جستجوی مقالات مرتبط با کلیدواژه "energy efficiency" در نشریات گروه "مکانیزاسیون کشاورزی"

The current research used a hybrid conveyor belt drying system, including a solar water heater and solar-powered infrared lamps, to dry rosemary leaves. Its performance characteristics were evaluated regarding drying time, total energy consumption, solar energy ratio and energy efficiency. In each experiment, 300 g of freshly harvested rosemary leaves at a drying air temperature of 50 °C and different values of inlet air velocity (7, 8 and 9 m/s) and infrared lamp power (0, 150 and 300 W) were fed into in the drying system. The optimum point for the working of the drying system was determined using Response Surface Method (RSM) by selecting the appropriate values for the inlet air velocity and infrared power based on these criteria: to minimize drying time, to minimize total energy consumption, to maximize energy efficiency, and to maximize solar energy ratio. Accordingly, the selected optimum point included infrared power of 300 W and an air velocity of 8.85 m/s. Under the defined conditions, the performance characteristics of the drying system, including drying time, total energy consumption, energy efficiency and solar ratio, were equal to 149.13 minutes, 3868.91 kJ, 52.37% and 0.75, respectively. According to the findings of this study, it can be concluded that using a developed drying system can significantly reduce the need for fossil fuel resources and lead to an acceptable performance efficiency in the drying process of medical plants.

Today, providing food security for the world's growing population by preserving the earth's resources & minimal environmental effects has become one of the basic & important challenges in sustainable agriculture, & the optimal use of resources is one of the main requirements of sustainable agriculture. In this study, the pattern of energy consumption during peach production, analysis & modeling of energy & performance of peach production in Nazarabad city was investigated. Data were collected through interviews & filling specialized questionnaires. The results showed that the total energy consumption & production were equal to 72716.83 & 5234.89 megajoules per hectare, respectively. Electricity was the most consumed input with a share of 59% of the total input energy. The indices of energy efficiency, energy efficiency, energy intensity and net energy were obtained as 0.07, (kg/MJ) 0.03, (MJ/Kg) 26.39 and (MJ) -67481 respectively. Modeling was done with three methods enhanced gradient regression, decision tree regression, and random forest regression, and RRMSE was -0.003, -0.0090, and -0.0091, and R2 was 0.98, 0.95, and 90, respectively was calculated. The results showed that the enhanced gradient method is able to accurately predict the values of the energy efficiency indices of peach production. The results showed that the energy efficiency and production can be predicted with high accuracy through the inputs of irrigation water, electricity, chemical and animal fertilizers, labor force, chemical poisons, diesel fuel and machines and machine learning method. Sensitivity analysis was performed with SHAP and the results showed that the most influential input in energy prediction was nitrogen fertilizer.

Solar energy as a renewable energy source can be used to produce heat and electricity. Among solar energy power production systems, photovoltaic thermal (PV/T) technology is almost a new and widely-used hybrid technology that can simultaneously produce heat and electricity. In recent years, nanomaterials in solar energy systems have significantly increased. In the present study, the effect of using nano-fluid water-aluminum oxide at three volumetric concentrations (0.10, 0.07, and 0.05%), and three inlet flow rates (0.6, 0.9, and 1.2 l/min ) on the electric efficiency, thermal efficiency and exergy efficiency of PV/T system at different times of the day were numerically calculated using CFD. Then, their results were compared with the observed experimental results. The inlet flow rate of 1.2 liters min-1 and the aluminum oxide nano-fluid concentration of 0.10% were optimized as input points due to the proper cooling of the system. The thermal efficiency is a function of the difference between the inlet and outlet temperatures of the fluid, and its highest value was observed at the maximum irradiation condition (960 W/m2 ) with 53%. Additionally, the highest and lowest exergy efficiency values were 21.6% and 15.9%, respectively, in the afternoon.

