The conversion from native forest to other land-use systems can decline the soil organic carbon (SOC) in tropical soils. However, conservationist management could mitigate SOC losses, promoting the functioning and stability of agricultural soils. This study aimed to address the influence of conversion from native forest to different land-use systems on SOC fractions in Northeastern Brazil. Topsoil soil samples were collected in areas under pasture (PAS), no-tillage (NT1 and NT2), eucalyptus (EUC), and native forests of Cerrado in Northeastern, Brazil. Total organic C, microbial biomass (MBC), particulate (POC), and mineral-occluded organic C (MOC), as well as fulvic acids (C-FA), humic acids (C-HA), and humin (C-HUM) fractions were accessed. The results showed that land conversion maintained similar levels of humic fractions and total organic carbon (TOC) stocks in the PAS, NT1, NT2, and EUC as compared to native Cerrado. Soils with the input of permanent and diverse fresh organic material, such as NT2, PAS, and EUC, presented high levels of MBC and POC, and the lowest C-FA:TOC and C-HA:TOC ratios. The land conversion to agricultural systems that include cropping rotations associated with pasture species such as Mombasa grass and eucalyptus prevents topsoil losses of active C compartments in the Cerrado of the Brazilian Northeast. It suggests that sustainable and conservationist management should be emphasized to maintain and improve the status of soil organic C.

Soil chemical and physical analyses are the major sources of data for agriculture. However, traditional soil analyses are time-consuming, not cost-efficient, and not environmentally friendly. An alternative to traditional soil analyses is soil spectroscopy. This technique is a low-cost and quick analytical method, which can be implemented in a laboratory and/or in-situ. Nevertheless, some spectrometers are expensive and do not contemplate the entire spectrum. Despite this limitation, the main objective of the study was to create a soil spectral [...] ABSTRACT Soil chemical and physical analyses are the major sources of data for agriculture. However, traditional soil analyses are time-consuming, not cost-efficient, and not environmentally friendly. An alternative to traditional soil analyses is soil spectroscopy. This technique is a low-cost and quick analytical method, which can be implemented in a laboratory and/or in-situ. Nevertheless, some spectrometers are expensive and do not contemplate the entire spectrum. Despite this limitation, the main objective of the study was to create a soil spectral

The conversion of the native Cerrado into agricultural systems promotes a reduction in the input of organic residues on the soil, which can compromise the contents of soil organic carbon. The spatial distribution of carbon and nitrogen stocks in the soil is normally influenced by environmental and anthropogenic factors. This research aimed to map and evaluate the spatial variability of carbon and nitrogen stocks in the soil, in different integrated systems and pasture areas in the edaphoclimatic conditions of the Cerrado biome, in the state of Maranhão. The work was set up in a Red-Yellow Latosol with different management methods: crop-livestock integration with no-till farming, crop-livestock integration with patch scarification and harrowing, crop-livestock-forest integration, and pasture. The samples were removed at a depth of 0.0-0.20 m, in a grid with a regular interval of 50 m, totaling 193 points. The data were subjected to descriptive statistics, geostatistics, and kriging interpolation. The mean and median values are similar for the carbon and nitrogen stocks, in their respective management systems, indicating symmetric data distribution, confirmed by the asymmetry and kurtosis values close to zero. The spatial distribution of the carbon stocks is more homogeneous in the crop-livestock integration with no-till farming, whereas the crop-livestock integration with patch scarification and harrowing presents greater homogeneity in nitrogen distribution.

