Current Issue : October - December Volume : 2013 Issue Number : 4 Articles : 6 Articles
Over 93% of Uganda�s population relys on wood fuel in form of either charcoal or fuelwood for cooking. Uleppi\r\nsub-county in Arua district is a typical example of such areas in Uganda where households entirely use fuelwood to meet their\r\nenergy demand for cooking. The use of fuelwood is however associated with the use of inefficient stoves that accelerate\r\ndeforestation thus increasing carbon dioxide (CO2) emissions. The use of fuelwood is also associated with a smoky\r\nenvironment that has adverse health impacts on women and children who spend long hours in the kitchen. In addition, women\r\nand children spend long hours gathering fuelwood which significantly reduces farm productivity. This project was therefore\r\naimed at design and construction of a biogas plant ideal for a household in Uleppi sub-county as an alternative to fuel wood.\r\nThe research involved sizing of the floating drum biogas digester and gasholder, economic analysis as well as estimating CO2\r\nemission reduction. For a household with an average of three heads of cattle managed in a free range system, the biogas\r\ndigester and gasholder were sized as 1.4 m3 and 0.29 m3 respectively with 0.48 m3 of biogas produced per day. At this\r\ncapacity, it was found that biogas utilization can reduce individual household consumption of wood fuel by 66.32% for a\r\nhousehold size of five persons. The carbon emission reduction for all households was estimated at 432 tons of CO2 per year.\r\nThe benefit-cost ratio was found to be 3.26, hence worthy to invest in the biogas technology. The capital recovery period for\r\n459 USD of the biogas plant installation with an economic life of 15 years at 23 % interest rate was found to be two years....
Sorting of tomatoes has been an issue faced by producers as well as sellers due to the sheer volumes handled and the\r\ndelicate nature of the fruit. This paper describes the development of a low cost machine vision system using webcams and\r\nimage processing algorithms for defect detection and sorting of tomatoes. In the case of agricultural products, good efforts and\r\nappropriate techniques are necessary to distinguish between defected and good ones when using machine vision for sorting.\r\nTomatoes having two major defects namely Blossom End Rot (BER) and Cracks could be separated from good tomatoes with\r\ncalyx. The sorting decision was based on three features extracted by the image processing algorithms. The color features were\r\nused for detecting the BER from good tomatoes and shape factor combined with the number of green objects was used for\r\ndifferentiating the calyxes from crack defects. Two methods, rule based and neural network approaches, were developed for\r\ndecision based sorting. A control system was developed with a belt conveyor to transport the tomatoes and a cylinder pushrod\r\ncoupled to a solenoid was used to push the defective tomatoes after determining their defect by the algorithms. The color image\r\nthreshold method with shape factor were found efficient for differentiating good and defective tomatoes. The overall accuracy\r\nof defect detection attained by the rule based approach and the neural network method were 84 and 87.5% respectively. The\r\ninspection speed of 180 tomatoes min-1 was achieved by the algorithms and the prototype developed. Comparison of the results\r\nobtained by the rule based and neural network approaches are also presented in this paper....
Fisheries are required to grant convenient environmental conditions for fish growth with minimum cost afford.\r\nProviding these environmental conditions should essentially correlate fish type, pond dimensions, water properties, and weather\r\nconditions to the fish growth rate, feeding and metabolism. The large uncertainty margin of such parameters relations and\r\neffects drives the farmers to have economically inefficient practices in their farms. The present work was divided into two\r\nparts. The first part introduced an interactive Microsoft Excel spreadsheets as a decision support system (DSS) for the\r\npurposes of fish farm area planning according to the different required purposes of ponds, water evaluation to insure the most\r\nsuitable environment of fish growth, and mechanical aeration management. The design of this DSS took the simplicity of\r\nrequired input data and data output into consideration. The second part was a microcontroller based open loop control system\r\nfor mechanical aeration process based on the calculations of the DSS. The aeration management part input and output data fed\r\nto the control system with a specially developed program using �µC-language. This program performs the calculations of\r\naeration requirements and energy demands based on the DSS calculations. Furthermore, the controller had the feature of\r\nworking from isolated power supply or in collaboration with renewable energy system. These utilities have been created to be\r\nsuitable for three fish types, which are Mullet, Tilapia, and Carp fish. These types have a wide acceptance in the aquaculture\r\nactivities under warm water conditions. The data obtained from the calculations of the spreadsheet under simulated and real\r\nfield conditions were compared to a reference data. The spreadsheet showed an agreement with the reference values. The\r\ncontrol systems succeed to operate 1hp-3phase induction motor for a time that was identical to the required aeration time\r\ncalculated through the DSS. It was recommended to rely on the created DSS and the control system for farm area planning,\r\nwater environment evaluation, and mechanical aeration management and operation. In addition, improvements for the control\r\nsystem should be carried out to be a real-time system especially with water quality parameters considering system power\r\nrequirements and operating costs....