In this study, the amount of shadow in different types of flat-plate solar collectors according to the geographical conditions of Iran was estimated by using artificial neural network models (MLP and RBF) and Support Vector Machine (SVM). In this study, two types of LM and BR training algorithms with sigmoid tangent transfer function (TanSig) and different number of neurons in a hidden layer with k-fold cross validation method were used to create random datasets at each stage of modeling. The results showed that the MLP model with BR training algorithm and (5-23-1) structure, can create high-precision data similar to real values. The average MAPE and R2 statistics for the above model were estimated to be 0.42 ± 0.10 and 0.99±0.01, respectively. Also, there was no significant difference between the actual data and the predicted values (95% probability) at mean, variance and distribution. The results of sensitivity analysis showed that the distance of the absorber plate and the glass cover is the most important factor influencing the formation of shadows.

Reducing material waste in agricultural production is one of the most important strategies to increase efficiency in the agricultural sector. Accordingly, various methods have been used to measure the economic efficiency and energy of agricultural production. However, most of these methods do not take into account the hidden costs of measuring the efficiency of the production system. Material Flow Cost accounting (MFCA) enables farmers to be aware of the amount of energy and value-added losses that results from material waste. In this study, a new approach (ISO 14,051) was used to measure the economic and energy indicators of canola production in Ardabil province. Data were obtained through face-to-face interviews with 65 farmers in the 2,018. According to the obtained results, the highest amount of input energy is related to fossil fuels and nitrogen fertilizer. Based on energy and economic indicators calculated by two methods of conventional accounting and accounting based on material flow cost accounting, it was found that the total value of canola production according to conventional accounting is equal to 59,055,260 Rials per hectare and in material flow costing is 65,694,700 Rials per hectare. However, in case of reducing material and energy waste (negative production), the benefit-cost ratio in the production process will increase by 0.12 units. Energy efficiency and specific energy were the same in the two accounting approaches because of the non-interference of output energies in their calculation. But net energy in conventional accounting differs by 9,162 megajoules from MFCA. The findings of the present study will help to better understand the issues and challenges related to reducing waste and environmental emissions and optimizing production systems as well as investing in crop production.

Some unit operations of food process engineering such as drying consumes a high amount of energy. Therefore, analysis of energy and exergy can be a suitable method to manage the energy consumption of the drying. Hence, in the present research, analysis of energy and exergy for the drying process of lemon verbena leaves was performed.

A cabinet solar dryer was employed to investigate the energy consumption of thin layer drying of lemon verbena leaves. The dryer had a galvanized solar plate collector which had a surface area of 0.75 m2 and to absorb the maximum solar energy, the collector painted with the black color. The collector was set at an angle of 45 degrees relative to the horizon and an electric blower was installed in the bottom of the collector to blow the ambient air through the solar collector and hence, hot air entered the drying chamber to dry the lemon verbena leaves. In order to record the air temperature and humidity in different locations of the dryer, an Arduino board with 8 smart sensors (AM2301, with temperature accuracy of 0.5°C and humidity accuracy of 3%) were used. To obtain the initial moisture content of the leaves, they inserted in an electrical oven for 16 hours at a temperature of 70°C. In order to measure the moisture content of the leaves during drying, they weighted at different times using a digital balance (A & D, Japan with accuracy of 0.001 g).Energy consumption rate of the drying was calculated by Equation (1):Where, Ein: energy consumption rate (kW), : mass flow rate of drying air (kg s-1), cp: specific heat of drying air (kJ kg-1 °C-1), Δt: temperature difference between the ambient air and drying air (°C).Also, the specific energy consumption of drying (SEC) was calculated by Equation (2):Where; SEC: Specific energy consumption (MJ kg-1 of removed water) t: drying time (s), and M: mass of removed water from the drying material (kg).Also, useful power can be calculated from Equation (3):Where; Eout: useful power (kW), ms: Evaporation rate (kg s-1), lg: latent heat of vaporization (kJ kg-1 of water)In order to calculate energy efficiency, Equation (4) was used: Also inlet and outlet exergy were calculated by equations (5) and (6), respectively: Where; T1: Inlet air temperature into the drying chamber (°C), T2: Outlet air temperature from the drying chamber (°C), T0: Ambient air temperature (°C).
Also, Equations (7) and (8) were used to calculate exergy efficiency and loss, respectively:

The results of energy analysis showed specific energy consumption (SEC) increased with increasing of drying temperature and decreasing of air velocity. Accordingly, in the air velocity of 2 m s-1 and the temperatures of 30, 40, and 50 ˚C, SEC were 276.3, 694.7, and 708.0 MJ kg-1 of removed water, respectively. While SEC for an air velocity of 2.5 m s-1 and air temperatures of 30, 40, and 50 ˚C were 266.9, 469.8, and 638.0 MJ kg-1 of removed water, respectively, the corresponded values for air velocity of 3 m s-1 were as 217.0, 391.3, and 501.8 MJ kg-1 of removed water, respectively. Also, the results revealed that with an increase of temperature and a reduction of velocity, energy efficiency reduced, so that the maximum value of energy efficiency observed in an experiment with temperature of 30˚C and velocity of 3 m s-1. Also, the highest value of exergy efficiency obtained in temperature of 50˚C and velocity of 3 m s-1.

A hot air solar dryer was used for drying lemon verbena leaves. Results of specific energy consumption of drying showed a high amount of fossil fuels can be saved by using this dryer. Also, from the aspect of energy and exergy efficiency, using of the dryer in the lower temperature and higher air velocity is recommended.

Introduction :

Agriculture is an energy conversion process. In this process, solar energy, fossil fuel, and electricity are converted mainly into food and fiber. In the agricultural section, the trend of energy consumption increases rapidly every year. Constraints on agricultural land, population growth, changes in infrastructure, and a trend towards high living standards have contributed to increase energy use in the agricultural sector. Fuel, electricity, machinery, seeds, chemical fertilizers, and chemical pesticides have a significant share in supplying energy sources. Effective use of energy in agriculture reduces environmental problems and prevents the destruction of natural resources and develops sustainable agriculture as an economic production system. Wheat is the most strategic crop in Iran that more than 50.39% of arable land belongs to wheat.  

The current study has been done with the objects of evaluation of inputs and crop yield, input and output energy, and energy indices for irrigated wheat for seven provinces such as Alborz, Isfahan, Ardebil, Khorasan-e Razavi, Khuzestan, Golestan, and Hamadan. For this purpose, the required information gathered via study of publications, face to face interview with experts and leading farmers, and questionnaire completion by the irrigated wheat farmers in different cities of each understudy province. Then, with the help of equivalent energy equations, input and output energy and energy indices were calculated. In this research, simple random sampling method was used.

According to the results, total input energies of Alborz, Isfahan, Ardebil, Khorasan-e Razavi, Khuzestan, Golestan, and Hamadan provinces were calculated with 45458.84, 92714.8, 38755.34, 104701, 50971.2, 26198, and 49362. 64 MJ ha-1 respectively, while the output energy for those provinces were 162169.28, 131958.8, 77381.39, 122297, 141901.2, 134106, and 125511.69 MJ ha-1, respectively. The maximum share of energy input for Alborz, Ardebil, Khuzestan, Golestan, and Hamadan provinces were regarding to chemical fertilizers with amounts of 43.06, 43.16, 58.33, 38.05, and 47.57 percent, respectively, while irrigation energy requirement had maximum share in Isfahan and Khorasan-e Razavi with 62.36 and 57.17 percent, respectively. The minimum share of energy input for Alborz, Isfahan, Ardebil, Khorasan-e Razavi, and Golestan provinces was calculated for labor energy requirement with 0.39, 0.29, 0.79, 0.18, and 0.26 percent, respectively, while in Khuzestan and Hamadan, chemicals consumed the lowest energy with 0.55 and 0.89 percent, respectively. Share of direct energies for all understudy provinces were 44.61, 72.13, 41.22, 67.48, 30.75, 39.44, and 39.91 percent, share of indirect energies were 55.39, 27.87, 58.78, 32.52, 69.25, 60.56, and 60.09 percent, share of renewable energies were 27.99, 65.91, 32.35, 60.57, 19.26, 34.92, and 35.16 percent, and share of nonrenewable energies were 72.01, 34.09, 67.65, 39.43, 80.74, 65.08, and 64.84 percent, respectively. Energy ratio for Alborz, Isfahan, Ardebil, Khorasan-e Razavi, Khuzestan, Golestan, and Hamadan provinces were 3.57, 1.42, 3.48, 1.17, 2.78, 5.12, and 2.54, respectively, and energy productivities were 0.26, 0.11, 0.26, 0.08, 0.21, 0.38, and 0.18 kg MJ-1, respectively. Average input energy, output energy, energy ratio, energy productivity, and net energy gain for all provinces were 58308.83 MJ ha-1, 136092.15 MJ ha-1, 2.87, 0.212 kg MJ-1 and 77783. 31 MJ ha-1, respectively. Total input energy cost for irrigated wheat production was 57.966 ×106 Rial ha-1. The Energy intensiveness, Energy intensiveness value, Energy intensity cost, and Energy ratio cost were found as 1.299 MJ (103 Rial)-1, 0.641 MJ (103 Rial)-1, 10853.05 Rial kg-1, and 1.21, respectively.

