Precision Farming
R. Fathi; M. Ghasemi-Nejad Raeini; S. Abdanan Mehdizadeh; M. Taki; M. Mardani Najafabadi
Abstract
IntroductionInnovative technologies, such as smart sprayers, are pivotal catalysts for modernizing the agricultural sector and play an indispensable role in providing food for human consumption. Without the utilization of these technologies and the implementation of proper input management, it is predicted ...
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IntroductionInnovative technologies, such as smart sprayers, are pivotal catalysts for modernizing the agricultural sector and play an indispensable role in providing food for human consumption. Without the utilization of these technologies and the implementation of proper input management, it is predicted that environmental impacts will worsen in the future. Attaining sustainable production, while implementing programs to ensure food security, presents a considerable challenge for researchers and policymakers worldwide. In this research, the performance of a fixed-rate orchard sprayer was evaluated. Employing various equipment, the sprayer was then upgraded to a variable-rate sprayer, and its performance was reevaluated and compared to the fixed-rate model.Material and MethodsThis research comprehensively evaluated a fixed-rate orchard sprayer and subsequently upgraded it to a variable-rate sprayer for further assessment. The primary components of the developed variable-rate sprayer, consists of an ON-OFF solenoid valve, a digital camera for imaging purposes, an ultrasonic sensor, a flow meter, and a control circuit. The necessary modifications were implemented on a fixed-rate turbine sprayer. The development of the variable-rate sprayer was devided into two distinct phases. The initial phase involved determining the canopy volume and acquiring the necessary information pertaining to the spraying target, specifically the tree. The subsequent phase focused on decision-making and control of the spraying rate, thereby facilitating variable-rate application. Upon laboratory examination of the samples, spectroscopic results were obtained, and the total concentration of the pesticide solution was calculated across different sections of a one-hectare orange orchard. An investigation into the sedimentation of pesticide solution was conducted across different treatments in two spraying modes namely, variable-rate and fixed-rate and at three distinct speeds: low (1.6 km hr-1), medium (3.2 km hr-1), and high (4.8 km hr-1) resulting in six treatments.Results and DiscussionThe comparative analysis of average pesticide deposition on trees revealed a significant difference between the two spraying modes; variable-rate and fixed-rate. All indicators demonstrate that the type of sprayer and the spraying speed significantly influence changes in pesticide deposition across different treatments. However, the interaction effect of the type of sprayer and the speed of spraying did not significantly impact the amount of pesticide deposition on the trees and the total consumption of pesticide per hectare. The results indicated that neither the type of sprayer, nor the speed of spraying, nor their interaction had a significant effect on the spraying quality index. Furthermore, the numerical median diameter and volume median diameter were not significantly different across the treatments.The maximum pesticide consumption savings in the variable-rate spraying mode was 46%, achieved at a speed of 1.6 km hr-1. The maximum efficiency was 70% in the variable-rate spraying mode, occurring at a speed of 3.2 km hr-1. The lowest amount of pesticide deposition on the canopy of trees was observed in the variable-rate spraying method at the speed of 4.8 km hr-1 (1303 L ha-1), and the highest amount of deposition occurred in the fixed-rate spraying at the speed of 1.6 km hr-1 (2121 L ha-1). The highest amount of pesticide release in the air was also calculated in the fixed-rate spraying mode with a speed of km hr-1 (241 L ha-1) and the lowest value was calculated in the variable-rate spraying mode with a speed of 3.2 km hr-1.ConclusionEmerging technologies, such as smart sprayers, play a crucial role in increasing the productivity of the agricultural sector. If these technologies are not utilized, the challenges related to the sustainability of production will increase in the future. One of the critical operations in the production of agricultural products is the spraying phase. In this research, a fixed-rate sprayer was upgraded to a variable-rate sprayer, both sprayers were evaluated, and the results of this evaluation were then used to compare the two spraying systems. The results revealed that because the amount of the pesticide sprayed is controlled in real time by canopy volume detection in the variable-rate sprayer, in the best case (speed 1.6 km hr-1), it reduced pesticide consumption by 46% and reached 70% efficiency. In all the studied treatments, both the type of sprayer and the speed of spraying significantly affected changes in pesticide deposition. However, the interaction between the type of sprayer and the speed of spraying did not have a significant effect on the amount of pesticide deposition on trees or total pesticide consumption per hectare. There was no significant difference in the coverage percentage of the pesticide deposition on the target in different treatments, and the best spraying quality occurred in variable rate spraying with a speed of 4.8 km hr-1.By using a variable-rate sprayer, while saving on the costs of chemical pesticide consumption and spraying, toxic emissions that cause environmental pollution will also be reduced. Future research should focus on developing a variable-rate system based on independent nozzles, allowing for real-time control of each individual nozzle's spraying.
Agricultural systems engineering (greenhouse, fish farming, mushroom production)
M. Jalali; A. Banakar; B. Farzaneh; M. Montazeri
Abstract
IntroductionIn the poultry industry, reducing energy consumption is essential for reducing costs. Energy requirements in the poultry industry include heating, cooling, lighting, and power line energy. Identifying factors that increase energy usage is crucial, and providing appropriate solutions to reduce ...
