Agricultural mechanization
Majid Namdari; Shahin Rafiee; Soleiman Hosseinpour
Abstract
Introduction Considering the essential role of the agricultural sector in Iran's economy, it is very important to investigate and identify optimal production methods from an economic point of view. The purpose of this study is to calculate the economic indicators of sugar beet production, use of the ...
Read More
Introduction Considering the essential role of the agricultural sector in Iran's economy, it is very important to investigate and identify optimal production methods from an economic point of view. The purpose of this study is to calculate the economic indicators of sugar beet production, use of the Data Envelopment Analysis (DEA) method to identify the efficient units, and use of the Adaptive Neuro-Fuzzy Inference System (ANFIS) method to predict the benefit-cost index based on the consumption of production inputs in Hamedan province.Materials and Methods In this study, 88 farmers were studied. Data were collected from Hamadan province, Iran. Inputs included labor, machinery, diesel fuel, electricity, seeds, chemicals, farmyard manure, chemical fertilizers, and irrigation water. The indices of gross revenue, net income, gross income, economical productivity and benefit-cost ratio were calculated using information obtained from farmers. Then technical, pure technical, scale and cross efficiencies were calculated using CCR and BCC models for farmers. The benefit-to-cost ratio was considered as the economic index criterion in modeling with ANFIS. In this modeling, value of various inputs used for sugar beet production were selected as input variables. Various membership functions such as Triangular, Trapezoidal, Gaussian, Logarithmic and Gbell functions were tested. Also, different configurations were examined to provide the best configuration that predicts the model. In order to measure the accuracy of ANFIS models for estimating the observed values some quality parameters including the coefficient of determination (R2), root mean square error (RMSE) the mean relative error (RME) between the observed and the predicted values were applied to evaluate the performance of different models with different configurations.Results and Discussion The results showed that most of the production costs were in the category of variable costs. Variable costs account for 84% and fixed costs account for 16% of the total costs of sugar beet production. Cost of labor, water consumption, and land rent have the largest share of costs among all fixed and variable costs. The indexes of gross income, net income and benefit-cost ratio were obtained as 1188.99 $ha-1, 694.28 $ha-1 and 1.34, respectively. The results of data envelopment analysis showed that from the total of 88 farmers, considered for the analysis, 19 and 55 farmers were found to be technically and pure technically efficient, respectively. In other words, the farmers who are identified with the BCC model are more efficient than the farmers who are identified with the CCR model. Average technical efficiency, net technical efficiency, and scale efficiency were calculated as 0.73, 0.94 and 0.77, respectively.Data envelopment analysis indicates that farmers should focus on increasing the degree of mechanization of production by reducing the cost of human labor. The saving percentage of total input costs in the CCR model is higher than the BCC model. Optimization of input consumption in sugar beet production decreased the cost by 51.64% in the CCR model and by 28.27% in the BBC model. To predict the economic performance using inputs in sugar beet production, the three-layer arrangement with seven parameters obtained the best results. The modeled ANFIS is able to predict economic performance values with R2 of 0.96. This prediction is acceptable due to its high coefficient of determination and can be used in modeling.Conclusion Considering the high share of variable costs compared to fixed costs, it can be concluded that by applying appropriate management methods, the total costs of sugar beet production in Hamadan province can be significantly reduced. By mechanizing farms, the variable costs of farms can be reduced significantly. If the cultivated land does not have a problem with weeds, the use of conventional seeds can also reduce production costs. The DEA results showed that based on the CCR model, about 78.4% of farmers produce outside the efficiency and by providing management solutions taken from efficient DMUs (the recommendations of this study), they can reduce consumption costs by keeping product yield constant. The results of multi-level ANFIS implementation showed that the three-level ANFIS structure including four ANFIS models in the first level, two ANFIS models in the second level and a final model in the third level have the best performance for benefit-cost ratio prediction. It is proposed that implementation of multi-level ANFIS is a useful tool in helping to predict the economic indices of agricultural production systems.