In order to reduce the share of indirect energy and non-renewable energy, organic fertilizers should be replaced by chemical fertilizers and plant residues in the field. Minimum tillage should also be used in land preparation operations to reduce fuel consumption, maintain organic matter and soil moisture and reduce soil erosion. To compensate for some of the elements taken from the soil by the plant and the increase of organic matter and fertility of the soil, it is recommended to return part of the plant residues to the soil. The use of combined machines that can perform several simultaneous operations and minimizing and protecting soil tillage to reduce fossil fuel consumption through minimum use of machinery should be investigated as a national necessity.

The purposes of this study were to determine energy use pattern and study the relationships between energy inputs and yield, costs and revenue for plum production in Khansar Township. In this research, the required information was collected by questionnaire and face-to-face interview with gardeners. The inputs included labor, machinery, diesel fuel, chemical and organic fertilizers, irrigation water and electricity. The Cobb-Douglas model and sensitivity analysis were used to investigate the effect of input energy on performance. In this study the total energy used to produce plum was 56721.19 MJ/ha, and the electricity input with 66.25% was as the most common source of energy in plum production. The share of renewable energy for this product was 3.36%. The results of the Cobb Douglas function showed that the energy inputs of human labor, electricity, chemical fertilizer had a significant effect on performance. The results of sensitivity analysis showed that among the energy inputs, human labor energy had the highest marginal physical productivity (MPP) and the energy of human labor had the highest effect (0.87) compared with other sources in the production of plums. Energy efficiency for plum production was 0.46 and the human labor accounted for the highest production cost with 70.75%. Also, the benefit to cost ratio in the production of plum was calculated as 1.9.

In this paper the energy and exergy analysis of flat plate solar collector simulator equipped with Inclined Broken Rib roughness was investigated based on experimental data in open circuit as well as optimizing system operating conditions. The experiments were carried out with nine levels of mass flow rates (0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.10 and 0.11 kg/s), five levels of heat flux (1000, 1100, 1200, 1300 and 1400 W/m^2) and three levels of ambient air temperature (20, 25 and 30 °C). The results showed that the highest and lowest values of energy efficiency were found 49.8 and 0.3%, in treatments with ambient temperature of 20 and 25 °C, mass flow rate of 0.11 kg/s and heat flux of 1000 and 1400 W/m^2, respectively. Also, the highest and lowest exergy efficiency were calculated 5.75 and 0.607% in treatments with ambient temperature of 20 and 30 °C, mass flow rate of 0.11 kg/s and 0.03 and heat flux of 1000 W/m^2, respectively. The response surface methodology was employed to optimize solar collector operating conditions. Optimum operating conditions were found to be anambient temperature of 20 °C, mass flow rate of 0.11 kg/s and heat flux of 1000 W/m^2. At this optimum condition, the energy and exergy efficiency were found to be 42.08 and 5.76%, respectively at a desirability level of 0.92.