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IntroductionIn the poultry industry, reducing energy consumption is essential for reducing costs. Energy requirements in the poultry industry include heating, cooling, lighting, and power line energy. Identifying factors that increase energy usage is crucial, and providing appropriate solutions to reduce costs and energy consumption is inevitable. One of the major and expensive factors in the poultry industry is the use of fossil fuels, which also causes pollution. Energy costs directly impact the cost of production and increase the per capita cost of production in the meat and egg sectors. In Iran, poultry farms are among the most widely used energy consumers, especially for heating breeding halls, making them a significant subset of the agricultural sector.Materials and MethodsThe problem under study is the thermal simulation of a meat poultry farm located in Ardestan city, Isfahan province. Ardestan city is situated in a desert region in the north of Isfahan province, at a latitude of 33 degrees and 23 minutes north, and a longitude of 52 degrees and 22 minutes east. The dimensions of the poultry hall floor are 5 meters by 8 meters, and it has a capacity of 300 poultry pieces. There are two inlet air vents (windows), each with dimensions of 1.90 by 1.6 meters. The roof has an average height of 2.5 meters and is sloping, made from a combination of plastic carton, fiberglass, and sheet metal.To reduce energy consumption in this poultry farm, a solar heating system is designed and studied in this research. The farm is one of the functions of Isfahan province, with dimensions of 8 meters in length and 5 meters in width. The simulation is performed using TRNSYS software.Results and DiscussionThe results demonstrate that a collector surface area of 26 m2 is necessary to reach the technically optimal point, where the sun's maximum production is achieved with no energy dissipation. Furthermore, the findings indicate that a balance of 16 m2 is required to align the solar system with the auxiliary system.ConclusionBy installing 2 square meters of solar collectors, 5.2% of the total energy demand can be met with solar energy. To fully meet the energy demand using solar energy, a collector area of 30 square meters is required. As the solar fraction increases, the system's ability to extract solar energy also increases. The maximum production of solar energy without any wastage is achievable with a collector area of 26 square meters. Moreover, to maintain a balance between the use of solar energy and the auxiliary system, a collector area of 16 square meters is needed.
Bioenergy
M. Eshaghi Pireh; M. Gholami Par-Shokohi; D. Mohammad Zamani
Abstract
IntroductionBiodiesel is an eco-friendly renewable alternate fuel and is made from transesterification of vegetable oils and animal fat. The use of biodiesel fuel as a strategy to conserve energy and reduce emissions is becoming increasingly important in engines. Biodiesel fuels increase NOx emissions ...
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IntroductionBiodiesel is an eco-friendly renewable alternate fuel and is made from transesterification of vegetable oils and animal fat. The use of biodiesel fuel as a strategy to conserve energy and reduce emissions is becoming increasingly important in engines. Biodiesel fuels increase NOx emissions in the engines. Compensate for the negative effect, the use of particles additive can be a reliable solution. In this study, the state of heat balance in a single-cylinder, four-stroke diesel engine with different fuel combinations with DXBYGZ formula (X % diesel fuel, Y % biodiesel mass, and Z ppm graphene oxide nanoparticles), has been studied experimentally.Materials and MethodsGraphene nanoparticles in three levels of 30, 60, and 90 ppm were mixed with biodiesel produced from cooking waste oil by transesterification method with volume percentages of 5 and 20% and pure diesel was used. The test engine was a diesel engine, single-cylinder, four-stroke, compression ignition, and water cooling, in the laboratory of renewable energies of agricultural faculty, Moghadas Ardabili University. The engine is connected to a dynamometer and data were obtained after reaching steady state conditions. In thermal balance study, the combustion process merely as a process intended to free up energy fuel, and the first law of thermodynamics is used. The energy contained in the fuel is converted to useful and losses energies by combustion. Useful energy measured by dynamometer as brake power and losses energy including exhaust emission and cooling system losses. Variance analysis of all engine energy balance was done by split-plot design based on a completely randomized design and the means were compared with each other using the Duncan test at 5% probability.Results and DiscussionThe results showed that by adding 60 ppm of graphene oxide and 20% biodiesel to diesel fuel, the useful output power is reduced to a minimum and is reduced by about 5.52%. The results of the model evaluation of useful power, exhaust emissions, and thermal losses in the cooling system showed that the exponential model had a better fit. By adding biodiesel and graphene oxide nanoparticles to diesel fuel, the useful power was reduced. In order to achieve the maximum useful output power and with the priority of adding biodiesel to a high amount, the fuel composition of D80B20G90 had relatively better conditions. By adding 30 ppm of graphene to pure diesel fuel, the equivalent power of exhaust fumes was reduced to a minimum of about 18.5%. In general, heat loss through the cooling system in pure diesel fuel (D100) was lower than other fuel compounds. Pure diesel fuel was recognized as the best fuel mixture due to having the highest useful power, and lowest energy losses in the form of exhaust fumes and through cooling.ConclusionBy adding graphene oxide to pure diesel fuel, the useful output power was reduced to a minimum. With the increase of biodiesel to diesel fuel, the amount of power of the cooling system also increased. By adding graphene oxide to pure diesel fuel, the equivalent power of the exhaust fumes was reduced. Heat loss through the cooling system increased with the increase of nano-graphene and biodiesel.
A. Kaab; M. Sharifi; H. Moradi
Abstract
IntroductionCantaloupe is a one-year-old herb of gourds and edible fruit with very good properties. Cantaloupe is one of the best sources of vitamin A and is rich in beta carotene, which is converted into vitamin A in the body. In addition, it contains other useful nutrients such as potassium, steel, ...
