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

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Crop type influences soil aggregation and organic matter under no-tillage

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Compositional analysis for an unbiased measure of soil aggregation

Soil aggregation is an index of soil structure measured by mean weight diameter (MWD) or scaling factors often interpreted as fragmentation fractal dimensions (D-f). However, the MWD provides a biased estimate of soil aggregation due to spurious correlations among aggregate-size fractions and scale-dependency. The scale-invariant D-f is based on weak assumptions to allow particle counts and sensitive to the selection of the fractal domain, and may frequently exceed a value of 3, implying that D-f is a biased estimate of aggregation. Aggregation indices based on mass may be computed without bias using compositional analysis techniques. Our objective was to elaborate compositional indices of soil aggregation and to compare them to MWD and D-f using a published dataset describing the effect of 7 cropping systems on aggregation. Six aggregate-size fractions were arranged into a sequence of D-1 balances of building blocks that portray the process of soil aggregation. Isometric log-ratios (ilrs) are scale-invariant and orthogonal log contrasts or balances that possess the Euclidean geometry necessary to compute a distance between any two aggregation states, known as the Aitchison distance (A(x,y)). Close correlations (r>0.98) were observed between MWD, D-f, and the ilr when contrasting large and small aggregate sizes. Several unbiased embedded ilrs can characterize the heterogeneous nature of soil aggregates and be related to soil properties or functions. Soil bulk density and penetrater resistance were closely related to A(x,y) with reference to bare fallow. The A(x,y) is easy to implement as unbiased index of soil aggregation using standard sieving methods and may allow comparisons between studies. (C) 2012 Elsevier B.V. All rights reserved.

Discrimination of geomorphic surfaces with multivariate analysis of soil attributes in sandstone - basalt lithosequence

O conceito de superfície geomórfica permite uma interligação entre os diferentes ramos da ciência do solo, tais como geologia, geomorfologia e pedologia. Esta associação favorece a compreensão da distribuição espacial dos solos na paisagem, e torna possível compreender o comportamento dos atributos do solo, que estão principalmente relacionadas com a estratigrafia e formas do relevo. Assim, este estudo visa à aplicação da estatística multivariada para categorizar superfícies geomórficas em uma litossequência arenito-basalto, de modo a fornecer uma base para a avaliação do solo em áreas afins. A área de estudo está localizada no município de Pereira Barreto, São Paulo, Brasil. A área escolhida possui 530 hectares, onde foram localizadas e mapeadas três superfícies geomórficas (I, II e III). Na área, 134 amostras foram coletadas nas profundidades de 0,0-0,2 m e 0,8-1,0 m, foram determinados os conteúdos de areia, silte e argila, pH em CaCl2, conteúdo de MO, P, Ca, Mg, K, Al e H+Al. Com base nos resultados, foram realizadas a análise univariada e multivariada de variância, clusters e principal componente, a fim de comparar as três superfícies geomórficas. A análise estatística univariada dos atributos do solo não foi eficiente na identificação das três superfícies geomórficas. Utilizando-se os atributos físicos e químicos do solo, as técnicas estatísticas multivariada permitiram à separação dos três grupos de corpos naturais do solo que foram equivalentes as três superfícies geomórficas mapeadas. Estes resultados são interessantes, pois demonstram a viabilidade da utilização de classificação numérica das superfícies geomórficas para ajudar no mapeamento de solo.

Fuzzy Logic and Geostatistical Techniques for Spatialization of Soil Texture in Region with Rough Terrains

From the geotechnical standpoint, it is interesting to analyse the soil texture in regions with rough terrain due to its relation with the infiltration and runoff processes and, consequently, the effect on erosion processes. The purpose of this paper is to present a methodology that provides the soil texture spatialization by using Fuzzy logic and Geostatistic. The results were correlated with maps drawn specifically for the study area. The knowledge of the spatialization of soil properties, such as the texture, can be an important tool for land use planning in order to reduce the potential soil losses during rain seasons. (c) 2011 Published by Elsevier Ltd. Selection and peer-review under responsibility of Spatial Statistics 2011

Inter-relation between soybean yield and soil compaction under degraded pasture in Brazilian Savannah

As pastagens cultivadas do Cerrado brasileiro são responsáveis pela metade da produtividade da carne bovina destinada à alimentação da população, enquanto as culturas agrícolas o são pela terça parte de sua produtividade de grãos, desempenhando importante papel econômico-financeiro para o país. Dessa forma, no ano agrícola 2005/2006, na Fazenda de Ensino e Pesquisa da Faculdade de Engenharia de Ilha Solteira - FEIS/UNESP, foram estudadas a variabilidade e a dependência espacial entre atributos físicos do solo e a produtividade da soja, quando rotacionados após a pastagem degradada com Brachiaria, sobre um Latossolo Vermelho distroférrico. Também foram estudadas correlações lineares e espaciais entre esses atributos, apurando condições que proporcionassem aumento da produtividade agrícola. Para isso, na área com a referida pastagem instalou-se uma malha contendo 124 pontos amostrais, com espaçamentos de 10,0 x 10,0 e de 5,0 x 5,0 m entre eles, numa área total de 7.500 m². Dos pontos de vista linear e espacial, a elevada produtividade de grãos de soja pode ser explicada em razão do número de grãos por planta e da macroporosidade do solo. A alta variabilidade obtida na maioria dos atributos do solo denotou que a integração lavoura-pecuária é um sistema que proporciona heterogeneidade do ambiente físico do solo.