This study was carried out to evaluate the energy efficiency of safflower production units using data envelopment analysis technique in Jolgeh district of Isfahan province in 2016. Data were collected from a total of 30 safflower farms using questionnaires and face to face interviews. The results showed that the input and output energy were 30843.1 and 6775.71 megajol/ha, respectively. The highest share of energy consumption was allocated to chemical fertilizers (48.18%), fuel (24.55%) and water (12.44%) respectively. The average technical efficiency, net technical efficiency and efficiency of Safflower product scale were 94.28%, 99.93% and 94.33%, respectively. According to the CCR model, the highest intakes of excessive intake units are related to the inputs of chemical fertilizers, especially urea (58%), diesel fuel (18%), water (12%) and seed consumption (8%). Fuels with 49% and then urea fertilizer with 35% have the largest share in the emissions of greenhouse gases in the production of safflower (Figure 4-16). Therefore, using managed mechanized systems, it is necessary to control the use of machinery to reduce fuel consumption and to reduce the consumption of urea crop by replacing livestock fertilizers in order to reduce the pollution caused by greenhouse gas emissions and pollution of the water resources of the area.This study was carried out to evaluate the energy efficiency of safflower production units using data envelopment analysis technique in Jolgeh district of Isfahan province in 2016. Data were collected from a total of 30 safflower farms using questionnaires and face to face interviews. The results showed that the input and output energy were 30843.1 and 6775.71 megajol/ha, respectively. The highest share of energy consumption was allocated to chemical fertilizers (48.18%), fuel (24.55%) and water (12.44%) respectively. The average technical efficiency, net technical efficiency and efficiency of Safflower product scale were 94.28%, 99.93% and 94.33%, respectively. According to the CCR model, the highest intakes of excessive intake units are related to the inputs of chemical fertilizers, especially urea (58%), diesel fuel (18%), water (12%) and seed consumption (8%). Fuels with 49% and then urea fertilizer with 35% have the largest share in the emissions of greenhouse gases in the production of safflower (Figure 4-16). Therefore, using managed mechanized systems, it is necessary to control the use of machinery to reduce fuel consumption and to reduce the consumption of urea crop by replacing livestock fertilizers in order to reduce the pollution caused by greenhouse gas emissions and pollution of the water resources of the area.

Now day, global warming is too considerable due to consumption of fossil fuels. Use of fossil fuels in power plants for electricity generates has the largest portion of greenhouse gas and emissions in the world. Agricultural section has the outstanding contribution in electricity industry; furthermore the processing and drying of agricultural products have the highest consumption energy. In the current research, the parameters of energy, the environment (global warming) and social costs of drying of apples slices at three temperatures 45, 55 and 65° C and the air velocity 0.5 m/s for different pretreatment of osmotic, ultrasound, blanching and microwave (each pretreatment at three levels) were evaluated. Result shown that the amount of time, energy consumption, specific energy and heat consumption decreased with increasing temperature and using different pretreatments as compared to control treatment. Also, energy, drying and thermal efficiency, increased with increasing air temperature. The highest amounts of energy and drying efficiency were obtained %5.04 and %5.62, respectively for microwave pretreatment involving 360 W power and 2.5 min at 65° C temperature. Normal treatment with 45°C temperature gave the lowest value of efficiency energy (%2.27) and drying (%2.38). Results revealed that the highest and lowest greenhouse gas for the withdrawal one kilogram of water from apple slices was produced 21.19 and 9.37 kgCO2, 10.05×10-4 and 4.45×10-4 kgCH4, 2.01×10-4 and 0.89×10-4 kgNO2 respectively. Also, the highest and lowest social costs for  leaving one kg of water from apple slices was obtained 34927.60 and 15449.04 Rials for steam power plant, 35263.45 and 15597.59 Rials for power plant and 30561.66 and 13517.91 Rials for combined cycle power plant, respectively.

