نشریه ماشین های کشاورزی
سال هفتم شماره 2 (پیاپی 14، نیمسال دوم 1396)

Great areas of the orchards in the world are dedicated to cultivation of the grapevine. Normally grape vineyards are pruned twice a year. Among the operations of grape production, winter pruning of the bushes is the only operation that still has not been fully mechanized while it is known as the most laborious jobs in the farm. Some of the grape producing countries use various mechanical machines to prune the grapevines, but in most cases, these machines do not have a good performance. Therefore intelligent pruning machine seems to be necessary in this regard and this intelligent pruning machines can reduce the labor required to prune the vineyards. It this study in was attempted to develop an algorithm that uses image processing techniques to identify which parts of the grapevine should be cut. Stereo vision technique was used to obtain three dimensional images from the bare bushes whose leaves were fallen in autumn. Stereo vision systems are used to determine the depth from two images taken at the same time but from slightly different viewpoints using two cameras. Each pair of images of a common scene is related by a popular geometry, and corresponding points in the images pairs are constrained to lie on pairs of conjugate popular lines.
Photos were taken from gardens of the Research Center for Agriculture and Natural Resources of Fars province, Iran. At first, the distance between the plants and the cameras should be determined. The distance between the plants and cameras can be obtained by using the stereo vision techniques. Therefore, this method was used in this paper by two pictures taken from each plant with the left and right cameras. The algorithm was written in MATLAB. To facilitate the segmentation of the branches from the rows at the back, a blue plate with dimensions of 2×2 m2 were used at the background. After invoking the images, branches were segmented from the background to produce the binary image. Then, the plant distance from the cameras was calculated by using the stereo vision.
In next stage, the main trunk and one year old branches were identified and branches with thicknesses less than 7 mm were removed from the image. To omit these branches consecutive dilation and erosion operations were applied with circular structures having radii of 2 and 4 pixels. Then, based on the branch diameter, one-year-old branches were detected and pruned through considering the pruning parameters. The branches were pruned so that only three buds were left on them. For this aim, the branches should be pruned to have a length of 15 cm. To truncate the branches to 15 cm, the length of the main stem was measured for each of the branches, and branches with length less than 15 cm were omitted from the images. Then the main skeleton of grapevine was determined. Using this skeleton, the attaching points of the branches as well as attachment points to the trunk were identified. Distance between the branches was maintained. At the last step, the cutting points on the branches were determined by labeling the removed branches at each step.
The results indicated that the color components in the texture of the branches could not be used to identify one year old branches and evaluation results of algorithm showed that the proposed algorithm had acceptable performance and in all photos, one year old branches were correctly identified and pruning point of the grapevines were correctly marked. Also among 254 cut off-points extracted from 20 images, just 7 pruning points were misdiagnosed. These results revealed that the accuracy of the algorithm was about 96.8 percent.
Based on the reasonable achievement of the algorithm it can be concluded that it is possible to use machine vision routines to determine the most suitable cut off points for pruning robots. By an intelligent pruning robot, the one year old branches are diagnosed properly and the cut off points of the plants are determined. This can reduce the required labor to perform winter pruning in vineyards which subsequently reduces the time required and the costs needed for pruning the vineyards.

Stereo vision means the capability of extracting the depth based on analysis of two images taken from different angles of one scene. The result of stereo vision is a collection of three-dimensional points which describes the details of scene proportional to the resolution of the obtained images.
Vehicle automatic steering and crop growth monitoring are two important operations in agricultural precision. The essential aspects of an automated steering are position and orientation of the agricultural equipment in relation to crop row, detection of obstacles and design of path planning between the crop rows. The developed map can provide this information in the real time. Machine vision has the capabilities to perform these tasks in order to execute some operations such as cultivation, spraying and harvesting.
In greenhouse environment, it is possible to develop a map and perform an automatic control by detecting and localizing the cultivation platforms as the main moving obstacle. The current work was performed to meet a method based on the stereo vision for detecting and localizing platforms, and then, providing a two-dimensional map for cultivation platforms in the greenhouse environment.
In this research, two webcams, made by Microsoft Corporation with the resolution of 960×544, are connected to the computer via USB2 in order to produce a stereo parallel camera.
Due to the structure of cultivation platforms, the number of points in the point cloud will be decreased by extracting the only upper and lower edges of the platform. The proposed method in this work aims at extracting the edges based on depth discontinuous features in the region of platform edge.
By getting the disparity image of the platform edges from the rectified stereo images and translating its data to 3D-space, the point cloud model of the environments is constructed. Then by projecting the points to XZ plane and putting local maps together based on the visual odometry, global map of the environment is constructed.
To evaluate the accuracy of the obtained algorithm in estimation of the position of the corners, Euclidian distances of coordinates of the corners achieved by Leica Total Station and coordinates and resulted from local maps, were computed.
Results showed that the lower edges have been detected with better accuracy than the upper ones. Upper edges were not desirably extracted because of being close to the pots. In contrast, due to the distance between lower edge and the ground surface, lower edges were extracted with a higher quality. Since the upper and lower edges of the platform are in the same direction, the lower edges of the platform have been only used for producing an integrated map of the greenhouse environment. The total length of the edge of the cultivation platforms was 106.6 meter, that 94.79% of which, was detected by the proposed algorithm. Some regions of the edge of the platforms were not detected, since they were not located in the view angle of the stereo camera.
By the proposed algorithm, 83.33% of cultivation platforms’ corners, were detected with the average error of 0.07309 meter and mean squared error of 0.0076. Non- detected corners are due the fact that they were not located in the camera view angle. The maximum and minimum errors in the localization, according to the Euclidian distance, were 0.169 and 0.0001 meters, respectively.
Stereo vision is the perception of the depth of 3D with the disparity of the two images. In navigation, stereo vision is used for localizing the obstacles of movement. Cultivation platforms are the main obstacle of movement in greenhouses. Therefore, it is possible to design an integrated map of greenhouse environment and perform automatic control by localization of the cultivation platforms. In this research, the depth discontinuity feature in the locations of the edges, was used for the localization of the cultivation platforms’ edges. Using this feature, the size of the points required for establishing the point cloud model and also the associated processing time decreased, resulting improvement in the accuracy of determining coordination of the platforms’ corners.

