mohammad javad sheikh davoodi

This research presents a model for the analysis of sugarcane basket emptying operations. Traffic of sugarcane carrying baskets in front of the factory door will cause a long waiting line to form. Factors influencing the formation of queues include shift changes, accidents due to tractor crowding, tractor breakdowns, and factory shutdowns, which will lead to an increase in the time intervals between harvesting the crop and emptying the canes. Using queuing theory, the relevant system was simulated as a based model and the effect of each of the existing factors on the amount of time wastage and queue formation was evaluated. Based on the three scenarios (the investigation of queuing order, improve the bottleneck by deploying existing or non-existing discharge sources) proposed and the analysis of the system, based on the realization of each of the scenarios, the costs and queue conditions were investigated. According to the investigated cases, it was concluded that both sources in the factory should be used to empty the canes during the peak harvest time. The waiting time of the baskets in the system in the first, second and third scenario has decreased by 2%, 30%, and 59%, respectively, and the exit rate of the baskets has increased by 1.56%, 100%, and 198%, respectively. Comparing the efficiency of the scenarios using TOPSIS method according to the criteria of waiting time and cost showed that the second scenario has the highest rank.

 Nowadays demand for producing agricultural products has been increasing. So to investigate the effect of tillage and planting pattern using crop residue for corn forage a research was carried out in the research field of in the Dezful city of Khuzestan province.

A split strip plot design was applied using 3 replications based on randomized complete block design. Treatments tillage methods at three levels (tillage, minimum tillage and no-tillage) was as the main factor and management of wheat residues (Chamran cultivar) at two levels (maintaining residues standing and removing all crop residues from the soil surface) was as a secondary factor.

The results were shown that conventional tillage under no residue and no-tillage under residue condition product the most and the least emergence rate of 3.73 and 1.96 respectively. Also conventional tillage under no residue used 10230 m3/ha compared to no-tillage covered by residue 6341 m3/ha (p≤0.01).No-tillage with an average of 2.74 and conventional tillage with 2.19 kg/m3 showed the highest and lowest physical efficiency of water consumption, respectively (p≤0.01).

The use and development of conservation cultivation systems (especially minimum tillage) in corn can help maintain conservation of production resources such as water, soil and the environment. The use of conservation tillage systems along with the preservation of residues at the soil surface, increasing moisture storage, reducing irrigation water consumption, increasing soil organic matter and fertility and saving labor and time spent on tillage operations can be a model suitable for planting corn.

Cooling systems such as refrigeration and air conditioning are considered as basics of everyday life. In these years, the demand for both energy/associated services to address economic and social along with ameliorate human comfort and health is continuously increasing. Since approximately 1850, the global use of fossil fuels (coal, oil and gas) has dramatically raised to dominate energy supply. However, the required energy for the above-mentioned applications is mainly generated by non-renewable electricity. Due to the depletion of fossil fuels as a source of electricity, the development of renewable energies for such systems is necessary. Considering all these issues, as cooling needs, most of the time coincides with the solar radiation availability; therefore, exploring solar energy seems an exciting idea. A number of investigations were performed to design/develop new cooling techniques using solar energy. A solar cooling system is capable of considerably reducing the environmental effects of traditional refrigerating machines while allowing significant energy saving. The present work searches for the best choice of configuration/design factors of food refrigeration systems combined with solar-powered absorption chillers unit in Ahvaz city as a case study.

 In the present study, a linear parabolic collector with specific dimensions, was made, so that first, the initial design of the collector with longitudinal dimensions of 1 and a width of 0.6 meters was selected by Katia software, and then using related relations and calculations of other structural parameters based on which the collector was built, the collector simulation was performed using NASA radiation data for the place and time of the experiments and by using the Transient Simulation Software and its performance in the days of the month July, August and September 2019 were reviewed and evaluated. According to the results, the average energy obtained for the collector in the three months of July, August, and September was about 216.054 w-h/m2. Finally, the area of the collector was calculated, the results showed that the required surface of the collector was found to be 584.687 m2. Also, the necessary calculations were performed on the results of performance tests by Excel software, and diagrams of changes in the radiant energy absorbed by the collector and the efficiency of the radiated energy absorbed were drawn from 10:00 AM to 6:00 PM. Using the diagrams obtained from the system simulation in TRNSYS (Transient System Simulation Tool) software, it is concluded that the built-in collector has the ability to produce a fluid with a temperature above 98 degrees Celsius required for the absorption chiller in July, August, and September.

