Design and Construction
M. Teimorzadeh; J. Baradaran Motie; A. Rohani; Y. Selahvarzi
Abstract
IntroductionNeglecting the water requirements of trees can result in inefficient irrigation practices, leading to either water wastage or drought stress. Effective irrigation management necessitates precise information on the quantity and pattern of water consumption by trees. To achieve optimal irrigation, ...
Read More
IntroductionNeglecting the water requirements of trees can result in inefficient irrigation practices, leading to either water wastage or drought stress. Effective irrigation management necessitates precise information on the quantity and pattern of water consumption by trees. To achieve optimal irrigation, a reliable method for quantifying plant water needs is crucial, ensuring that trees avoid drought stress. Current methods for assessing tree water requirements often focus on specific components, such as stems or leaves. These techniques typically require manual intervention, which is time-consuming and resource-intensive, thereby restricting their application mainly to research environments.Materials and MethodsA sap-flow meter device was developed to generate a heat pulse in a tree trunk at 15-minute intervals. The device comprises measuring probes, a processing unit, and a data logger. For a comprehensive evaluation, device probes were positioned on the trunk of a Ficus benjamina tree within a controlled environment at two distinct heights. The resulting sap flow through the vascular tissue was then compared to data obtained using the lysimetric method. The Ficus benjamina tree, with a trunk diameter of 3.5 cm and a height of 196 cm, was prepared during the summer of 2022. By measuring the rate of heat pulse dissipation and applying heat transfer principles, sap flow is estimated under the assumption that heat transfer occurs primarily through the sap flow within the vascular tissue. This estimation was achieved using the heat ratio method (HRM).The trunk was triple drilled with holes of 1.5 mm in diameter and 25 mm in depth. Following drilling, the probes were inserted into these holes (Figure 1). To prevent heat transfer from the probes to the surrounding environment, the trunk was wrapped with glass wool insulation. To assess the reliability of the device, the lysimetric method was employed to measure tree transpiration. For this purpose, the soil surface of the pot was covered with cellophane to ensure that evaporation and weight loss of the pot occurred exclusively through the tree's leaves. Hourly measurements of the pot's weight were taken using a digital scale. Changes in the pot's weight indicate the amount of water evaporated, which corresponds to the water transpired by the tree through its vascular tissue.Results and DiscussionThe results showed that the sap-flow meter device slightly overestimates the tree's water consumption compared to the values obtained using the lysimetric method. Sap flow and transpiration follow a similar trend, both escalating throughout the day and reaching their highest levels in the early afternoon. This value reached 17.98 ml h-1 for sap flow and 16 ml h-1 for transpiration (by lysimetric method), followed by a rapid decrease in the late afternoon as the air cooled down. In addition, the results of device measurements showed that spraying water on the leaves lowers both the rate and volume of sap flow. When the canopy becomes wet, the evaporation of water from the leaf surface leads to a drop in the temperature, which in turn significantly slows down the flow of sap.The v1/v2 ratio is not constant over time, making it crucial to choose the right starting point for measurements to ensure effective data acquisition during the device's operational cycle. It is essential to measure (by the device) the difference between temperature probes 40 seconds after heat pulse generation. The sap flow and transpiration followed a similar trend during the experiments. The sap flow and transpiration increased throughout the day, peaking in the early afternoon. On the first day, sap flow reached 17.98 ml h-1, while the second day recorded an even higher rate of 19.75 ml h-1. Correspondingly, the transpiration measured using the lysimetric method peaked at 16 ml h-1, followed by a rapid decline in the late afternoon.ConclusionThe results obtained from the developed device indicate several key findings. Sap flow and transpiration exhibit a similar trend during the test period, with the estimated sap flow value being approximately 30% higher than that obtained using the lysimetric method. The device effectively demonstrated the impact of surface irrigation; spray irrigation influences the sap flow rate such that when the canopy becomes wet, the sap flow rate decreases significantly. Additionally, sap flow and transpiration are positively correlated with air and canopy temperatures, and negatively correlated with relative humidity. Following calibration, the results show that the heat pulse method can accurately and effectively measure sap flow in the vascular tissue of trees.
Design and Construction
A. Sadin; M. H. Aghkhani; M. A. Ebrahimi-Nik; J. Baradaran Motie
Abstract
IntroductionPlanting rice seedlings in the main field followed by periodic or intermittent irrigation is often considered a form of dry farming. Research suggests that flood irrigation in rice cultivation is primarily favored by farmers for its ability to control weeds and ensure a reliable water supply, ...
