degradation of starch and cell walls, the flesh of apple softens. The relationship between fruit quality and its physiological changes has been widely investigated. Using techniques according to the principles of force-deformation, impact, and vibration tests, texture of fruit and its mechanical properties can be associated, conventionally. In analyzing the vitality of biomaterials; a non-invasive technique based on the optical phenomenon is the Biospeckle method which occurs when the surface of the sample is illuminated by laser light. It seems that because of the fact that the laser light can penetrate tissue, it is possible to obtain information about the texture and cell condition from tissue under the skin. This means that, there would be a chance to detect and monitor the variation of cells and try to make a model to predict mechanical properties. Therefore, the overall objective of this study was to develop prediction models based on biospeckle imaging to predict mechanical properties of ripe Golden Delicious apples. The 400 fresh and intact 'Golden Delicious' apples were harvested and were prepared for mechanical tests and biospeckle imaging. Biospeckle imaging was carried out first, followed by compression and creep test and then penetration test. During imaging, to avoid environmental reflections, the process was carried out in a dark and closed chamber. Biospeckle activity was saved as a video (AVI format) in a computer for analyzing. The THSP method was used to analyze biospeckle activity in samples. The indices which have been used for analyzing biospeckle images are divided into 3 statistical features and 4 textural features.
Apples were cut in half. One of the halves was used for cylindrical sample extraction for uniaxial compression and creep tests and another was used for penetration test. From compression tests the tangent modulus of elasticity, stress and strain of bio-yield and failure energy for toughness calculation were determined. The creep behavior was obtained by fitting the Burger's model to the experimental data. In penetration test, a stainless steel probe with a hemispherical tip was used for peeled and unpeeled samples. For each sample maximum penetration force and energy were obtained.
Prediction of mechanical property was carried out using adaptive neuro-fuzzy inference system (ANFIS). To reduce the dimension of the input vector the PCA was used. Four significant adjustments were made in the structure of ANFIS in order to find the best models. The models were evaluated using RMSECV, RMSEP, MBEC, MBEP, RC, and RP. Models for modulus of elasticity prediction have Rp=0.821, 0778, 0.791, 0.880, and 0.843 for 4 compression rate and secant modulus, respectively. Clearly, the results from this research are encouraging, indicating the potential of using speckle imaging system for predicting apple fruit mechanical properties. Comparing to the all texture analysis techniques, Wavelet and GLRLM provided good results for most properties leading to select them as the best techniques for analysis of biospeckle images because of their consistency in prediction performance. Prediction model for break strain has the highest Rp (Rp=0.920) followed by the retarded time (Rp=0.890), retarded viscosity (Rp=0.886) and maximum penetration force in unpeeled case (Rp=0.883). A lower correlation (Rp = 0.728) was observed for initial viscosity. The described optical method based on biospeckle represents an innovative and reliable method for rapid and non-invasive detection of mechanical properties. The results of the evaluation showed that, as time passes, fresh apples due to the loss of water in both the elasticity and the biospeckle activity were dropped. Biospeckle imaging can accurately predict mechanical properties. The average accuracy of best prediction of mechanical properties models was R2=0.899. The present results can provide the basis of future development of in-line quality monitoring during apple quality control.

One of the most important factors in agricultural production is nitrogen which has a great impact on plant growing, yield performance and plant quality production. The optimum amount of nitrogen fertilizer is varied from fields to fields. There are some time consuming and costly ways to measure the nitrogen content of plants or soil, which are inappropriate for extended field or for a long growing season. Fast and remote optical sensors calculate greenness of plant using reflectance or absorbance of light from green leaves. Measuring chlorophyll with SPAD managed the nitrogen requirement for maize, Poinsettia and Nagoya Red. Whereas SPAD was not a suitable choice for chlorophyll measurement at the end of growing period. Therefore, GreenSeeker was applied as a non-contact to record the NDVI of tomato’s and cucumber’s leaves. The purpose of this research was the evaluation of GreenSeeker ability to estimate nitrogen requirement and then the plant health. The study was performed on Matin and Nahid cultivars of tomato and cucumber, respectively. The pots were 291 and filled with 3 kg sieved soil. The bottom layer of each pot was filled with stone for better drainage. Before planting, the soil was analyzed in order to define the ingredients. All pots put in the greenhouse with polycarbonate structure in two floors. Measurements were repeated every week with SPAD and GreensSeeker and fertigation was started 50 days after planting (DAP). In order to provide other nutrient elements, all pots got Humic-acid at 37DAP and the effect was measured in 43rd DAP. Fertigation was continued until 71st DAP and first, second and third treatments were supplemented with extra fertilizer to reach the amount of fertilizer to fifth treatment. To calculate Total Nitrogen (TN), the concentrations of nitrate-N and nitrite-N are determined and added to the total Kjeldahl nitrogen. Chlorophyll meter (SPAD) and GreenSeeker optical sensor have become available for site-specific and need-based N management in greenhouse. The GS was located at 60 cm above the plant and measured the average NDVI. This sensor has red and NIR diodes which reflect and absorb the spectra in 660±15nm and 770±15nm regions, respectively. The SPAD values were recorded by inserting the middle portion of the index leaf in the slit of SPAD meter. As well as, chlorophyll meter can confirm the GreenSeeker output (NDVI). GreenSeeker is a suitable optical sensor because it is not affected by light and temperature variation or wind intensity.
