Volume 42, 2018

Selection of Environmental Covariates for Classifier Training Applied in Digital Soil Mapping

Alcinei Ribeiro Campos, Elvio Giasson, José Janderson Ferreira Costa, Israel Rosa Machado, Elisângela Benedet da Silva, Benito Roberto Bonfatti

26/nov/2018

ABSTRACT A large number of predictor variables can be used in digital soil mapping; however, the presence of irrelevant covariables may compromise the prediction of soil types. Thus, algorithms can be applied to select the most relevant predictors. This study aimed to compare three covariable selection systems (two filter algorithms and one wrapper algorithm) and assess their impacts on the predictive model. The study area was the Lajeado River Watershed in the state of Rio Grande do Sul, Brazil. We […]

Paleoenvironmental Characterization of a High-Mountain Environment in the Atlantic Forest in Southeastern Brazil

Eduardo Carvalho da Silva Neto, Jaqueline Jesus Santana dos Santos, Marcos Gervasio Pereira, Deyvid Diego Carvalho Maranhão, Fabiana da Costa Barros, Lúcia Helena Cunha dos Anjos

02/nov/2018

ABSTRACT: Records of changes in the phytosociological structure of vegetation can be observed more clearly in soils that have more significant accumulation of organic matter, like those occurring in high-mountain environments. The aim of this study was to characterize soils formed in high-mountain environments in the Itatiaia National Park (INP), state of Rio de Janeiro, southeastern Brazil, and to discuss the potential of preserved phytoliths as markers of vegetative history and environmental factors. Four profiles were selected, which were morphologically […]

Visual Abstract

Multivariate Analysis and Machine Learning in Properties of Ultisols (Argissolos) of Brazilian Amazon

Cristiano Marcelo Pereira de Souza, André Thomazini, Carlos Ernesto Gonçalves Reynaud Schaefer, Gustavo Vieira Veloso, Guilherme Musse Moreira, Elpídio Inácio Fernandes Filho

26/nov/2018

ABSTRACT: Ultisols are the most common soil order in the Brazilian Amazon. The Legal Amazon (LA) has an area of 5 × 106 km2, with few accessible areas, which restricts studies of soils at a detailed level. The pedological properties can be estimated more efficiently using statistical procedures and machine learning techniques, tools which are capable of recognizing patterns in a large soil database. We analyzed the main chemical and physical properties of the B horizons of the Ultisols of […]

Visual Abstract

Digital Soil Mapping Using Machine Learning Algorithms in a Tropical Mountainous Area

Martin Meier, Eliana de Souza, Marcio Rocha Francelino, Elpídio Inácio Fernandes Filho, Carlos Ernesto Gonçalves Reynaud Schaefer

02/nov/2018

ABSTRACT: Increasingly, applications of machine learning techniques for digital soil mapping (DSM) are being used for different soil mapping purposes. Considering the variety of models available, it is important to know their performance in relation to soil data and environmental variables involved in soil mapping. This paper investigated the performance of eight machine learning algorithms for soil mapping in a tropical mountainous area of an official rural settlement in the Zona da Mata region in Brazil. Morphometric maps generated from […]

Visual Abstract

Edaphic and Topographic Factors and their Relationship with Dendrometric Variation of Pinus Taeda L. in a High Altitude Subtropical Climate

Taciara Zborowski Horst, Ricardo Simão Diniz Dalmolin, Alexandre ten Caten, Jean Michel Moura-Bueno, Luciano Campos Cancian, Fabrício de Araújo Pedron, [...]

26/nov/2018

ABSTRACT The study of the relationships between the yield potential of forest stands and the conditions offered for plant development is fundamental for the adequate management of the forest when aiming at sustainable high yields. However, these relations are not clear, especially in commercial forests, on rugged terrain where relationships between the landscape, soil, and plants are more complex. Considering this, we tested the hypothesis that the morphological aspects of the soil conditioned by topography are the main limiting factors […]

Visual Abstract

Determining the In Situ Apparent Thermal Diffusivity of a Sandy Soil

Oscar Fernando Silva Aguilar, Jorge Alberto Andaverde Arredondo, Beatris Adriana Escobedo Trujillo, Artemio Jesús Benitez Fundora

02/nov/2018

ABSTRACT: The thermal wave amplitude method is used to determine soil thermal diffusivity in situ for a sandy soil in Mexico (Coatzacoalcos, Veracruz). Soil diurnal temperature fluctuations were measured from depths of 0.05 to 0.65 m, in 0.01 m increments, during the months of April and August. Five mean diffusivity values were obtained experimentally, corresponding to the different depths combination. The soil thermal diffusivity ranged between 2.26 × 10−7 and 8.71 × 10−7 m2 s−1. The diffusivity values obtained are […]

Soil Water Retention Curve as Affected by Sample Height

Maria Laiane do Nascimento Silva, Paulo Leonel Libardi, Fernando Henrique Setti Gimenes

02/nov/2018

ABSTRACT: The soil water retention curve is one of the main instruments to assess the soil physical quality and to improve soil management. Traditionally, the equipment most used in the laboratory to determine the retention curve has been Haines funnels and Richards chambers. An important factor to which little attention has been given in the use of these equipaments is the height of the undisturbed soil sample. This work proposes to evaluate the influence of different heights of undisturbed samples […]

Reversibility of the Hardening Process of Plinthite and Petroplinthite in Soils of the Araguaia River Floodplain under Different Treatments

Angélica Pires Batista Martins, Glenio Guimarães Santos, Virlei Álvaro de Oliveira, Deyvid Diego Carvalho Maranhão, Leonardo Santos Collier

18/jun/2018

ABSTRACT Although ferruginous materials occur frequently in soils of tropical regions, information about the reversal of the hardening process of these materials is scarce. This study assessed the influence of different chemical treatments and periods of immersion on the reversibility of the hardening process of plinthite and petroplinthite in soils of the Araguaia River plain. Soil samples were collected from the plinthic horizons in 0.10 m high and 0.15 m diameter PVC cylinders and divided into subsamples with a rock […]

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