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IntroductionCantaloupe is a one-year-old herb of gourds and edible fruit with very good properties. Cantaloupe is one of the best sources of vitamin A and is rich in beta carotene, which is converted into vitamin A in the body. In addition, it contains other useful nutrients such as potassium, steel, fiber, magnesium, iodine and vitamins B5, B3, B6 and B1. Life cycle assessment in recent years has become an appropriate tool for assessing environmental impacts in agricultural and food industries. The purpose of this study was to evaluate the life cycle assessment of this horticultural crop in terms of energy consumption and the environmental impacts in the city of Iwan West, Ilam province.Materials and MethodsThe data were collected from dryland cantaloupe producers in the city of Iwan West, Ilam province using questionnaires and interviews were collected from farmers. In this study, four important energy indices were energy use efficiency (EUE), energy productivity (EP), specific energy (SE), and net energy gain (NEG). Environmental impacts on dryland cantaloupe production were evaluated using a life cycle assessment approach and the obtained indexes were calculated using the CML 2 baseline 2000 model. Ecoinvent databases were used to access needed information and data analysis was done with Simapro software. In a life cycle assessment project, all production processes of a product from the stage of extraction of materials to disposal of the remaining waste from the product are reviewed and the results of the reduction of environmental degradation are applied. Each life cycle assessment project has four essential steps including, goal and scope definition, life cycle inventory, environmental impact assessment, and interpretation.Results and DiscussionInput and output energy analysis in dryland cantaloupe productionThe total input and output energies for dryland cantaloupe were calculated to be 39021.59 and 39190.43 MJ ha-1, respectively. Diesel fuel, agricultural machinery and nitrogen fertilizers were the most widely used energy inputs with 51%, 24%, and 14%, respectively. Energy use efficiency for dryland cantaloupe production was calculated at 1.004.Analysis of environmental impacts in dryland cantaloupe productionIn this study, the global warming potential per produced product in dryland cantaloupe production was estimated to be equal to 202.45 kgCO2 eq. from among inputs, diesel fuel had the most impact on the effects of abiotic depletion and ozone layer depletion, and in all parts of the effects of agricultural machinery and nitrogen fertilizers, the largest share of pollutants was allocated. The results of normalization showed that the effect of marine aquatic ecotoxicity and freshwater aquatic has the highest environmental burden on dryland cantaloupe production.ConclusionThe results of energy analysis showed that the total energy inputs were equal to 39021.59 MJ ha-1. Among inputs of diesel fuel, agricultural machinery, and nitrogen fertilizer were the most consumed energy inputs. The energy use efficiency index and the net energy in this study were 1.004 and 168.84 MJ ha-1, respectively. The results of environmental impacts had shown that diesel fuel, nitrogen fertilizer, and agricultural machinery had been most affected. It is recommended that proper management of agricultural machinery, equipping fields with new and suitable machines and avoiding the use of tractors and worn-out tools should be put in order to minimize the energy consumption and environmental pollutants generated by the production. Less use of chemical fertilizers (especially nitrogen) and its replacement with organic fertilizers can also be affected.
Design and Construction
H. Dehghan-Hesar; D. Kalantari
Abstract
Introduction Optimizing the energy consumption in mechanized agriculture is becoming more important due to the limited energy sources in the world. In this regard, optimization of the cutting blades is presented in this study by modifying the geometric form of the blade to reduce the forage cutting energy. ...
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Introduction Optimizing the energy consumption in mechanized agriculture is becoming more important due to the limited energy sources in the world. In this regard, optimization of the cutting blades is presented in this study by modifying the geometric form of the blade to reduce the forage cutting energy. Hence, two new blades, inspired by the geometric profiles of front claws of mole crickets and teeth of grasshoppers were designed and built using the biomimetic method (the method for transferring biological solutions to the engineering ones). Finally, the new biomimetic blades were tested and compared with two other conventional blades (flat and bent blades) by cutting 8 different types of crops and weeds. Materials and Methods The main idea of building one of the blades was inspired by the geometric forms of mole crickets' scissors-like front legs and lower teeth of grasshoppers. Therefore, five adult mole crickets and five grasshoppers were collected from a farm in Kalat-e Naderi, Khorasan Razavi Province. In the next step, different images were captured from the front leg of mole cricket and tooth of grasshopper using the stereomicroscope (Nikon, SMZ-U, Japan). In the next step, the images were transferred to the image analysis software (Image J) and the boundary lines of images were selected. Then, the selected boundary lines were imported to SolidWorks software and the points on the selected curve were extracted. The obtained points were drawn in Matlab software and several fitting curves for the points were examined, e.g., Fourier function, Gaussian function, and polynomial function. According to the obtained results, the Gaussian profile was selected to design the blade with the highest correlation coefficient (R2=0.99), see Fig. 1d. To design the desired blade, a section of the Gaussian curve between points A and B were used. Finally, the biomimetic blade of the mole cricket and grasshopper were drawn in SolidWorks software (Fig. 1e). After designing the blades in the SolidWorks software, the biomimetic blades were built by a CNC machine. Results and Discussion In all the treatments, a significant difference was observed between the biomimetic blades and the conventional flat and bent blades according to the results of Tukey's test at the level of 5%. The obtained results showed that there was no significant difference between the mole cricket and grasshopper blades at the level of 5% for cutting. According to the results obtained in this study, there was a significant difference at the level of 5% between the grasshopper and flat blades for cutting alfalfa, clover, amaranth, orach, and poaceae; as well as between the grasshopper and bent blades for cutting alfalfa, clover, nutsedge, and amaranth, also between mole cricket and flat blades for cutting alfalfa, clover, purslane, amaranth, orach, paddy, and poaceae and finally between mole cricket and flat blades in cutting alfalfa, clover, nutsedge, amaranthus, and paddy. In this regard, no significant difference at the level of 5% was observed between the flat and bent blades for all cutting treatment. The batches containing 6 stems were used for cutting the soft stems with low shear stress and the batches containing 4 stems were used for cutting thick stems with high shear stress. Conclusion The results obtained in this study indicated that the geometrical form of the blade has a significant influence on the amount of required shear energy. The mole cricket biomimetic blade reduced the cutting energy compared to the flat blade by 23.37% to 52.51% (with the mean of 39.11%) and compared to the bent blade by 10.46% to 52.46% (with the mean of 32.8%). The grasshopper biomimetic blade also reduced the cutting energy compared to the flat blade by 15.78% to 53.82% (with the mean of 33.59%) and compared to the bent blade by 2% to 46.29% (with the mean of 27.87%). According to the results of this study, the mole cricket biomimetic blade showed better performance in comparison with the grasshopper biomimetic blade for cutting the plants and as a final result could be recommended to build the plant cutting blades.
