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Infrared reflectance spectroscopy has demonstrated potential as a tool for monitoring and preventing contamination in different environments. The objective of this study was to evaluate the usage of near-infrared spectroscopy for predicting heavy-metal contamination in mangrove soils from the Botafogo River estuary located in Pernambuco State, Northeastern Brazil. These soils exhibit the highest mercury (Hg) levels ever reported for Brazilian mangrove soils. Sixty-one samples (obtained at depths ranging from 0 to 5 cm) were collected and measured using near-infrared (1000–2500 nm) reflectance spectroscopy. Preprocessing methods were applied, and partial least squares regression was used to build prediction models for attributes such as clay content, soil organic matter (SOM), pH, Eh, and concentrations of Cr, Cu, Hg, Ni, Pb, and Zn. The models were evaluated using root mean squared error (RMSE), the adjusted coefficient of determination (R2adj), bias, the ratio of performance to interquartile distance (RPIQ), and Lin's concordance correlation coefficient (CCC). The best outcomes were noted for concentrations of Cr, Cu, Hg, Ni, and Pb (RPIQ > 2.5 and R2adj > 0.80); second-best outcomes were found for Zn and SOM (RPIQ > 1.5 and R2adj > 0.70). Clay content, pH and Eh exhibited the poorest outcomes (RPIQ < 1.5). The importance of spectral preprocessing is highlighted, notably with Savitzky-Golay derivatives and Multiplicative Scatter Corrections, which boosted performance for most of the variables. Near-infrared spectroscopy can be efficiently used to predict Cr, Cu, Hg, Ni, Pb and SOM and represents a technique complementary to traditional analyses. [ABSTRACT FROM AUTHOR]

Reflectance spectroscopy has great potential to monitor and evaluate soils at large scale; however, its effectiveness in predicting properties from tropical soils still needs to be tested since their mineralogy, organic matter levels, and charge and ion adsorption dynamics are different from temperate soils. Also, it is important to assess the most appropriate spectral range for quantification of specific soil property. Therefore, this study aimed to predict physical, chemical, and mineralogical soil properties using vis–NIR (350–2500 nm) and mid-IR (4000–400 cm − 1 ) spectral libraries and statistically compare their modeling performances. We used 1259 soil samples distributed along four Brazilian States. Soil particle size, chemical analyses including macro and micronutrients, and oxides from sulfuric acid digestion were performed. Vis–NIR reflectance data were obtained by the FieldSpec Pro sensor while mid-IR data were collected using the Nicolet 6700 FT-IR sensor. Support Vector Machine was used as multiple regression algorithm and modeling performance was evaluated by R 2 , RMSE and RPIQ. This research presented a complete prediction analysis of soil properties important for survey, classification, and fertility management. Models fit very well (0.76 ≤ R 2 ≤ 0.90 and 2.81 ≤ RPIQ ≤ 5.62) for sand, clay, Al 3+ , H + Al 3+ , CEC, clay activity, Fe 2 O 3 , and TiO 2 predictions, and showed reasonable performance (0.50 ≤ R 2 ≤ 0.73 and 1.83 ≤ RPIQ ≤ 3.78) for OC, Ca, Mg, SB, V%, m%, pH in H 2 O, oxides (Si, Al, and Mn), and Cu and Mn (micronutrients). Phosphorus, potassium and some micronutrients (Fe and B) were not reliably quantified (R 2 ≤ 0.47 and RPIQ ≤ 1.83). For both spectral ranges, performance indices were kept in testing steps, and no atypical distribution pattern was identified by residual analysis. Statistically, mid-IR spectral models showed better performance for 60% of the studied properties. For some oxides (Al, Fe, Ti, and Mn), vis–NIR models were better. Models developed from vis–NIR and mid-IR spectral libraries are effective and useful to quantify properties suggesting soil mineralogy, reactivity, fertility and acidity of tropical Brazilian soils; however, mid-IR is the greatest potential spectral range. The excellent results of clay (0.85 ≤ R 2 ≤ 0.88 and 3.88 ≤ RPIQ ≤ 5.56) and sand (0.85 ≤ R 2 ≤ 0.90 and 4.85 ≤ RPIQ ≤ 5.62) modeling prove that at least soil particle size analyses can be efficiently replaced by the reflectance spectroscopy methods. [ABSTRACT FROM AUTHOR]