This study examines the pattern of energy consumption in the production of alfalfa, economic analysis and modeling of energy and the production cost of alfalfa in the Bukan township. Data were collected through interviews and filling specialized questionnaires. The results showed that the consumption and production total energy were 212428 and 232567 respectively. Electricity with a share of 68 percent of the input total energy was the most consumed inputs. Indicators of energy efficiency, energy efficiency, energy intensity, net energy, net income, the ratio of benefit to cost and economic efficiency were 1.09, 14.43 Mj/kg, 0.07 kg/Mj, 20139.6 Mj, 1527.14 $/ha, 2.06 and 10.17 kg/$ respectively. Values of R, RMSE and RMSE for the final ANFIS in modeling of energy efficiency were 0.97, 0.033 and 0.2, respectively and for the final ANFIS in modeling of production cost, 0.98, 0.011 and 0.1, respectively. R2 value between actual and predicted values of Production costs and energy productivity was 0.94 and 0.97 respectively

The high energy consumption is one of the serious problems in poultry industry. The poultry industry consume about five percent of total energy sources in different countries, with consideration of losses, it increases up to 16-20%. In the year 2003 also, the Iranian chicken meat consumption per capita was 13.3 kg, while in the year 2013 it increased to 25.9 kg (FAO, 2014). It shows that in the diet of Iranian people, the chicken meat has become a strategic food. Poultry industry is one of the biggest and most developed industries in Iran. In the past two decays, mainly due to population growth and increase demand of white meats, it is necessary to change and improve energy efficiency in this industry.
Technical efficiency of broiler farms in the central region of Saudi Arabia was analyzed through stochastic frontier approach (Alrwis and Francis, 2003). They reported that many farms under study work lower than their total capacity. In the research, the output was chicken meat weight in the term of the kilogram per one period and the inputs were the number of chicks, feed, the total of all variable expenses and fixed input except chicks and feed and the total cost of fixed inputs including building, equipment and machinery used for the broiler houses. They found that the small and large size broiler farms in the Central Region of Saudi Arabia were produced chicken with mean technical efficiency 83 and 88%, respectively (Alrwis and Francis, 2003). Efficiency measurement of broiler production units in Hamadan province was investigated by Fotros and Solgi (2003). They reported that the minimum, maximum and mean technical efficiency under variable return to scale were 12.7, 100 and 64.4%, respectively. Their results showed that technical efficiency at 16.5 (14 units) and 42.35% (24 units) of farms were more than 90 and 70%, respectively (Fotros and Salgi, 2003).
Khorasan Razavi province after Esfahan and Mazandaran provinces is the third largest producer of broilers in Iran. This research was performed because it is necessary to have energy consumption status; also there is a few data about broiler’s energy consumption in Mashhad. In this research, the data of Mashhad’s broilers was analyzed by Data Envelopment Analysis Method. The other objectives of this study were to separate efficient and inefficient units to use energy resource efficiently and determine total energy saving.
This study was performed in 2013 in Mashhad, Iran. The data were collected through interviews and questionnaires from 36 poultry farmers for a growing period of April to May. Input energies were the feed, fuel (gas and gas oil), electricity, labor, equipment and chicken, and the output energies were the chicken meat and the manure. The energy consumption for each element was calculated by multiplied amount of inputs/outputs to energy equivalents.
The total of input and output energies were obtained 125.2, 24.9 GJ/1000Birds, respectively. Energy indices such as energy ratio, energy efficiency and specific energy were determined to be 0.2, 0.019 kg/MJ and 52.55 MJ/kg, respectively. The highest share of energy consumption were 50.84 and 42.43%, for fuel (natural gas and diesel fuel) and feed respectively, the lowest share among the input energies were 0.39 and 0.06%, for chicken and labor respectively. Comparison of energy in three levels of farm sizes (≤15000, 15000-30000 and ≥30000 chicks) showed the energy ratio for large farms were higher than the other levels.
Data Envelopment Analysis (DEA) was used to evaluate the poultry efficiency. The results showed that 13 poultry units had average technical efficiency (0.93) in the definition of Constant Returns to Scale (CRS), and 21 poultry units had pure technical efficiency (0.99) in the definition of Variable Returns to Scale (VRS).
The Fuel (natural gas and diesel fuel) consumption energy had the highest shares of energy consumption; it is because of the low efficient heating equipment in poultry houses and low fuel prices in Iran. Energy efficiency of broiler farms in Mashhad was obtained 0.2 that show low energy efficiency. Improvements in energy efficiency could be achieved by increasing yield or reducing inputs energies.