H. R. Gazor; A. Moumeni
Abstract
Introduction High energy consumption and non-uniformity drying in conventional batch type dryer are the common problems in paddy dying industry. Non-uniformity drying causes to kernel breaking chance in the milling process. Using new dryers with better performance can solve the drying problem and energy ...
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Introduction High energy consumption and non-uniformity drying in conventional batch type dryer are the common problems in paddy dying industry. Non-uniformity drying causes to kernel breaking chance in the milling process. Using new dryers with better performance can solve the drying problem and energy saving. In this research, the operation of a re-circulating batch dryer was compared with a fixed bed batch dryer (conventional dryer) for paddy drying. Materials and Methods This research was done in a paddy milling factory in Ferydonkenar and deputy of Rice Research Institute of Iran, in Amol, Mazandaran province. Both re-circulating dryer and conventional batch type dryer were made by Khazar Electric Company in Amol- Iran and they had 5 tonnes capacity. In the re-circulating dryer, ambient air was warmed in the furnace and blown to drying zone inside of grain bin. Natural Gas (NG) was used for air warming in dryers. Warm air absorbed paddy moisture and pushed away from the dryer. Drying temperature ranges for re-circulating dryer and conventional dryer was 48-50 °C and 38-52°C, respectively. The paddy variety was one of the Iranian rice varieties as Tarom and initial moisture content of grains was 21% (w.b), it was decreased using drying to 8-9% (w.b) for milling process. Paddy moisture content was measured each 60-120 min by SUNCUE TD-6 portable moisture tester-Taiwan. Energy consumption calculated by fuel and electrical energy summation in each experiment. Natural Gas and electrical power consumption were measured by Gas and electric counters respectively. Drying time, paddy moisture change trend and energy consumption were investigated for paddy drying in each dryers. Also, milling ratio, breaking percent, whitening degree, and elongation rate after cooking were studied after the milling process for rice dried using national standard methods and deputy of Rice Research Institute facilities in Amol. Experimental samples were 150 g and husker (SATAKE THU35B), a whitener (SATAKE TMU05) and KETT C-100 were used for husking, whitening and whiteness degree, respectively. All Experiments were done with three replication and data analyzed using T- student method in 5% probability. Results and Discussion Results showed that re-circulating dryer caused to reduce 54.12 percent in drying time and energy saving in paddy drying in compare with conventional paddy dryers. The trend of moisture content changes was longer and over-drying occurred in lower layers in conventional batch type dryer compared to re-circulating dryer. Paddy drying was 20 hours more in batch type than the re-circulating dryer. It caused wasting time and energy consumption. Specific energy consumption for water evaporating in the re-circulating batch dryer was 3.9 MJ/kg water and it was 76.25 percent less than fixed bed batch dryer. After the drying process in both dryers, paddy moisture content was in range 8-9 percent (% w.b). Using re-circulating dryer did not have a significant effect on milling yield but it had a significant effect on broken rice. Broken rice decreased by 5 percent after the milling process when paddy dried by re-circulating. Uniformity of layers drying and normal heat stress in rice kernels in re-circulating dryer reduced broken rice in the milling process. Whiteness degree of rice dried using fixed bed dryer was 2.4 percent more than the re-circulating batch dryer. Also, rice dried had more elongation rate about 6.2 percent after cooking when paddy dried by conventional dryer. Conclusion Results of this paper showed that using of re-circulating dryer would decrease time and modify energy consumption in paddy drying. The costs of installation for the re-circulating batch dryer was about 5.3 times more than fixed bed batch dryer. It seems too expensive at first but considering energy and time-saving in the drying process and suitable effect on decreasing grain breakage in paddy milling, using of the re-circulating batch dryer is recommendable in rice milling factories.
S. Haroni; M. J. Sheikhdavoodi; M. Kiani Deh Kiani
Abstract
Introduction One of the most important sources of the sugar production is sugarcane.Sugar is one of the eight human food sources (wheat, rice, corn, sugar, cattle, sorghum, millet and cassava). Also sugarcane is mainly used for livestock feed, electricity generation, fiber and fertilizer and in many ...
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Introduction One of the most important sources of the sugar production is sugarcane.Sugar is one of the eight human food sources (wheat, rice, corn, sugar, cattle, sorghum, millet and cassava). Also sugarcane is mainly used for livestock feed, electricity generation, fiber and fertilizer and in many countries sugarcane is a renewable source for the biofuel. The efficient use of inputs in agriculture lead to the sustainable production and help to reduce the fossil fuel consumption and greenhouse gases emission and save financial resources. Furthermore, detecting relationship between the energy consumption and the yield is necessary to approach the sustainable agriculture. It is generally accepted that many countries try to reduce their dependence to agricultural crop productions of other countries. The being Independent on agricultural productions lead to take more attention to modern methods and the objective of all these methods is increasing the performance with the efficient use of inputs or optimizing energy consumptions in agricultural systems. Energy modeling is a modern method for farm management that this model can predict yield with using the different amount of inputs. The objective of this study was to predict sugarcane production yield and (greenhouse gas) GHG emissions on the basis of energy inputs. Materials and Methods This study was carried out in Khouzestan province of Iran. Data were collected from 55 plant farms in Debel khazai Agro-Industry using face to face questionnaire method. In this study, the energy used in the sugarcane production has considered for the energy analysis without taking into account the environmental sources of the energy such as radiation, wind, rain, etc. Energy consumption in sugarcane production was calculated based on direct and indirect energy sources including human, diesel fuel, chemical fertilizers, pesticides, machinery, irrigation water, electricity and sugarcane stalk. Energy values were calculated by multiplying inputs and outputs per hectare by their coefficients of energy equivalents. Input energy in agricultural systems includes both direct and indirect energy and renewable and non-renewable forms. Direct energies include human labor, diesel fuel, water for irrigation and electricity and indirect energies consisted of machinery, seed (cultivation of sugarcane has been done with cutting of sugarcane