 According to the evaluations of the collector's performance in the three months of July, August, and September from 10 AM to 6 PM showed that collector energy and efficiency reached their maximum values in July with 318.240 w-h/m2 and 63.05 %, respectively. While in August, the amount of energy and efficiency was found to be 299.311 w-h/m2 and 61.94%, respectively. According to the results, the average energy obtained for the collector in the three months of July, August, and September was about 216.054 w-h/m2. Finally, the area of the collector was calculated, the results showed that the required surface of the collector was found to be 584.687 m2.The minimum value of the parameters were recorded as 283.379 w-h/m2 and 61% in September, respectively. The potential analysis conducted showed an excellent saving potential in terms of energy obtained. According to the results, the useful collector energy was achieved to be 227.664 w-h/m2, 217.006 w-h/m2, and 210.406 w-h/m2 in July, August, and September, respectively. According to the obtained results, the maximum refrigeration load needed for the studied cold storage was about 126324 w. According to the results, the average energy obtained for the collector in the three months of July, August, and September was about 216.054 w-h/m2. Finally, the area of the collector was calculated, the results showed that the required surface of the collector was found to be 584.687 m2.

 The development of renewable energies for such systems is necessary. Solar cooling system for food products cold storage in Ahvaz city is a promising and innovative alternative to decline the peak energy consumption generated by the combustion of fossil fuels, especially during the summer months.

In this study, the application of a solar system for heating a greenhouse of twin type with arched structure and single layer polyethylene coating was investigated. For this purpose, initially, the heating needs of the greenhouse were determined. Then, according to the obtained results, a flat-panel solar water heater with a collector of 6 square meters and a tank volume of 500 liters was selected and installed next to the greenhouse cucumber production unit to heat the air inside the greenhouse with 4 unit of 10-blade aluminum radiators. Then, using paired t-test, the results obtained in this greenhouse were compared with the conventional type in the area that had a diesel heater. The results showed that in terms of carbon dioxide, average temperature and relative humidity, there was no significant difference between the two greenhouses, but in terms of chlorophyll index and crop yield, there was a significant difference between the two greenhouses, at a probability level of 1 and 5 percent, respectively. Diesel had a higher average in these factors. Also, managing the four factors of minimum temperature, average temperature, chlorophyll content and maximum relative humidity in the greenhouse equipped with solar water heater and controlling the two factors of minimum temperature and chlorophyll content in the greenhouse equipped with diesel heater can improve photosynthesis and increase yield.

Biogas, a product of anaerobic digestion of biomass resources, is one of the major renewable energies with the potential to replace fossil fuels. Anaerobic digestion is performed under specific conditions and according to a specific chemical process. Sugar cane is one of the most common sources of sugar and bioethanol production in the world. In the ethanol distillation process, large quantities of vinasse are produced. The direct consumption of vinasse as fertilizer has many environmental problems. Anaerobic digestion of vinasse is a potential solution to such environmental problems. Factors affecting the performance of an anaerobic digester can be classified into three main categories: (1) raw material characteristics, (2) reactor design, and (3) operating conditions. Among the operating conditions, temperature and pH are the most important parameters, so in this study, these two parameters were investigated.

