Repeatability of commercially available visible and near infrared proximal soil sensors

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 (R-2 = 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.

Automated summary

The integration of reflectance sensors into commercial planter or tillage components has allowed for detailed quantification of spatial soil variability. However, there is limited knowledge regarding sensor performance and reproducibility. A study conducted in Missouri, USA in 2019 aimed to investigate the accuracy of sensors in estimating soil organic matter (OM) and the repeatability of sensor output across different sensing dates.