instead of seed), chemical fertilizer. Renewable energies include machinery, sugarcane stalk, chemical fertilizer while non-renewable energy consisted of machinery, chemical fertilizer, electricity and diesel fuel. Energy values were calculated by multiplying inputs and outputs per hectare by their coefficients of energy equivalents. The amounts of GHG emissions from inputs in sugarcane production per hectare were calculated by CO2 emissions coefficient of agricultural inputs. Energy modeling is an attractive subject for engineers and scientists who are concerned about the energy management. In the energy area, many different of models have been applied for modeling future energy. An artificial neural network (ANN) is an artificial intelligence that it can applied as a predictive tool for nonlinear multi parametric. Artificial neural network has been applied successfully in structural engineering modeling ANNs are inspired by biological neural networks. Results and Discussion The total energy used in the farm operations during the sugarcane production and the energy output was 1742883.769 and 111000 MJha_1, respectively. Electricity (52%) and chemical fertilizers (16%) were the most influential factors in the energy consumption. The electricity contribution was the highest due to the low efficiency of energy conversion in electric motors which were used for irrigation in the study area. In some areas, inefficient surface irrigation wastes a lot of water and energy (in forms of electricity). Another reason is that electricity energy equivalent for Iranian electricity production is higher than developed countries because Iran’s electricity grid is highly dependent on fossil fuels, so that 95% of the electrical energy in Iran is generated in thermal power plants using fossil fuels sources. In addition, the electricity transmission system is too old. GHG emissions data analysis indicated that the total GHG emissions was 415337.62 kg ha-1 (CO2eq) kgCO2eq ha-1 in which burning trash with the share of 62% had the highest GHG emission and followed by electricity (32%), respectively. The ANN model with 7-5-15-1 and 5-5-1 structure were the best model for predicting the sugarcane yield and GHG emissions, respectively. The coefficients of determination (R2) of the best topology were 0.98 and 0.99 for the sugarcane yield and GHG emissions, respectively. The values of RMSE for sugarcane production and GHG emission were found to be 0.0037 and 4.52×10-6, respectively. Conclusion The statistical parameters of R2 and RMSE demonstrated that the proposed artificial neural networks results have best accuracy and can predict the yield and GHG emission. It is generally showed that artificial neural networks have good potential to predict the yield of the sugarcane production.
K. Andekaeizadeh; M. J. Sheikhdavoodi; M. Byria
Abstract
Introduction Sugarcane is an important plant in the world that cultivate for the production of sugar and energy. For this purpose, evaluation of Sugarcane (SC) and Energycane (EC) methods is necessary. Energy is vital for economic and social development and the demand for it is rising. The international ...
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Introduction Sugarcane is an important plant in the world that cultivate for the production of sugar and energy. For this purpose, evaluation of Sugarcane (SC) and Energycane (EC) methods is necessary. Energy is vital for economic and social development and the demand for it is rising. The international community look toward alternative to fossil fuels is the aim of using liquid fuel derived from agricultural resources. According to calculations, about 47% from renewable energy sources in Brazil comes from sugarcane so as, the country is known the second largest source of renewable energy. Sugarcane in Brazil provides about 17.5% of primary energy sources. Material such as bagasse and ethanol are derived from sugarcane that provide 4.2% and 11.2 % consumed energy, respectively . In developing countries, the use of this product increase in order to achieve self-sufficiency in the production of starch and sugar and thus independence in bioethanol production. Evaluation of energy consumption in manufacturing systems, show the measurement method of yield conversion to the amount of energy. Many of products of Sugarcane have ability to produce bioenergy. Many materials obtain from sugarcane such as, cellulosic ethanol, biofuels and other chemical materials. Hence, Energycane is introduced as a new method of sugarcane harvesting. But, one of the problems of this method is high cost and high energy consumption of harvester. So that the total cost of Energycane method is 38.4 percent of production total costs, whereas, this cost, in Sugarcane method is 5.32 percent of production total costs. In a study that was conducted by Matanker et al. (2014) with title “Power requirements and field performance in harvesting EC and SC”, the power requirements of some components of sugarcane harvester and its field capacity, in Sugarcane and Energycane methods were examined. The consumed power by basecutter, elevator and chopper was measured in terms of Mega grams per hour (Mg.h-1) Chopper energy consumption in Energycane method was 1.65 KJ more than Sugarcane method. The quantitative parameters including forward speed (km.h-1), field capacity (ha.h-1), the field performance (Mg.ha-1) and reed output (Mg.h-1) were also measured. Finally, statistical comparison was conducted between the two methods. The aim of this study is to provide Simple Additive Weighting (SAW) method using the calculated parameters by the Matanker et al. This method provides decision-making ability for a manager. Materials and Methods In this study, quantitative parameters including fuel consumption (Lit.ha-1), harvester power (kW), efficiency of engine torque (%), energy of used hydraulic oil in basecutter, chopper and elevator (Mj.Mg-1), forward speed (km.h-1), field capacity (ha.h-1), the field performance (Mg.ha-1) and reed output (Mg.h-1 ) and qualitative parameters including the mean of average diameter of the stem (mm), stem height (m), number of stems on the meter (m-1), the percentage of cut stems and intact, cut stems and partially damaged and strongly damaged stems. The average height of straw and the stubble (mm), average of bulk density (kg.m-3), the average of moisture content, average of dry matter (biomass), (Mg.ha-1) were measured. Data analysis was conducted with Simple Additive Weighting (SAW) method. Tables 1 and 2 in terms of qualitative and quantitative parameters for the two methods of A and B, to form of rij matrix and based on measured criteria (C) have arranged, respectively. Conclusion Choosing the appropriate method for sugarcane harvesting should be according to the purpose of harvesting. Energycane method has high energy consumption that it increases the operational costs. On the other hand, the quality of the obtained biomass from it is better, but Sugarcane method has high energy efficiency. But in terms of quality, the plant is not in good condition. For this reason, it is necessary, aim of harvesting and its type, be specified before crop planting.