The main raw material was vinasse. Some other additives were used to alter its chemical properties. To have a proper substrate composition, the ingredients before loading into the digesters were evaluated for their chemical and physical properties, including pH, concentration and C/N ratio. The bovine rumen contents of 10% of the final volume of input material were added to supply methanogenesis bacteria as well as to modulate the (C/N) ratio. The Total Solid Content (TS), Volatile Solid (VS) and Chemical Oxygen Demand (COD), were evaluated before and after digestion. A series of batch reactor were used to perform the experiment. The experiment was carried out in a split plot design in a completely randomized design. The main and sub-factor was respectively temperature (at four levels of 30, 35, 40 and 45 ° C) and pH (at four levels of 6.8, 7, 7.2 and 7.4), and the experiment was performed in three replication. To measure the volume of gas produced, a 50 ml water tank connected to the digester outlet as a U-tube was used. The amount of water movement in the U-shaped tube is an indicator of the volume of biogas produced. For better detection of water displacement, some color was dissolved in water. Passing the gas produced from the three-molar NaOH solution, its impurities (mainly carbon dioxide) were absorbed, and the resulting pure gas was re-measured using a U-shaped tube. Using the law of complete gases, the biogas volumetric index was converted to the standard gas volume and finally converted to values based on (ml/gVS) and the new values were analyzed by analysis of variance and mean comparison.

Almost all main and interaction effects on all the factors studied were significant at the 1% probability level. The amount of gas produced increased with increasing temperature but with increasing pH, it first increased and then decreased. The amount of gas produced at 35, 40 and 45 °C was not significantly different. So because of economic and energy constraints, an operating temperature of 35 °C is recommended for anaerobic digestion of vinasse. The graph of the interaction of temperature and pH shows that at higher temperatures the rate of gas production increases with increasing pH. Although the highest gas volume was obtained at pH of 6.8 and 7.4, but the gas produced in the pH range of 7–7.2 was more pure. Therefore, the best combination of pH and temperature to produce the highest and purest gas is 7 and 35 °C, respectively. But since the vinasse produced in the alcohol factories has high temperature and therefore higher temperatures are possible, so 40 °C is also recommended. It was also clearly observed that the smaller the volume of gas produced, the greater its purity. The VS-R factor is also more sensitive to temperature changes than to pH changes. Thus, in anaerobic digestion of vinasse, pH control is more important than temperature control. VS-R performs best at pH 7. This factor was not significantly different at 35, 40 and 45 °C. Therefore, considering the cost of providing more heat at temperatures of 40 and 45 °C compared to 35 °C, 35 °C is the best temperature for manure production with the highest volatile organic matter removal. The COD-R process was similar at all pHs. COD-R at pH 7 was higher at all temperatures than at other pHs. It was also significantly higher at 40 and 45 °C, compared to other temperatures. So like other factors, the best pH and temperature based on this factor are 7 and 40 °C, respectively. Conclusion According to all factors studied, the best pH and operating temperature of anaerobic digestion of sugar cane vinasse is 7 and 35 ° C, respectively. Another important conclusion to be drawn from this study is that changes in all parameters studied are affected by pH changes rather than temperature changes. Therefore, sufficient care must be taken to ensure that pH variations in the anaerobic digestion medium be very low and around the range proposed (about 7).

Today, one of the main challenges is to control fuel consumption, which has an effective role on other sectors of the economy. In this situation, efficient practices are necessary to reduce fuel consumption leading to lower costs. This paper shows how an intelligent control system has been designed and how an electronic engine speed control system was replaced with the mechanical system. The aim of construction and evaluation of an electronic system was to control engine speed in harvesting machines. The conventional control of engine speed in 7000 series sugarcane harvesters is mechanical. Stepper motor, drivers, micro-controller, joystick and potentiometer were used, as well as the C programming in code-vision to program the microcontrollers. A t test was conducted to compare fuel consumption between the systems. The statistical analysis showed significant difference between the control systems in 1% probability level. Results from the implementation of this system represented the design and proper functioning of the system. The results showed a reduction of about 6.3% in fuel consumption when electronic control system was used, comparing to mechanical control and this was due to the use of intelligent and automatically control of engine speed. Installation of this system on existing sugarcane harvesters will save about 505,000 liters of fuel annually.

