TY - JOUR
T1 - Proximal sensors for modeling clay mineralogy and characterization of soil textural fractions developed from contrasting parent materials
AU - Silva, Fernanda Magno
AU - Silva, Sérgio Henrique Godinho
AU - Andrade, Renata
AU - Coblinski, João Augusto
AU - Inda, Alberto Vasconcellos
AU - Frosi, Gustavo
AU - Lima, Suane de Souza Franco
AU - Menezes, Michele Duarte de
AU - Tavares, Tiago Rodrigues
AU - Guilherme, Luiz Roberto Guimarães
AU - Weindorf, David C.
AU - Curi, Nilton
N1 - Publisher Copyright:
© 2024 Elsevier B.V.
PY - 2024/6
Y1 - 2024/6
N2 - Proximal sensors combined with X-ray diffraction (XRD) have optimized soil characterization, but scarce studies have focused on predicting the contents of minerals under this scope. The objectives herein were to: a) use the portable X-ray fluorescence (pXRF) spectrometry, diffuse reflectance spectroscopy in the range of visible and near-infrared (Vis-NIR), magnetic susceptibility (χ) and XRD to characterize the mineralogy of soils derived from representative Brazilian soil parent materials, and b) create models to quantify the minerals obtained via XRD. Twenty-two soil profiles developed from gabbro, gneiss, quartzite, mineral and organic sediments were described with 53 soil horizons sampled. Each sample had the sand, silt and clay fractions separated and analyzed with XRD, pXRF, χ, and Vis-NIR. Models were created using the Random Forest algorithm permuting the following predictor variables (separately and combined): pXRF, parent material (PM), χ, soil texture (sand, silt, and clay content), and Vis-NIR. Models’ accuracy was calculated using the leave-one-out cross-validation method. Si, Al, Fe, Ca, K, and Ti contents obtained by pXRF and the χ discriminated the soil particle size fractions according to the parent material. XRD analysis allowed the evaluation of the pedogenetic development of soils and their relation to the respective parent material. The best models for mineral contents were found for hematite (Hm) (1 0 4)+(Gt) (1 3 0) (R2 = 0.85), Hm (1 1 0) + Mh (1 3 1) (R2 = 0.76), kaolinite (Kt) (0 0 1) (R2 = 0.73), Kt (0 0 2) (R2 = 0.80), mica (Mc) (0 0 1) (R2 = 0.77), and Mc (0 2 0) + Kt (0 2 0) (R2 = 0.81). Clay mineralogy content was accurately modeled using only pXRF and parent material data. This approach can facilitate and speed up detailed soil mineralogy characterization. Further studies are encouraged to model the content of minerals found in the sand and silt fractions of soils with diverse mineralogy via proximal sensors and using larger data sets.
AB - Proximal sensors combined with X-ray diffraction (XRD) have optimized soil characterization, but scarce studies have focused on predicting the contents of minerals under this scope. The objectives herein were to: a) use the portable X-ray fluorescence (pXRF) spectrometry, diffuse reflectance spectroscopy in the range of visible and near-infrared (Vis-NIR), magnetic susceptibility (χ) and XRD to characterize the mineralogy of soils derived from representative Brazilian soil parent materials, and b) create models to quantify the minerals obtained via XRD. Twenty-two soil profiles developed from gabbro, gneiss, quartzite, mineral and organic sediments were described with 53 soil horizons sampled. Each sample had the sand, silt and clay fractions separated and analyzed with XRD, pXRF, χ, and Vis-NIR. Models were created using the Random Forest algorithm permuting the following predictor variables (separately and combined): pXRF, parent material (PM), χ, soil texture (sand, silt, and clay content), and Vis-NIR. Models’ accuracy was calculated using the leave-one-out cross-validation method. Si, Al, Fe, Ca, K, and Ti contents obtained by pXRF and the χ discriminated the soil particle size fractions according to the parent material. XRD analysis allowed the evaluation of the pedogenetic development of soils and their relation to the respective parent material. The best models for mineral contents were found for hematite (Hm) (1 0 4)+(Gt) (1 3 0) (R2 = 0.85), Hm (1 1 0) + Mh (1 3 1) (R2 = 0.76), kaolinite (Kt) (0 0 1) (R2 = 0.73), Kt (0 0 2) (R2 = 0.80), mica (Mc) (0 0 1) (R2 = 0.77), and Mc (0 2 0) + Kt (0 2 0) (R2 = 0.81). Clay mineralogy content was accurately modeled using only pXRF and parent material data. This approach can facilitate and speed up detailed soil mineralogy characterization. Further studies are encouraged to model the content of minerals found in the sand and silt fractions of soils with diverse mineralogy via proximal sensors and using larger data sets.
KW - Magnetic susceptibility
KW - Parent material
KW - Portable X-ray fluorescence
KW - Soil mineralogy
KW - Tropical soils
KW - Vis-NIR spectroscopy
UR - http://www.scopus.com/inward/record.url?scp=85191361138&partnerID=8YFLogxK
U2 - 10.1016/j.catena.2024.108053
DO - 10.1016/j.catena.2024.108053
M3 - Article
AN - SCOPUS:85191361138
SN - 0341-8162
VL - 241
JO - Catena
JF - Catena
M1 - 108053
ER -