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Crop-machinery management system for field operations and farm machinery selection

机译:用于田间作业和农机选择的农机管理系统

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The main objective of this study is to develop a computer system for farm management and selection of required farm machinery to perform field operations in time for crops grown in rotations. Excel and Visual basic software were used to develop the program. The input data included 4 crops (sorghum, sesame, sunflower and cotton), 3 field operations (seedbed preparation, seeding, and weeding operations) and 3 farming systems (zero-tillage, conventional, and heavy machines farming systems). In addition, tractor and 6 implements (wide level disk, disk harrow, chisel plow, row crop planter, inter-row cultivator and sprayer) were also used. The system estimates the size and number of machine, power requirement and fuel consumption for the implements and operations. Verification showed that, the system has the ability to estimate the required parameters as soon as input data was entered. System validation indicated no significant differences between predicted results and actual data. The sensitivity analysis showed that, changing of input variables affects the output parameters and consequently selection is possible. The system was applied to estimate the required output variables in the mechanized rainfed agriculture in Gedarif, Sudan. It can be used for proper crop and machinery management as pre-season decision making with great confidence.
机译:这项研究的主要目的是开发一种用于农场管理的计算机系统,并选择所需的农业机械以及时进行轮作生长的农作物的田间作业。使用Excel和Visual Basic软件开发该程序。输入数据包括4种作物(高粱,芝麻,向日葵和棉花),3种田间作业(苗床准备,播种和除草操作)和3种耕作系统(零耕,常规和重型机械耕作系统)。此外,还使用了拖拉机和6种机具(宽幅圆盘,圆盘耙,凿犁,行间种植机,行间中耕机和喷雾器)。该系统估计机器和机器的大小和数量,功率需求以及燃料消耗。验证表明,输入输入数据后,系统便能够估算所需的参数。系统验证表明,预测结果与实际数据之间没有显着差异。灵敏度分析表明,输入变量的变化会影响输出参数,因此可以进行选择。该系统用于估算苏丹格达里夫机械化雨养农业所需的产出变量。可以很有信心地将其用于季前决策中的适当作物和机械管理。

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