Introduction :

Sugarcane is a tropical, perennial grass that forms lateral shoots at the base to produce multiple stems. It is the main source of sugar production and one of the most important sources of energy production in the world. Today, the use of artificial intelligence and data mining findings to help predict product production is considered. Determining the relationship between inputs and outputs of production process using artificial intelligence (AI) has drawn more attention rather than mathematical models to find the relationships between input and output variables by training, and producing results without any prior assumptions. The adaptive neuro-fuzzy inference system (ANFIS), as a form of AI, is a combination of artificial neural network (ANN) and fuzzy systems that uses the learning capability of the ANN to derive the fuzzy if-then rules with appropriate membership functions worked out from the training pairs, which in turn leads to the inference.Particle swarm optimization (PSO) is an algorithm modeled on swarm intelligence, in a search space, or model it finds a solution to an optimization problem and predict social behavior in the presence of objectives. The PSO is a population-based stochastic computer algorithm, modeled on swarm intelligence. Swarm intelligence is based on social psychological principles and it provides insights into social behavior, also helps to many engineering applications. Feature selection is becoming very important in predictive analytics. Indeed, many data sets contain a large number of features, so we have to select the most useful ones. One of the most advanced methods to do that is the genetic algorithm (GA). Genetic algorithms can select the best subset of variables for predictive model. The purpose of this research is to evaluate the applicability of one artificial intelligence technique including adaptive neuro-fuzzy inference system and also combining this technique with particle swarm optimization to increase the accuracy and speed of training of the neuro-fuzzy system in prediction of yield and recoverable sugar percentage (R.S%) of sugarcane.

Materials and Methods:

 In this paper, one main pattern of adaptive neuro-fuzzy inference system (ANFIS) and one synthetic model of adaptive neuro-fuzzy inference system with particle swarm optimization (PSO) were used to predict the studied properties by MATLAB version 2017. Initial data for this study were collected from Debal-Khozaie Agro-industry Company in Khouzestan province, Iran. The actual data for the seven periods of sugarcane harvest from 2010 to 2017 were used for modeling. The studied parameters included a set of agronomic factors, soil characteristics, irrigation and climate in the study area. The test data sets were used for comparison of selected ANFIS and ANFIS with PSO, as well as for the observation values. This comparison was performed by using three statistical indices: Determination Coefficient (R2), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE).

Results and Discussion:

From all of the studied parameters, eleven parameters were selected as the effective features by the binary genetic algorithm (BGA). In feature selection, the function to optimize is the generalization performance of a predictive model. More specifically, in this method, purpose was to minimize the error of the model on an independent data set not used to create the model. The data were randomly divided into two groups: training and testing. Each pattern was modeled separately and then the results were compared. The results showed that the combination of adaptive neuro-fuzzy inference system with particle swarm optimization algorithm (ANFIS-PSO) had better performance in predicting cane yield and recoverable sugar percentage. In ANFIS-PSO model the root mean square error, mean absolute percentage error and coefficient of determination values were found 0.0181, 0.0217, 0.9237 and 0.0086, 0.0138, 0.9847 respectively for two variables of cane yield and recoverable sugar percentage. In relation to the predicted cane yield by the neuro-fuzzy network with particle swarm algorithm, it can be concluded that among the effective factors, with increasing plant age and use of resistant varieties, the amount of yield was decreased and increased, respectively.

Conclusion:

 The hybrid pattern of adaptive neuro-fuzzy inference system with the particle swarm optimization has been directed against the mere neuro-fuzzy system to a more accurate and stronger solution. Indeed, it can be concluded that ANFIS model with the PSO has the ability for precise estimation of sugarcane yield and recoverable sugar percentage.