Statistical analyses were performed on the pooled data of both tomato and cucumber using Statistical Product and Service Solutions (SPSS). Regression equations were fitted between fertilizer and the readings recorded with different gadgets at different growth stages. Chlorophyll content and NDVI of tomato and cucumber increased during the growing stages except in 71st DAP for cucumber. The percentage of total nitrogen of 1st, 2nd and 3rd treatments were further than two others because of supplementary fertilizer. According to the Kjeldahl result of cucumber, the 3rd treatment had the lowest nitrogen accumulation in fruits. In addition, chlorophyll and NDVI of cucumber almost showed the increasing correlation by fertilizer enhancement while the opposite behavior was seen for tomato. That would be related to different fertilizer needs of them. The linear regression of fertilizer and reading NDVI of 2nd to 5th treatments were ascending. The number of increasing leaves was calculated in all pots every weeks as another studied element. Each pot had new grown leaves every weeks that was more or sometimes less than last weeks. However, accurate correlation coefficient was reported with NDVI in all treatments, whereas chlorophyll did not show a direct relation. The result of the study confirmed the useful GreanSeeker as an accurate and fast technology for prediction of NDVI. Among different fertilizer treatments of cucumber, 3rd one showed the acceptable results. Since tomatoes did not reach to fertility stage, it would not possible to extract the best nitrogen fertilizer treatments. It is obvious that evaluation of pots in complete growth stages reach us to codify manual fertilization.

Garlic (Allium sativum L.) is an important Allium crop in the world. Due to its therapeutic properties, it was cultivated in many countries. Furthermore, garlic is usually used as a flavoring agent; it may be used in the shape of powder or granule as a valuable condiment for foods. In addition to its use in food products, it was also widely used as an anticancer agent. Shallot (Allium hiertifolium Boiss. L) is a perennial and bulbous plant. It is from Alliaceae family and is an important medicinal plant. The shallot is native of Iran, and grows in the high pastures. Shallot is consumed in dry areas in most parts of the country. Also shallots have been well known in Iranian folk medicine and its bulbs have been widely used for treating rheumatic and inflammatory disorders. In addition, this plant is used in the preparation of significant amounts of potassium, phosphorus, calcium, magnesium, sodium, pickles and as an additive to yogurt and pickles. ANN as a modern approach has successfully been used to solve an extensive variety of problems in the science and engineering, exclusively for some space where the conventional modeling procedure fail. A well-trained ANN can be used as a predictive model for a special use, which is a data processing system inspired by biological neural system. When mathematical equations are difficult to extrapolate, and fuzzy logic is better when decisions must be made with the estimated values below the incomplete information. The fuzzy logic theory effectively addresses the uncertainty problems that solve the ambiguity. The aim of this study was to predict moisture ratio of garlic and shallot during the drying process with fluidized bed dryer using mathematical model, artificial neural networks and fuzzy logic methods. Tests were carried out on three levels of inlet air temperature (40, 55 and 70 °C) and three inlet air velocities (0.5, 1.5 and 2.5 m/s). To estimate the drying kinetic of garlic and shallot, five mathematical models were used to fit the experimental data of thin layer drying. Three factors (air temperature, air velocity and drying time) to forecast moisture ratio in fluidized bed dryer as independent variables for artificial neural networks and fuzzy logic was considered. Cascade forward back propagation (CFBP) and feed forward back propagation (FFBP) with Levenberg-Marquardt (LM), Bayesian learning (BR) algorithms for ANN and the Mamdani Fuzzy Inference System using triangular membership function were used for training patterns. Consequently, the Page and Midilli et al. model was selected as the best mathematical model to describe the drying kinetics of the garlic and shallot slices, respectively. The results of artificial neural networks model for predicting MR showed that the R2 of 0.9994 and 0.9996; and and RMSE of 0.0036 and 0.0014 were obtained for garlic and shallot, respectively. Also, The fuzzy inference system presented the R2 of 0.9997 and 0.9998; and and RMSE of 0.0027 and 0.0011 for garlic and shallot, respectively. Comparing the results obtained from mathematical models, artificial neural networks and fuzzy logic, showed that the RMSE in the fuzzy logic was lower than artificial neural network and mathematical models. Three factors (air temperature, air velocity and drying time) were considered for forecasting moisture ratio in fluidized bed dryer as independent variables using mathematical model, artificial neural networks and fuzzy logic. Cascade forward back propagation (CFBP) and feed forward back propagation (FFBP) with Levenberg-Marquardt (LM), Bayesian learning (BR) algorithms and the Mamdani Fuzzy Inference System using triangular membership function were used for training the patterns. Comparing the results obtained from mathematical models, artificial neural networks and fuzzy logic, showed that the root mean square error in fuzzy logic was lower than others.

Convective air drying is one of the oldest and most popular drying methods. Designing and controlling the convective air drying needs the mathematical description of the moisture transfer during the drying process, known as drying kinetics. Fick’s second law of diffusion can be used for modelling the moisture distribution inside the moist object during drying process.