The aims of this study were to investigate the energy flow and its modeling in Shablon cultivar of plum production in Golestan province of Iran. Data were collected through questionnaires and also interviews with producers. Cobb-Douglass model and sensitivity analysis were used to determine the effects of energy inputs on plum yield. The results revealed that the total energy inputs and energy use efficiency of plum production in the region were 25870.33 MJha-1 and 1.04, respectively. Diesel fuel and chemical fertilizer as the highest energy inputs were 33 and 30 percent, respectively.The shares of renewable energy and non-renewable energy of production were 88 and 12 percent, respectively. The Cobb-Douglas model results showed that the effects of human labor, agricultural machinery, diesel fuel, biocide and farmyard manure were positive on the yield while the effect of chemical fertilizers on plum yield was negative.

Direct planting becomes more common in the recent years, because it conserves soil and water as well as it saves energy and time. However, this technology needs special implements such as seed planter. Given that direct planting is practiced in undisturbed lands, so it was needed to design a special furrow opener. In order to obtain a suitable furrow opener this experiment was conducted in rain-fed Agricultural Research Institute in Maragheh.
Most of seed planters that are used for cultivation in rain fed conditions are equipped by hoe-type furrow opener. Hoe-type furrow openers have good penetration in hard and dry soils. However, they do not have the ability for direct planting. Hoe-type furrow opener was chosen as a model. Then by changing the geometric form of the depth to width ratio (d/w), the two openers were designed. In the first design, which was called O1 two wings and a narrow blade acting as a coulter were added in front of the hoe-type furrow opener. In the second design, which was called O2, in addition to the O1 modification, furrow opener width was decreased and a disk blade was added for seed sowing (Fig. 1).
The performance of O1 and O2 openers were compared with the conventional hoe-type furrow opener (check) in soil bin and in field conditions. At three different forward speeds (1, 1.5 and 2 m.s-1) with 3 replications, the effects of the openers designs of vertical and horizontal soil forces were evaluated in soil-bin conditions. In order to evaluate the performance of the furrow opener in field conditions, an experiment was conducted using a split plot design based on RCBD at 4 replications. Furrow openers formed the main plots and forward speeds formed the sub plots. Each plot size was 22 meters long in two rows for each treatment. After germination of wheat crop, the numbers of seedlings in two rows were counted (along a one meter). After crop maturity, all plots were harvested by hand and grain and biological yield was measured. ANOVA test, uniformity test and mean comparison were conducted by using Genstat software.
The soil bin test results showed that opener design and forward speed both have significant influences on the horizontal force (p It can be concluded that the newly designed furrow opener (O2) could improve the energy efficiency with increasing crop yield. Hence, O2 furrow opener could be recommended for direct planting in rain-fed farming.

Poultry industry is one of the biggest and most developed industries in Iran. One of the important issues in broiler industry is the energy consumption. In this study, the energy consumption flow and the amount of energy production were investigated for broiler farms in Alborz province. Data were collected through interviews and questionnaires. Input energies were the feed, fuel (natural gas and diesel), electricity, labor, equipment and chicken, and the output energies were the broiler and manure. The total of input and output energies obtained were 125.2, 24.9 GJ/1000Birds, respectively. Energy indices, including energy ratio, energy efficiency and specific energy were obtained were 0.2, 0.019 kg/MJ and 52.55 MJ/kg, respectively. The highest share of energy consumption belonged to fuel (gas and diesel) with 50.84% and feed with 42.43% , and the chicken and labor with 0.39 and 0.06 % were the lowest share among the input energies.

