The Brazilian Program of soil analysis via spectroscopy (ProBASE): Combining spectroscopy and wet laboratories to understand new technologies

Abstract

Spectroscopy has been extensively used in soil analysis. However, users, such as commercial laboratories, still do not know the application, potential, and limitations of this technique. This paper aims to present a given course going from theory to practice for end-users regarding spectroscopy technique. The paper combines the use of soil spectroscopy and wet laboratories to perform a scientific-teaching dynamic using their own data, allowing for a better understanding of the technique. The course is denominated ProBASE (The Brazilian Program of Soil Analysis via Spectroscopy). Soil samples from 35 laboratories were sent (34 from Brazil and 1 from Paraguay) to a central spectroscopy laboratory. Samples were measured for visible-near-short-wave-infrared, Vis-NIR (400–2500 nm), and mid-infrared, MIR (3000–25000 nm) ranges and by portable X-ray Fluorescence (pXRF) sensor. We also used the Brazilian Soil Spectral Library (BSSL) dataset (Vis-NIR). We performed three different population models with Vis-NIR as follows: a) using the dataset of each laboratory (Local), b) using the entire ProBASE-dataset (Regional), and c) using the BSSL (Country). Afterward, we developed spectral models using the other spectral ranges for comparison. We also used a qualitative approach to detect errors from the wet laboratory analyses using Vis-NIR data and evaluated their impact on spectral modeling. The models that used Local samples had the best performance, with R2 in validation reaching up to 0.93 for clay, 0.92 for sand, 0.86 for P, 0.82 for pH, 0.81 for organic matter (OM), 0.75 for Ca2+, 0.72 for cation exchange capacity (CEC), 0.71 for aluminum saturation, 0.71 for Al3+, 0.70 for Mg2+, 0.64 for base saturation (V%), and 0.56 for K+. However, the base saturation presented greater variation from good to poor results. For the comparison dataset, the results can be summarized as follows: a) pXRF was better for P, Ca2+ B, V% and Mn; b) MIR was better for clay, sand, OM, pH, Mg2+, CEC and Mn; c) Vis-NIR was better for H + Al; d) the three spectral ranges had good performance for OM, sand, silt and clay. In addition, our findings indicate that all spectral ranges are useful for a wet laboratory, where each model has advantages and limitations, but they can be used complementary to each other. Spectroscopy can detect inconsistencies of the wet laboratory analyses, affecting thus the quality of the results. The commercial laboratory community viewed the techniques positively. The results indicate the viability to create a hybrid laboratory, combining both wet and dry (soil spectroscopy) chemistry.