The thin layer drying kinetics of chilli is experimentally investigated in hot air oven and fluidized bed dryers.\r\nExperiments were conducted at inlet air temperatures of 45??, 50??, 55??, 60?? and 65??. The power consumption and quality\r\nparameters (color and capsaicin content) were measured in each experiment. Thirteen different thin layer mathematical drying\r\nmodels were compared by using their regression coefficient, chi square value and RMSE (root mean square error). The Midilli\r\nmodel was found to be the best mathematical model which could use to satisfactorily predict the moisture ratio of chilli at\r\ndifferent drying air temperatures in each type of dryers used. Surface colour chromaticity parameter a* changed from 32.5 at\r\n45?? to 25.8 at 65?? temperature in hot air dryer whereas it was changed from 29.3 at 45?? to 23.8 at 65??. When temperature\r\nincreases from 50?? to 65??, there is a considerable reduction in the colour of chilli in both dryers. Capsaicin concentration was\r\ninversely related with the air temperature and there was a sharp reduction of capsaicin concentration when increasing the\r\ntemperature from 60?? to 65??. The energy consumption was higher in fluidized bed dryer than the hot air oven dryer when\r\nmoisture content of chilli reduced from 280% to 9% (d.b) during drying process. The retention time of the fluidized bed dryer in\r\nall operating temperatures was nearly three times less that of hot-air oven dryer due to higher air flow characteristics. Lowest\r\npower consumption occurred at 65?? temperature setting in both dryers while the fluidized bed dryer consumed nearly 75% more\r\npower....
To get a proper energy consumption pattern and an increase in energy productivity, determining a relationship\r\nbetween energy inputs and outputs is necessary. In this study, the equivalent energy of inputs and outputs data used in wheat\r\nproduction in Abyek town of Ghazvin province, Iran was collected from farmers over three years. The energy ratio was\r\nobtained as 2.11, 2.08 and 2.03 and energy productivity was obtained as 0.15, 0.14 and 0.14 (kg MJ-1) for 2010, 2009 and 2008,\r\nrespectively. It was found that the contributions of indirect and non-renewable energies on wheat yield were more than the\r\nimpacts of direct and renewable energies. To determine the effects of energy inputs on wheat yield, the Cobbââ?¬â??Douglas\r\nproduction function was used. Model 1 was composed of individual energy inputs: labor, machinery, electricity, diesel fuel,\r\nwater for irrigation, fertilizer, chemicals and seed energies In Model 2 energy inputs divided to direct and indirect energies\r\nand in Model 3 they divided to renewable and non-renewable energies. The R2 values in all three models were more than 0.98\r\nand showed that the models can estimate well. The sensitivity analysis results for Model I showed that the major marginal\r\nphysical productivities (MPPs) were water for irrigation, human labor and water for irrigation in 2010, 2009 and 2008,\r\nrespectively. In Model II, the major MPP belongs to for renewable energy in the same years....
Solar energy is the most promising of the renewable energy sources in view of its apparent limitless potential. A\r\nsmall scale villageââ?¬â??level solar dryer for tomato was developed under Yola weather at latitude 9Ã?°14 N and longitude 12Ã?°26 E\r\nusing locally available materials and the performance was evaluated. The essence of the dryer was to achieve the effective\r\nmethod of tomato preservation and eliminate the drudgery and product deterioration associated with traditional methods of open\r\nsun drying of tomatoes. This is in view of alleviating the weather limitation experienced by farmers in crop drying especially\r\nfor tomatoes. The solar dryer consists of tray, reflective walls and glass roof, a preheating air absorber plate, inner panels for\r\nremoval of moisture and chimney through which air stream passes across the dryer. Evaluation of the dryer showed a raised\r\ntemperature of about 47?? attainable in the drying chamber. The dryer temperature and drying rate was found to be higher\r\nthan the natural open sun drying method. The dryer was able to reduce moisture content of tomato from initial moisture\r\ncontent of 94% wet basis to 4% in three days with effective drying time of 24 h, efficiency of 64%, air mass flow rate of\r\n0.025 kg s-1 and drying rate of 0.03906 kg h-1. The results showed a considerable advantage of solar dryer over the traditional\r\nopen sun drying method in term of drying rate and less risk for spoilage....
Loading....