Greenhouse is a structure which provides the best condition for the maximum plants growth during the cold seasons. In cold climate zones such as Tabriz province, Iran, the greenhouse heating is one of the most energy consumers. It has been estimated that the greenhouse heating cost is attributed up to 30% of the total operational costs of the greenhouses. Renewable energy resources are clean alternatives that can be used in greenhouse heating. Among the renewable energy resources, solar energy has the highest potential around the world. In this regard, application of solar energy in greenhouse heating during the cold months of a year could be considerable. The rate of thermal energy required inside the greenhouse depends on the solar radiation received inside the greenhouse. Using a north brick wall in an east-west oriented greenhouse can increase the absorption of solar radiation and consequently reduces the thermal and radiation losses. Therefore, the main objective of the present study is to investigate the effect of implementing of a north wall on the solar radiation absorption and energy consumption of an east-west oriented single span greenhouse in Tabriz.
This study was carried out in Tabriz and a steady state analysis was used to predict the energy consumption of a single span greenhouse. For this purpose, thermal energy balance equations for different components of the greenhouse including the soil layer, internal air and plants were presented. For investigating the effect of the north wall on the energy consumption, the Ft and Fn parameters were used to calculate the radiation loss from the walls of the greenhouses. These factors were determined using a 3D–shadow analysis by Auto–CAD software. An east-west oriented single span greenhouse which has a north brick wall and is covered with a single glass sheet with 4 mm thickness was applied to validate the developed models. The measurements were carried out on a sunny winter day (November 30, 2015). The hourly variations of solar radiation on a horizontal surface were measured to calculate the total solar radiation received by the greenhouse using the Liu and Jordan equations. For heating of a greenhouse in nighttime, an electrical heater was used while an additional required energy was measured using a single phase meters. The inside and ambient temperatures of the air were recorded using SHT11 temperature sensors. A computer-based program of EES (engineering equations solver) was developed to solve the energy balance equations. Different statistical indicators were used to predict the accuracy of the presented models.
The obtained results showed that in winter months the greenhouse without the north brick wall can receive 14% more solar radiation than the greenhouse with a north brick wall. On the other hand, the use of a north wall in the greenhouses can reduce the radiation and thermal loss from north wall. To maintain the temperature at 25 °C in day-time and 15 °C in night-time, the additional required energy was calculated for greenhouse with and without north brick wall. The results indicated that the total energy requirement to keep the plants warm was 313.8 MJ in greenhouse without north brick wall and 210.8 MJ in greenhouse with the north brick wall. In other word, use of the north brick wall in the greenhouse can contribute to reduce energy consumption by 32%. Comparisons between the predicted and measured results showed a fair agreement for greenhouse energy requirements. The correlation coefficient and mean percentage error for this model were determined to be 0.79 and -2.34%, respectively. Due to the small values, the radiative exchange within greenhouse cover and the sky was neglected. Therefore, the results of the presented model showed fewer values in comparison with the experimental results. It can be concluded from the final results that a considerable amount of the incident radiation has been lost to the ambient by convection from the cover of the greenhouse (glass walls and north walls).
In the present study, the effect of north brick wall on solar radiation absorption and energy consumption of a single span greenhouse located in Tabriz was investigated. Results showed that use of north brick wall in an east-west oriented single span greenhouse leads to a reduction of 14% in solar radiation absorbed by the greenhouse. The results indicated that use of the north brick wall in the greenhouse can decrease energy consumption by 32%. There was a fair agreement between the experimental and theoretical results with the calculated correlation coefficient and mean percentage error of 0.79 and -2.34%, respectively.

Greenhouses provide a suitable environment in which all the parameters required for growing the plants can be controlled throughout the year. Greenhouse heating is one of the most important issues in productivity of a greenhouse. In many countries, heating costs in the greenhouses are very high, having almost 60-80% of the total production costs. In recent years, several studies have attempted to reduce the heating costs of the greenhouses by applying more energy efficient equipment and using the renewable energy sources as alternatives or supplementary to the fossil fuels.
In the present study a novel solar greenhouse heating system equipped with a parabolic trough solar concentrator (PTC) and a flat-plate solar collector has been developed. Therefore, the aim of this paper is to investigate the performance of the proposed heating system at different working conditions.
The presented solar greenhouse heating system was comprised of a parabolic trough solar concentrator (PTC), a heat storage tank, a pump and a flat plate solar collector. The PTC was constructed from a polished stainless steel sheet (as the reflector) and a vacuum tube receiver. The PTC was connected to the tank by using insulated tubes and a water pump was utilized to circulate the working fluid trough the PTC and the heat exchanger installed between walls of the tank. The uncovered solar collector was located inside the greenhouse. During the sunshine time, a fraction of the total solar radiation received inside the greenhouse is absorbed by the solar collector. This rises the temperature of the working fluid inside the collector which led to density reduction and natural flow of the fluid. In other words, the collector works as a natural flow flat plate solar collector during the sunshine time. At night, when the greenhouse temperature is lower than tank temperature, the fluid flows in a reverse direction through the solar collector and the stored heat transferred from the collector surface to the greenhouse.
The evaluation tests were conducted at three levels of fluid flow rate through the solar concentrator (0.44, 0.75 and 1.5 Lmin-1) and two different working modes of the heat exchanger.
The variation of thermal efficiency of the PTC at different flow rates has been illustrated in Fig 3. As shown, thermal efficiency increased with flow rate mainly because the fluid convection coefficient enhances with raising the velocity of the fluid inside the tubes.
The heat storing process began from 9 am and the highest amounts of the stored heat during sunshine time occurred between 10 am and 2 pm. Fig 5 showed that the stored energy in the tank enhanced when the flat plate collector was employed beside the PTC. Also, increasing the fluid flow rate from 0.44 to 1.5 Lmin-1 improved the index of stored heat by 32.14%. Energy consumption during the night time was also significantly changed with flow rate and the mode of heating. Fig 7 indicated that the electrical energy consumption was lower with flat plate solar collector and it is possible to save the electrical energy by 26.67% using the flat plate collector. Bouadila et al., (2014) concluded that the electrical energy consumption reduced by 31% employing a natural convection flat plate solar collector system equipped with phase changed heat storage material for greenhouse heating.
Since increasing the flow rate enhanced the thermal efficiency of the solar concentrator system and led to an improvement in stored thermal energy during the sunshine time, solar fraction increased with raising the flow rate from 0.44 to 1.5 Lmin-1. A maximum solar fraction of 66% was achieved at the highest flow rate when using the flat plate solar collector beside the PTC.
An experimental comparative study was conducted to investigate the performance of a novel solar greenhouse heating system at the different fluid flow rates and two modes of heating (with and without flat plat solar collector). The results can be summarized as follows: A maximum thermal efficiency of about 71% was achieved at the flow rate of 1.5 Lmin-1.
Raising the flow rate from 0.44 to 1.5 Lmin-1 improved the index of stored heat and solar fraction by 32.14% and 21%, respectively.
The highest value of solar fraction was found to be 66% at the highest flow rate when engaging the flat plate solar collector beside the PTC.

Growth of population, deficiency of resources, environmental hazards, fast spatial science progress and relevant subjects have resulted in significant effects of enhanced accuracy and modern technologies in agricultural technology and management methods. One of the modern technologies’ utilities in production and nondestructive tests is determination of product characteristics (such as product height), using electronic sensors at different stages of plant growth. In recent years, electric sensors improved widely in farm science. Regarding to wide performance of sensors, from simple sensors such as thermo, light and moisture sensors, to complex ones such as GPS and lidar, also the ability of electronic sensors to exact identification and measurement of special farm properties, makes these sensors to an important part of precision agriculture. The subject of this study is to identify and measure the height of the product using ultrasonic technology to automate control of breeding and harvesting operations. Suitable price and noise and dust resistance of ultrasonic sensor, make it an attractive subject in biosystem industries and farm operations.
Plant height measurement Ultrasonic sensor includes an ultrasonic transmitter and receiver with more than 20 kHz frequency. As other waves, ultrasonic waves diffuse constantly from a source by mechanical distracting in a gas, liquid or solid environment. The distance between sensor and object is a function of the wave passing time from generation point to receive point. Plant height calculated by estimating this distance and minus it from sensor height. The sensor used in this research had a diffuse angle of 40 degrees to center axis of source. The sensor ability to height measurement depends on leaves angle, leaves surface, plant aggregation in area and plant height. Leaves angle is the most important factor in recognization ability of ultrasonic sensor.
Electronic system design: The height measurement electronic system includes: 40 kHz Ultrasonic transmitter with diameter of 10 mm, 67 db ultrasonic receiver, Signal amplifier circuit (op-amp), AVR Microcontroller, (atmega 128) and a 64×128 pi LCD. Electronic part of system produces 40 kHz pulse initially and locates on one of the outlet bases of microcontroller. Then, this pulse is amplified and sent to ultrasonic sensor transmitter for maximum performance of the transmitter. The received pulse has low power so it shoud be amplified by an amplifier to be recognizable by the microcontroller. The received signal transmitted to digital signal by a high-speed 128 AVR atmega microcontroller. The sensor calibrated in the first phase using artificial barriers, the data analyzed by linear regression and paired mean comparison test in SPSS and EXCEL software.
Corn height measured by designed system in a test by 100 plots and 10 blocks. Thus, the blocks had a dimension of 1m length and 10cm width. System output recorded in first block and the block length passed by system with 10cm distances. Actual measurement accuracy comprised as pixels to data from manual measurement. The results didn’t show any significant difference between means. The regression coefficient of model was calculated 99%. The operating phase continued in a lab to measure maize height. The results showed high linear correlation between ultrasonic output voltage and manual measurement. This linear correlation led to present a linear regression model with the regression coefficient of 95%. Correlated mean comparison used for all of data too, i.e. the data obtained by the two measurement methods were compared by t-paired test. So it’s defensible that with 99% confidence, sensor can estimate the real value of height with high accuracy.
Utilization of measurement technologies and accuracy enhancement in agricultural production systems are unavoidable. In this research, corn height was measured accurately by ultrasonic technology. According to the results, identifying the presence or absence of plant, precision control of the operations (e.g. spraying) and measuring the height of the plants (to set the cutting height at combine harvester). Obviously, the produced device can identify plant height with precision, and can use in different phases of precision agriculture such as seeding row identification, machinery path determination to minimize plant’s loss, poison optimization and harvesting.

