Evaluating how operator experience level affects efficiency gains for precision agricultural tools

IF 2.3 4区 农林科学 Q1 AGRICULTURE, MULTIDISCIPLINARY
Tulsi P. Kharel, Amanda J. Ashworth, Phillip R. Owens
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引用次数: 1

Abstract

Tractor guidance (TG) improve environmental gains relative to nonprecision technologies; however, studies evaluating how tractor operator experience for nonguidance comparisons affect gains are nonexistent. This study explores spatial relationships of overlaps and gaps with operator experience level (0–1, 2–3, 6+ yr) during fertilizer and herbicide applications based on terrain attributes. Tractor paths recorded by global navigation satellite systems were used to create overlap polygons. Results illustrate operator experience level is critical for better efficiency gains estimation (for non-TG comparisons). Operators with 6+ yr of experience reduced overlap by 7.7 and 20.6% compared with operators with 2–3 and 0–1 yr of experience, respectively. New operators had consistently higher overlap across all slope (<0.5, 0.5–1, 1–2, 2–5, 5–9, and 9–15%) and roughness classes (<0.1, 0.1–0.2, 0.2–0.3, 0.3–0.5, 0.5–0.7, 0.7–1 and >1). A low interpersonal reliability value of 0.02–0.03 indicates operator experience is crucial to estimate TG efficiency gains and consistent drivers experience levels are needed when evaluating economic and environmental gains from TG.

Abstract Image

评估操作员经验水平如何影响精密农具的效率提高
拖拉机制导(TG)相对于非精确技术提高了环境效益;然而,评估拖拉机操作员非指导性比较经验如何影响收益的研究并不存在。本研究探讨了在基于地形属性的化肥和除草剂施用过程中,重叠和差距与操作员经验水平(0–1、2–3、6年以上)的空间关系。全球导航卫星系统记录的拖拉机路径用于创建重叠多边形。结果表明,操作员经验水平对于更好的效率增益估计至关重要(对于非TG比较)。与具有2-3年和0-1年经验的操作员相比,具有6年以上经验的操作员分别减少了7.7%和20.6%的重叠。新操作员在所有斜坡上的重叠始终较高(1)。0.02–0.03的低人际可靠性值表明操作员经验对于估计TG效率增益至关重要,在评估TG的经济和环境增益时,需要一致的驾驶员经验水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
3.70
自引率
3.80%
发文量
28
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