Irrigated fruit growing in the São Francisco Valley has been standing out in the Northeast region of Brazil and the incorrect management of fertilization has caused problems of physical and / or chemical degradation of the soil. The work aimed to evaluate the spatial variability of the chemical attributes of a Latossolo Vermelho-Amarelo (Oxisol) grown with banana (Musa spp). The study was carried out in the irrigated perimeter of Nupeba in Riachão das Neves / BA. In an area cultivated for 18 years with silver banana fertigated by micro sprinkling. In April 2017 simple soil samples were collected at depths of 0 -0.20 m and 0.20 -0.40 m, from an experimental grid consisting of 40 georeferenced points and spaced every 10 meters. The soil samples determined: pH (H2O); Organic carbon; Phosphorus (P); Potassium (K+); Calcium (Ca2+); Magnesium (Mg2+) and Potential acidity (H + Al) and the sum of bases (BS), cation exchange capacity (CEC) and base saturation (V%) were calculated. The results of the analyses were evaluated using descriptive statistics and the geostatistics technique. The descriptive analysis identified the normality of the data. The spatial variability was confirmed, allowing the making of maps. The analyzed area has low fertility (V <55%) and the inadequate management of soil correction and fertilization can reduce the availability of nutrients for the implanted crop, making the soil susceptible to degradation with the use of irrigation. The distribution maps allow the visualization of the area, allowing the application of inputs with varying rates, aiming at homogenizing the soil fertility.

Management systems that include trees tend to provide higher amounts of plant biomass to the soil, contributing to the increase in carbon (C) and nitrogen (N) stocks. This study simulated C and N stocks and their compartments in a crop-livestock-forest integration system in the edafoclimatic conditions of the Maranhão Cerrado using the Century 4.5 model. The evaluated areas were native Cerrado vegetation (NV) and crop-livestock-forest integration (CLFI). The calibration process gradually modified the model parameters to better fit the simulated and observed soil C and N stocks. The best fit between the data was obtained after changes in the main parameters (DEC3(2), DEC4, and DEC5) that controlled the rate of decomposition of soil organic matter. C and N stocks increased by 14% and 15%, respectively, over 14 years after replacing NV with CLFI. The slow compartment of C presented greater sensitivity to changes in management, with an increase of 47% compared with that of NV. The active compartment increased by 31% and the passive compartment remained constant for over 14 years. Future scenarios, where pasture was maintained between the eucalyptus trees and the scenario that allowed the soybean, corn, and Brachiaria rotation between the trees, were more effective, accumulating approximately 37 Mg C ha-1. The continuous contribution of residues from the trees and pasture increased C and N stocks in the long-term in the slow fraction, where the total organic carbon increased from 32 to 36 Mg ha-1 when NV was replaced with CLFI. The model predicted the C and N stocks with accuracies ranging from 1 to 11% of the observed values

Diffuse reflectance spectroscopy is a promising technique for advances in soil studies. Thus, the objective of this work was to evaluate the efficiency of diffuse reflectance spectroscopy in the mid-infrared range to estimate the sand, silt, clay, pH, H+ Al, sum of bases, organic matter contents, phosphorus, and remaining phosphorus of Argissolo Amarelo distrocoeso típico (Typic Hapludult) in the state of Maranhão, Brazil. Two areas with different characteristics were selected for sampling: Area 1 and Area 2. A square sampling grid with 121 points was used for each area. Samples were collected from the 0.0–0.2 m soil layer. The spectra were recorded in the mid-infrared range (2500–25000 nm; 4000–400 cm⁻¹) at 8 cm⁻¹ resolution. The data of Area 1 were used for chemometric model calibrations by Partial Least Squares Regression analysis. The data of Area 2 were used for the geostatistical modeling. All attributes presented, in general, positive calibration parameters, with adjusted coefficient of determination (R²_adj) for sand (0.76), silt (0.51), clay (0.77), pH (0.51), H+ Al (0.45), sum of bases (0.75), organic matter contents (0.71) and remaining phosphorus (0.6), and residual prediction deviation equal to or higher than 1.4, except for phosphorus. The lowest prediction errors were found for sand (17%) and silt (19%) contents, pH (15%), and remaining phosphorus (8%). The distribution of spatial attributes – measured and predicted – presented positive correlation, confirming the potential of diffuse reflectance spectroscopy as an alternative for prediction of soil attributes.