Preserving of crop residues in the field surface after harvesting crops, making difficult farm operations. The farmers for getting rid of crop residues always choose the easiest way, i.e. burning. Burning is one of the common disposal methods for wheat and corn straw in some region of the world. Present study was aimed to investigate the accurate methods for monitoring of residue management after wheat harvesting. With this vision, the potential of Landsat 8 sensor was evaluated for monitoring of residue burning, using satellite spectral indices and Linear Spectral Unmixing Analysis. For this purpose, correlation of ground data with satellite spectral indices and LSUA data were tested by linear regression.
In this study we considered 12 farms where remained plants were burned, 12 green farm, 12 bare farms and 12 farms with full crop residue cover were considered. Spatial coordinates of experimental fields recorded with a GPS and fields map were drawn using ArcGissoftware, version of 10.1.
In this study,t wo methods were used to separate burned fields from other farms including Satellite Spectral Indices and Linear Spectral unmixing analysis. In this study, multispectral landsat 8 image was acquired over 2015 year. Landsat 8 products are delivered to the customer as radiometric, sensor, and geometric corrections. Image pixels are unique to Landsat 8 data, and should not be directly compared to imagery from other sensors. Therefore, DN value must be converted to radiance value in order to change the radiance to the reflectance, which is useful when performing spectral analysis techniques, such as transformations, band ratios and the Normalized Difference Vegetation Index (NDVI), etc.
In this study, a number of spectral indices and Linear Spectral Unmixing Analysis data were imported/extracted from Landsat 8 image. All satellite image data were analyzed by ENVI software package. The spectral indices used in this study were NDVI, BAI, NBR and NBRT. Classification accuracy was evaluated and expressed by confusion matrix and Kappa coefficient.
Natural surfaces are rarely composed of a single uniform material. Spectral mixing occurs when materials with different spectral properties are represented by a single image pixel. The condition where scale of the mixing is large (macroscopic), mixing would occur in a linear fashion. However for microscopic situations, the mixing is generally nonlinear. The linear model ahich wasadopted in this study, assumes that there is no interaction between materials. Assumption of LSUA is that each pixel on the surface is a physical mixture of several constituents weighted by surface abundance, and the spectrum of the mixture is a linear combination of the endmember reflectance spectra.
Within the context of this study, LSUA is a classification method that can determine contribution of each material (or endmember) such as soil or residue for each image pixel.
The spectral response curve extracted from Landsat 8 image used as input into the LSUA model in ENVI software. As expected, crop burned residue (Ash) spectra had lower reflectance when compared to the soil, residue and green plant spectra. The contrast between residue, green plant, soil and residue ash spectra was particularly evident in the NIR and SWIR bands. It is suggested that these bands are essential for residue discrimination. Differences of reflectance in the visible bands were minimal, providing little discrimination between residue, green plant, soil and residue ash. Burned area estimated by LSUA method from Landsat 8 image was correlated against the ground data (measured coincident to the ground data). The overall accuracy of classification with BAI index and LSUA method was 91.7 and 88.3 and Kappa coefficient was 0.89 and 0.84 respectively.
Results indicated that burned field area can be located and its area can be estimated using Landsat 8 images. The Index BAI was selected as discernment index for burned/unburned fields in Landsat 8 images.
Present study was aimed to evaluate the accurate methods for monitoring residue management after wheat harvesting. With this vision, the potential of Landsat 8 sensor local data for monitoring residue burning was evaluated using satellite spectral indices and Linear Spectral Unmixing Analysis. Results indicate that residue ash spectra had lower reflectance when compared to the residue, soil and green plant except NIR band spectra. The contrast between residue, soil, green plant and residue ash spectra was particularly evident in the NIR bands. Results indicated that burned field area can be located and its area can be estimated using Landsat 8 images. The Index BAI was selected as discernment index for burned/unburned fields in Landsat 8 images.

Pistachio nut is one of the most delicious and nutritious nuts in the world and it is being used as a saltedand roasted product or as an ingredient in snacks, ice cream, desserts, etc. The purpose of roasting is to promote flavour and texture changes in nuts that ultimately increase the overall palatability of the product.Roasting involves a number of physico-chemical changes, including heat exchange, chemical reactions and drying. Knowledge of desorption kinetics is essential to predict the behavior of the material during roasting process and to design roaster equipment.The main aim of this research was to evaluate suitable models for predicting moisture ratio, the effect of air temperature and velocity on the drying kinetics of pistachio nuts and obtain the effective diffusivity coefficient and activation energy in the drying process during the roasting of pistachio nuts.
Dried Ahmadaghaei pistachio nuts were supplied from Kashefan Kavir company (Doraj co.) in Rafsanjan. Pistachio nuts were soaked in 17% salt solution for 8 minute and roasting was investigated at air temperatures of 120,130, 145, 160 and 170 °C and air velocities of 0.6, 0.88, 1.3, 1.72 and 2 ms-1. Five semi-theoretical and two empirical kinetic models were fitted to drying experimental data using nonlinear regression analysis techniques in the Curve Expert 2.2 computer program.
Tow-way ANOVA indicated that temperature and hot air velocity significantly affected the drying process during roasting of shelled pistachio nuts. The higher roasting temperatures and air velocities resulted in the higher drying rates. During first 10 min of roasting at constant air velocity of 1.3 ms-1, 64.5%, 70.3%, 77.1%, 83.5%, 89.7% of the moisture were removed at roasting air temperatures of 120 °C, 130 °C, 145 °C, 160 °C, 170 °C, respectively. The high regression coefficients (R2>0.996) and low reduced chi-square (χ2), mean relative deviation modulus P (%) and Root Mean Square Error (RMSE) indicated that the Weibull models are suitable for predicting moisture ratio. Correlations of the Weibull model constants with the variables of temperature and velocity were determined. Additionally, effective diffusivity (Deff) determined by using Fick’s second law was varied from 4.418×10-09 to 2.648×10-08 m2s-1 over the temperature and air velocity ranges. The lowest and highest Deff values were found for samples roasted at temperature of 120°C with air velocity of 0.6 m s-1and temperature of 170°C with air velocity of 2 ms-1, respectively. Temperature dependence of the diffusivity coefficient was described by Arrhenius-type relationship. Also average activation energy was obtained 26.615 kJ mol-1.
The results of this study showed that temperature and hot air velocity significantly affect the drying kinetics during roasting of pistachio nuts.The effective diffusion coefficient determined in this study was more than the limits specified in food products drying at lower temperatures and there was direct relationship between temperature and hot air velocity with effective diffusion. Activation energy was obtained close to some agricultural products.

