Optimizing a Standard Spectral Measurement Protocol to Enhance the Quality of Soil Spectra: Exploration of Key Variables in Lab-Based VNIR-SWIR Spectral Measurement

Abstract

The method of proximal VNIR-SWIR (with a spectral region of 400–2500 nm) spectroscopy in a laboratory setting has been widely employed in soil property estimations. Increasing attention has been focused recently on establishing an agreed-upon protocol for soil spectral measurement, fueled by the recognition that studies carried out under different laboratory settings have made future data sharing and model comparisons difficult. This study aimed to explore the key factors in a lab-based spectral measurement procedure to provide recommendations for enhancing the spectra quality and promoting the development of the spectral measurement protocol. To this aim, with the support of the standard spectral laboratory at Jilin University, China, we designed and performed control experiments on four key factors—the light interference in the measurement course, soil temperature, soil moisture, and soil particle size—to quantify the variation in the spectra quality by the subsequent estimation accuracies of different estimation models developed with different spectra obtained from control groups. The results showed that (1) the soil–probe contact measurement derived the optimum spectra quality and estimation accuracy; however, close-non-contact measurement also achieved acceptable results; (2) sieving the soil sample into particle sizes below 1 mm and drying before spectral measurement effectively enhanced spectra quality and estimation accuracy; (3) the variation in soil temperature did not have a distinct influence on spectra quality, and the estimation accuracies of models developed based on soil samples at 20–50 °C were all acceptable. Moreover, a 30-min warm-up of the spectrometer and contact probe was found to be effective. We carried out a complete and detailed control experiment process, the results of which offer a guide for optimizing the process of laboratory-based soil proximal spectral measurement to enhance spectra quality and corresponding estimation accuracy. Furthermore, we present theoretical support for the development of the spectral measurement protocol. We also present optional guidance with relatively lower accuracy but effective results, which are save time and are low cost for future spectral measurement projects.

Keywords

• laboratory VNIR-SWIR hyperspectral measurement
• spectral measurement protocol
• control experiment
• soil organic carbon content (SOC)
• partial least squares regression (PLSR)
• spectral transformation