A Farm Machinery Management System for Rainfed Crops

The objective of this study was to develop a machinery management system for rain fed crops for planning and decision making. The system consisted of three units, the rainfall analysis unit, which estimates rain amount on probability level by the following equation: Y = 10 (a+ (log(X))xb). Accordingly, determines the crops that can be grown. The second unit estimates machinery workable days using soil and climate data. A day was assumed to be suitable for field work when the soil moisture which was estimated by the following equation, was at or below 80% of field capacity. MC (%) = Mp + P _ R _ D _ E. This unit predicts workdays every ten days for any month. The outputs of the unit were compared with actual workdays for two successive seasons and the results gave a high correlation coefficient (square R = 0.89). The third unit deals with four crops: sorghum, sesame, sunflower and cotton and three field operations: seedbed preparation, seeding and weed control as well as three farming systems: zero-tillage, conventional and heavy machinery application. It also deals with tractor and six machines; wide level discs, disc harrow, chisel plough, row crop planter, inter row cultivator and sprayer. The unit estimates with mathematical equations, the suitable numbers and width of machine needed, power requirement, fuel consumption and operation cost. The unit also estimates the total cost and net return of the farm. The developed system was applied for Gedarif area by using annual rain amount for 33 years (1977 to 2009). The comparison between the actual and predicted rainfall gave a high correlation coefficient (square R = 0.87). It was also found that rain amount at 20%, 50% and 80% probability were 638, 526 and 480 mm, respectively. These rain amounts were enough to grow sorghum, and sesame, while sunflower can only be grown on 20% and 50%. The system was used to estimate workdays for the 33 years in Gedarif. It was found that the average workdays for seedbed preparation, seeding and weeding operations were 28, 25 and 23 days, respectively. Results showed no significant differences between estimates and actual data. The system was also used to explore the effects of changing one or more input on outputs. The results also showed that conventional farming system gave small values of power required, fuel consumed and operations cost compared to heavy machinery system. It was observed that when more crops were planted in a farm, more net return can be earned. Excel and Visual basic computer soft ware were used to prepare the units and build the system. Each unit was built in a separate file and the user can execute each unit separately or collectively. The system can be used for crop and machinery management and decision making in rain fed areas