Variabilidade espacial de atributos físicos de um latossolo vermelho-amarelo, sob lavoura cafeeira

Kamimura, Karina Marie; Santos, Gérson Rodrigues dos; Oliveira, Marcelo Silva de; Dias, Moacir de Souza; Guimarães, Paulo Tácito Gontíjo

doi:10.1590/s0100-06832013000400006

Cited by 17 publications

(16 citation statements)

References 31 publications

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“…Similar classifications were found by Kamimura et al (2013) for all soil physical properties, except for microporosity (Mi), in a Typic Hapludox soil under coffee. Grego and Vieira (2005) found a medium CV for soil water storage capacity (SWSC).…”

Section: Results and Discusionsupporting

confidence: 76%

Sampling Design of Soil Physical Properties in a Conilon Coffee Field

Santos

Gontijo

Silva

et al. 2017

Rev. Bras. Ciênc. Solo

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Establishing the number of samples required to determine values of soil physical properties ultimately results in optimization of labor and allows better representation of such attributes. The objective of this study was to analyze the spatial variability of soil physical properties in a Conilon coffee field and propose a soil sampling method better attuned to conditions of the management system. The experiment was performed in a Conilon coffee field in Espírito Santo state, Brazil, under a 3.0 × 2.0 × 1.0 m (4,000 plants ha -1 ) double spacing design. An irregular grid, with dimensions of 107 × 95.7 m and 65 sampling points, was set up. Soil samples were collected from the 0.00-0.20 m depth from each sampling point. Data were analyzed under descriptive statistical and geostatistical methods. Using statistical parameters, the adequate number of samples for analyzing the attributes under study was established, which ranged from 1 to 11 sampling points. With the exception of particle density, all soil physical properties showed a spatial dependence structure best fitted to the spherical model. Establishment of the number of samples and spatial variability for the physical properties of soils may be useful in developing sampling strategies that minimize costs for farmers within a tolerable and predictable level of error.

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Section: Results and Discusionsupporting

confidence: 76%

Sampling Design of Soil Physical Properties in a Conilon Coffee Field

Santos

Gontijo

Silva

et al. 2017

Rev. Bras. Ciênc. Solo

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“…Ao lado do Nitrogênio, o potás-sio é um dos elementos mais extraídos pelas plantas e sua função é contribuir em várias atividades bioquímicas, sendo um ativador de grande número de enzimas (MALAVOLTA, 2006). Kamimura et al, (2013) discutem que o conhecimento da variabilidade dos atributos físicos e químicos do solo é importante para o monitoramento de sua qualidade, haja vista que eles estão diretamente relacionados com a sustentabilidade da produção agrícola. O estudo da variabilidade espacial dos atributos químicos do solo visa aperfeiçoar as aplicações de corretivos e fertilizantes, reduzindo a degradação ambiental e melhorando o controle do sistema de produção das culturas (SOUZA; MARQUES JUNIOR; PEREIRA, 2004;SILVA et al, 2007;OLIVEIRA;ROCHA, 2011).…”

Section: Resultsunclassified

Probabilidade De Ocorrência Dos Atributos Químicos Em Um Latossolo Sob Plantio Direto