Soil profile, relief features and their relation to structure and distribution of Brazilian Atlantic rain forest trees

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Spatial and linear correlations between soil and corn

O conjunto de tecnologias aplicadas ao sistema de produção agrícola tem como características principais a verticalização da produtividade, diminuição de custos, melhoria nas características físicas, químicas e biológicas do solo para proporcionarem o crescimento sustentável do meio de produção. Desta forma, o trabalho teve como objetivo determinar a variabilidade e as correlações lineares e especiais entre os atributos da planta e do solo, visando selecionar um indicador da qualidade física do solo de boa representatividade para produção de forragem. No ano agrícola de 2006, na Fazenda Bonança, município de Pereira Barreto (SP), foram analisados a produtividade de forragem do milho outonal (FDM) em sistema plantio direto irrigado e os atributos físicos do solo, num Latossolo Vermelho distrófico. O objetivo foi estudar a variabilidade e as correlações lineares e espaciais entre os atributos da planta e os do solo, visando selecionar um indicador da qualidade física do solo de boa representatividade para a produtividade da forragem. Foi instalada a malha geoestatística, para coleta de dados do solo e planta, contendo 125 pontos amostrais, numa área de 2.500 m². Os atributos estudados, além de não terem variado aleatoriamente, apresentaram variabilidade dos dados entre baixa e muito alta e seguiram padrões espaciais bem definidos, com alcances entre 7,8 e 38,0 m. Por outro lado, a correlação linear entre os atributos da planta com o do solo foi baixa e extremamente significativa. Os pares Massa Seca de forragem versus Microporosidade e Diâmetro do colmo versus Densidade do Solo foram melhor correlacionados na camada de 0-0.10m, enquanto os outros pares - Massa Seca de Forragem versus Macroporosidade - e Porosidade Total - apresentaram correlação inversa para a mesma camada. Entretanto, do ponto de vista espacial, houve uma alta correlação inversa entre Massa Seca de Forragem com Microporosidade, de modo que a microporosidade na camada de 0-0.10m pode ser considerada um bom indicador de qualidade física do solo, tendo em vista a produção de forragem de milho.

Short-term temporal changes in the spatial variability model of CO2 emissions from a Brazilian bare soil

In this work, the spatial variability model of CO2 emissions and soil properties of a Brazilian bare soil were investigated. Carbon dioxide emissions were measured on three different days at contrasted soil temperature and soil moisture conditions, and soil properties were investigated at the same points where emissions were measured. One spatial variability model of soil CO2 emissions was found for each measurement day, and these models are similar to the ones of soil properties studied in an area of 100 x 100 m. (C) 2000 Elsevier B.V. Ltd. All rights reserved.

Correlation of properties of Brazilian Haplustalfs with magnetic susceptibility measurements

Magnetic susceptibility (chi, mass specific) is useful for easy indirect estimation of other soil properties at a low cost. The aim of this study was to assess the use of chi as measured with an analytical balance for predicting properties with a substantial influence on the management of Typic Haplustalfs in southern Brazil. To achieve this 48 topsoil samples were taken at the intersection points in a rectangular grid of 20 m x 20 m cells, with 38 of these used for calibration and 10 for validation in regression analyses. The obtained chi values were slightly higher than, and highly correlated (r = 0.970; P < 0.001) with those measured with a susceptibility meter. Highly significant (P < 0.001) correlations were also found between chi and other soil properties relevant to soil classification and management such as clay content (r = 0.68), cation exchange capacity (r = 0.62), P sorption capacity (r = 0.76) and haematite content (r = 0.82). Results from a principal component analysis of eight properties important for soil classification explained 11% of the variance in the data set. The good predictive ability of chi was consistent with current knowledge on the formation pathways for pedogenic ferrimagnets. In summary, chi, which can be readily measured with an analytical balance, has the potential for quantifying soil attributes and may therefore be used in pedotransfer functions.

Spatial and temporal variability of soil CO2 emission in a sugarcane area under green and slash-and-burn managements

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Nickel in a tropical soil treated with sewage sludge and cropped with maize in a long-term field study