Near-infrared reflectance spectroscopy (NIRS) has been accepted as a fast method to evaluate various soil constituents. However, very few studies have used NIRS as a predictor of the textural and mineralogical content of tropical soils. The objective of this study was to investigate the potential use of NIRS as a tool for assessment of diverse soil properties, with specific attention to the prediction of properties related to the mineralogy of a wide range of Latosols from the Cerrado region of central Brazil. The reflectance of the soil samples, 148 in total, taken from 0.0 to 0.2 and 0.6 to 0.8-m depth, was determined in the near-infrared region between 1100 and 2500 nm at 2-nm intervals with a NIRS spectrophotometer. Our results show that for soil sampling corresponding to a large-scale map and taking into account the variability of Latosols over a wide region, NIRS can predict most of the mineralogical properties of the Latosols accurately. Near-infrared spectroscopy did not predict most of the physico-chemical characteristics of soils accurately, in particular those that are largely dependent on agricultural practice, such as pH or CEC. However, the main characteristics that correspond to soil constituents (organic matter and clay content) were relatively well predicted. [ABSTRACT FROM AUTHOR]

The phase change of a natural hemimorphite sample from Minas Gerais (Brazil) was investigated by two X-ray diffraction (XRD) methods and by near-infrared reflectance spectroscopy. Applying successive thermal treatments, the crystal structure undergoes two orientation conversions. The first one occurs at about 550 °C, and it was revealed by the Laue method. Below 500 °C, the water molecules were partially expelled without changing the crystal structure. A fact that supports this statement is the sequential disappearance of the water bands at 1400 and 1900 nm by thermal treatment. The second conversion takes place below 939 °C. Moreover, at 972 °C a phase change to the willemite mineral (α-Zn2SiO4) has been observed. This last conversion was confirmed by the power XRD. In addition, natural hemimorphite displayed a high pyroelectricity, which is related both to the absence of inverse centre and to the presence of molecular water and hydroxyl groups in the crystal structure. [ABSTRACT FROM AUTHOR]

• Genesis of an apparently homogenous and 4.5 m deep Oxisol profile was investigated. • Proximal sensors data brought to light variations within and between horizons. • Very low fertility even in C horizon was found. • X-ray diffraction correlated well with Vis-NIR data of sand, silt and clay fractions. • Maps of elemental contents determined by pXRF showed high variation in the profile. This study combined proximal sensors and soil analyses for the assessment of a 4.5-m deep Oxisol representative of southeastern Brazil. The soil was derived from gneiss. Soil samples were collected in a 20 × 20 cm grid design across the profile wall, analyzed for texture and chemical properties, and scanned by visible near infrared diffuse reflectance spectroscopy (Vis-NIR DRS), portable X-ray fluorescence spectrometry (pXRF), and X-ray diffraction (XRD). Total elemental contents by pXRF analyses were mapped to provide 2D elemental content maps. The elemental contents revealed alternating patterns in the C horizon attributed to the mafic and felsic bands of the gneiss. The extremely low exchangeable/available nutrient contents in the C horizon are remarkable. Profile maps showed Si accumulation downwards and relative Fe and Al accumulation in the upper horizons indicating desilication and intense weathering. Vis-NIR DRS spectra differentiated horizons and detected mineralogy traits. Vis-NIR DRS data correlated well with XRD data, strengthening its potential for assessing soil mineralogy. Proximal sensors can detect variations of soil properties in apparently homogeneous soil profiles, and improve studies of soil genesis. [ABSTRACT FROM AUTHOR]