Mathematical modeling of drying process is a very important tool, as it contributes to understand better moisture distributions inside the product which helps designing, improving and controlling drying operation in the food industry.
Implementation of the partial differential equations subject to the correspondent initial and boundary conditions is one of the main methods of mathematical modeling to describe the physical phenomena such as moisture transfer during drying. In the recent decades, considerable number of research works have been devoted to numerical solution of mass transfer phenomena during convective drying of food products by using the common numerical solution such as FDMs, FEMs and FVMs.
The spectral collocation (pseudospectral) methods is a powerful tool for the numerical solutions of smooth PDEs like mass transfer equations. Pseudospectral methods are able to achieve the high precision with using a small number of discretization points compared to FDMs and FEMs and with low computational time and computer memory.
The objective of present research is to simulate the mass transfer phenomena in one dimension during convective drying of apple slices. The validation of the presented numerical model was done by comparing experimental drying data taken from Kaya et al. (2007) and Zarein et al. (2013). For more confirming the numerical approach, a numerical example with the exact solution is provided and the related errors were evaluated. Estimation of mass transfer coefficients
The convective mass transfer coefficient in the surface of the apple slice was obtained according to the relationship presented by Paitil (1988) and Janjai et al. (2008).
(1)
Estimation of effective moisture diffusivity coefficient
Fick’s second law of diffusion was applied to obtain the effective moisture diffusivity coefficient of the apple slices. The analytical solution of this equation can be written as follows (Crank, 1975): (2)
In this study, we consider the Pseudospectral methods for solving 1D mass transfer equation. In order to develop the model, the following common assumptions are considered: negligible heat changes during drying process, moisture is transferred inside the slices by diffusion, one-dimensional mass transfer in apple slices, non-shrinkage and non-deformation of the slice. In the field of numerical analysis, the main advantage of pseudospectral methods compared to others such as FDMs and FEMs are exponential convergence and sufficient accuracy (Sun et al., 2012). The values of parameters and coefficients of mathematical model are summarized in Table 1. The comparisons between the predicted average moisture content and the experimental data are shown in Fig. 1 & 2. It can be seen, the numerical results are in good agreement with the experimental data. The values of the correlation coefficient and the root mean square error from comparison of numerical result with experimental data taken from Zarein et al. (2013) and Kaya et al. (2007) were 0.9996, 0.0729 and 0.997, 0.1561 respectively. Moreover, the running time for solving 1D mass transfer equations was about 3 seconds. This result is the evident that the presented model is successful for predicting the moisture content history during drying process.
Moreover, by using the considered numerical method the approximate solutions of defined numerical example for different discretizing points was evaluated and the associated error history are shown in Figure 3. It can be seen that the values of errors are very low and about 10-3 and 10-5, that confirms the high accuracy, robustness and efficiency of the suggested numerical approach. Spectral collocation (pseudospectral) method is presented to solve mass transfer equation in one dimensional in during convective drying process approximately. The model was validated by the reported experimental data from convective drying of apple slices. Also, a numerical example, which had an exact solution in a closed form, was provided to illustrate the high accuracy of the proposed method. The results of statistical computations ( and ) and numerical example showed the efficiency, applicability and robustness of the presented approach.

Nowadays the packaging of a product is considered as a symbol of its quality and has a direct effect on its consumer-satisfaction and sales. The visual inspection method is much slower and more error-prone than that of automated method which is used for mass production. Also, this method has other problems such as high labor cost, fatigue, low accuracy, and inconsistency due to various environmental conditions such as lighting, or lack of concentration as well as lack of standards and skilled worker. Machine vision has different applications in the industry. In the packaging of liquid such as cooking oils and different beverages (mineral water, soft drinks, fruit juices ...) that liquid can leak out. So, inspecting cap defects, seal ring defects and liquid level are urgent. Also, label placement plays an important role in customer satisfaction. Machine vision can be able to detect these defects; therefor its application will be effective and useful. So, the advantages of machine vision are non-destructive, accurate, and consistent. Researchers have been used the machine vision system for different area including inspection of surface and structural flaw inspection; steel strips and pharmaceutical tablets. Also, machine vision was used for online control of grading and separation of different agricultural products, such as kiwi, pomegranate, dates, cucumber, almonds, potatoes, tomato and peach. The aim of this research was to manufacture and application a system based on machine vision for inspection and classification of defects in bottles on production lines (case study: soft drink). Sample quality was included of three defects: cap defaults, liquid level and label placement. 300cc Coca Cola bottles were used as samples for this research. The research was performed to inspect the common defects, including of the cap defaults, liquid level and label placement. In this research, a bottle classification system was designed and developed which it consists of hardware and a software unit. The hardware includes of a conveyor belt, a power system and a power transmission unit, light source, a digital camera, a mechanical ejector and a computer. In this project Lab view 2011 software was used. In this online system, decision was done based on Boolean logic and the defected bottles were separated from the normal ones. For image acquisition and algorithm design the different steps were followed: Vision acquisition, image processing and programming. Clamp (Rake) function was used for inspection of liquid level. It calculated the maximum distance between the cap and liquid level and its result was compared to the edge strength and threshold level. Inspection of cap defaults and label placement was performed using pattern matching and edge detection algorithm, respectively. The appropriate time of ejector must be calculated to take defective samples out of the production line. Research results were reported at four parts including of cap defects, liquid level and label placement inspection furthermore the combination of all three groups. To find of inspection accuracy, it was repeated 100 times for each default. Accuracy of inspection of the cap, label placement and liquid level were earned as 95, 90 and 100%, respectively. The average accuracy of system was 95.6%. With regard to the conveyor belt’s speed (20cm s-1) and the distance (10cm) between the bottles, the required time to inspect each bottle was 500ms. So, program’s performance was acceptable according to process time of 150-250ms. Finally, the operational capacity of the system was 7200 bottles per hour. These findings were similar to results reported by other researchers. They reported the accuracy of 97 and 90.61% for beer bottles inspection and tomatoes separating, respectively. Average of total accuracy for this system was obtained as 95.6%. It separately was 100, 95 and 92% for inspection of liquid level, cap, and label placement, respectively. The highest and lowest accuracy were for inspection of liquid level and label placement. So, performance of the algorithm was suitable for use on production lines. Also, it will be applicable to liquid packaging in the food industry, chemical industry and so on.

