Changes in Physical Properties of Soils with Land Use Time in the Brazilian Savanna Environment

Soils from central Brazil have been intensively used over the last decades because of the rapid conversion of savannas ( Cerrado ) into corn/soybean fields. The objective of this work is to study modifications in the physical properties of soils in the Rio Verde watershed, as a function of the land use time for agriculture, determined from classification of Landsat satellite images between 1980 and 2010. Soil samples were collected at surface (0–20 cm) and subsurface (20–40 cm) horizons for the different classes of land use time (<10, 10–20, 20–30, and >30 years). The following physical properties were measured: bulk density (BD), air permeability (K_a), penetration resistance (PR), microporosity (MI), macroporosity (MA), and total porosity (TP). Results showed a strong expansion with time of agriculture that occupied 35·3% (1980), 37·4% (1990), 51·3% (2000), and 60·9% (2010) of the watershed area. When properties were compared with those from the reference areas (preserved soils under native vegetation), significant differences were observed for all the physical attributes of soils for a land use time higher than 20 years. Overall, BD and PR increased with land use time, and the opposite was verified for K_a, MA, and TP. Some physical properties presented values (e.g., 1·54 g cm⁻³ for BD and 0.06 cm³ cm⁻³ for MA) close to the critical ones reported to affect crop development, but they were not still impacting on local soybean yield. Copyright © 2013 John Wiley & Sons, Ltd.     

First report of Seville root-knot nematode (Meloidogyne hispanica) infecting tobacco in the Brazil

Journal of Plant Diseases and Protection - Tobacco (Nicotiana tabacum L.) is one of the major nonfood crops in the Southern of Brazil. During 2019/2020 and 2020/2021 crop seasons, Root Knot...     

Contrasting edge and pasture matrix effects on ant diversity from fragmented landscapes across multiple spatial scales

Landscape Ecology - Harmful effects of habitat loss and fragmentation can be detected across multiple spatial scales, yet most studies that aim to characterize these effects take place at a single...     

Proximal sensor-enhanced soil mapping in complex soil-landscape areas of Brazil

Portable X-ray fluorescence (pXRF) spectrometry and magnetic susceptibility (MS) via magnetometer have been increasingly used with terrain variables for digital soil mapping. However, this methodology is still emerging in many countries with tropical soils. The objective of this study was to use proximal soil sensor data associated with terrain variables at varying spatial resolutions to predict soil classes using the Random Forest (RF) algorithm. The study was conducted on a 316-ha area featuring highly variable soil classes and complex soil-landscape relationships in Minas Gerais State, Brazil. The overall accuracy and Kappa index were evaluated using soils that were classified at 118 sites, with 90 being used for modeling and 28 for validation. Digital elevation models (DEMs) were created at 5-, 10-, 20-, and 30-m resolutions using contour lines from two sources. The resulting DEMs were processed to generate 12 terrain variables. Total Fe, Ti, and SiO₂ contents were obtained using pXRF, with MS determined via a magnetometer. Soil class prediction was performed using the RF algorithm. The quality of the soil maps improved when using only the five most important covariates and combining proximal sensor data with terrain variables at different spatial resolutions. The finest spatial resolution did not always provide the most accurate maps. The high soil complexity in the area prevented highly accurate predictions. The most important variables influencing the soil mapping were MS, Fe, and Ti. Proximal sensor data associated with terrain information were successfully used to map Brazilian soils at variable spatial resolutions.