et al. 2015

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RESUMO -Este trabalho teve como objetivo avaliar a variabilidade espacial utilizando o método de krigagem indicativa na elaboração de mapas de probabilidade da ocorrência de atributos químicos do solo e produtividade. Os dados foram coletados em uma área de solo cultivados com soja no sistema de plantio direto com uma malha regular de amostragem de 60 x 60 m, totalizando 124 pontos. Em cada um destes foram coletadas amostras deformadas do solo para a determinação dos atributos químicos (pH, Potássio, Cálcio, Magnésio e Alumí-nio trocáveis, Fósforo disponível, Zinco, acidez potencial, matéria orgânica do solo, capacidade de troca catiônica e saturação por bases). Para a determinação da produtividade foram coletadas todas as plantas dentro de 1 m² do ponto amostral. Os dados foram categorizados em códigos binários em função dos valores apresentados na recomendação para o uso de corretivos e fertilizantes. Posteriormente, foi utilizada a análise geoestatística. Os atributos potássio, fósforo, magnésio e saturação por bases apresentaram dependência espacial e foram submetidos à krigagem, como a técnica de interpolação. Foram elaborados mapas de probabilidade de ocorrência dos atributos avaliados que apresentaram dependência espacial. Os mapas probabilísticos mostraram que a região central da área avaliada apresentou maior probabilidade de necessidade de correção para os teores dos atributos potássio, fósforo, magnésio e saturação por bases. A partir da análise dos mapas foi possível detectar áreas com deficiência de nutrientes e realizar correções e utilização de técnicas de manejo de forma localizada, minimizando o custo operacional e econômico dessa cultura.Palavras-chave: Soja. Geoestatística. Mapas de Probabilidade. Krigagem Indicativa. OCCURRENCE PROBABILITY OF CHEMICAL ATTRIBUTES ON LATOSOL UNDER PLANTING DIRETOABSTRACT -This study aimed to evaluate the spatial variability using the indicative kriging method in preparing probability maps of the occurrence of soil chemical properties and productivity. Data were collected in a ground area planted with soybeans in a no-till system, with a regular grid sampling of 60 x 60 m, totaling 124 points. At each point were deformed soil samples collected to determine the chemical attributes (pH, Potassium, Calcium, Magnesium and Aluminum exchangeable, available phosphorus, zinc, potential acidity, soil organic matter, cation exchange capacity and base saturation). To determine productivity were collected all the plants within 1 m² of the sample point. Data were categorized into binary codes on the amounts presented in the recommendation for the use of lime and fertilizer. Later it used the geostatistical analysis and attributes potassium, phosphorus, magnesium and base saturation that presented spatial dependence underwent kriging as interpolation technique. Occurrence probability maps were drawn of the evaluated attributes presented spatial dependence. The probabilistic maps showed that the central area evaluated was more likely to need correction to the levels of potassi...

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“…The geoR package (Ribeiro and Diggle, 2001) was used to quantify the spatial distribution of the six hydraulic properties, applying the Box-Cox parameter (l) transformation of the distributions when necessary. Experimental semivariograms were fitted with spherical, wave, and Gaussian semivariogram models, which yielded spatial dependence (a), nugget effect (C 0 ), partial sill (C 1 ), and sill (C) parameters (Kamimura et al, 2013). The most parsimonious variogram model was identified using the criteria of maximum log-likelihood (VER), with other model differentiation criteria yielding similar results.…”

Section: Statistical and Geospatial Proceduresmentioning

confidence: 99%

An Assessment of Pedotransfer Function Performance for the Estimation of Spatial Variability of Key Soil Hydraulic Properties

Silva

Armindo

Brito

et al. 2017

Vadose Zone Journal

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Core Ideas PTFs have been widely applied in environmental and hydrological watershed studies. PTFs can simulate the spatial variability of hydraulic functions. The simulation of hydraulic maps using PTF data should be performed with care. The reliable applications of soil water dynamics and its spatial variability are very important in hydrological and environmental studies. However, determination of some hydraulic properties requires time and sometimes high costs. Pedotransfer functions (PTFs) have been applied as an alternative for the prediction of soil hydraulic properties by working with some easily measurable physical properties. This study examined the performance of the Splintex and Rosetta PTFs for estimating the spatial variability of some soil hydraulic properties such as available water capacity (AWC), field capacity (θfc), permanent wilting point (θpwp), specific water capacity [C(θ)], conductivity [K(θ)], and diffusivity [D(θ)] in a sandy soil from southeastern Brazil. Based on the log‐likelihood, Akaike, and Bayesian information criteria, semivariogram models were fitted and used to krige the assessed variable maps. The results showed the feasibility of using these PTFs to estimate the spatial variability in soil hydraulic properties and functions, which would greatly benefit vadose zone flow and transport modeling. Geostatistical analyses presented similarities in kriged maps of both observed K(θ) and C(θ) data with kriged maps by Rosetta estimates, as well as the kriged map of the observed AWC data with the kriged map by Splintex estimates sometimes revealing the same semivariogram data pattern. Predicted maps of θfc, θpwp, and D(θ) were, however, different from kriged maps of the observed data, showing that this approach should be used carefully. The use of the range parameter from the semivariogram models was efficient to determine the optimal sample density for the studied area.

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Variabilidade espacial de atributos físicos de um latossolo vermelho-amarelo, sob lavoura cafeeira

Cited by 17 publications

References 31 publications

Sampling Design of Soil Physical Properties in a Conilon Coffee Field

Sampling Design of Soil Physical Properties in a Conilon Coffee Field

Probabilidade De Ocorrência Dos Atributos Químicos Em Um Latossolo Sob Plantio Direto

An Assessment of Pedotransfer Function Performance for the Estimation of Spatial Variability of Key Soil Hydraulic Properties

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