Read More
IntroductionPlanting rice seedlings in the main field followed by periodic or intermittent irrigation is often considered a form of dry farming. Research suggests that flood irrigation in rice cultivation is primarily favored by farmers for its ability to control weeds and ensure a reliable water supply, rather than necessarily enhancing rice quality or yield. Depending on the rice variety, intermittent irrigation can sometimes improve both the quality and yield per unit area. The transplanting process in this method can be carried out manually without machinery or through mechanized methods using a planter.Materials and MethodsConventional rice transplanters designed for use in flooded land are not suitable for transplanting in dry land farming due to technical constraints. Therefore, it is necessary to develop a specialized rice transplanter tailored for such soil condition. This transplanter encompasses essential components, including a furrow opener, coverer, seedling storage tank or tray, seedling mechanism (distributor), seedling transfer mechanism (seedling transport piston), end separator for seedlings in the soil, power transmission system, depth adjustment shoe, and main and sub chassis. To evaluate the planter's performance, various parameters were assessed, including the percentage of lost plants, the average vertical angle of plant orientation, the average spacing between plants in the crop row, and the average number of seedlings per plant. Moreover, a factorial randomized block design was employed, with three replications for each level of the independent variables. The independent variables were forward speed (X1) at three levels of 0.25, 0.5, and 1 m s-1, planting depth (X2) at three levels of 4, 8, and 12 cm, and the size of the outlet opening of the seedling tray (X3) in three levels of 10, 15, and 20 mm.Results and DiscussionThe developed single-row planter features key specifications, including a working width of 250 mm, a power requirement of 0.57 kW, a theoretical field capacity of 0.06 ha h-1, and a field efficiency of 66.67%. The research findings revealed that forward speed, planting depth, and outlet opening size, along with their interactions, significantly impact the percentage of lost plants at the 99% confidence level. Among the three levels of forward speed (X1), the best speed level is 0.25 m s-1, as it results in the lowest percentage of lost seedlings. As the forward speed increases, the percentage of lost seedlings increases. The lowest percentage of lost plants (Y1) occurs at the planting depth of 8 cm and an outlet opening size of 20 mm. Furthermore, forward speed, planting depth, and their interaction have a noteworthy influence on the vertical angle of plants are established, at the 99% confidence level. With the increase of forward speed and planting depth, the average vertical angle of seedling establishment deviates from the vertical position. The forward speed of 0.25 meters per second and the planting depth of 8 cm show the best results for the establishment of seedlings. The sole factor affecting the spacing between plants in the row is the forward speed. The size of seedling tray’s outlet opening significantly affects the number of seedlings per plant at the 99% confidence level, while planting depth affects it at the 95% confidence level.ConclusionGiven the recent water crisis, adopting the dry rice farming method and using transplanters offers a viable solution for managing and conserving water in agriculture. Implementing dry planting with a custom-made transplanter yields several benefits, including reduced water consumption, lower cultivation costs, improved soil aeration, increased efficiency, and simplified planting processes. Utilizing this transplanter is an effective strategy to decrease both the time and expenses related to transplanting, while also mechanizing rice planting in dry fields.
Modeling
J. Baradaran Motie; M. H. Aghkhani; A. Rohani; A. Lakziyan
Abstract
Introduction 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 ...
Read More
Introduction 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. Materials and Methods 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. Results and Discussion 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. Conclusion 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.
M. H. Aghkhani; J. Baradaran Motie
Abstract
Introduction: Separation and grading of agricultural products from the production to supply, has notable importance. The separation can be done based on physical, electrical, magnetic, optical properties and etc. It is necessary for any development of new systems to study enough on the properties and ...
Read More
Introduction: Separation and grading of agricultural products from the production to supply, has notable importance. The separation can be done based on physical, electrical, magnetic, optical properties and etc. It is necessary for any development of new systems to study enough on the properties and behavior of agricultural products.
Some characteristics for separation are size (length, width and thickness), hardness, shape, density, surface roughness, color, speed limit, aerodynamic properties, electrical conductivity, elasticity and coefficient of static friction point.
So far, the friction properties of agricultural products used in the separating process, but the effect of electrostatic charging on static and dynamic coefficients of friction for separation had little attention. The aim of this study was to find out the interactions between electrostatic and friction properties to find a way to separate products that separation is not possible with conventional methods or not sufficiently accurate. In this paper, the separation of close and smiley pistachios by electrostatic charging was investigated.
