نشریه تحقیقات سامانه ها و مکانیزاسیون کشاورزی
پیاپی 78 (تابستان 1400)

Given the vastness of the country's border area and the climatic diversity of the crop and garden various regions, it is an undeniable necessity to achieve a suitable cultivation pattern that can maximize the utilization of factors and institutions of production, especially the water-limiting factor. The main question in this study is that considering the current situation in horticulture in Qazvin province, what parameters emphasize the optimal conditions for determining the cultivation pattern and allocating inputs in different orchards. For this purpose, in this study, first, the relevant technical, environmental, social and economic indices and criteria that have been presented in various research sources were examined. Then, using multi-criteria decision making methods, a composite index of the mentioned indices was presented. In this study, a simple two-step random sampling method was used. In this research, in order to present a suitable pattern for cultivating horticultural products from the ideal planning method using Lingo 17 software was used. According to the results of the model, in the case of phosphate and potash fertilizers, the consumption reduction was observed to be 9.5% (above the ideal level), but in the case of nitrogen fertilizer, the consumption was reduced by 8%. In the case of the three ideals of reducing the consumption of herbicides, insecticides and fungicides, excessive success was observed, i.e. a decrease in consumption of 4.5, 5.7 and 8 percent, respectively. Due to the abundance of water resources in this area, in the case of 12 ideals related to water reduction, too much success was observed, i.e. a one percent decrease in water consumption per month. The results show that the application of ideal planning method in optimizing goals and allocation for each product provides more logical results than single-objective models.

Soil compaction causes the lack of water and oxygen in the soil; therefore, development of the roots is restricted. Therefore, vibrating subsoilers recommended for better soil crushing and for increasing the power transfer efficiency from tractor to soil. The vibration used in the subsoiler is available from the type of sweep and its main reason is the use of the tractor power axis (P.T.O) as the source of vibration creation. In this study a subsoiler, which was equipped with a rotational vibration system, was fabricated and used to provide rotational vibration, the vibration frequency control and the side of rotation, be controlled with electrical power. Factorial statistical design was performed in a completely randomized manner with speed and frequency, as independent variables. The dependent variables were: tillage depth, tillage cross section, clod mean weight diameter, tensile force and total energy. The effect of rotational vibration with confidence of 95% on tillage depth and with confidence of 99% on tillage side and mean weight of the clot was significant. Frequency (-36 Hz) had the best crushing of the soil. The effect of rotational vibration on tensile force was significant with confidence of 99% and the frequency (+36 Hz) had the lowest tensile force. The energy used for tillage was reduced with confidence of 99% and the frequency (+36 Hz) had the lowest energy consumption. By considering the amount of crushing for energy consumption, the marker was defined as the subsoiler efficiency (the amount of energy consumed for the crushing). The result of this marker is the priority of the rippering of the treatments with frequency (+36, -36, -18, +18 and 0 Hz) respectively.

One of the important processes in agriculture is separating of agricultural products. The use of cyclones is one of the methods that with lower costs, shorter separation time and simpler operation, has a high efficiency compared to other separation methods (Such as separation by hand and so on). The aim of this research is to designing, simulation and construction a cyclone separation device and evaluation it in order to separate the stigma from the saffron petals. In this research, cyclone simulation was performed using ANSYS FLUIN software and computational fluid dynamics (CFD) analysis method and the separation efficiency was obtained. The device was designed using SOLID WORKS software and its prototype was made and evaluated at three levels of 1.5, 2.5 and 3.5 m/s of air speed and at five levels of moisture content (10, 20, 40 and 60)%wb. For this purpose, a factorial experiment with completely randomized design with three replications was used. The evaluation results of the device showed that the highest separation of the device at 20% moisture content and 3.5 m/s air speed was 80% efficiency and the lowest was 11% efficiency for 80% moisture content and 1.5 m/s air speed which was very close to the best result of simulating the device in ANSYS FLUINT software which it was 89% efficiency at 3.5 m/s air speed.