Mint (Mentha spicata L.) cbelongs to the Lamiaceae family, is an herbaceous, perennial, aromatic and medicinal plant that cultivated for its essential oils and spices. Since the essential oil is extracted from dried plant, choosing the appropriate drying method is essential for gaining high quality essential oil.Vacuum drying technology is an alternative to conventional drying methods and reported by many authors as an efficient method for improving the drying quality especially color characteristics. On the other side, solar dryers are also useful for saving time and energy. In this study the effect of two method of dryings including vacuum-infrared versus solar at three different conventional temperatures (30, 40 and 50°C) on mint plant is evaluated while factorial experiment with randomized complete block is applied. Drying time as well as color characteristics areconsidered for evaluation of each method of drying.
Factorial experiment with randomized complete block was applied in order to evaluate the effect of drying methods (vacuum-infrared versus solar) and temperature (30, 40 and 50°C) on drying time and color characteristics of mint. The initially moisture content of mint leaves measured according to the standard ASABE S358.2 during 24 hours inside an oven at 104 °C. Drying the samples continued until the moisture content (which real time measured) reached to 10% wet basis. The components of a vacuum dryer consisted of a cylindrical vacuum chamber (0.335 m3) and a vacuum pump (piston version). The temperature of the chamber was controlled using three infrared bulbs using on-off controller. Temperature and weight of the products registered real time using a data acquisition system. The components of a solar dryer were consisting of a solar collector and a temperature control system which was turning the exhaust fan on and off in order to maintain the specific temperature. A date acquisition system was applied to register and monitoring product weight real time. For imaging of dried samples, a semi-professional digital cameras Fujifilm Fine Pix HS55model Barzvlvshn 921000 pixel was applied. Dry samples were used to determine the RGB color model that consists of three whole red (Red), green (Green) and blue (blue) light intensity 0 to 255 (in this case, zero for black and 255 for white pixels) Finally, the average of RGB changes color index were calculated as the mean change color of samples during the drying.
The results showed that drying time of solar dryer is more than vacuum-infrared (averaged: 201 versus 153 minutes). For two methods of drying, increasing temperature, made reduction in drying time. The maximum drying time registered 237 minutes for solar method which was set to 30°C and minimum drying time was registered 112 minutes relating to vacuum –infrared which was set to 50°C. Color evaluation showed that the effect of drying method on the changes of colour index (before and after drying) is reasonable. Vacuumed-infrared dryer case with 8.75% color change was showed to be much efficient than solar dryer with 11.96% change. Analysis of variance was performed due to the drying temperature index mint color changes and results showed the reasonable difference. The highest and lowest color change related to the temperature of 50°C (11.767%) and 30°C (9.197%) respectively.
Drying method as well as applying temperature showed rescannable effects on daring time and color quality of mint. The vacuum-infrared method reduces drying time for all temperature treatments considered in this study. Beside this, using vacuum-infrared showed minimum changes on color characteristic and can be say more efficient in aspect of color quality especially at its lowest applicable temperature (30°C). Increasing temperature causes the samples to be more darken for both drying methods. This phenomena may be related to replacement of magnesium by hydrogen inside the chlorophyll and then causing the chlorophyll to be destroyed.

Preserving food products has been much regarded due to the population growth and food scarcity. Drying food is one of the methods of preventing the waste of food products. Spray drying for which products that are initially in the liquid phase is the most suitable method of drying the moisture. In this method, the solution is turned into particles and droplets via mechanism and synchronous collision with the hot air that enters the drying case. Moisture content is one important aspect of the food powder which is associated with an increase of adhesion. The particles size is an important feature of the product due to its effect on the product appearance, solubility, and powder fluidity.
In this study for producing tomato powder, 10 kg of tomato available in the market which was not good and did not have a good appearance but suitable for juicing was supplied. A meat grinder was used for juicing. Tomato juice was filtered to become pure. Tomato juice was put in the 1.5 lit bottles and was kept in the refrigerator for experiments. To spray the tomato juice, an ultrasonic nozzle with 20 kHz frequency was used. Energy sources (TOPSONICS 400W, 20 kHz) was used to provide the atomizer power with adjustable power from 0 to 400 W. In this study a hot-plate spray dryer was used to change the tomato juice into powder. An oven was used to measure the tomato powder moisture content. 0.5 g of tomato powder was weighed and was put in the oven with 70°C for 24 hours to be dried to lose moisture. To measure the size of the particles the analysis of two-dimensional images was used. The photos were taken with optical microscope OLYMPUS CX21þequipped with a digital camera- SONY DSC-HX1. To illustrate the photos, the Digimizer software was applied. SAS software was used for further statistical analysis.
Analysis of variance results indicated that the effect of the studied parameters was significant on the average of the particles size except for dryer plates temperature (p The results of this study indicated that the parameters such as ultrasoud power, flow rate, and the dryer plates temperature on the physical properties of tomato powder like the particles size average and moisture content were significant (p

Honey is a supersaturated sugar and viscose solution taken from the nectar of flowers, collected and modified by honeybees. Many producers of honey add some variety of sugars in honey that make difficulties with detection of adulterated and pure honey. Flavor is one of the most important parameters in the classification of honey samples and the smell emitted by the honey depending on the different flowers and constituents that could be different. This causes using an electronic nose system to detect honey adulteration.
Honey samples used in this study were lotus honey that was supplied from a market in Karaj city, Alborz province, Iran. Adulterated honey, along with percentages of fraud (by weight) of zero, 20, 35 and 50 percent, was prepared by mixing sugar syrup. Each group of samples, nine times were tested by the electronic nose system. The proposed system, consists of six metal oxide semiconductor sensors, sensor chamber, sample chamber, data acquisition systems, power supply, electric valves, and pumps. Electronic nose is planned for three-phase system baseline correction, the smell of sample injection and cleaning of the sensor and sample chambers with clean air (Oxygen). Responses of the sensors were collected and stored in 420 seconds by a data acquisition system and LabView ver 2012 software. We used fractional method in this study, in order to improve the quality of the information available and to optimize the array output before passing it on to the pattern recognition system. Linear Discriminant Analysis (LDA), Principal Component Analysis (PCA) and Artificial neural network (ANN) were the methods used for analyzing and recognizing pattern of electronic nose signals. Data processing was carried out using Microsoft Excel, neuralsolution 5 and Unscrambler X 10.3 (CAMO AS, Norway).
PCA PCA reduces the complexity of the data-set and is performed with no information on the classification of samples. It is based on the variance of the data-set. For PCA analysis, overall PC1 and PC2 explained 91% of the total variance among Lotus honey samples and the adulterations (PC1=80% and PC2=11%). The results indicate that it is clearly possible to recognize Lotus honey with adulterant using electronic nose systems.
LDA The LDA method for the detection of adulterated honey samples using leave-one-out validation was estimated. The method is most widely used as a method of classification that maximizes variance between the clusters and minimizes variance of within classes. By applying LDA on the collected data, 100% accurate classification for detecting of honey and their adulterations was obtained. It can also be concluded that this method could recognize adulterated honey samples properly.
ANN The back propagation multilayer perceptron algorithm was used to classify and to detect honey and adulterated types. Performance evaluations of each designed networks were compared by mean square error (MSE) and correlation coefficient (r).The data were divided to three subsets: 60% was used for training, 20% for testing and the remaining 20% were kept for cross validation.After network training and validation using optimized ANN model, i.e. 6-8-4 structure, success rate for 4 outputs (0, 20, 35 and 50% adulterated levels)were found to be 100%.After detecting adulteration, e-nose system accompanied with ANN can accurately classify honey from honey mixtures with fraud materials.
An electronic nose based on six metal oxide semiconductor sensors was used to detect adulterated honey samples. Electronic nose system can successfully classify between original honey and the adulterated one by pattern recognition method. The PCA, LDA and ANN techniques and analyzes of the electronic nose were very useful for evaluating the quality of the lotus honey. The results of these methods were used to classify the fraud in Lotus honey. However, there is a need to do more researches on the detection of adulteration in other agricultural and food products by electronic nose system.