In this study, to predict sugarcane yield, an Artificial Neural Network based on meta-heuristic algorithms is used as an efficient method to estimate crop yield based on actual data. In order to predict sugarcane yield, effective parameters such as plant characteristics, electrical conductivity of soil and water, maximum temperature and average hours of sunshine during the growing season and on a time scale of seven years were used. Accordingly, four hybrid models were used to build neural networks which including of artificial neural network based on Back Propagation (BP) algorithm, combining neural network with Genetic Algorithm (GA), combining neural network with Particle Swarm Optimization (PSO) algorithm and finally a new approach as combining neural network with GA-PSO. The results show that the neural network performance can be improved using meta-heuristic algorithms and can be increased significantly the prediction power. The Mean Square Error (MSE) and correlation coefficient (R) in the hybrid method of neural network with GA-PSO were obtained 0.00057 and 0.91457 respectively on the test data, which show the superiority of this method to other patterns. In addition, cross validation test of the proposed model by K-Nearest Neighbors showed the accuracy of training and test data to predict sugarcane yield has been equal to 98.5% and 95.5%, respectively.

Production and use of biogas, as an alternative renewable fuel, along with increasing energy security, can reduce the use of fossil fuels and thus reduce the environmental impact of these fossil fuels. Biogas production is subject to certain conditions and is influenced by some parameters such as pH, Hydraulic Retention Time (HRT), Solid Retention Time (SRT), temperature, agitation and so on. The existence of a laboratory digester to control and identify the best conditions of these effective parameters is of great importance. Therefore, three types of anaerobic digester, were built to digest liquid wastes, considering the advantages and disadvantages of various digesters, factors affecting biogas production and also considering the cost issues. In these digesters, it was possible to control the parameters affecting biogas production (temperature, pH, concentration and retention time) and were also equipped with a system to measure the amount of gas produced. These digests were batch type and the feasibility of experimental designs to study the effect of parameters affecting biogas production was predicted. Batch digests are more suitable than continuous ones to study raw materials that require longer retention time, such as lignocellulosic biomass. Due to the transparent body of these digesters, it was also possible to study optical treatments. The most important and difficult part of the construction was the possibility of sealing the joints. Glass digester, if properly sealed, is the best one and meets almost all requirements for testing the factors affecting biogas production. Its main problem is the possibility of air leakage and liquid penetration into the mixer electromotor. Due to the flexibility of polyethylene digesters, it is easy to extract air and provide an anaerobic environment. The disadvantage was the requirement of manual or magnetic mixing and a possible error in measuring the volume of gas produced. Use of the Erlen vacuum, rubber cap, needle and heparin locker were appropriately meet the requirements of an anaerobic digester, but steel mixing in the digester is done manually or by magnetic stirring.

In this project precision planting method has been tested and evaluated for planting sugarcane billet. For this purpose a single devise known as “billet planting simulator” built and two metering devise were tested. For this research three different treatments that were applied: forward speed in three levels of 1, 2 and 3 Km/h, Billet transferring system in two levels of angled surface and conveyor and metering devices in two levels of toothed shaft and star wheel model. Factorial design based on Randomized complete design with three repetition were used. Four indexes had been measured and calculated which consist of: quality of feed index, precision index, multiple index and miss index. Teethed Shaft showed higher multiple indexes while star wheel showed higher miss index. Two metering devise had no significant differences in quality of feed index. In forward speed has been found that higher speed means less desirable planting. It also cleared that using conveyor with positive billet feed to metering devise, had significant rising in good planting indexes. Best mode can be found with QFI index and precision index. By using star wheel devise and conveyor with 2 Km/h speed the best planting can be reached. In fact it seems that using star wheels, conveyor and low speed is essential properties of a suitable precision billet planting system.