Materials and Methods: Kallehghoochi pistachio cultivar has the top rank in production in Iran. Therefore, it was used as a sample.
The experimental design that used in this study, had moisture content at three levels (24.2, 14.5 and 8.1 percent), electric field intensity at three levels (zero, 4000 and 7000 V), speed of movement on the surface at three levels (1300, 2500 and 3300 mm per minute), friction surface (galvanized sheet iron, aluminum and flat rubber) and pistachio type at two levels (filled splits and closed) that was measured and analyzed in completely randomized factorial design.
A friction measuring device (built in Ferdowsi University of Mashhad) used to measure the friction force. It has a removable table that can move in two directions with adjustable speed. The test sample put into the vessel with internal dimensions of 300 × 150 × 25 mm and with wall thickness of 5 mm placed on trolleys. In the bottom of the container a separate aluminum plate was installed as the negative pole of the electric field. The friction plates as a positive pole placed on top of the sample. There were no contact between friction plates and walls of vessel (samples were about 2 to 3 mm higher from the edges of wall).
Frictional force changes due to movement of table, measured and recorded by an accurate load cell. From force-displacement curves, the coefficient of dynamic friction and static coefficient of friction calculated. In general, according to the experimental design, 486 tests were performed.
Results and Discussion: According to the results of statistical analysis, there is significant interaction affect between pistachios type and electrical field, as well as, the interaction between electrical field and speed, on dynamic coefficient of friction. It means two pistachio types can be separated by electrical charging.
Different physical properties of surface of filled non-splits pistachio nuts (such as corners and edges) and filled splits ones, caused differences in the distribution of electric charge and as a result, its interaction with the electric field were significant.
Changes in dynamic coefficient of friction according to the electric field intensity at different levels of moisture content and speed on the friction surfaces of iron, aluminum and rubber, was drawn in Fig.4, 5 and 6, respectively. These figures reflected the reduction of dynamic coefficient of friction by increasing the movement speed of table.
According to Fig.7, increasing the intensity of the electric field increases the dynamic coefficient of friction. Because this leads to build the opposition charge on samples and galvanized iron sheets, and with increase of electrical field, these charges will rise.
Fig.9 shows different trends of variation of dynamic coefficient of friction against moisture on rubber surface. This chart shows the higher coefficient of friction of filled non-splits samples than filled splits in all cases and shows an increasing trend with increasing humidity.
Conclusions: Table 2 presents the dynamic coefficients of friction in different states on different levels of moisture content. According to this table, the maximum difference was achieved in moisture content of 8% (which is close to the product storage moisture) in rubber surface with field strength of 7000 V and 1300 mm per minute speed. On 14 percent moisture content, the maximum difference was achieved on aluminum surface by 2500 millimeter per minute speed and 7000 V field strength. By the results, on 24 percent moisture content (the moisture close to peeling process) the maximum difference between filled non-splits and filled splits pistachios friction was achieved on aluminum surface, 7000 V electric field strength and 2500 millimeter per minute table speed.
Thus, to have a separation system, the aluminum surface, 7000 V electric field strength and adjustable speed between 1300 to 2500 mm per minute is recommended.
Design and Construction
A. Damirchi; M. H. Aghkhani; M. Khojastehpour; J. Baradaran Motie
Abstract
Introduction: In conventional farming, the soil and crop are considered uniform in different locations of the farm and the fertilizers are applied according to the average of soil needs with an additional percentage for safety (Loghavi, 2003). Non-essential chemical fertilizers in the field have harmful ...