Presently, the loss of ground water levels and the increase in dissolved salts have given importance to the determination of salinity and the management of their variations in irrigated farms. Soil electrical conductivity is an indirect method to measure soil salts. The direct electrode contact method (Wenner method) is one of the widely used methods to rapidly measure soil ECa in farms. However, soil scientists prefer soil actual electrical conductivity (saturated extract electrical conductivity) (ECe) as an indicator of soil salinity, though its measurement is only possible in the laboratory. The aim of this study was to find a relationship between the prediction of soil actual electrical conductivity (ECe) in terms of temperature, moisture, bulk density and apparent electrical conductivity of soil (ECa). Thereby, the estimation of ECe would allow the partial calculation of ECa that is dependent upon soil salinity and dissolved salts. This study used RBF neural network in Box-Behnken statistical design to explore the impacts of effective parameters on direct contact method in the measurement of soil ECa and provided a model to estimate ECe from ECa, temperature, moisture content and bulk density. In this study soil apparent electrical conductivity (ECa) was measured by direct contact (Wenner) method. The present study considered four most effective factors: ECa (saturated paste extract EC), moisture, bulk density, and temperature (Baradaran Motie et al., 2010). Given the characteristics of farming soils in Khorasan Razavi Province (Iran), the maximum and minimum of each independent variable were assumed as 0.5-6 mS.cm-1 for ECe, 5-25% for moisture content, 1-1.8 g.cm-3 for bulk density, and 2-37°C for soil temperature. Considering the experimental design, three moisture levels (5, 15 and 25%), three salinity levels (0.5, 3.25 and 6 mS.cm-1), three temperature levels (2, 19 and 37°C) and three compaction levels with bulk densities of 1, 1.4 and 1.8 g.cm-3 were assumed in 27 trials with predetermined arrangement on the basis of Box-Behnken technique. 13 common algorithms were explored in MATLAB software package for the training of the artificial neural network in order to find the optimum algorithm (Table 4). The input layer of the network designed by integrating a Randomized Complete Block Design (RCBD) with k-fold cross-validation. Using k-fold cross-validation, 20 different datasets were generated for training and validation of RBF neural network. A combination of an RCBD and k-fold cross-validation was used. The results of both training and validation phases should be considered in the selection of training algorithm. In addition, R2 of T1 training algorithm had a much lower standard deviation than other training algorithms. The lower standard deviation is, the more capable the algorithm would be in learning from different datasets. Considering all aspects, trainbr (T2) training algorithm was found to have the best performance among all 13 training algorithms of the neural network. Table 7 tabulates the results of means comparison for R2 of RBF model for both training and validation phases resulted from the application of some combinations of S and L2 factors as interaction. As can be observed, R2 = 0.99 for all of them with no significant difference. However, the magnitude of order differed between training and validation phases. Given the importance of the training phase, L2=9 and S=0.1 were regarded as the optimum values.
The sensitivity analysis of the network revealed that soil ECa, moisture, bulk density, and temperature had the highest to lowest impact on the estimation of soil ECe, respectively. This model can improve the precision of soil ECa measurement systems in the estimation and preparation of soil salinity maps. Furthermore, this model can save in time of data analysing and soil EC mapping because it does not need data recollection for the calibration of systems. A validation prose was done with a 60 field collected data set. The results of validation show R2=0.986 between predicted and measured ECa. The present research focused on improving the precision of soil ECe measurement on the basis of easily accessible parameters (ECa, temperature, moisture, and bulk density). In conventional methods of soil EC mapping, the systems only measure soil ECa and then calibrate it to ECe by collecting some samples and using statistical methods. In this study, Soil ECe was estimated with R2 = 0.99 by a multivariate artificial neural network model with the inputs, including ECa, temperature, moisture, and bulk density of soil without any need to collect further soil samples and calibration process. The Bayesian training algorithm was introduced as the best training algorithm for this neural network. Thereby, soil EC variation maps can be prepared with higher precision to estimate the spatial spread of salinity in farms. Also, the results imply that soil ECa, moisture, bulk density and temperature have the highest to lowest effectiveness on the estimation of soil ECe, respectively.