Winter wheat is an important, well-adapted grain crop under dryland condition of the northwest of Iran. Soil water is the most limiting resource for crop growth in dryland areas. Therefore, farmers need to use crop residues and minimum tillage to control the soil erosion and effectively store and to use the limited precipitation received for crop production.
Crop rotation and tillage system could affect crop yield due to their effects on water conservation and soil chemical and physical properties. Galantini et al., (2000) studied the effect of crop rotation on wheat productivity in the Pampean semi-arid region of Argentina and found that a wheat–vetch (Vicia sativa L.) rotation resulted in higher yield and protein content, and greater yield components than the other rotations.Payne et al. (2000) stated that where precipitation amount is marginal (400 mm), dry field pea offers a potential alternative to summer fallowing. The purpose of this study was to identify the optimal tillage system for increasing crop productivity in a vetch–wheat rotation in dryland farming of the northwest of Iran.
The field experiment was carried out from 2010 to 2014 at the Dryland Agricultural Research Station (latitude37° 12´N; longitude 46◦20´E; 1730 m a.s.l.), 25 km east of Maragheh, East Azerbaijan Province, Iran. The long-term (10 years) average precipitation, temperature and relative humidity of the station are 336.5 mm, 9.4 ◦C and 47.5%, respectively. The soil (Fine Mixed, Mesic, Vertic Calcixerepts, USDA system; Calcisols, FAO system) at the study site had a clay loam texture in the 0–15 cm surface layer and a clay texture in the 15–80 cm depth.
This study was conducted in vetch (Vicia pannonica)- wheat (Triticum aestivum L.) rotation. The experiment was arranged in a randomized complete block design with four replications. The tillage treatments consisted of (1) conventional tillage: moldboard plowing followed by one pass of a disk harrow (CT); (2) reduced tillage:chisel packer (CH); (3) minimum tillage: Stubble mulch cultivator (MT); and (4) no-till (NT) with retained previous crop residue.
At beginning prior to the tillage operation, only wheat stubble was present on the soil surface. A uniform tillage treatment was applied to all plots using a chisel packer in October. A shallow tillage was also performed using a tandem disk harrow just prior to winter vetch planting. In the second, third, fourth and fifth years, the tillage treatments for the vetch and wheat planting were similar. A winter wheat cultivar (Azar 2) was sown 6 cm depth at a rate of 350 seeds per square meter with an Alvand conventional and Baldan NT 250 no-till drill. Vetch cultivar Golsefied was drilled 8 cm depth at a seeding rate of 85 kg ha−1 using Alvand drill.
The following parameters were measured: heads of wheat per square meter, 1000-kernel weight, kernels per head, head length, plant height, and wheat grain yield. Grain yield was obtained with a plot combine harvester. The dry matter content was determined and yield corrected to a standard moisture content of 130 g kg−1.
Rain use efficiency (RUE) was calculated by dividing dry weight of grain yield by growing season precipitation.
Soil water content and dry bulk density were measured gravimetrically (drying method, w/w) in cropping seasons.
Conservation tillage treatments resulted in water saving in soil layers. In both stages of soil sampling, the most soil moisture variability to initial state was observed in plots which planted as no-tillage. The moisture variability of no-tillage system was 23.4% higher than that of conventional tillage system at 10-20 cm soil layer in flowering stage of wheat.
Effect of treatments on soil bulk density in different soil depths illustrated that conservation tillage can reduce soil bulk density during four years.
According to the results of this study the overall infiltration in no-tillage was 1.58 times more than that of conventional tillage system.
Yields under no-tillage and reduced tillage were higher (4% and 6% respectively) than conventional tillage. Grain yields under direct drilling were similar to those obtained using the reduced-tillage (Chisel packer) system.
Based on the results of a 4-year field study on a dryland production system in the northwestern cold continental climate of Iran, minimum- or no-till winter wheat crop production in a vetch–wheat rotation were the most efficient soil management practice from the standpoint of grain yield production and rain use efficiency. Overall, in this study, the no-tillage treatment is proposed as the best treatment in terms of grain and biomass yields and mechanical properties of soil.

The dynamic response of soil on tillage tools, is an important factor in determining their performance. For a tractor with a certain size, a reduction in draft force, the working width and speed of tools can rise and result in increasing performance and reduce costs. Researches carried out in order to reduce the draft force led to design and build new tillage tools called Bent Leg and Parra plows. The dual bent blade sub-surface tillage tool was built and examined inspired by the shape of a bent leg. The researches indicated that the combination of a dual bent blade sub-surface tillage tool and chisel plow could be used in order to reduce draft force, loosen the seed bed by the chisel plow and wings, increase in soil disturbance area by the wings, and create a suitable space for root growth by chisel plow. Since the fuel consumption and traction power of tractor are the limiting factors for pulling tools in the soil. The rake angle of tillage tools is the penetration factor of the tools to the soil. It is necessary to determine the optimized rake and bend angles according to their effect on draft force and better penetration in soil. In this research, the Response Surface Methodology (RSM) was utilized to determine the optimized points of wing geometry of winged chisel plow in order to minimize the draft and vertical forces of tillage tool.
Using the properties of dual bent blade subsurface tillage implement and chisel plow, the winged chisel plow was designed by Catia V5R20 software and was built in the workshop of mechanics of biosystems engineering department at Shiraz University. The effect of three factors of working depth of wing (5, 10, and 15 cm), bend angle (10, 20, and 30 degree), and rake angle (7.5, 15, and 22.5 degree) were analyzed on draft and vertical forces of wined chisel plow in soil bin of Karaj Agricultural Engineering Research Institute. The length, width, and depth of the soil bin were 24 m, 1.7 m, and 1 m, respectively. The most important issue was to study the main effects and interactions of factors. So, the Response Surface Methodology was selected. With the help of this statistical design, the numbers of experiments were reduced and all coefficients of quadratic regression and interaction factors were estimated. The experiments were conducted based on the central composite design considering three main surface including central and axial points for each factors. For each response the quadratic polynomial models were obtained using the multiple linear regression.
The results indicated that fitted quadratic model for draft force corresponded with the experimental data by determination coefficient of up to 94% (R2 0.94). Increasing the depth of wing, the contact with loosened soil decreased that led to failure in unloosened soil around the chisel blade and increase in pressure to the blade. The results showed that the effect of bend angle was significant on draft force and increasing the bend angle, the tip of wing located in deeper place so, the draft force was increased that was in line with previous researches. The effect of rake angle was not significant on the draft force and its effect on the model was positive and negligible which was reported positive and significant in previous works. The fitted quadratic model for vertical force corresponded with the test data by determination coefficient of up to 93% (R2 0.93). The effects of wing depth and bend angle were positively significant on the vertical force of the tool but the effect of rake angle was negligible. The increase in vertical force with increasing bend angle was further in deeper wing position. However, the impact of rake angle was seen in vertical force and the effect of bend angle was not significant in vertical force in rake angles of 7.5° and 15°, but it was significant in rake angle of 22.5°.
The draft and vertical forces were determined 3.43 and 1.31 kN, respectively, at optimum condition (wing depth of 5cm, bend angle of 11.1°, and rake angle of 19.46°). The proposed model to predict the dependent variables were very close to the results of obtained experimental findings. The wing depth and bend angle had positive and significant effects on draft and vertical forces but the effect of rake angle was positive and insignificant on both measured traits.