N. Gholamrezaei; K. Qaderi; K. Jafari Naeimi
Abstract
Introduction 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 ...
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Introduction 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. Materials and Methods 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. Results and Discussions 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. Conclusion 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.
K. Andekaeizadeh; M. J. Sheikhdavoodi; M. E. Khorasani
Abstract
Introduction Main part of energy consumption in agricultural mechanization is tillage operations therefore optimization of energy consumption in tillage operation is very important. A management method for system to optimize in agriculture is Simple Additive Weighting (SAW) methodology that this method ...
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Introduction Main part of energy consumption in agricultural mechanization is tillage operations therefore optimization of energy consumption in tillage operation is very important. A management method for system to optimize in agriculture is Simple Additive Weighting (SAW) methodology that this method can operate according to criteria of the systems. This method states that, which system has better performance? (for example the system for agricultural tractors, type of implements, methods of tillage, planting and harvesting, and etc). Fuel consumption is the most important factor in terms of energy consumption in tractor because the fuel energy contributes to help tractor to work . Specific draught is important force that measured for investigation of energy consumption of tillage implements, it can show the amount of drawbar force that optimized (for work width 1 meter implements tillage) by using this method. The multiplication of the drawbar force in forward speed factor resulted drawbar power. The most common method is using of tractors drawbar power in mechanized agriculture. Important factor for assessment and determination performance of tractor is drawbar power. Several studies have been showed that about 20 to 55%of available drawbar power was wasting by implements tillage. Another important parameters that affect on traction efficiency pull’s machine is slip. A simple additive weighting two-step procedure involving basic weighted as follows: (1) scale the values of all attributes to make them comparable; (2) sum up the values of the all attributes for each alternative. Materials and Methods In this study, three implements tillage were studied including moldboard plow, disk plow and disk harrow and they called A, B and C, respectively. Three different forward speeds of 3, 4, 5, 6 km.h-1 for each implements were selected according to the type of work at various depths. In this study fuel consumption factor was measured by means of micro-oval flow meter, forward speed was measured by a Doppler radar, Slip was measured by Proxy Sensor, and drawbar force was measured by a three point auto hitch dynamometer. Depth tillage was maintained by depth-knob control system. tillage implements for comparison proper class was rated tables (1), (2) and (3) that includes low depth (12.4 cm moldboard plow, disk plow 12.3 cm and 12.4 cm disk harrow), middle depth (18 cm moldboard plow, disk plow 17.4 cm and 15.2 cm disk harrow) and the high depth (23.5 cm moldboard plow, disk plow 23.4 cm and 17.2 cm disk harrow). Results and Discussion The results of Table 5 shows a higher combined ratio of the amount of energy that is optimum performance in the form of (1), (2) and (3). Also Combined ratio is a way that the whole system will be valued according to their criteria that objective criteria according to the study, we classified as positive and negative criteria and all its problems the system had a higher combined ratio than the rest of the system is the optimal system performance. Kheiralla et al. (2004) in their research used statistical methods and indicated that energy efficiency disk harrow, disk plow and moldboard plow was better than the other devices but Simple Additive Weight way of energy efficiency in different conditions partially expressed. Conclusion The results showed that disk plow in different depth tillage and forward speed, has higher energy efficiency. Disk harrow compared with other tillage implements recommended for the high depth. Disc harrow is not optimal in the low depth because it compared to other implements has lower slip and tractive efficiency. Moldboard plow is optimum use energy in depth and average speeds (4 and 5 km h-1).
A. Farhadi; S. Rostami; B. Ghobadian; Sh. Besharati
Abstract
Introduction Nowadays, due to higher environmental pollution and decreasing fossil fuels many countries make decisions to use renewable fuels and restrict using of fossil fuels. Renewable fuels generally produce from biological sources. Biodiesel is an alternative diesel fuel derived from the transesterification ...
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Introduction Nowadays, due to higher environmental pollution and decreasing fossil fuels many countries make decisions to use renewable fuels and restrict using of fossil fuels. Renewable fuels generally produce from biological sources. Biodiesel is an alternative diesel fuel derived from the transesterification of vegetable oils, animal fats, or waste frying oils. Considering the differences between diesel and biodiesel fuels, engine condition should be modified based on the fuel or fuel blends to achieve optimum performance. One of the simplest and yet the most widely used models is the thermodynamic model. After verification of the data obtained by model with experimental data it is possible to generalize the extracted data to an unlimited number of functional conditions or unlimited number of fuel types which saves time and reduces costs for experimental engine tests. Using the second law of thermodynamics, it is possible to calculate and analyze the exergy of the engine.4 Materials and Methods In this work, the zero-dimensional model was used to account for internal energy variations, pressure work, heat transfer losses to the solid walls and heat release. The applied assumptions include: The cylinder mixture temperature, pressure and composition were assumed uniform throughout the cylinder. Furthermore, the one-zone thermodynamic model assumes instantaneous mixing between the burned and unburned gases. The cylinder gases were assumed to behave as an ideal gas mixture, Gas properties, include enthalpy, internal energy modeled using polynomial equations associated with temperature. In this research, the equations 1 to 20 were used in Fortran programming language. The results of incylinder pressure obtained by the model were validated by the results of experimental test of OM314 engine. Then the effects of injection timing on Energy and Exergy of the engine were analyzed for B20 fuel. Results and Discussion Comparing the results of the model with the experimental data shows that there was a good agreement between the model and experimental results. The results showed that advancing fuel injection timing increases the peak cylinder pressure. When fuel injecting occurs before the standard injection timing, the pressure and temperature of the charged air in the cylinder is less than that of the fuel when it is injected at standard injection timing. Thus, ignition delay of the injected fuel extends further. As a consequence, the reaction between fuel and air improves, which prepares a good mixture for burning. When the combustion starts, the rate of heat release increases in the premixed or rapid combustion phase of the combustion process due to the suitability of the mixture of air and fuel and hence the peak pressure of cylinder increases. When the injection timing is retarded, the fuel is injected into charged air that has a high temperature and pressure. Thus, in the injection timing of 10 degrees before top dead center, the maximum of incylinder pressure and temperature are reduced compared to the standard injection timing. By retarding the fuel injection into the cylinder, the indicator availability, the heat loss availability by heat transfer from cylinder walls and irreversibility are increased and by advancing the fuel injection into the cylinder, the indicator availability, the heat loss availability by heat transfer from the cylinder walls and irreversibility are reduced. High temperature will increase the produced entropy, so by advancing the injection timing the produced entropy will increase while the retarding injection timing reduces the produced entropy. Exergy and energy efficiencies increased by advancing the injection timing. At 2000 rpm the total availability and heat loss availability by heat transfer was increased compared to 1200 and 1600 rpm. Conclusion The proposed model was able to predict the pressure and temperature of the cylinder at different injection timings. By advancing the fuel injection timing energy and exergy efficiency and heat loss availability by heat transfer was increased. At 2000 rpm the total availability and heat loss availability by heat transfer was increased.
