RESUMO O intemperismo do material de origem é o processo inicial que garantirá ao solo maior ou menor fertilidade, tornando o estudo desse processo fundamental para entender a dinâmica do solo. Grande parte dos estudos de intemperismo é baseada em índices que calculam a taxa de dissolução dos feldspatos (CIA, CIW e PIA, por exemplo) muitas vezes não refletindo a complexidade do intemperismo ocorrendo no perfil de solo. Outras metodologias- como balanço geoquímico, diferença elementar (DE) e índice W- têm sido desenhadas para melhorar esses estudos. Avaliar se essas metodologias serão mais eficientes que os índices CIA, CIW e PIA para apontar as variações intempéricas em perfis recentes desenvolvidos de basalto é o objetivo desse trabalho. Foram utilizados dados de óxidos principais para calcular o balanço geoquímico, DE, CIA, CIW, PIA e W e analisar a intensidade do intemperismo em dois perfis originados de basalto no Estado de São Paulo. Foram fatorados também os índices Ki e Kr e a relação Fe o/Fed e analisada a mineralogia dos horizontes dos solos e da rocha de origem. O índice W e a DE mostraram maior variação intempérica que CIA, CIW e PIA. O balanço geoquímico, a mineralogia e as razões Ki e Kr, Feo /Fed foram eficientes em explicar as variações que ocorreram entre os horizontes. A junção da DE com o balanço geoquímico trouxe novas informações para a análise do intemperismo que a observação isolada de CIA, CIW e PIA.

ABSTRACT Weathering of the parent material is the initial process that plays an essential role in soil fertility. The study of this process has become crucial to better understand soil dynamics. Most studies on weathering are based on indexes that calculate the feldspar dissolution rate (for example, CIA, CIW, and PIA) which not always reflect the complexity in the soil profile. Other methodologies have been designed to improve these approaches, such as geochemical balance, difference of elemental contents (DE), and the W index. This work aim to assess the efficiency of these methods to identify variations in recent soil profiles developed from diabase as compared to the CIA, CIW, and PIA indexes. Data on the main oxides were used to calculate the geochemical balance, DE, CIA, CIW, PIA, and W indexes to analyze weathering intensity in two profiles originated from diabase in the São Paulo State, Brazil. The Ki and Kr indexes and Feo /Fed ratio were also factored and we analyzed the mineralogy of soil horizons and the source rock. The W index and DE presented greater weathering variation than the CIA, CIW, and PIA in both profiles. The geochemical balance, mineralogy, and the Ki, Kr and Feo /Fed ratios explained the variations between the horizons. The DE and geochemical balance together generated new information for the analysis of the weathering process than the isolated indexes.

ABSTRACT: The study of soils, including their physical and chemical properties, is essential for agricultural management. Soil quality must be maintained to ensure sustainable production of food and conservation of natural resources. In this context, soil mapping is important to provide spatial information, which can be performed using remote sensing (RS) techniques. Modeling through use of satellite data is uncertain regarding the amplitude of replicability of the models. The aim of this study was to develop a quantification model for soil texture based on reflectance information from a continuum of bare soils, obtained by overlapping multi-temporal satellite images, and apply this model to an unknown region to evaluate its applicability. Spectral data were extracted from two Landsat TM 7 satellite images containing only bare soil, representing two distinct regions in Brazil (Area 1 and Area 2). The spectral data (obtained from six bands) and laboratory data (particle size from the 0.00-0.20 m layer) of Area 1 were modeled and extrapolated to Area 2. The bare soil images differentiated textural classes as sandy, sandy loam, clayey loam, clayey, and very clayey soil. The coefficients of determination between the determined and estimated values were higher than 0.5 and errors lower than 13 % for Area 1 and 30 % for Area 2, indicating applicability of the model to unknown areas.