Improving the efficiency of all agricultural operations has always been important for farmers and engineers. It is well known that the force required for cutting a soil using narrow blades is a function of soil and environmental physical properties, tool shape geometry and the tool’s surface characteristics like soil-tool adhesion and friction. Soil tool adhesion can reduce ploughing efficiency and quality. It may also halt the movement of tillage machines in more severe conditions. Adhesion can also disable some machine abilities, which can result in a significant reduction of machine performance. Adhesion of the soil to seed-bed preparation tools like furrowers can significantly affect the germination rate. Reducing soil tool adhesion of furrowers can reduce draft force and improve ploughing efficiency. Many researchers have worked on methods of reducing draft force by modifying the surface material and/or surface texture of the plough tools. A good prediction on draft force of a tool before producing it has always been important for farmers and engineers. There are some models for predicting the draft force of narrow blades in soil. McKyes-Ali’s model is widely used because of its accuracy and simplicity. Ultra-high molecular weight polythene (UHMW-PE) is a polymer with ultra-high weight and long molecular chains and is well known for its outstanding physical and chemical properties and self-cleaning abilities, which reduce soil-tool adhesion. The aim of this study was to investigate usability of UHMW-PE coated furrower tines for draft force. Analytical and experimental investigations were carried out during the research. A comparison was conducted between the analytical and the experimental method. The results of this comparison can be used to determine reliability of the analytical model for predicting the draft force improvement caused by the surface modification on tines using different surface coatings.
Eight tines have been built. Four of them had a thick coating layer of UHMW-PE, and the other four were made of pure mild steel. Each set of the tines have been installed on a four shanked chisel plough chassis and then attached to a tractor. The draft force required for pulling the furrowers attached to the tractor has been measured by a simple load meter mechanism connecting two tractors. Draft force has been measured in two different speeds. Slip ratio of the tractor has been recorded. Each test has been repeated three times.McKyes-Ali’s proposed model for evaluating the draft force of narrow blades has been chosen to predict draft force of the traditional steel furrower tines and the surface coated ones. To drive the model, a computer program has been coded in the script environment of Matlab software. The model required some of the mechanical properties of the soil and the tool to operate. Specific gravity, cohesion and internal friction angle of the soil have been measured by routine laboratory methods. Soil-tool adhesion and friction of the mild steel and the UHMW-PE plates have been measured using the direct shear apparatus.
MkKyes-Ali’s model has predicted draft forces with an accuracy of 90%. According to the results of the driven model, applying a UHMW-PE coating layer to the surface of the tines can improve draft force by 13%. The change of tractor speed from 3.5 km h-1 to 5.5 km h-1 have no significant effect on the predicted draft forces. The model also predicted different angles of the soil failure zone for coated and uncoated tines. On the other hand, the improvement of the draft force for the UHMW-PE coated tine in the field test was about 27%. According to The results obtained from the field test, the draft force of the furrower tines had significant correlation with the speed.
The UHMW-PE coated tines required significantly less draft force to work in compare with the steel tines. McKyes-Ali’s model predicted a significant improvement (13%) in draft force for the UHMW-PE coated tines. According to the experimental results, the improvement of the draft force was about 27%, which was almost twice as predicted. Although the McKyes-Ali’s model could predict an improvement for draft force of the UHMW-PE coated tine, but the actual improvement was about twice of the prediction. According to analytical and experimental results, applying a layer of UHMW-PE plastic on furrower tines can improve the draft force significantly.

One of the most important problems arising with operation of the conventional rototillers is severe vibration of the machine handle which is transmitted to the user’s hands, arms and shoulders. Long period exposure of the hand-transmitted vibration may cause various diseases such as white finger syndrome. Therefore in this study, vibrations of a new type of rototiller with ridged blades were investigated at the position of handle/hand interface in different working conditions. Finally, the maximum allowable exposure time to the rototiller users in continuous tillage operation was obtained according to ISO 5349-1.
Experiments were carried out in one of the farms with silty clay soil texture, located in Sari city, Mazandaran province, Iran. Vibration measurements were performed according to ISO 5349-1 and ISO 5349-2 standards in two different modes, including in situ mode and tillage mode. Vibrational parameters were obtained in three blade rotational speeds, i.e., low speed (140-170 rpm), medium speed (170-200), and high speed (200-230). Blade rotational speed varied by changing engine speed using the throttle control lever. In each experiment, different vibrational values were individually recorded in three directions (x, y, and z). Experimental design and data analysis were performed in a Randomized Complete Block Design with three replications using the SPSS16 software.
Based on the obtained results in this study, the RMS of acceleration increased by increasing in rotational speed for all of the conducted experiments. The reason is that number of cutting per unit of time and consequently the frequency of changing in the dynamic forces exerting on the blades dramatically increases with increasing the rotational speed of the blades. Noteworthy is that in most cases the variation of acceleration in the tillage mode showed similar trend with vibrational values in the idling mode. This represents a significant contribution of the combustion engine in vibration of the examined rototiller. Meanwhile, contribution of the engine in the total measured vibration was more than 50% at different rotational speeds and different directions. The minimum engine contribution was measured equal to 56.39% in z-direction at 155 rpm, whereas the maximum engine contribution was observed equal to 79.5%, in x-direction and rotational speed of 215 rpm. These results indicate the importance of selecting a proper combustion engine for reducing the rototiller vibration. It should be noted that the contribution of the engine in total vibration reached its minimum value at the speed related to the maximum generated torque, i.e., 185 rpm of the rotor speed.
This result indicates that using the combustion engine in its optimum speed reduces the entire device vibration in the vertical direction. By increasing the rotational speed of the blades in the y-direction, engine contribution in device vibration showed different trends in compare to the other directions. The most value was equal to 74.25% which was obtained at the rotation speed of 185 rpm. By increasing blade rotational speed from 155 rpm to 215 rpm, the engine contribution in device vibration in the z direction and the total acceleration steadily increased.
With growing mechanization and entering various types of machines to the farm, importance of considerations to human health is also increased, especially in working with rotational machines. Therefore, the current study was undertaken with the specific attention to the rototillers operational vibration at the handle/hand interface. Results of the conducted experiments showed that vibration of the examined rototiller depends more on the operation of the mounted combustion engine, rather than the soil working blades. Therefore, it is suggested to select a higher quality engine with less vibration or isolate the engine from chassis by a damper (such as a compressed rubber) to reduce the vibration transmitted to the operator’s hands and arms.

