Two different makes of row crop planters were evaluated for performance by laboratory and field tests. The laboratory test was conducted to investigate the seed rate, uniformity of seed spacing and seed damage during operation, while the field test examined the effective field capacity, field efficiency, planter drive wheel slippage and fuel consumption, and two planting speeds were used (5.5, 8.5km/hr). The experimental study was carried out at the farm of College of Agricultural Studies, where the soil is considered light clay soil. The field was tilled by discing once and harrowing once followed by leveling to prepare a uniform field for the planters work. An average weight of 17 kg/ha and 31.5kg/ha of seeds were discharged during the test from Giad make and Rome make respectively. The seed spacing varying from the theoretical for the two planters, with a noticed minimum seed damage of 0.6% and 0.72% for Giad and Rome make planters respectively. Field evaluation results showed that planter make had significant effect (p<0.05) on seed rate, seed spacing, fuel consumption and effective field capacity. Planting speed had a significant effect on seed rate, fuel consumption and effective field capacity. Interaction effect between planters and planting speed had significant effect (p<0.05) on seed rate and fuel consumption only. The highest fuel consumption and driven wheel slippage were obtained with Giad make planter. Giad make planter gave lower field efficiency compared to Rome make planter at 5.5km/hr forward speed. From the study the two planters were able to effectively meter high seed rate with minimum damage to the seeds. Rome make gave better performance that resulted in lower fuel consumption, wheel slippage and high field efficiency.

The optimization machinery model was developed to aid decision-makers and farm machinery managers in determining the optimal number of tractors, scheduling the agricultural operation and minimizing machinery total costs. For purpose of model verification, validation and application input data was collected from primary & secondary sources from Elsuki agricultural scheme for two seasons namely 2011-2012 and 2013-2014. Model verification was made by comparing the numbers of tractors of Elsuki agricultural scheme for season 2011-2012 with those estimated by the model. The model succeeded in reducing the number of tractors and operation total cost by 23%. The effect of optimization model on elements of direct cost saving indicated that the highest cost saving is reached with depreciation, repair and maintenance (23%) and the minimum cost saving is attained with fuel cost (22%). Sensitivity analysis in terms of change in model input for each of cultivated area and total costs of operations showing that: Increasing the operation total cost by 10% decreased the total number of tractors after optimization by 23% and total cost of operations was also decreased by 23%. Increasing the cultivated area by 10%, decreased the total number of tractors after optimization by(12%) and total cost of operations was also decreased by 12% (16669206 SDG(1111280 $) to 14636376 SDG(975758 $)). For the case of multiple input effect of the area and operation total cost resulted in decrease maximum number of tractors by 12%, and the total cost of operations also decreased by 12%. It is recommended to apply the optimization model as pre-requisite for improving machinery management during implementation of machinery scheduling.

This study was carried out to investigate the effect of fuel type ( pure diesel, blending 10% of Jatropha oil with diesel (J10%), blending 14% of Jatropha oil with blending (J14%),blending 10% of ethanol with diesel (E10%), blending 14% of ethanol with diesel (E14%), blending 10% of Jatropha oil and 10% of ethanol with diesel (J10%, E10%) and blending 14% of Jatropha oil and 14% of ethanol with diesel (J14%, E14%)), on exhaust gases, engine speed, implement draft and power requirement and fuel consumption. The results showed that, Blending J14%, E14% recorded the highest rate of fuel consumption as 4.60 l/h compared with pure diesel which recorded 3.90 l/h. Pure diesel fuel recorded the lowest engine speed of 2174 rpm, while the fuel blends recorded engine speed in the range of 2529 -2583 rpm. The fuel blend J14% recorded the lowest ppm of CO and of NO 2 .The J10%, E14% and J10% with E10% blending's recorded the lowest SO 2 as zero ppm. Pure diesel recorded the highest power requirement of 6.81 kW while J14% recorded the lowest power of 5.32 kW. Ethanol blending's showed higher power than Jatropha blending by 19.7%. Statistical analysis showed that, the effect of fuel blending on draft and power, gases exhausted, engine speed and fuel consumption were not significant.