In this research, the status of energy consumption and the rate of emission of pollutants were evaluated using the life cycle assessment of rice produced in Guilan province, Iran. Potential influencing factors included global warming potential, acidification potential, terrestrial eutrophication, depletion of oil resources, depletion of phosphate resources, depletion of potassium resources and depletion of water resources were evaluated. The results of this study showed that the total energy required to produce one ton of rice paddy was 88064 MJ per ha. While the energy output of rice paddy was 58173 MJ per ha. Diesel fuel and agricultural machinery inputs with a total of 65.52% accounted for the largest amount of input energy. The energy efficiency and energy productivity in rice paddy production were calculated as 0.66 and 0.04, respectively. According to the results of the life cycle assessment, carbon dioxide emission (740.38 kg per ton of paddy) was higher than other pollutants produced by applying other inputs. It has been reported that one ton of rice paddy, globally, is responsible for producing 1116.61 kg of carbon dioxide as pollutant. The depletion of oil resources due to the use of diesel fuel was 7587 MJ and the depletion of water resources was 3354 m3. Depletion of phosphate and potassium resources were calculated as 2.15 kg P2O5 eq and 0.62 kg K2O eq, respectively. Also, the ecosystem index and the resource depletion index per 1 ton of rice paddy were 0.5789 and 1.7057, respectively.

The study was conducted to evaluate canola transplanting possibility and to compare this method with seeding method in Khuzestan province. In transplanting (TR) method, some 9 plants of 38-days old seedlings were transplanted in one m2. In seeding (SD) method, 6 kg/ha of canola seeds were planted in furrow and ridge pattern at a distance of 60 cm. The results showed that there were no significant difference between two methods of plantation from the point of view of  the yield, thousand- seeds weight, number of lateral stems, plant height, and the amount of extracted oil. Two-year average grain production in TR and SD were 2225.2 and 2391.8 kg/ha respectively. So, it can be concluded that Khuzestan province has the potential for canola TR, without any grain yield reduction, comparing to SD method. The results also showed that there was significant difference (P<0.01) between the treatments in terms of number of capsules per each lateral stem. More plant spacing cause to greater vegetative growth and then 64% more capsules per stem produced in TR as compared to SD. The diameter of main and lateral stems in TR method with 19.33 and 7.23 mm were 30 and 16.2 percent more than that of DS method respectively. Water use efficiency in TR and DS were calculated as 0.38 and 0.44 kg/m3 respectively. Benefit to cost ratio for one hectare of canola production in TR and DS were 0.98 and 3.02 respectively.

In recent year, using smart systems in agriculture in order to save costs, increase the production per unit area, minimize the hard working conditions as well as dangerous and long works, and also the precise control and supervision is unavoidable in the modern agriculture. The positioning of a mobile agriculture robot with any kind of structure and working role is one of the most fundamental and essential issues in the area of agricultural machines, and it is also a prerequisite of movement for any kind of mobile system in the farm. Therefore, this positioning always faces challenges and also is gotten a lot of attention from scholars working in this field of study. Sensor data fusion from several information sources and using various data fusion methods gives us a general precise image of the agriculture robot’s position. The Dempster-Shafer theory is one of these mentioned methods which benefits from a better performance compared with other data fusion methods, regarding the variable and unspecified workspace of agricultural robots. In this study, the methods of Dempster-Shafer and Kalman filter were used as two major tools of positioning sensors fusion related to an agriculture controllable tractor, in order to achieve the best estimation of the positioning, regarding the environmental conditions. So as to use Dempster-Shafer method in the fusion of numerical data of global positioning system (GPS), inertial measurement unit (IMU) and wheel (shaft) encoder sensors, the data reliability of each sensor is firstly determined by the standard deviation of data for each last n generated data. Then, the weighting is accomplished by the Shannon entropy method. In the simulation section, the dominant geometric equations of the studied tractor are extracted, and a proportional integral derivative (PID) controller is used in order to kinematic control of the robot. Afterward, the simulation process is run in Sim-mechanics MATLAB software. Finally, the performance of two investigated methods in this work is assessed and then compared by addition of different noises into the data of each sensor.

The 4th generation industrial livestock farming reduces livestock losses, increases fertility rates, reduces operating costs, manages human resources, and generally increases productivity. In this research, a set of wearable sensors including a cattle collar and a leg mounted sensor was designed for automation of livestock farming. A LoRaWAN based internet of things network was designed using a set of custom gateways in three livestock farms. An intelligent livestock big data analysis framework that uses edge and cloud computing was designed for processing and modelling of the behaviour of the cattle using the collected sensor data. A decision support system for estrous cycle management, stress and health control and cattle behaviour modelling was designed using machine learning based modelling of this data. The proposed system monitored the cattle and provided the vital signs such as body temperature, mobility, feeding behaviour and estrous behaviour for management and veterinarian decision support. The accuracy of the KNN algorithm for modelling livestock behaviour was 78% and the accuracy of convolutional deep neural networks was 84%. However, due to the simplicity of the KNN algorithm, this method increased the battery life of the system by 4.5 times and therefore, it was a more appropriate choice for commercial livestock farming.