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Repeatability of commercially available visible and near infrared proximal soil sensors

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Abstract

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.

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Data availability

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

CV:

Coefficient of variation

ECa :

Soil apparent electrical conductivity

OC:

Soil organic carbon

OM:

Soil organic matter

VNIR:

Visible and near-infrared reflectance

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Acknowledgements

The authors appreciate the effort put forth by Kurt Holiman and several part-time student employees for helping prepare equipment and collect data for this study. We also thank David Troth for allowing the research to be conducted on his field. The research was partially funded by the USDA Agricultural Research Service through Projects 5070-12610-005 and 58-5070-9-017. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. USDA is an equal opportunity provider and employer. The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. USDA-ARS Cropping Systems and Water Quality Research Unit, Columbia, MO, USA

    Lance S. Conway, Kenneth A. Sudduth & Newell R. Kitchen

  2. Department of Soil, Environmental, and Atmospheric Sciences, University of Missouri, Columbia, Columbia, MO, USA

    Stephen H. Anderson

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  1. Lance S. Conway
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  2. Kenneth A. Sudduth
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  3. Newell R. Kitchen
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  4. Stephen H. Anderson
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Correspondence to Kenneth A. Sudduth.

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Conway, L.S., Sudduth, K.A., Kitchen, N.R. et al. Repeatability of commercially available visible and near infrared proximal soil sensors. Precision Agric 24, 1014–1029 (2023). https://doi.org/10.1007/s11119-022-09985-1

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