Repair and maintenance cost is considered as one of important items for machinery management and selection. The present study was carried out in Dongola area for tractor repair and maintenance costs estimation. The data was collected from records of Elshimalya Company for Agricultural Inputs. Forty four tractors rep resenting two sizes of tractors, 75hp and 150hp used in the area were selected for this study. Based on the data collected, regression correlation analysis was carried out and mathematical models were derived to predict the accumulated repair and maintenance (R and M) costs as percent of purchase price in relation to accumulated hours of use and age (years) for each tractor size, and also for the two sizes collectively. Five model forms (linear, logarithmic, polynomial, power and exponential) were derived and the power function was found the best fit to explain the relation. The accumulated Rand M costs as percent of purchase price (Y) was increased as the accumulated hours of use (x) and age (g) of the tractor in years were increased. A high correlation was found between the accumulated R and M cost and both accumulated hours of use and tractor age in years (Average R2 = 0.93).

Sugarcane is one of the strategic cash crops in Sudan for production of sugar and other products for local consumption and export. The objective of this research study was to investigate and calculate the amounts of energy used in sugarcane production, to evaluate the energy use efficiency at Kenana Sugarcane Company. Data were collected from this company and literature to compute the required energy parameters. The results indicated that total energy input was 85496.6 MJha-1 and total energy output was 112812 MJha-1 and urea fertilizer energy used in sugarcane production systems had the highest share with 37.0 percent, followed by electricity for irrigation pumps, diesel fuel and seed cuttings used, as 17.1, 15.5 and 13.4 percent energy respectively. The energy use efficiency, energy productivity, specific energy, renewable energy and non-renewable energy of sugarcane production were 1.31, 1.10 KgMJ-1, 0.91 MJkg-1, 19989.2 MJha-1, 65507.4 MJha-1 and 26980 MJha-1 respectively. The energy use efficiency of sugarcane production shows value higher than one, so the system earned energy for sugarcane production in Kenana-Sudan.

No abstract

Sugar cane production requires a number of operations to be carried out in the field through number of implements and machines. Therefore, time consuming and required large amount of energy. A combined field cultivator was designed in Kenana agricultural implements factory (KAIF) to carry out at one time multi operations (cultivation, furrow-reforming and Fertilizer placement). This is to increase field productivity, reduce farm power and lower operation time and cost. The combined implement was evaluated in Kenana cultivation fields and compared with three individual implements, rigid tine cultivator, furrow-reformer and fertilizer applicator. The measured parameters were drawbar pull, power requirements, field capacity, fuel consumption and total time in the field. The results showed highly significant differences at 1% level between the different implements for the field capacity, fuel consumption and significant differences at 5% for the drawbar pull. A power requirement in (kW) for the combined cultivator was 77% of those individual implements. Total time per feddan to accomplish the required operations by the combined cultivator was 57% of that required by the individual implements. Fuel consumption was reduced to 57% when combined implement was used compared to that consumed by individual implements. It was concluded that the combined cultivator was effective in increasing field productivity and reducing power and cost of operation.

Applying different types of fertilizers to different depths of soil according to demand is advantageous in that it can optimize the distribution of nutrients in arable soil, adjust the nutrient supply of each growth stage of wheat, and increase grain yield. In the study, a layered fertilization opener that could realize the layered fertilization was developed. The interaction model between the opener, fertilizer and soil was established using EDEM simulation software. A response surface analysis was used to determine the optimal parameters of the opener. Specifically, the horizontal distance between the fertilizer drop openings was 140 mm, the machine speed was 1.05 m/s, and the angle of the opener was 37°. Furthermore, field experiments demonstrated that the average depth of upper layer was 8.39 cm, the average depth of middle layer was 16.465 cm, the average depth of lower layer was 24.025 cm, the average spacing of upper layer was 8.075 cm, and the average spacing of lower layer was 7.6 cm. The corresponding findings demonstrated that the layering effect of the opener met the requirements of the fertilization standard.