The use of landforms to predict the variability of soil and orange attributes

Siqueira, Diego Silva; Marques, José Carlos; Pereira, Gener Tadeu

doi:10.1016/j.geoderma.2009.11.024

Cited by 89 publications

(78 citation statements)

References 70 publications

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“…in this study, the variability of soil macroporosity (Ma) was very high (table 1). these results disagree with observations of Megda et al (2008), who reported medium variability for Ma and Siqueira et al (2010), who stated high variability for Ma. the variability of gravimetric soil water (gSw) was medium and low for soil water storage (SwS) (table 1).…”

Section: Resultscontrasting

confidence: 99%

Spatial relationships between soil attributes and corn yield in no-tillage system

Rodrigues¹,

Corá

Fernandes

2012

Rev. Bras. Ciênc. Solo

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SummaRYSoil properties play an important role in spatial variability of crop yield. however, a low spatial correlation has generally been observed between maps of crop yield and of soil properties. the objectives of the present investigation were to assess the spatial pattern variability of soil properties and of corn yield at the same sampling intensity, and evaluate its cause-and-effect relationships.

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Section: Resultscontrasting

confidence: 99%

Spatial relationships between soil attributes and corn yield in no-tillage system

Rodrigues¹,

Corá

Fernandes

2012

Rev. Bras. Ciênc. Solo

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“…Siqueira et al (2010), in a previous study of some soil properties, found the first two PCs to account for 57.62 % of the variance in combination; in addition, Carvalho Jr. et al (2008) examined various physical and chemical properties of soil and found PC1 to explain 28.29 % of their variance.…”

Section: Resultsmentioning

confidence: 98%

Iron oxides and quality of organic matter in sugarcane harvesting systems

Barbieri¹,

Júnior

Siqueira³

et al. 2014

Rev. Bras. Ciênc. Solo

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Improvements in working conditions, sustainable production, and competitiveness have led to substantial changes in sugarcane harvesting systems. Such changes have altered a number of soil properties, including iron oxides and organic matter, as well as some chemical properties, such as the maximum P adsorption capacity of the soil. The aim of this study was to characterize the relationship between iron oxides and the quality of organic matter in sugarcane harvesting systems. For that purpose, two 1 ha plots in mechanically and manually harvested fields were used to obtain soil samples from the 0.00-0.25 m soil layer at 126 different points. The mineralogical, chemical, and physical results were subjected to descriptive statistical analyses, such as the mean comparison test, as well as to multivariate statistical and principal component analyses. Multivariate tests allowed soil properties to be classified in two different groups according to the harvesting method: manual harvest with the burning of residual cane, and mechanical harvest without burning. The mechanical harvesting system was found to enhance pedoenvironmental conditions, leading to changes in the crystallinity of iron oxides, an increase in the humification of organic matter, and a relative decrease in phosphorus adsorption in this area compared to the manual harvesting system.

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“…Apesar da formação dos solos não ocorrer de maneira aleatória (estocástica), a Figura 5 mostra um indicativo de que seus atributos mineralógicos podem ter este comportamento sendo recomendado utilizar a simulação estocástica SSG para a caracterização espacial confirmando a hipótese de Yamamoto Deste modo, é essencial testar outros algoritmos e técnicas que incorporem qualidade das informações geradas pela inferência espacial, conforme já reportado por Herbst et al (2010) e Siqueira et al (2010). Esta afirmação foi comprovada por Silva Júnior et al (2012b) em que a combinação da geoestatística com análise, juntamente com modelos de paisagem, é eficiente na caracterização espacial de atributos dos solos.…”

Section: Figura 1 Pontos De Amostragem (•) Em Malha Regularunclassified

Métodos geoestatísticos na modelagem espacial do diâmetro médio do cristal da goethita

Silva

Pereira

Camargo

et al. 2013

Rev. bras. eng. agríc. ambient.

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RESUMOUma das necessidades da agricultura de precisão é avaliar a qualidade dos mapas dos atributos dos solos. Neste sentido, o presente trabalho objetivou avaliar o desempenho dos métodos geoestatísticos: krigagem ordinária e simulação sequencial gaussiana na predição espacial do diâmetro médio do cristal da goethita com 121 pontos amostrados em uma malha de 1 ha com espaçamentos regulares de 10 em 10 m. Após a análise textural e da concentração dos óxidos de ferro, calcularam-se os valores do diâmetro médio do cristal da goethita os quais foram analisados pela estatística descritiva e geoestatística; em seguida, foram utilizadas a krigagem ordinária e a simulação sequencial gaussiana. Com os resultados avaliou-se qual foi o método mais fiel para reproduzir as estatísticas, a função de densidade de probabilidade acumulada condicional e a estatística epsilon ε y da amostra. As estimativas E-Type foram semelhantes à krigagem ordinária devido à minimização da variância. No entanto, a krigagem deixa de apresentar, em locais específicos, o grau de cristalinidade da goethita enquanto o mapa E-Type indicou que a simulação sequencial gaussiana deve ser utilizada ao invés de mapas de krigagem. Os mapas E-type devem ser preferíveis por apresentar melhor desempenho na modelagem.Palavras-chave: agricultura de precisão, krigagem ordinária, simulação sequencial gaussiana, pedometria Geostatistical methods in spatial modelling of the middle diameter of the goethite crystal ABSTRACT In precision agriculture it is necessary to assess the quality of the maps of soil attributes. This paper aimed to evaluate the performance of geostatistical methods: ordinary kriging and sequential Gaussian simulation on spatial prediction of mean diameter of the goethite crystal in a regular grid with 121 points collected in a grid of 1 ha with regular spacing of 10 to 10 m. After the particle size and concentration analysis of iron oxides the values of the mean diameter of the goethite crystal were calculated. These were analysed by descriptive statistics and geostatistics, ordinary kriging and sequential Gaussian simulation was used for production of maps. With the results which evaluated the method is more faithful to make statistics, the cumulative probability density function conditional epsilon statistics ε y . E-Type estimates were similar to ordinary kriging, due to the minimization of the variance. However, the ordinary kriging did not perform well in specific locations for crystallinity of goethite, while the E-Type map by sequential Gaussian simulation should be used instead of kriging maps. The E-type maps should be prefered as they present better performance in modeling.

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The use of landforms to predict the variability of soil and orange attributes

Cited by 89 publications

References 70 publications

Spatial relationships between soil attributes and corn yield in no-tillage system

Spatial relationships between soil attributes and corn yield in no-tillage system

Iron oxides and quality of organic matter in sugarcane harvesting systems

Métodos geoestatísticos na modelagem espacial do diâmetro médio do cristal da goethita

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