Energy and Renewable Energies
Abolfazl Hedayatipour; Mohsen Soleymani; Mostafa Kiani Deh Kiani
Abstract
Introduction In recent years, due to its availability and low environmental pollution, the use of Earth-Air Heat Exchanger (EAHE) has been developed as an efficient energy system in heating and cooling residential buildings and agricultural greenhouses. In this system, air is circulated by a fan through ...
Read More
Introduction In recent years, due to its availability and low environmental pollution, the use of Earth-Air Heat Exchanger (EAHE) has been developed as an efficient energy system in heating and cooling residential buildings and agricultural greenhouses. In this system, air is circulated by a fan through a pipe buried deep in the ground. Depending on the geographical location and soil type, the soil temperature at a depth of 2-3 meters remains unchanged throughout the season. Of course, this depth varies throughout the year and according to climatic changes. The heat exchange between the soil and the air inside the pipe depends on the type of soil and its moisture content, the length and diameter of the air transmission pipe, the depth of burial and the velocity of the air flow (air velocity). Air circulation can be done in an open-loop or closed-loop circuit.Materials and Methods: A factorial experiment was conducted in the form of a completely randomized block design with two factors (pipe length at three levels (34, 17 and 52 meters) and air velocity at two levels (5 and 10 m/s)) in three replications, to investigate the effect of these factors on the coefficient of performance (COP), system efficiency and outlet air temperature. The experiment was conducted in a greenhouse in Arak city, Iran, in Joune 2022. This 150 square meter greenhouse was equipped with geothermal equipment. Air was circulated through a 200 mm diameter PVC pipe buried three meters deep in the ground. Air was circulating through an open loop circuit. Dependent variables were measured during the hot hours of the day (from 12:00 to 18:00) for one week at the end of July. The air temperature at the fan inlet and at 17, 34 and 52 meters along the pipe was measured by a single-channel data logger. Hourly changes in outlet air temperature, COP and efficiency were measured in a 24-hour period and plotted using Excel software.Results and DiscussionThe outlet air temperature for the pipe length of 34 and 52 m did not change when the air velocity decreased from 10 m/s to 5 m/s. But for the pipe length of 17 m, the maximum temperature, COP and efficiency were observed at an air velocity of 5 m/s. Regardless the air velocity, the average temperature of the outlet air for the three levels of the pipe length was 28.5, 25.5 and 25.3°C, respectively. The outlet air temperature was almost the same for the 34 and 52 m pipe lengths. In other words, the optimal length of the pipe is about 34 meters. The mean efficiencies for these two pipe length levels were 0.69 and 0.66, but the COP depended on the air velocity. The average COP for air velocity of 5 and 10 m/s was obtained 1.4 and 2.5, respectively. Based on these results, the best performance of the system in terms of output temperature reduction, cooling efficiency and COP is obtained in situation that the length of the pipe is 34 m and the air velocity is 10 m/s. when the length of the pipe is 17 meters, the temperature of the air outlet at two velocities of 10 and 5 m/s was 29.9 and 27 °C, respectively. The cooling efficiency and COP at two velocity of 10 and 5 m/s, were 0.34, 0.54; and 2.1, 1.7 respectively. If the desired temperature is 28-30 °C, pipe length of 17 m and the air velocity of 5 m/s is recommended. The results of hourly performance analysis showed that the highest difference between inlet and outlet air temperatures, is obtained at middle hours of the day. The higher the ambient temperature, the higher the efficiency of the EAHE system. ConclusionThis system successfully met the cooling needs of a model greenhouse in the weather conditions of Markazi Province in June. Based on the results, the optimal pipe length and air velocity were obtained as 34 m and 10 m/s, respectively. The average air outlet temperature and cooling efficiency were 25.5, 0.66 and 2.5 respectively. The higher the ambient temperature, the higher the EAHE efficiency. This is mainly due to the higher temperature difference between the outgoing and incoming air during the hottest hours of the day. As a result, system efficiency and COP increase at the hottest hours of the day.
