Integration of reflectance sensors into commercial planter or tillage components have allowed for dense quantification of spatial soil variability. However, little is known about sensor performance and reproducibility. Therefore, research was conducted in Missouri, USA in 2019 to determine (i) how well sensors can estimate soil organic matter (OM) and (ii) whether sensor output would be repeatable among sensing dates. Soil sensor data were collected across three weeks on an alluvial soil with the Precision Planting SmartFirmer and Veris iScan. Output layers used in analyses included OM and the proprietary Furrow Moisture variable from the SmartFirmer, as well as OM, reflectance and soil apparent electrical conductivity from the iScan. Ground-truthing soil samples were collected at 0–50 mm on the first date to determine OM and on all dates to determine soil gravimetric water content. Results showed OM estimations by the iScan, which included the manufacturer’s specified field-specific calibration, were reproducible among the three sensing dates, with average root mean square error (RMSE) across dates of 2.02 g kg⁻¹. SmartFirmer results showed OM was over-estimated in areas of low OM, and under-estimated in areas of high OM when compared to laboratory-measured data (R² = 0.34; RMSE = 6.90 g kg⁻¹). Additionally, variability existed in OM estimations between dates in areas that were lower in laboratory-measured OM, soil moisture and clay content. These results suggest real-time estimations of OM may be subject to variability, and local information is likely necessary for consistent soil reflectance-based OM estimations.

将反射传感器集成到商业播种机或耕作组件中，可以对空间土壤变异性进行密集量化。然而，人们对传感器性能和再现性知之甚少。因此，2019 年在美国密苏里州进行了一项研究，以确定 (i) 传感器对土壤有机质 (OM) 的估计能力以及 (ii) 传感器输出在传感日期之间是否可重复。使用 Precision Planting SmartFirmer 和 Veris iScan 在冲积土壤上收集了三周的土壤传感器数据。分析中使用的输出层包括 OM 和来自 SmartFirmer 的专有犁沟水分变量，以及来自 iScan 的 OM、反射率和土壤表观电导率。在第一个日期收集 0-50 毫米的地面真实土壤样本以确定 OM，并在所有日期确定土壤重力含水量。结果表明，iScan 的 OM 估计（包括制造商指定的现场特定校准）在三个传感日期之间是可重复的，跨日期的平均均方根误差 (RMSE) 为 2.02 g kg^-1。SmartFirmer 结果显示，与实验室测量数据相比，OM 在低 OM 区域被高估，在高 OM 区域被低估（R ²  = 0.34；RMSE = 6.90 g kg ⁻¹）。此外，在实验室测量的 OM、土壤水分和粘土含量较低的地区，日期之间的 OM 估计存在变异性。这些结果表明 OM 的实时估计可能会发生变化，并且对于一致的基于土壤反射率的 OM 估计可能需要本地信息。