In recent years, the exergy analysis method has been widely used in the design, simulation and performance assessment of various thermal systems. In this regard, this method may be applied to various types of engines for identifying losses and efficiencies. This analysis is based on the second law of thermodynamic. Exergy is a potential or quality of energy. It is possible to make sustainable quality assessment of energy. In this study, the second law of thermodynamics is employed to analyze the quantity and quality of exergy in a fourstroke, four-cylinder, diesel engine using diesel fuel and biodiesel fuel. Four experiment variables in the present study including the operating parameters, load and speed, and the added volume of biodiesel of diesel fuel were considered as effective factors on the Break exergy efficiency. Designs that can fit model must have at least three different levels in each variable. This is satisfied by Central Composite Rotatable Designs (CCRD). Similar to the case of the energy analysis, the same assumptions were valid for exergy analysis; the whole engine was considered to be a steady-state open system. For exergy analyses, the entire engine was considered to be a control volume and a steady-state open system. Fuel and air enter, and mechanical work, heat loss and exhaust gases leave the control volume at a constant rate. The exergy balance for the control volume can be stated as.
where is the exergy transfer rate associated with the heat loss from the control volume to the environment, assumed to be through cooling water; is the exergy work rate, which is equal to the energetic work rate; is the mass flow rate; is specific flow exergy; and is the exergy destruction (irreversibility) rate. exergy efficiency increased with increasing engine load. This relationship could be attributed to the reason that brake power increased with increasing engine load, and the other side, there was a positive direct relationship between brake power and exergy efficiency, resulting in an increase of exergy efficiency. Although fuel consumption increased along with increasing engine load, increase in the brake power was much greater than increase in the fuel consumption. On the other hand, an increase in the engine load enhanced combustor temperature which was provided an appropriate condition for combustion and caused an increase in cylinder pressure. At all engine operating conditions, with increasing engine speed, the thermal efficiency at first increased, at moderate speed reached to a maximum amount and finally with more increase in engine speed, the thermal efficiency decreased. The initial increase in thermal efficiency could be attributed to the increase in air to fuel ratio and engine torque which caused an increase in the brake power. Decreasing thermal efficiency in high levels of engine speed could be caused by a decrease in volumetric efficiency of the combustion chamber, because of the time limit on filling cylinder. With increasing biodiesel concentration in the fuel blend, exergy efficiency decreased. The reason could be due to the lower calorific value and the higher viscosity of biodiesel compared to diesel fuel. At all engine operating conditions, the exergy efficiency of the engine increased with increasing engine load also with increasing percentages of biodiesel into synthetic fuel, exergy efficiency increased. 43.09% of the fuel exergy was completely destructed and was not convertible to work. The results of optimization indicated that the most exergy efficiency (37.72%) was occurred for the pure diesel at 2036 rpm and 95% load.

Tillage as a preliminary step for agricultural production consumes large amounts of energy. Regarding the energy crisis and the greenhouse gas emissions caused by the indiscriminate use of fossil fuels, many efforts have been done to reduce energy consumption as much as possible. About half of the energy used in the crop production has been dedicated to tillage operations; hence the optimization of tillage tools performance can lead to decrease the energy loss. Tillage operation in most regions of Iran is carried out by moldboard plow. The ability of this plow in turning the soil has made it impressively different from the other plows. The energy used in tillage operations depends on various factors such as soil type and its conditions (soil moisture and texture), plow depth and forward speed. The aim of this study is to investigate the effect of forward speed, plow depth and soil moisture on fuel consumption and required tensile force during tillage operation with a moldboard plow which uses three plows in clay soil. The current study was carried out to optimize the tillage operation with a moldboard plow in the clay soil. Tillage experiments were performed to evaluate the effect of forward speed, plow depth and soil moisture content on the required tensile force and tractor fuel consumption. A moldboard plow with three single-sided plows was used to conduct experiments. Two tractors (MF285 and U650) and a dynamometer were used to measure the required tensile force. To measure the fuel consumption of the tractor during operation, the fuel level was measured in a separate tank system installed on the tractor's fuel system.
Experiments were carried out using response surface method and central composite design (CCD) by taking three levels of forward speed (4, 5 and 6 kmh-1), three plow depth (20, 25 and 30 cm) and three levels of soil moisture content (12, 16 and 20%). Design Expert 8.0.6 software was used to analyze the experimental data. The result of the analysis of variance showed that the effects of plow depth, forward speed and soil moisture, as well as the interaction between forward speed and moisture content on the fuel consumption during tillage operations with moldboard plow are significant. The results also indicated that the increase in forward speed decreased the fuel consumption. Also, fuel consumption decreased with increasing in moisture content at first, but then increased. The reason for this was probably because of the increased strength of soil particles due to the reduced moisture content (the stronger coherence force between the particles), which required more energy to shear the soil.
