Portable shifted excitation Raman difference spectroscopy for on-site soil analysis

On-site soil analysis in the framework of precision agriculture is gaining significant importance to achieve improved crop productivity, increased soil health and reduced fertilizer application. In situ sensing techniques can provide the information required for decision support systems immediately on the field, for example, to control fertilization and liming. Shifted excitation Raman difference spectroscopy (SERDS) pilot investigations for on-site soil analysis are presented using a portable SERDS sensor system specifically developed for in-field studies. The SERDS sensor includes a dual-wavelength diode laser at 785 nm integrated in an in-house realized turnkey laser system and an optical power of 36 mW at the sample was chosen for our experiments. Outdoor pre-investigations with the device and polystyrene as test sample show the capability of SERDS for qualitative and quantitative analysis under changing daylight conditions. On-site soil analysis is carried out and SERDS extracts Raman signals from disturbing background interference with a 15-fold improvement of the signal-to-background-noise ratio. Beside others, closely neighboured Raman signals of calcite and dolomite are identified and even mixtures of both soil carbonates are discriminated using SERDS. The number of accumulations for generating an averaged SERDS spectrum of soil with a sufficient signal stability and signal-to-background-noise ratio is evaluated to optimize the overall exposure time for such in situ experiments. The presented results demonstrate the large capability of the developed portable SERDS sensor system for on-site soil investigations as promising tool for precision agriculture.

Automated summary

On-site soil analysis plays a crucial role in precision agriculture by improving crop productivity, soil health, and reducing fertilizer use. In this study, a portable SERDS sensor system was developed for in-field studies, which showed great potential for qualitative and quantitative analysis under changing daylight conditions. The system effectively extracted Raman signals from background interference, allowing for the identification and discrimination of soil carbonates. The results demonstrate the significant capability of the developed system for on-site soil investigations in precision agriculture.