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429 results

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


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 […]

Modeling in the Adjustment of Fertilization Recommendation through Leaf Analysis in Fertigated ‘Prata’ Banana

José Aridiano Lima de Deus, Júlio César Lima Neves, Ismail Soares, Víctor Hugo Alvarez V., Fabricio Martinazzo Regis de Albuquerque, Lauana Lopes dos Santos, [...]


ABSTRACT: In banana cultivation, fertilization recommendations are almost exclusively based on soil chemical analysis, without considering leaf analysis and expected yield, which can help in the adjustment of fertilization programs. The aim of this study was to develop a method to recommend macronutrient fertilization rates which integrates data on leaf analysis, soil chemical analysis, and yield. Yield, soil chemical analysis, and leaf analysis data of fertigated plantations of ‘Prata’ banana were obtained for the first and second halves of the […]

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


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 […]

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, [...]


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 […]

Digital Soil Mapping of Soil Properties in the “Mar de Morros” Environment Using Spectral Data

Patrícia Morais da Matta Campbell, Elpídio Inácio Fernandes Filho, Márcio Rocha Francelino, José Alexandre Melo Demattê, Marcos Gervasio Pereira, Clécia Cristina Barbosa Guimarães and, [...]


ABSTRACT Quantification of soil properties is essential for better understanding of the environment and better soil management. The conventional techniques of laboratory analysis are sometimes costly and detrimental to the environment. Thus, development of new techniques for soil analysis that do not generate residues, such as spectroscopy, is increasingly necessary as a viable way to estimate a wide range of soil properties. The objective of this study was to predict the levels of organic carbon (OC), clay, and extractable phosphorus […]

Estimation of the Retention and Availability of Water in Soils of the State of Santa Catarina

Diego Bortolini, Jackson Adriano Albuquerque


ABSTRACT: Soil water retention and availability are important properties for agricultural production, which can be measured directly or estimated by pedotransfer functions. Some studies on this topic were carried out in Santa Catarina, Brazil. To improve the estimates, it is necessary to evaluate other properties, to analyze more soil types, as well as to use other analysis techniques such as artificial neural networks and regression trees. Thus, the objective of the study was to estimate the field capacity (FC), permanent […]

Functionalized Charcoal as a Buffering Matrix of Copper and Zinc Availability

Gelton Geraldo Fernandes Guimarães, Amanda Soares Giroto, Breno Cardoso Teixeira, Leonardus Vergütz, Reinaldo Bertola Cantarutti


ABSTRACT: High copper (Cu) and zinc (Zn) contents in soil can cause phytotoxicity to plants and contaminate surface and groundwater, with negative effects on agriculture and the environment. Functionalized charcoal (OCh) has high cation exchange capacity (CEC) and the ability to adsorb Cu and Zn and control their availability in the soil and water. An adsorption study at two pH levels was carried out to evaluate increasing Cu and Zn sorption capacity provided by the functionalization process of a charcoal. […]

Potassium Dynamics in Ruzigrass Rhizosphere

Marcelo Raphael Volf, Tiara Moraes Guimarães, Daniele Scudeletti, Igor Vilela Cruz, Ciro Antonio Rosolem


ABSTRACT: Ruzigrass (Urochola ruziziensis) has a large capacity to take up K from the soil, including non-exchangeable forms, and can play an important role in nutrient cycling in integrated production systems. However, K transport to roots of brachiarias is not well known, nor the nutrient dynamics in the rhizosphere, where a concentration gradient may be established towards the non-rhizospheric soil, creating a favorable environment for the release of non-exchangeable K. This study aimed to evaluate the effect of ruzigrass on […]

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


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 […]

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


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 […]

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