In this study, the energy and economic analysis of peanut production in Guilan province of Iran was studied. Data were collected from questionnaires of 75 farmers. The data were collected from three farm size categories namely: 0.1–0.5 ha, 0.5-1 ha and larger than 1 ha. The results revealed that 19407.36 MJ ha-1 energy input was totally consumed. The highest share of energy consumption belonged to diesel fuel (50.05%) followed by chemical fertilizers (19.14%). The mean difference of energy inputs including machinery, diesel fuel and electricity among different sizes of farms was significant at the 5% level. The average energy efficiency in different farm size categories including less than 0.5 ha, 0.5-1 ha and more than 1 ha were 3.67, 4.02 and 4.12, respectively. The energy productivity of these sizes was calculated as 0.155, 0.169 and 0.174 kg MJ-1, respectively. The Cobb-Douglas model results showed that the effects of inputs including human labor, machinery, chemical fertilizers and electricity on the yield were positive, while the effect of inputs including seed, diesel fuel and chemicals on peanut yield were negative. The benefit-cost ratio was calculated as 1.82. Farmers with a farm larger than 1 ha used the least amount of energy and input costs.

The objective of this study is the estimation of energy consumption during various stages of broiler production and analysis the effects of numbers of chick and ventilation system type on energy efficiency of these units. Data for this study were collected from 44 growers by using a face to face questionnaire method during January–February 2010. Collected data were classified into three groups according to the numbers of chicks and two groups according to type of ventilation system. The effects of numbers of chicks at three levels (less 10000 bird, 10000 to 20000 bird and more 20000 bird) and ventilation system type at two levels (tunnel and cross ventilation) were analyzed on energy efficiency. The results indicated energy ratio, energy productivity and specific energy as 0.15, 0.014 kg MJ-1 and 71.95 MJ kg-1, respectively. The results of ANOVA presented that the number of chicks had significant effect on energy efficiency (P<0.01) and level 3 (more 20000 bird) had the biggest energy ratio. The effect of ventilation system type was significant at 5% level and tunnel ventilation system used in 61% of units had the bigger energy efficiency.

In this research energy efficiency for greenhouse cucumber production in Shahreza¬ township located in Esfahan province using data envelopment analysis (DEA) technique was studied. In this study, data were obtained from 25 randomize active vegetable greenhouses from 60 greenhouses in Shahreza township and villages environs. The results showed that the highest and lowest consumed energy were related to fuel and water inputs with 47% and 1.2% respectively. The results of data envelopment analysis showed in CCR and BCC models 24% and 36% of farmers were efficient and the others were inefficient. Mean technical efficiency, net technical efficiency and scale efficiency were calculated as 90.37, 95.09 94.6 respectively. Also technical efficiency of inefficiency units in CCR model was 87% that shows13% of total energy input could be saved with upgrade efficiency in these units. In this research, total saved and unsaved energy related to fuel consumption.

In this research energy efficiency for dry wheat production in three levels including 0.1 up to2, 2.1 up to 5 and over 5.1 hectares for the farming year 2008-2009 in Silakhor plain located in Borujerd and Dorud divisions of Lorestan province was studied using data envelopment analysis (DEA) technique. The results showed that the input energy for seed, fertilizer and pesticides had the highest levels of energy consumption and the share of that in each studied level were 63.63, 56 and 54.07 percent respectively. The results of data envelopment analysis showed that the average of energy efficiency levels were 82, 78 and 68 percent, respectively. First level, that consumes more input energy than other two studied levels, had highest energy efficiency, because in this level output yield were more than other levels. Technical efficiency of inefficiency units in CRS model in three levels is 79%, 77% and 66% respectively. This issue indicates that 21, 23 and 34 of total energy input could be saved with upgrade efficiency in these units. All wrong using and also all share of total saved energy in three levels related to grain, fertilizer and pesticides and then fuel consumption.