According to the results of analysis of variance, it can be concluded that all three factors of forward speed, plow depth and soil moisture had a significant effect on the required tensile force of moldboard plow at %1 probability level. With increasing the plow depth and forward speed, required tensile force increased significantly. The dependent variables were modeled as second order regression equations and optimal values of independent variables were determined. Optimum performance with maximum desirability was determined at forward speed of 5.08 kmh-1, plow depth of 20 cm and soil moisture content of 16.41%. With increasing plow depth, tensile force and fuel consumption increased. Also, tensile force increased with increasing forward speed, but this increase was not severely affected by the plow depth and reduced the fuel consumption. The quadratic regression models can well predict the required tensile force and fuel consumption. Using response surface method, optimum performance was determined at forward speed of 5.08 kmh-1, plow depth of 20 cm and soil moisture content of 16.41%.

Today, grapes are cultivated in a vast zone worldwide. Grapes are among the major horticultural produced in Iran and the country is ranked 10th in the world for the grape production. Therefore, efficient use of energy from this crop is very important. Energy is one of the principal requirements for the economic growth and development of agriculture. Scientific forecasts and analysis of energy consumption will be of great importance for planning the energy strategies and policies. The enhancement of the energy efficiency not only helps in improving competitiveness through cost reduction but also results in minimized greenhouse gas (GHG) emissions and environmental impacts. In other hand, energy analysis in the crop production systems enables to identify the effective farming system in different farm size with respect to energy parameters. Based on mentioned points, the objective of this study was to evaluate the energy flow of grape production in three sizes (small, medium and large) of land and then, the life cycle of the production in Hazavah Region of Arak city, Iran. In this study, data were obtained from 58 growers using face-to-face questionnaires in Arak county of Iran. Orchards were selected using stratified random sampling. Investigation of the energy flow in a production system necessitate calculating input–output energies. In order to deal with this part, energy coefficients were taken into account to convert all agricultural inputs to their energy equivalent. In other words, each input was converted to its energy equivalent by multiplying the application rate of agricultural inputs used within the system by its energy coefficient. In order to evaluate how efficient, the system under study is, some well-known indicators have been introduced and widely applied when a production system is appraised. In this study, a life cycle approach was used for assessment of environment impacts of the grapes production. Life Cycle Assessment (LCA) refers to the process of compiling and evaluating the inputs, outputs and the potential environmental impacts of a product system throughout its life cycle. Goal and scope definition, inventory analysis, life cycle impact assessment and life cycle interpretation are four mandatory steps, which should be followed in a full LCA study. The characterization factors used in this study were adapted from Simapro software which is linked to EcoInvent database. On average, the values of consumed and produced energies were 1854 MJ ton−1 and 11800 MJ ton−1, respectively. Among all input energies, chemical fertilizers held the first rank with an amount of about 704 MJ ton−1. It accounted for 38% of the total energy used in the production season. Energy use efficiency, which is a ratio between output and input energy, was calculated as 5.75. Also, the energy productivity was estimated as 0.48, meaning that 0.48 kg grapes is produced when one MJ energy is consumed. The total Global Warming (GW) was calculated as 508.63 kg CO2 eq. ton−1. The farm size had an influential effect on the GW and other impact categories. An increase in the farm size led to reduction in the environment impacts. It means that the value of GW for large farms fell at 498.68 kg CO2 eq. ton−1 and the value of GW for small farms fell at 698.69 kg CO2 eq. ton−1. The upshot was that GW and other impact categories for large farms were significantly less than its counterpart in small farms due to the high value of grapes produced in large farm groups. Impacts of manure played a more important role on GW. Also, direct emissions of chemical fertilizers made high contribution to acidification and eutrophication. Management of using chemical fertilizers can be an appropriate way to reduce the acidification, eutrophication and other environmental impacts on the grape production. Chemical fertilizers (38%), demonstrated their pivotal roles in total energy consumption. The direct emissions in the grape production resulted from high application of chemical fertilizers contributed considerably to some environmental impacts. It suggested establishing a sustainable and environmental friendly grape production system in the region with application of efficient fertilizers by integrated nutrient management.