Measuring the efficiency of operating systems in comparison with the methods of comparing the performance of systems explains the various dimensions of issues such as, the lack of full use of agricultural machinery capacity, improper selection of machine, incorrect use of machinery, ownership, etc.. Any improvement in operating system conditions reduces costs,, consumption of inputs, increases the efficiency of production factors and consequently reduces the price and increases agricultural profitability. The main objective of this research is to compare the operational-management efficiency of operating systems in Alborz province and comparison of managerial and operational efficiency of agricultural machinery farming systems by calculating the efficiency of its major components in agricultural machinery farming systems including efficiency, social, economic, technical-operational and managerial and ranking them in order to understand the optimal model of agricultural machinery systems.
This research is a survey study.The study population was beneficiaries of agricultural machinery in the Alborz province which in the multi-stage random sample was determined. Alborz province has 31,438 agricultural operations, of which 543 are exploited agricultural machinery. Cochran formula was used to determine sample size. Since, Cronbach's alpha coefficient greater than 0.7 was obtained by questionnaire, the reliability of the questionnaires was assessed as desirable. To calculate the efficiency the component data were extracted from 4 specialized questionnaires after the initial examination and encoding, then they were analyzed using the software SPSS, MCDM Engine. TOPSIS techniques were used for ranking managerial performance operating system for operating agricultural machinery Alborz province.
The results showed that social efficiency of dedicated-professional operation with an average of 6.6 had maximum efficiency operation among the three systems of agricultural machinery. Economic efficiency of professional operation system with an average of more than 1.43 units is capable of the highest rate among the three systems and economic performance of the dedicated operation less than one and equal to 0.76 in the three systems have the lowest rate. In other words, the professional operation of the annual profit is 43%, but the annual dedicated operation is facing a 24 percent loss. Performance of management operation system is dedicated 6.19 and was the highest performance among systems. The number of dedicated- operation system 5.42 is the least efficient management of three farming system agricultural machinery in Alborz province. Appear organizing, planning, directing and coordinating, decision-making, control and supervision of the operation system was far better than the other two systems. The operating efficiency of the dedicated operating system is 76.537% and in this respect, it has the highest value among the three operating systems and the lowest operational efficiency is related to the professional operating system.
The increased operational efficiency of the dedicated operating system is further influenced by the high average scores for the indicators of timely operations, the availability of the machine and the quality of the operation. Kruskal-Wallis statistical tests were performed to compare the average of four types of efficiency (social, economic, managerial, technical-operational) in three agricultural machinery farming systems, with mean difference for all items at 5% and 1% significance.
Ranking of managerial-operational efficiency of agricultural machinery utilization systems using TOPSIS technique: The ranking criterion of this technique is a similarity index, with a range of 0 to 1 variation. The results showed that among the three systems of agricultural machinery exploitation, the professional farming system with the rank of 0.9219 ranked first, the professional- dedicated farming system with 0.5261 had second rank and dedicated farming system with 0.1556 ranked third
The results showed that the managerial-operational efficiency of the professional operating system was more than the other two operating systems, which was due to the high effectiveness of the management-operation of the economic efficiency and technical-operational efficiency, which in this system was more efficient from other systems. Investigating the importance of factors affecting the efficiency of agricultural machinery farming systems showed that the weight economic factors is far more than other factors and the effect of economic efficiency on the efficiency of the entire farming systems is much higher. The cost of ownership of a machine is very important among economic agents, this factor directly affects the choice of operating systems, and it also indirectly affects other factors. Therefore, it can be concluded that the key for improving agricultural machinery management and increasing the productivity of this important input is to perpend different aspects of the cost of ownership.

Planning and scheduling of farming mechanized operations is very important. If the operation is not performed on time, yield will be reduced. Also for sugarcane, any delay in crop planting and harvesting operations reduces the yield. The most useful priority setting method for agricultural projects is the analytic hierarchy process (AHP). So, this article presents an introductry application manner of the Analytical Hierarchy Process (AHP) as a mostly common method of setting agricultural projects priorities. Analytic Hierarchy process (AHP) is a decision making algorithm developed by Dr. Saatyin 1980. It has many applications as documented in Decision Support System literature. Currently, this technique is widely used in complicated management decision makings which AHP was preferred from other established methodologies as it does not demand prior knowledge of the utility function; it is based on a hierarchy of criteria and attributes reflecting the understanding of the problem, and finally, because it allows relative and absolute comparisons, thus making this method a very robust tool. The purpose of this research is to identify and prioritize the effective parameters on lack of timeliness of operations of sugarcane production using AHP in Khuzestan province of Iran.
The effective parameters effecting on lack of timeliness of operations have been defined based on expert’s opinions. A questionnaire and personal interviews have formed the basis of this research. The study was applied to a panel of qualified informants made up of fourteen experts. Those interviewed were distributed in Sugarcane Development and By-products Company in 2013-2014. Then, by using the Analytical hierarchy process, a questionnaire was designed for defining the weight and importance of parameters affecting on lack of timeliness of operations. For this method of evaluation, three main criteria considered were yield criteria, cost criteria and income criteria. Criterions and prioritizing of them was done by questionnaire and interview with sophisticated experts. This technique determined and ranked the importance of criteria affecting on lack of timeliness of operations based on attributing relative weights to factors with respect to comments provided in the questionnaires. By using of software (Expert choice) Analytical Hierarchy Process was done and the inconsistency rate on expert judgments was investigated. Expert Choice software (Expert Choice 1999) was applied to examine the structure of the proposed model and achieve synthesis/ graphical results considering inconsistency ratios.
The Expert Choice software performed well in conjunction with the panel of experts for choosing the criteria and assigning weights under the AHP methodology. According to results, effective parameters on lack of timeliness of operations of sugarcane production consist of delays caused by management, delays caused by human, delays caused by machine and delays caused by procedure (the production process).Weight of criteria effective factors (yield, cost and income) on lack of timeliness of operations obtained from paired comparison in the experts’ view which has been calculated with Expert choice software. The result of this survey by AHP techniques showed that cost criteria had the most and income criteria had the least importance for expert in sugarcane production. In this stage of research, alternatives paired comparison relative to criteria was separately formed and information of questionnaire which relates to paired comparison of criteria was obtained. Between effective parameters on lack of timeliness of operations, machine factors to 0.366 weighted average was the most effective factor and production process to 0.298 weighted average, management factors to 0.177 weighted average and human factors to 0.160 weighted average was later respectively (Inconsistence Rate =0.03). The results are examined by monitoring sensitivity analysis while changing the criteria priorities. Since different judgments are made on comparison of criteria, we use sensitivity analysis in order to provide stability and consistence of analysis. With increase or decrease of the criteria, we will conclude that ratio of other indices will not change.
The analytic hierarchy process, as developed by Saaty, has been successfully applied in recent research to cases of agricultural project. This paper looks at AHP as a tool used in Sugarcane Agro-Industries to help in decision making. Results showed that criteria studied in this research can help prioritizing the effective parameters on lack of timeliness of operations of sugarcane production. Cost criteria are the main criteria effective on lack of timeliness operations of sugarcane production. The most important factor is machine factor.

One of the most important agricultural crops is rape seed oil as its special features can play an important role in the agricultural region. Due to the presence of more than 40% oil and 25% protein in the grain can play an important role in the supply of edible oil. After determining of various factors such as uniformity of planting depth, evenness between shrub, plant height and grain yield concluded that Nordsten drill along the seeding density of 75 cm for mechanized planting is acceptable yield. Afzali nia et al. (1999) in one study aimed to assess the performance of common grain drills in Iran in Zarghan area in Fars Province showed that differences between treatments in terms of seed distribution uniformity factor, plant population per unit area and yield product is not significant. The purpose of this study was to evaluate and select the most suitable types of canola planter and variable seed rate planting density and aims to increase the canola cultivated area by the highest yield.
Moghan Plain, located in the north areas of Ardebil province, is considered as an important areas of canola planting in Iran. This study was performed in the agricultural research center of Ardabil Province (Moghan) (39°39´N; 48°88´E; 78 m a.s.l.) in Northwest of Iran. To evaluate different planters with varied seed rates on canola yield. The experimental design was carried out in a randomized complete block design with strip splits (varied seed rates 6, 8 and10 kg per hectare and different drills consist of B1: Barzagar Hamadani drill (conventional method) B2: Amazon drill pals teeth harrow, B3: Gaspardo drill pals teeth harrow and B4: Agromaster drill) and four replications. To investigatethe different treatments in the experiment, various parameters such as percent germination, seeding uniformity of width and depth intervals, plant establishment, effective field capacity, fuel consumption rate andgrain yield were measured.
The evaluation of results of drill types showed that there was significant difference between the planters type and other performance parameters. Different planters with varied seed rates also had significant effects on germination at 1% probability level and B4 had maximum percentage of seed germination (89.45%). Uniformity of seed distribution was found to be the highest for B4 in vertical distribution uniformity (72.62%) and inter-row uniformity (84.25%). The analysis of variance for two years showed that the grain yield and establishment of seed were significantly affected by year. Result of variance analysis for yield indicated that there was a significant difference between planting machines in 1% of probability level. Therefore, maximum yield in this experiment related to B4 with 2672 kg ha-1. The results of technical and economic comp ration indicate that the added net income of B4, was 4940 thousand Rails per hectare compared to the conventional method.
Results showed that the average of yield of the first year was significantly greater than that of the second year. Results indicated that use of B4 lead to the highest of yield 2672 kg ha-1. But in terms of plant height no significance was found. The results of technical and economic comp ration comparison indicated that the added net income from B4, was 4940 thousand Rails per hectare compared to the conventional method. Therefore, considering many factors, the Agromaster drill tested in this study was found to be the best suited planter and therefore is recommended for canola planting in the region.

