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Development of a Semi-Automated In-Situ Soil Sensor using Vis-NIR spectroscopy

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2020 ASABE Annual International Virtual Meeting  2000052.(doi:10.13031/aim.202000052)
Authors:   Roberto M Buelvas, Viacheslav I Adamchuk, Benjamin De Leener, Gabriel Mangeat
Keywords:   Automation, Control, On-the-spot sampling, Proximal soil sensing, Vis-NIR Spectroscopy.

Abstract. In the context of proximal soil sensing, soil spectroscopy technology has great potential when combined with the automation required for on-the-spot sampling by a mobile platform, especially if it makes measurements at controlled depths. The overall accuracy of soil spectroscopy applications might be improved by obtaining soil data in more locations, at various depths, and at different times. Although the accuracy of soil property predictions is lower than the accuracy of conventional laboratory tests, increasing the number of unbiased measurements may significantly increase the accuracy of thematic soil maps. This paper presents the design of a new, quick-install soil sensor system, equipped with a vertical drill to facilitate the collection of depth-specific measurements ranging from 0 cm to 20 cm below the surface. The ChrysaLabs probe performs vis-NIR soil scanning with 360° optical integration at every point of measurement, accurately defined by depth at every 1 cm. The ability of the user to open a borehole, insert the probe, take measurements, and remove the probe with a push of a button from inside the cabin of a vehicle improves the ergonomics and logistics of data collection surveys. The sensor readings can be visualized by the user from inside the cabin. Finally, the system can be quickly mounted and dismounted on many suitable, commercially available, agricultural vehicles. The combination of these features makes for an autonomous system with the goal of mapping soil status across a field. Proper use of this technology allows for the determination of spatially variable soil characteristics in real time.

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