Read More
Introduction: In conventional farming, the soil and crop are considered uniform in different locations of the farm and the fertilizers are applied according to the average of soil needs with an additional percentage for safety (Loghavi, 2003). Non-essential chemical fertilizers in the field have harmful effects and social, economic and environmental concerns will increase. Many fertilizers go into the surface waters and ground waters and cause poisoning and environmental pollution without being absorbed by the plants. In variable rate technology, the soil fertilizer needs a map of all parts of the farm which is prepared with the GIS system. This map is uploaded on the computer before variable rate fertilizer machine starts. The computer continually controls the fertilizing rate for each part of the farm using a fertilizing map and global positioning system. The purpose of this study is to construct and evaluate a map-based variable rate fertilizer system that can be installed on a common fertilizer in Iran to be used as a variable rate system.Materials and methods: In common variable rate fertilizers, the rotational speed change of the distributor shaft is used to apply fertilizers. In this way, a DC motor is assembled on the main shaft of all distributors, which reduces the fertilizing accuracy. The reason for this is that there is no separation for units along the width of the fertilizer. Therefore, we used one DC motor for each distributor and another motor to rotate the agitator in the tank.System Set up: To design and select a suitable engine, the required torque for the rotation distributor shaft was measured by a torque meter and the amount of 2.1 Nm was acquired for that. With regard to the maximum rate of nitrogen fertilizer for land and tractor speed at the time of fertilizing, the order of 350 kg per hectare and 8 km per hour, the maximum distributor shaft speed and power required to rotate distributor shaft were calculated to be 55 rpm and 6.9 watts, respectively. The selected motor was rated 27.5 watts, 24 volts and 7.5 amperes (Since there were no 6.9 watts motors in the market, a more powerful motor was selected). According to the gear ratio and motor speed, the speed of the distributor shaft was adjustable in the range of 0 to 65 rpm. To determine the speed and position with respect to the direction, a central encoder (E50S8-600-6-L-5 model manufactured by Autonix Korea) was used on the ground wheel. The encoder had 600 pulses per revolution of the axis.Performance evaluation of the system: Performance evaluation of the system consists of two parts; static and moving tests. In static tests, the purpose was the determination of the fertilizer loss (in grams), due to changes in distributor speed as well as the accuracy of the electromechanical control system according to the command values sent to the device. Results of this part were used for the calibration of the device.In motion tests: In motion tests, the assessment of fertilizer loss was due to values set in a given situation and the accuracy of planted fertilizer in place (delay and acceleration) is reviewed. The delay is found by the determination of the distance that the fertilizer was placed after the desired location on the ground and the acceleration is found by the determination of the distance that the fertilizer is placed before the desired location on the ground.Results and discussion: The distributor flow rate on F0 valve position was measured for different rotation speeds. The correlation (linear regression) between the planted fertilizer and rotation speed of distributor shaft (rpm) were 0.99 for y=71.636x+75.182. So, it can be deduced that these two parameters have a good linear correlation. The results achieved from diagrams and regression model were used in the programming of the system control unit. Thus, by reading the distributors motor speed, the amount of fertilizer can be calculated and the amount of used fertilizer according to the need of the farm in each part is controlled. The effect of plot length on the amount of fertilizing on 25% need level was not significant, but it was significant on 50% need level. This is due to stopping and starting fertilizer flow during the test, changes in motors speed and error of these on fertilizer output at a certain amount of fertilizing so that at the 25% need level, the error resulting from these factors had less share on the amount of plant fertilizer and the effect of plot length was not significant according to the system default. On the other hand, the effect of forward speed was significant on the 50% need level and insignificant on the 25% need level.Conclusions: In order to calculate the accuracy of the system, the error from the application amount of fertilizer was measured at different fertilizing rates. The correlation between the adjusted fertilizing rate and the measured fertilizing rate was 0.98 with regression model of y=1.0475x which shows the good accuracy of the system.
Design and Construction
J. Baradaran Motie; M. H. Aghkhani; M. H. Abbaspour-Fard; A. Lakziyan
Abstract
The issue of soil salinity is one of the snags for increasing agricultural productivity, which must be inhibited by appropriate devise and scientific management. One way to identify salty areas of farm lands is to prepare salinity maps. In this study, a prototype soil apparent electrical conductivity ...
Read More
The issue of soil salinity is one of the snags for increasing agricultural productivity, which must be inhibited by appropriate devise and scientific management. One way to identify salty areas of farm lands is to prepare salinity maps. In this study, a prototype soil apparent electrical conductivity measuring and mapping device, was designed and built. This device employs direct contact method of electrodes with soil (Also called Wenner method). The system inputs include power supply voltage, location signal from a GPS receiver and signal of voltage between the electrodes. The outputs include the apparent electrical conductivity with respective to geographical coordinate that created in a TEXT file, and then transmitted through a RS-232 serial port to a PC. Electrical conductivity data calibrated and mapped using ESAP-95 software package. To evaluate the device, electrical conductivity map of a land with area of 0.8 Ha surveyed in two ways: using the on the go EC mapper and capturing soil samples manually. The results of these two methods were then compared. Assessment of the device in a clay-loamy soil with low salt level, showed a good correlation with the laboratory EC, having mean error (ME) of -15.27μS.cm-1. Point to point comparison between surveyed data and laboratory EC’s shown that in 67 percent of measurements the errors were under 10 percent. These errors are acceptable mainly due to unknown soil variables and in comparison with other research findings.