Precision agriculture (PA) is a technology that measures and manages within-field variability, such as physical and chemical properties of soil. The nondestructive and rapid VIS-NIR technology detected a significant correlation between reflectance spectra and the physical and chemical properties of soil. On the other hand, quantitatively predict of soil factors such as nitrogen, carbon, cation exchange capacity and the amount of clay in precision farming is very important. The emphasis of this paper is comparing different techniques of choosing calibration samples such as randomly selected method, chemical data and also based on PCA. Since increasing the number of samples is usually time-consuming and costly, then in this study, the best sampling way -in available methods- was predicted for calibration models. In addition, the effect of sample size on the accuracy of the calibration and validation models was analyzed.
Two hundred and ten soil samples were collected from cultivated farm located in Avarzaman in Hamedan province, Iran. The crop rotation was mostly potato and wheat. Samples were collected from a depth of 20 cm above ground and passed through a 2 mm sieve and air dried at room temperature. Chemical analysis was performed in the soil science laboratory, faculty of agriculture engineering, Bu-ali Sina University, Hamadan, Iran. Two Spectrometer (AvaSpec-ULS 2048- UV-VIS) and (FT-NIR100N) were used to measure the spectral bands which cover the UV-Vis and NIR region (220-2200 nm). Each soil sample was uniformly tiled in a petri dish and was scanned 20 times. Then the pre-processing methods of multivariate scatter correction (MSC) and base line correction (BC) were applied on the raw signals using Unscrambler software. The samples were divided into two groups: one group for calibration 105 and the second group was used for validation. Each time, 15 samples were selected randomly and tested the accuracy of models, then other15 samples were added randomly to the previous set and it was done continuously. Finally, seven groups (15, 30... 105) were placed in each category.
All regression models on the whole pre-processed soil spectra were obtained in absorption mode. By increasing the number of samples in the calibration set of random group, RMSE was decreased from 0.2 to 0.13 nonlinearly. RMSE in the chemical test was also decreased almost linearly from 0.17 to 0.11. At the same time, R2 and RPD were increased from 0.46 to 0.72 and from 1.3 to 2.0 respectively. Finally, in categories based on PCA, the RMSE fell down almost linearly (0.19-0.13). Potassium prediction model with the least amount of R2 (0.48) and phosphorus with highest number of errors (RMSE = 5.28) were the weakest models in whole data. Other properties of the soil had a higher coefficient of determination (R2> 0.5). Therefore, prediction models had acceptable accuracy. At least 77, 105 and 105 samples are required for precise calibration model of OC, nitrogen and pH respectively. Due to the different conditions of farms, comparing these results with previous findings is very complex. Furthermore, model accuracy did not improve by increasing data of calibration models to the total number of samples. While in previous studies, more precise model was calibrated by considering the entire data sets. Among all factors of soil, acidity has little dependence on the other soil properties. The pH modeling is also confirmed by Moros (2009) however, the more error was reported here. There is no certain pH range in the NIR spectra, and usually it is distinguishable from the other properties of the soil (Kuang and Mouazen, 2011).
Spectroscopic methods exhibited good potential for detecting soil properties. MSC and BC can effectively remove irrelevant information to improve prediction accuracy. Using different methods to select numbers of data for the calibration models presented similar results, but in the meantime PCA technique provided the best answer. Supplementary, the ever-increasing number of data does not always improve modeling accuracy. It is better to choose numbers of data according to principal components (PCs) of PCA to obtain acceptable answer. It must be noted that every crops requires a specific soil and nutrients, so it is necessary to develop models for other soil properties.

Energy consumption management is one of the most important issues in poultry halls management. Considering the situation of poultry as one of the largest and most developed industries, it is needed to control growing condition based on world standards. The neural networks as one of the intelligent methods are applied in a lot of fields such as classification, pattern recognition, prediction and modeling of processes. To detect and classify several agricultural crops, a research was conducted based on texture and color feature. The highest classification accuracy for vegetables, grains and fruits with using artificial neural network were 80%, 86% and 70%. In this research, the ability to Multilayer Perceptron (MLP) Neural Network in predicting energy consumption, temperature and humidity in different coordinate placement of electronic control unit sensors in the poultry house environment was examined.
The experiments were conducted in a poultry unit (3000 pieces) that is located in Fars province, Marvdasht city, Ramjerd town, with dimensions of 32 meters long, 7 meters wide and 2.2 meters height. To determine the appropriate placement of the sensor, 60 different points in terms of length, width and height in poultry were selected. Initially, the data was divided into two datasets. 80 percent of total data as a training set and 20 percent of total data as a test set. From180 observations, 144 data were used to train network and 36 data were used to test the process. There are several criteria for evaluating predictive models that they are mainly based according to the difference between the predicted outputs and actual outputs. To evaluate the performance of the model, two statistical indexes, mean squared error (MSE) and the coefficient of determination (R²) were used.
In this study, to train artificial neural network for predicting the temperature, humidity and energy consumption, the trainlm algorithm (Levenberg-Marquardt) was used. To simulate temperature, humidity and energy consumption, networks were trained with two and three layers, respectively. Network with two layers with10 neurons in the hidden layer and one neuron in the output layer with (R²) equal to 0.96 and (MSE) equal to 0.00912, was given the best result for predicting temperature. For humidity electronic sensors, results showed that network with three layers with the 10 neurons in the first hidden layer, 20 neurons in the second hidden layer and one neuron in the output layer with (R²) equal to 0.8 and (MSE) equal to 0.00783 was the best for predicting humidity. Finally, network with two layers with 10 neurons in the first hidden layer, 10 neurons in the second hidden layer and one neuron in the output layer was selected as the optimal structure for predicting energy consumption. For this topology, (R²) and MSE were determined to 0.98 and 0.00114, respectively. Linear and multivariate regression for the parameters affecting temperature, humidity and energy consumption of electronic sensors was determined by the STATGR software. Correlation coefficients indicated that parameters such as length, height and width of the electronic control sensors placed in the poultry hall justified 82% of the temperature changes, 61% of the humidity changes and 92% of the energy consumption changes. Therefore, comparing with correlation coefficients obtained from the neural network models, the highest correlation coefficient was related to energy parameter and the lowest correlation was linked to humidity parameter.
The results of the study indicated the high performance for predicting temperature, humidity and energy consumption. The networks hadthree inputs including length, width and height of electronic sensor positions and an output for temperature, humidity and energy consumption. For training networks the multiple layer perceptron (MLP) with error back propagation learning algorithm (BP) was used. Functions activity for all networks in hidden layers were tangentsigmoid and in the output layer, linear (purelin). Comparing the results of artificial neural network and logistic regression model showed that artificial neural network model with correlation coefficients of 0.98 (energy), 0.96 (temperature) and 0.8 (humidity) provided closer data to the actual data compared with regression models with correlation coefficients of 0.92, 0.82 and 0.61 for the energy, temperature and humidity respectively.