Sugarcane, a perennial plant, has been cultivated in Khuzestan province, Iran, for a long time. Sugarcane seeds and stems (whole stalk or billet), both, are used for propagation, but stems planting is primary method of cultivation for sugar production purposes. Costs of sugarcane planting in Khuzestan differ when different planting methods are practiced. This study was conducted to find out proper planting methods  for Khuzestan’s conditions. To achieve the aims, various parameters were checked, then influencing variables were determined; experiments were carried out  in Hakim  agro-industrial farms, in 2016 . The following topics were considered: costs indices, billet burial quality, factors affecting field capacity, numbers of tractor coming and going on the farms, and finally ergonomic issues. Indicators were summarized as much as possible by merging into each other or turning. Factors weighting were done, using expert discretions and AHP to indicate the importance of each indicator. Integration of relative weights by multiplying the relative weight of each indicator on the above parameters was carried out and also consistency index was calculated by ratio of incompatibility and random index. In next step, by selecting factors and AHP, three planting methods were compered using Expert Choice software: conventional manual method, semi-mechanized planting method (by cutter planter), and mechanized planting method (by automatic billet planter). Results showed that semi-mechanized planting method was optimal method due to  minimum costs and maximum quality achieved in billet burial practice. Manual planting, in spite of achieving optimal way of planting compared with mechanized planting, received low advantages because of increasing in planting expenses.

Assessment of land suitability is one of the basic approaches to maximizing profits and protecting environmental resources. The purpose of this study was to determine the land suitability of Ahwaz county for cultivation of irrigated wheat using AHP Method and GIS. Ecological factors, agricultural factors and other parameters affecting wheat cultivation in Ahwaz county were determined. Soil permeability, soil texture, EC, pH, slope, accessibility to main roads and markets, and net income were selected. Data were collected by questionnaires distributed among farmers, experts, and government organizations. The results showed that economic criteria and soil characteristics had the highest weight, so that net income with the weight of 0.316 was ranked first. It has been found that average net income and benefit/cost ratio were 10.2 million rials per hectare and 0.44, respectively. The highest cost in wheat production was observed in machinery and equipment. Based on integration of GIS layers and assessment of land suitability, it was found that of total land area, 11.1% was very suitable, 32.5% was suitable, 30.4% was moderate, and 26% was unsuitable for wheat cultivation.

In assessment of agricultural sustainability, all environmental, economic, social and technical aspects must be taken into account. The purpose of this study is to evaluate and compare the sustainability of wheat, corn and sugarcane production in Khuzestan agro-industries. Data were collected from Shahid Rajaie and Debel khazai agro-industries. Indicators such as energy, the risk of chemical fertilizers and biocide pollution, the risk of soil compaction due to machines, air pollution, and employment were used to compare and evaluate the sustainability of farms. For integrated and comprehensive assessment of indicators and farms ranking, the TOPSIS methods were used. Although these indicators and multi-criteria methods did not show a complete overview of sustainability farms, but they were effective in comparing the sustainability of farms and improving their sustainability. The results showed that employment, the risk of soil compaction and nitrogen fertilizer, air pollution and energy indicators had the most important role in the sustainability of farms, respectively. In the wheat farms, except for employment, other indices were better than other farms. The risk of soil compaction due to agricultural machinery in sugarcane farms had been high and had become one of the main problems of these farms .On the other hand, employment in the sugarcane production per hectare was much higher than the production of wheat and corn. The sensitivity analysis showed that the sustainability of farms was very sensitive to the employment, so with a reduction of 25.39% in weight of employment indicator, sugarcane farms were ranked the last.

The Alcohol based fuels has attracted the attention of alternative fuel researchers. Fusel oil is an alcohol based fuel collected as a by-product during bioethanol production. The main objective of this study is to determine the optimal blend ratio of fusel oil–gasoline regarding the performance and emissions of spark ignition engine using response surface methodology based on CCD design. In this research work, experimental investigations have been performed with different fusel oil–diesel levels (0%, 5%, 10%, 15% and 20%), different load (0%, 25%, 50%, 75% and 100%) and different engine speed (1400, 1700, 2000, 2300 and 2600 rpm).The multi-objective optimization was performed to maximize the power, torque and minimized BSFC, NOx, UHC and CO emission. The best condition of engine parameters was 11.57% for fusel oil, 40% load and 2264 rpm engine speed. The optimal values were 1.9 kW, 10.9 N.m, 354.5 g/kW h, 0.19, 54.5,2.34 and 87.7(V%) for power, Torque, BSFC, CO, UHC, CO2 and NOx emissions respectively. were prolonged. The results showed that fusel oil usage increased power and torque. It was found that both NOx and UHC emissions decreased.

