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All publications of “Braz Calderano Filho”

4 results

Mapping Soil Cation Exchange Capacity in a Semiarid Region through Predictive Models and Covariates from Remote Sensing Data

César da Silva Chagas, Waldir de Carvalho Júnior, Helena Saraiva Koenow Pinheiro, Pedro Armentano Mudado Xavier, Silvio Barge Bhering, Nilson Rendeiro Pereira, [...]


ABSTRACT: Planning sustainable use of land resources requires reliable information about spatial distribution of soil physical and chemical properties related to environmental processes and ecosystemic functions. In this context, cation exchange capacity (CEC) is a fundamental soil quality indicator; however, it takes money and time to obtain this data. Although many studies have been conducted to spatially quantify soil properties on various scales and in different environments, not much is known about interactions between soil properties and environmental covariates in […]

Artificial neural networks applied for soil class prediction in mountainous landscape of the Serra do Mar

Braz Calderano Filho, Helena Polivanov, César da Silva Chagas, Waldir de Carvalho Júnior, Emílio Velloso Barroso, Antônio José Teixeira Guerra, [...]


Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS […]

Evaluation of statistical and geostatistical models of digital soil properties mapping in tropical mountain regions

Waldir de Carvalho Junior, Cesar da Silva Chagas, Philippe Lagacherie, Braz Calderano Filho, Silvio Barge Bhering


Soil properties have an enormous impact on economic and environmental aspects of agricultural production. Quantitative relationships between soil properties and the factors that influence their variability are the basis of digital soil mapping. The predictive models of soil properties evaluated in this work are statistical (multiple linear regression-MLR) and geostatistical (ordinary kriging and co-kriging). The study was conducted in the municipality of Bom Jardim, RJ, using a soil database with 208 sampling points. Predictive models were evaluated for sand, silt […]

Relationships between local farmers’ and pedologists’ knowledge on soil science: A case study in Rio Pardo de Minas, Brazil

João Roberto Correia, Lúcia Helena Cunha dos Anjos, Antonio Carlos Souza Lima, Delma Pessanha Neves, Luciano de Oliveira Toledo, Braz Calderano Filho, [...]


One of the challenges of constructing agricultural systems that aim to be sustainable, is the usage of scientific knowledge adapted to the peculiar social situation. For this purpose it is necessary to consider the knowledge that farmers accumulated over time and space. In the case of the soil resources, a modest amount of the local knowledge is considered in classrooms and in soil research. This is a constraint to the application of technologies based on local scientific knowledge involving traditional […]