A. Jalali; A. Mahmoudi; M. Valizadeh; I. Skandari
Abstract
Introduction: In recent years, production techniques and equipment have been developed for conservation tillage systems that have been adopted by many farmers. With proper management, overall yield averages for conventional and reduced tillage systems are nearly identical. Sometimes, field operations ...
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Introduction: In recent years, production techniques and equipment have been developed for conservation tillage systems that have been adopted by many farmers. With proper management, overall yield averages for conventional and reduced tillage systems are nearly identical. Sometimes, field operations can be combined by connecting two or more implements. Much research has focused on either reducing or eliminating tillage operations to develop sustainable crop production methods. The greatest costs in farm operations are associated with tillage due to greater specific energy requirement in tillage and the high fuel costs. Combined operations reduce both fuel consumption and time and labor requirements by eliminating at least one individual trip over the field. Light tillage, spraying, or fertilizing operations can be combined with eitherprimary or secondary tillage or planting operations. The amount of fuel saved depends on the combined operations. Generally, light tillage, spraying, and fertilizing operations consume between 0.25 and 0.50 gallons of diesel fuel per acre. Fuel savings of 0.12 to 0.33 gallons per acre can usually be expected from combining operations. Eliminating one primary tillage operation and combining one light tillage, spraying, or fertilizing operation with another tillage or planting operation can usually save at least a gallon of diesel fuel per acre. Combining operations has the added benefit of reducing wheel traffic and compaction. To improve the tillage energy efficiency, implementing effective and agronomic strategies should be improved. Different tillage systems should be tested to determine the most energy efficient ones. Tillage helps seed growth and germination through providing appropriate conditions for soil to absorb sufficient temperature and humidity. Tillage is a time consuming and expensive procedure. With the application of agricultural operations, we can save considerable amounts of fuel, time and energyconsumption. Mankind has been tilling agricultural soils for thousands of years to loosen them, to improve their tilth for water use and plant growth and to cover pests. Tillage is a process of creating a desired final soil condition for seeds from some undesirable initial soil conditions through manipulation of soil with the purpose of increasing crop yield.The aim of conservation tillage is to improve soil structure. Considering the advantages of conservation tillage and less scientific research works on imported conservation tillage devices and those which are made inside the country, and considering the importance of tillage depth and speed in different tiller performance, this investigation was carried out.
Materials and methods: This investigation was carried out based on random blocks in the form of split plot experimental design. The main factor, tillage depth, (was 10 and 20cm at both levels) and the second factor istillage forward speed, (was 6, 8, 10, 12 km h-1 in four levels for Bostan-Abad and 8, 10, 12, 14 km h-1 for Hashtrood) with 4 repetitions. It was carried out by using complex tillager made in the Sazeh Keshte Bukan Company, which is mostly used in Eastern Azerbaijan and using Massey Ferguson 285 and 399tractors and its fuel consumptionwas studied.
Results and Discussion: In this study, the effect of both factors on the feature of fuel consumption was examined. Regarding tillage speed effect for studies characteristic in Bostan-Abad at 1% probability level fuel consumption was effective. The effect of tillage depth has significance at 5% probability level on fuel consumption. The interaction effect of tillage speed and depth on fuel consumption was significant at probability level of 1% . In Hashtrood, the effect of tillage speed was significant on fuel consumption at probability level of 1% , and also tillage depth effect was significant on fuel consumption amount at probability of 1% . The interaction effect of tillage speed and depth on fuel consumption was significant at 1% level of probability .
Conclusions: In this study, the effect of both factors on fuel consumptionwas examined. In Bostan-Abad and Hashtroud on the whole, the results indicated that with the increase in the speed of tillage, fuel consumption, was reduced per hectar.The speed of 10 kilometers per hour was the best for this implemented work. Also, with an increasing depth of tillage, the fuel consumption increased.Through an increase in tillage speed, fuel consumption mass reduced at unit level. Moreover, the optimum speed was concluded to be 10km per hour. The best tillage depth using this machine is 10cm.
A. R. Taheri-Rad; A. Nikkhah; M. Khojastehpour; Sh. Nowrouzieh
Abstract
Introduction: Golestan province is one of Northern provinces in Iran. The area under cultivation of agricultural products in this province is 724.697 hectares, of which about 694.618 hectares are used for farm products (AJMDC, 2011). Cotton as one of oilseed is a potential feedstock for biodiesel production ...