The aim of this study was to design, Constructand evaluate an electronic system for control of the forward speed control in 7000 series sugarcane harvesters. The conventional method of control for the forward speed of sugarcane harvester in 7000 series is mechanical. The new electronic control system was developed to replace the traditional mechanical control system. MotorStepper, drivers, micro-controller, joystick and potentiometer were used to program microcontrollers as well as C programming in code-vision. The new control system was evaluated during two series of tests. To determine the strength of the maneuverability of the harvesting machine, the first test was conducted using a factorial experiment based on completely randomized design. The maneuverability was compared for mechanical and electronic control systems under different engine rpm. The location error at stoppage time in respect to the baseline was measured as basis for maneuverability. In the second test the response time was compared with a completely randomized design in two systems. The statistical analysis showed a statistically significant difference between the control systems in 1% probability level. The maneuverability of harvester equipped with electronic control system increased significantly and it was not affected by the changes in engine rpm (forward speed). In the second test the statistical analysis showed a statistically significant difference between the control systems in 5% probability level. Electronic forward speed control system resulted in reaction speed, and device maneuverability, ease of maintenance and use, a reduction in mechanical parts usage and finally the proper functioning of the system.

Potato is the fourth important food crop after wheat, rice and maize. Shrinkage  of  food  materials  has  a negative  consequence  on  the  quality  of  the dehydrated product. The main objective pursued in this paper is to investigate the shrinkage amount of potato slices during drying process using vacuum-infrared method. In this work, the effect of the infrared radiation powers (100, 150 and 200 Watt) and absolute pressure levels (20, 80, 140, 760 mmHg) at different thickness (1, 2 and 3 mm) on bulk volumetric shrinkage were investigated. Data analysis showed that shrinkage percentage decreased with decrease of sample thickness and increase of infrared power. It was found that either thickness or infrared power had any significant effects (P < 0.01) on shrinkage of potato slices in this drying system. The regression model is a three-variable linear that Coefficient of determination is 0.532 and implies that the model can explain 53.2 % of the volume ratio changes

The main objective pursued in this paper is to investigate the energy consumption for drying of potato slices using vacuum-infrared drying method. Drying of potato slices with the thicknesses of 1, 2 and 3 mm were conducted at vacuum levels of zero (without vacuum), 20, 80 and 140 mm [Hg], infrared radiation at power levels of 100, 150 and 200 W in the three repetition. The results show that with the slice thickness decreases, acts of vacuum and increasing lamp power, energy consumption be reduced. Maximum of energy consumption occurred in a vacuum of 140 mm Hg, but in general it can be stated that by applying vacuum, energy consumption is reduced due to the shortening of the drying time. Data analysis showed that use of vacuum in conjunction with infrared radiation drying increased energy consumption in comparison to merely infrared drying. In the combined vacuum-infrared process, drying time and consequently energy consumption decreased in comparison to the merely infrared drying. The maximum thermal utilization efficiency (31.01%) and minimum energy requirements (5.3 kWh/kg H2O) was calculated for drying of potato slices computed at infrared power of 150 W without vacuum at thickness of 1 mm. The minimum thermal utilization efficiency (2.13%) and maximum energy requirements (185.14 kWh/kg H2O) for drying of potato slices was achieved at infrared radiation power of 100 W with vacuum level of 80 mm [Hg] at thickness of 2 mm.