Geographical location and climatic conditions are the important factors affecting the wind energy potential of each region. Iran is a vast country with different climates and the exploitation of its wind energy needs to study and research on the meteorological data. In the study area during the warm season and the hottest hours of the day, coinciding with peak electricity consumption in the region and the country, wind blowing continuously carried out. The surpassed consumption over production of electricity in summer and vice versa in winter is considered as one of the country's problems. The aim of this study was to investigate the parameters of the wind energy and the feasibility of wind potential (in study area) in the warm season in particular and other seasons to supply the needed electrical power of area, avoid of unwanted blackouts, development of wind energy as an important renewable energy, attraction of investors, and policymakers to build wind farms in the study area. This study was conducted in the Dehloran city, located in the southern part of Ilam province. The region has a temperate winter and very hot and dry summer. The important criteria for construction of wind power plants and using of its energy are wind power density and the annual wind speed average. For this reason and analysis, and statistical analyzes, wind data includes three-hour direction and speed were obtained from the meteorological organization and during 2004 to 2013. The average of annual, monthly and daily wind speed and their standard deviation were calculated. Based on the commercial turbines in the country, and the rotor blades are at altitudes up to about 80 meters, the wind speed at altitudes of 40, 60 and 80 meters was calculated. To evaluate the potential of wind speed the Rayleigh and Weibull distribution functions were used and their parameters were calculated. The wind energy potential using the available data and the Weibull and Rayleigh functions were calculated. Based on the results of the ten-year data, average of wind speed had relatively slight variation, with the highest and the lowest value of 3.6 and 3.25 m/s in 2007 and 2010, respectively. The annual average was about 6 m/s in height of 50 meters that seems appropriate. The highest and the lowest monthly average values were 4.62 m/s and 2.24 m s-1 in June 2005 and November 2006, respectively. Generally, the warm months had significantly higher wind speed than that of cold months. The Weibull distribution function parameters, k and c were calculated. Minimum and maximum amount of k were 1 and 1.828, in December 2006 and May 2011, respectively. The minimum and maximum amount of c was 2.37 and 5.69 in November 2004 and June 2013, respectively. The highest value of wind power density was 312 w m-2 in June. The lowest power density was observed in November. Therefore, we can say that the wind energy potential of the region has coincident with peak electricity consumption in the warm months. The most frequent and the least frequent wind direction were the southeast and northeast, respectively. Daily evaluation of wind speed during different months, seasons and years showed a significant change during the day that represented the high value of the wind speed in noon and afternoon. The highest value of monthly wind energy density was for the warm season. The lowest and highest power density was in November and June, respectively. Therefore, we can say that the peak of wind energy potential of the region has a coincident with the country's peak power consumption in warm months. With considering that the study area has a warm climate and high consumption of energy in the hot days of a year and the probability of unwanted blackout of electricity in warm months, and the long hours of the wind blowing in the mentioned times, construction of wind farm in these areas can be reasonable.

More than 40 percent of the world population is now dependent on biomass as their main source of energy for cooking. In Iran, the lack of access roads and inefficient transportation structure have made some societies to adopt biomass as the main energy source for cooking. In such societies, inefficient traditional three-wall cook stoves (TCS) are the sole method of cooking with biomass, which corresponds to the large fuel consumption and smoke emission. Biomass gasifier cook stoves have been on the focus of many studies as a solution for such regions. In these stoves, biomass is pyrolized with the supply of primary air. The pyrolysis vapors are then mixed with secondary air in a combustion chamber where a clean flame forms. In this study, a biomass cook stove was manufactured and its performance was evaluated feeding with three kind of biomass wastes (e.g. almond shell, wood chips, and corn cob). A natural draft semi-gasifier stove was manufactured based on the stove proposed by (Anderson et al., 2007). It had two concentric metal cylinders with two sets of primary and secondary air inlet holes. It had 305 mm height and 200 mm diameter. The stove was fed by wood chips, almond shell, and corn cob. Thermal performance of the stove was evaluated based on the standard for water boiling test. It consisted of three phases of cold start, hot start, and simmering. Time to boil, burning rate, and fire power was measured in minute. A “K” type thermocouple was used to measure the water temperature. Emission of carbon monoxide from the stove was measured in three situations (e.g. open area, kitchen without hood, and kitchen under hood) using CO meter (CO110, Thaiwan). Neither particulate matter nor smoke was visually observed during the stove operation except at the final seconds when the stove was going to run out of fuel. The flame color was yellow and partly blue. The average time to boil was 15 min; not significantly longer than that of the LPG stove (13 min). Time to boil in hot phase was almost the same for all fuels which is not in line with the studies reported by (Kshirsagar and Kalamkar, 2014; Ochieng et al., 2013; Parmigiani et al., 2014). This is probably due to the stove body material. In fact, the hot phase test, aims to show the effect of the stove body temperature on the performance. In contrast with the most of the stoves, the one was used in the present study was made of a thin (0.3 mm) iron sheet which has a high heat transfer and low heat capacity. This results in a rapid increase in the stove body temperature up to its highest possible. The longest flaming duration (51 min) was observed by 350 g almond shell. Thermal efficiency on the other hand, was different in using different biomass fuels. The average thermal efficiency of 40.8 was achieved by the stove which is almost three times of open fire. The results from emission test showed that the average of carbon monoxide surrounding the operator in the case of open area, kitchen without hood, kitchen under hood, and traditional open fire were 4.7, 7.5, 5.2, and 430 ppm, respectively. The amount of carbon monoxide emitted to the room is in accordance with the US National ambient air quality standards (NAAQS) hence, compared with traditional methods of cooking in deprived regions, the stove burns cleaner with higher efficiency. In order to prohibit respiratory decreases in housekeeping women, this stove could be disseminated in some deprived regions of Iran.