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Introduction: Golestan province is one of Northern provinces in Iran. The area under cultivation of agricultural products in this province is 724.697 hectares, of which about 694.618 hectares are used for farm products (AJMDC, 2011). Cotton as one of oilseed is a potential feedstock for biodiesel production (Ahmad et al., 2011). In the study of energy consumption and greenhouse gas emissions for cotton production in Alborz province, results showed that the total energy input was 31.237 MJ ha-1. Energy efficiency and energy productivity were 1.85 and 0.11, respectively, and greenhouse gas emissions of cotton production in Alborz province were 1195.25 kg CO2eq ha-1 (Pishgar-Komleh et al., 2012). Another study on energy analysis, greenhouse gas emissions and economic analysis of agricultural production was performed in Northern Iran (AghaAlikhani et al., 2013; Royan et al., 2012; Pishgar-Komleh et al., 2011; Mohammadi et al., 2010; Taheri-Garavand et al., 2010). The aims of this study were to determine the energy flow, greenhouse gas emissions and economic analysis of cotton production in the Golestan province and also to determine the effect of energy inputs on cotton yield.
Materials and methods: This research was conducted during 2011-2012 in three areas including Gorgan, Aq’qala and Gonbad in the Golestan province. The primary data were collected from the rice producers through a field survey with the help of a structured questionnaire. The number of subjects were studied by the Cochran formula (Snedecor and Cochran, 1980). Accordingly, 43 cotton producers were determined. In this study, eight energy inputs including seed, labor, machinery, diesel fuel, chemical fertilizers, chemicals, water for irrigation and farmyard manure for cotton production system were considered as independent variables. The outputs of the system including lint and seed were considered as dependent variable. Energy indices including energy efficiency, energy productivity, specific energy and net energy were calculated. In this study, the effect of energy inputs on yield was estimated using the Cobb-Douglas function. In order to determine the sensitivity of energy inputs in the production of cotton in the Golestan province, the marginal physical productivity method was applied. Greenhouse gas emissions, inputs of agricultural machinery, fuel, chemical fertilizers, chemicals and farmyard manure in cotton production in the Golestan province were calculated by the coefficients of each of these inputs. For economic evaluation of cotton production in the Golestan province, the variable costs, fixed and total production per unit area were considered. Economic indices of total production value, gross income, net income, economic productivity and benefit to cost ratio were estimated. Data analysis was performed using JMP8 software.
Results and Discussion: Cotton yield in the Golestan province was about 2650 kg ha-1. Average cotton yield in the Alborz province was reported to be 3430 kg ha-1 (Pishgar-Komleh et al., 2012). In this study, diesel fuel had the highest energy consumer among other inputs like the other studies that have been done on energy crop production in Iran. Labor energy input with energy consumption of 2413 MJ ha-1, is known to be the fourth high-energy input in cotton production in the Golestan province. However, in many studies in Iran, this input was accounted to be less than one percent of the energy consumption in the production of agricultural products (Saeedi et al., 2013; Khoshnevisan et al., 2013; Mobtaker et al., 2012; Mobtaker et al., 2010). Chemical energy input with 1036 MJ ha-1, was allocated as 3.6% of energy consumption in the cotton production in the region. Seed energy input was the lowest energy among the other inputs in cotton production in the Golestan province. The results revealed that the total energy inputs for cotton production in the Golestan province was 28.898 MJ ha-1. The average energy efficiency for cotton production in the Golestan province was obtained to be 1.58. Energy productivity for cotton production in the Golestan province was calculated to be 0.092. From the results of Cobb-Douglas function to determine the relationship between energy input and yield of cotton in Golestan province, the effects of human labor, diesel fuel, water for irrigation, chemical fertilizers and farmyard manure inputs on the yield were positive, and the effects of agriculture machinery and chemicals inputs on cotton yield were negative. Greenhouse gas emission from diesel fuel input hadthe highest value of 646.23 kg CO2eq ha-1 with a 45.2 percent share. Farmyard manure with 23.5 percent of greenhouse emissions was identified as the second largest input in greenhouse gas emissions in cotton production. Variable costs, fixed and total cotton production in the Golestan province were calculated to be 3042429, 851880 and 3894309 Toman ha-1, respectively. Benefit to cost ratio for the cotton production in the Golestan province was calculated as 1.16.
Conclusions: The results of this study showed that the energy efficiency for cotton production in the Golestan province was less than the energy efficiency for cotton production in the Alborz province, Hatay province of Turkey, and canola, soybean and sunflower production in the Golestan province. Also, the energy efficiency of cotton production was less than that of cotton production in Antalya Turkey and canola in the Mazandaran province. The highest share of energy consumption and greenhouse gas emissions belonged to diesel fuel with the share of 45.6 and 45.2 percent, respectively. However, this input accounted for 2.7 percent of variable costs.
M. Rajabi Vandechali; A. Hemmat; A. Ghanbari Malidarreh
Abstract
About 60% of the mechanical energy consumed in mechanized agriculture is used for tillage operations and seedbed preparation. On the other hand, unsuitable tillage system resulted in soil degradation, affecting soil physical properties and destroying soil structure. The objective of this research was ...
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About 60% of the mechanical energy consumed in mechanized agriculture is used for tillage operations and seedbed preparation. On the other hand, unsuitable tillage system resulted in soil degradation, affecting soil physical properties and destroying soil structure. The objective of this research was to compare the effects of three types of secondary tillage machines on soil physical properties and their field performances. An experiment was conducted in a wheat farm in Jouybar area of Mazandaran as split plots based on randomized complete block design with three replications. The main independent variable (plot) was soil moisture with three levels (23.6-25, 22.2-23.6 and 20.8-22.2 percent based on dry weight) and the subplot was three types of machine (two-disk perpendicular passing harrow, Power harrow and Rotary tiller). The measured parameters included: clod mean weight diameter, soil bulk density, specific fuel consumption, machine efficiency and machine capacity. The effects of treatments and their interactions on the specific fuel consumption, machine efficiency and machine capacity and also the effects of treatments on bulk density were significant (P