In order to evaluate the effects of seed bed preparation, fertilization and weed control (after planting) methods on growth and corn yield in northern part of Khuzestan a field experiment was conducted as split blocks in a randomized complete block design with four replications during 2009 and 2010. Three seed bed preparations consisting of Makhar condition (wet seeding) + conventional tillage (plough + disk + leveler), makhar condition + reduced tillage (disk) and without makhar + reduced tillage were performed in horizontal plots. Two methods of fertilizing (Broadcast and Drill) as main factors and weed controlling methods (once using of field cultivator in four-leaf stage (20 cm height of plants), two times using rolling cultivator in four and seven-leaf stage (20, 40 cm height of plant), using two liters Nicosolforon herbicides when the plant produced 3 - 4 leaves, and checking treatments (weed free and weed infect) as the sub-factors were conducted in vertical plots. The results indicated that population and biomass dry weight of weeds were significantly (p< %5) affected by Makhar. Planting in without makhar soil, caused reduction in the population and weed weight (30% and 40%) in the 5th week. In all tillage methods, the effect of two times using rolling cultivator and chemical control on grain yield and biological yield was statistically similar. In fertilizer drill method, grain yield and biological yields, kernel in rows and rows in ear were significantly (P<%1) higher than broadcast method. The most grain and biological yield were obtained in combination of makhar condition and fertilizer drill (in treatment of makhar condition + reduced tillage, grain yield was 9003.25 kg/ha.). Two times using rolling cultivator reduced the population and weight of weeds significantly more than chemical control in farm with plenty of Bind weed. In all of the Broadcast fertilizer methods, chemical control treatment had more yield (16%), but in fertilizer drill method there was no significant difference between chemical and two times using of rolling cultivator treatments. It seems that in corn farms when broadcasting fertilizer method is used, the chemical control of weed due to higher yield (15%) is more effective; two cultivator weed control method is recommended if the distribution of fertilizer is used with drilling method. The highest grain yield (9183 kg/ha) was obtained from the combination of makhar, reduced tillage, fertilizer drilling method and two times using rolling cultivator.

This paper applied a non-parametric (Data Envelopment Analysis) method to analyze the efficiency of farmers, discriminate efficient farmers from inefficient ones and to identify wasteful uses of energy in order to optimize the energy inputs for greenhouse cucumber production in Lorestan province of Iran. Data were collected from 27 cucumber producers by using a face-to-face questionnaire.DEA creates a best-practice production frontier based on the growers that produce their level of greenhouse cucumber yield with the least amount of input energy. The results revealed that total operational energy of 521.37 GJ ha-1 is consumed in greenhouses. Most shares of this energy are allocated to fuel and chemicals by the shares of 56.66% and 12.19% respectively. Two basic DEA models, Constant Return to Scale (CRS) and Variable Return to Scale (VRS) were used to measure the technical efficiency (TE) of the greenhouses based on eight energy inputs and one output. The CRS and VRS models indicated that 10 and 19 greenhouses were efficient, respectively. The average values of TE, pure technical efficiency (PTE) and scale efficiency (SE) of greenhouses were found to be 0.89, 0.99 and 0.89 separately. Moreover, energy-saving target ratio (ESTR%) for greenhouse cucumber production was calculated as 26.85%, indicating that by following the recommendations resulted from this study,140 GJ ha-1 of total input energy could be saved while holding the constant level of greenhouse cucumber yield.

The aim of this study was to investigate the feasibility of hydrogen production from sugarcane bagasse by supercritical water gasification (SCWG) at low temperature and in presence of alkali catalyst. Experiments were carried out in a batch autoclave reactor at 400 °C and 9% solid content. Effect of reaction time and alkali catalyst on gas yield, gas composition, carbon gasification efficiency (CGE) and hydrogen gasification efficiency (HGE) were investigated. Influence of reaction time on gas yield and composition as well as on CGE was found to be insignificant. Extending the reaction time even up to 4 h could not cause an attractive conversion of bagasse. In the presence of catalysts (K CO, KHCO, NaHCO and NaOH), sugarcane 2 3 3 3 bagasse was partially gasified in SCW and hydrogen-rich gas containing CO as the main carbon compound 2 was produced. Among the implemented catalysts, K CO was identified to be the most effective for 2 3 improvement of HGE. Use of the catalyst under our experimental conditions, the maximum HGE of 19% was achieved; however the highest CGE occurred with KHCO. Results showed that feed to catalyst ratio of 2 was 3 high enough to reach the greatest possible gasification of hydrogen at 400 °C and 45 min. More CGE and HGE would be possible only by increasing the temperature, pressure and/or reaction time.