In this research, a part of the requirements for the establishment of a network of consultancy, agricultural engineering and technical services in the agricultural sector, which is related to the location of these centers, has been reviewed. The location of these centers has been done through the determination of the field of operation and the appropriate establishment of consulting, engineering, and agricultural consulting companies based on regional capacities and taking into account the distance between the types of customers of such centers. In the issue of locating service centers three main types of customer can be classified. First-class customers, which have the largest number among different types of customers, are farms and units that produce agricultural products. Each point of demand for these categories of customers may require different types of services at different times. Due to the large number and dispersion, these category of customers are considered as a focal point for ease of modeling in rural areas where they are located. Also, due to various reasons, including access to various facilities, security, traffic congestion and etc., the nominations for deployment of service centers are also considered in the same rural areas. In order to transport agricultural products from the place of production, the current location is considered to be the distance from the manufacturer's place, and the destination of the product is not studied in this issue. Second and third-type customers are demanding access to services at their own place. These types of customers may exist in some areas and agricultural supply chains. These two groups of customers include refineries, warehouses and silos mainly operating in the post-harvest of agricultural production. To meet the demand for each of the different demand points of different types of customers, the number of different trips from service centers to customer premises or vice versa is required. Each service center does not offer the same type of service to its customers. A total of 127 service packages are available for provision at a service center. The main basis for choosing the optimal location for covering models is the placement of demand points in the defined coverage radius for the candidate points. Different radius were tested to find the perfect coverage radius in each of the studied villages. For this purpose, a radius of five to 160 kilometers was examined. In some coverage radius, not only does the optimal location not change, but the number of served points is also fixed. The location of different types of customers is different, so that the first type of customers are fully located in the village, but second and third type customers are widespread in the Hamedan province. To conclude, it is necessary to consider the demand of customers located in the further distances of the service center due to the nature of the agricultural service, which requires inevitable traffic over long distances, when adjusting the operational plans of the agricultural service centers. To provide sufficient justification for the distance, though within the radius of coverage. Thus, the results of this research show that if all service centers cover 130 kilometers of radius, the largest number of customers will be covered. It should be noted that for the full coverage of all customers, the coverage radius of the service centers varies, but with the same radius, the 130 km radius is the largest coverage of the agricultural service centers in the Razan city.

Understanding the status of tractor power in any region is a key factor in setting a mechanization planning to improve the capacity of mechanized operations. For this reason, it is necessary that the available tractor power in each region meet the needs of agricultural operations in the most demanding time of cropping season in terms of operations related to machinery. The objective of this study is needs assessment and prioritizing the power arrival in the agriculture of Khuzestan province. Required data, such as the number of tractors, areas under crop cultivation, size and number of farmlands, and crop yield were collected from the beginning of the first economic, social and cultural development plan until the end of the fifth development plan. Given to peak of operations, working hours per day and the probability of working days, input power required for each county was calculated. To determine the priorities for arrival power to counties, four criteria, including mechanization level shortage, percentage of obsolete tractors, the harmonic mean of production and area (ha) per tractor ratio (ha/tractor) were applied using TOPSIS-AHP based approach. Technique for order preference by similarity to ideal solution (TOPSIS) is one of the strongest methods in multi-criteria decision making. This method is based on the calculation of geometric distance of alternatives from positive ideal solution and negative ideal solution. Analytical hierarchy process (AHP) was used for weighting to criteria. AHP is one of the most famous multi-criteria decision making methods which has been used to estimate a total score for each criterion, compare indices using pairwise comparison and assess their score for one criterion. AHP is based on the decision-maker experience and knowledge. But since decision-makers rely on their mental ability and experience for doing comparisons, for reasons such as inadequate knowledge and information, complexity of the problem, lack of confidence in decision-making environment and lack of a proper scale, they are not able to express their preferences in the form of pure numbers. So conventional AHP has not enough potential for working based on human thinking style. For solving this problem, the theory of fuzzy sets can be used. Based on the results, 6682 tractors with theoretical power equivalent as 75 hp should be added to provincial fleet to ensure timely agricultural operations in Khuzestan province. The required 75-hp tractor units are 1163, 750 and 742 for Dasht-e Azadegan, Andimeshk and Ahvaz, respectively and Abadan, Khoramshahr, Shadegan, Shushtar, Shush, Andika, Bavi, Behbahan and Hendijan did not need to import any new power due to higher theoretical power available compared to required power. The needs difference of counties came from the difference between counties area under cultivation in the peak work area. Almost there was one tractor per 50-ha area under cultivation in the province. Mechanization level was calculated as 1.2 hp ha-1. Based on the tractor classification by Mechanization Development Center, tractors over 13 years age are known as obsolete, so mechanization level could be reached down to 0.7 hp ha-1 by eliminating these tractors that included 40% of total tractors in the province. Coefficient of variation related to the mechanization level of counties was calculated as 47% that indicates imbalance between provincial regions. The average of variation coefficient of farm lands was obtained as 301.96 % for the province. Also correlation between mechanization level and coefficient of variation of farmlands was -0.436 in 5% level. In order to determine the priorities for importing power to each region of Khuzestan province, the ratio of area under cultivation (ha) to tractor unit assigned highest weight (0.3, 0.41, 0.54). Gotvand, Andimeshk, Izeh and Bagh-e Malek, had highest priority for importing power, respectively. Results indicate an inappropriate distribution of tractors without considering the actual local need for them. Appropriate distribution of power is more important than quantitative distribution of tractors in Khuzestan province, because power in some regions is more than required power that cause wasting capital. In opposite, the shortage of power resources in the peak of workload in other regions, cause timeliness costs for farmer. Based on this, a necessity for regional planning is felt in the provincial strategic plans to make appropriate and coherent environments.