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Statistical process control applied to mechanized peanut sowing as a function of soil texture

机译:统计过程控制应用于机械化花生播种作为土壤质地的函数

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摘要

The successful establishment of agricultural crops depends on sowing quality, machinery performance, soil type and conditions, among other factors. This study evaluates the operational quality of mechanized peanut sowing in three soil types (sand, silt, and clay) with variable moisture contents. The experiment was conducted in three locations in the state of São Paulo, Brazil. The track-sampling scheme was used for 80 sampling locations of each soil type. Descriptive statistics and statistical process control (SPC) were used to evaluate the quality indicators of mechanized peanut sowing. The variables had normal distributions and were stable from the viewpoint of SPC. The best performance for peanut sowing density, normal spacing, and the initial seedling growing stand was found for clayey soil followed by sandy soil and then silty soil. Sandy or clayey soils displayed similar results regarding sowing depth, which was deeper than in the silty soil. Overall, the texture and the moisture of clayey soil provided the best operational performance for mechanized peanut sowing.
机译:农作物的成功建立取决于播种质量,机械性能,土壤类型和条件等因素。本研究评估了水分含量可变的三种土壤类型(沙,淤泥和粘土)的机械化花生播种的操作质量。该实验是在巴西圣保罗州的三个地点进行的。跟踪采样方案用于每种土壤类型的80个采样位置。描述性统计和统计过程控制(SPC)用于评估机械化花生播种的质量指标。这些变量具有正态分布,从SPC的角度来看是稳定的。对于黏土,其次是沙土,然后是粉质土,花生播种密度,正常间距和幼苗生长初期表现最佳。沙质或黏土在播种深度方面显示出相似的结果,其深度比粉质土壤深。总体而言,黏性土壤的质地和水分为机械化花生播种提供了最佳的运行性能。

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