Sewage sludge produced by the SABESP wastewater treatment plant (Companhia de Saneamento Básico do Estado de São Paulo), located in Barueri, SP, Brazil, may contain high contents of nickel (Ni), increasing the risk of application to agricultural soils. An experiment was carried out under field conditions in Jaboticabal, SP, Brazil, with the objective of evaluating the effects on soil properties and on maize plants of increasing rates of a sewage sludge rich in Ni that had been applied for 6 consecutive years. The experiment was located on a Typic Haplorthox soil, using an experimental design of randomized blocks with four treatments (rates of sewage sludge) and five replications. At the end of the experiment the accumulated amounts of sewage sludge applied were 0.0, 30.0, 60.0 and 67.5 t ha-1. Maize (Zea mays L.) was the test plant. Soil samples were collected 60 d after sowing at depths of 0-20 cm for Ni studies and from 0 to 10 cm and from 10 to 20 cm for urease studies. Sewage sludge did not cause toxicity or micronutrient deficiencies to maize plants and increased grain production. Soil Ni appeared to be associated with the most stable fractions of the soil organic matter and was protected against strong extracting solutions such as concentrated and hot HNO3 and HCl. Ni added to the soil by sewage sludge increased the metal concentration in the shoots, but not in the grain. The Mehlich 3 extractor was not efficient to evaluate Ni phytoavailability to maize plants. Soil urease activity was increased by sewage sludge only in the layer where the residue was applied. © 2006 Elsevier Ltd. All rights reserved.

Digital soil mapping: evaluation of sampling systems for soil surveys and refinement of soil maps at lower cost using legacy data

In soil surveys, several sampling systems can be used to define the most representative sites for sample collection and description of soil profiles. In recent years, the conditioned Latin hypercube sampling system has gained prominence for soil surveys. In Brazil, most of the soil maps are at small scales and in paper format, which hinders their refinement. The objectives of this work include: (i) to compare two sampling systems by conditioned Latin hypercube to map soil classes and soil properties; (II) to retrieve information from a detailed scale soil map of a pilot watershed for its refinement, comparing two data mining tools, and validation of the new soil map; and (III) to create and validate a soil map of a much larger and similar area from the extrapolation of information extracted from the existing soil map. Two sampling systems were created by conditioned Latin hypercube and by the cost-constrained conditioned Latin hypercube. At each prospection place, soil classification and measurement of the A horizon thickness were performed. Maps were generated and validated for each sampling system, comparing the efficiency of these methods. The conditioned Latin hypercube captured greater variability of soils and properties than the cost-constrained conditioned Latin hypercube, despite the former provided greater difficulty in field work. The conditioned Latin hypercube can capture greater soil variability and the cost-constrained conditioned Latin hypercube presents great potential for use in soil surveys, especially in areas of difficult access. From an existing detailed scale soil map of a pilot watershed, topographical information for each soil class was extracted from a Digital Elevation Model and its derivatives, by two data mining tools. Maps were generated using each tool. The more accurate of these tools was used for extrapolation of soil information for a much larger and similar area and the generated map was validated. It was possible to retrieve the existing soil map information and apply it on a larger area containing similar soil forming factors, at much low financial cost. The KnowledgeMiner tool for data mining, and ArcSIE, used to create the soil map, presented better results and enabled the use of existing soil map to extract soil information and its application in similar larger areas at reduced costs, which is especially important in development countries with limited financial resources for such activities, such as Brazil.

Magnetic susceptibility in the prediction of soil attributes in two sugarcane harvesting management systems

This study aimed to investigate the potential use of magnetic susceptibility (MS) as pedotransfer function to predict soil attributes under two sugarcane harvesting management systems. For each area of 1 ha (one with green sugarcane mechanized harvesting and other one with burnt sugarcane manual harvesting), 126 soil samples were collected and subjected to laboratory analysis to determine soil physical, chemical and mineralogical attributes and for measuring of MS. Data were submitted to descriptive statistics by calculating the mean and coefficient of variation. In order to compare the means in the different harvesting management systems it was carried out the Tukey test at a significance level of 5%. In order to investigate the correlation of the MS with other soil properties it was made the correlation test and aiming to assess how the MS contributes to the prediction of soil complex attributes it was made the multiple linear regressions. The results demonstrate that MS showed, in both sugarcane harvesting management systems, statistical correlation with chemical, physical and mineralogical soil attributes and it also showed potential to be used as pedotransfer function to predict attributes of the studied oxisol.

Optimization of the sampling scheme for maps of physical and chemical properties estimated by kriging

The sampling scheme is essential in the investigation of the spatial variability of soil properties in Soil Science studies. The high costs of sampling schemes optimized with additional sampling points for each physical and chemical soil property, prevent their use in precision agriculture. The purpose of this study was to obtain an optimal sampling scheme for physical and chemical property sets and investigate its effect on the quality of soil sampling. Soil was sampled on a 42-ha area, with 206 geo-referenced points arranged in a regular grid spaced 50 m from each other, in a depth range of 0.00-0.20 m. In order to obtain an optimal sampling scheme for every physical and chemical property, a sample grid, a medium-scale variogram and the extended Spatial Simulated Annealing (SSA) method were used to minimize kriging variance. The optimization procedure was validated by constructing maps of relative improvement comparing the sample configuration before and after the process. A greater concentration of recommended points in specific areas (NW-SE direction) was observed, which also reflects a greater estimate variance at these locations. The addition of optimal samples, for specific regions, increased the accuracy up to 2 % for chemical and 1 % for physical properties. The use of a sample grid and medium-scale variogram, as previous information for the conception of additional sampling schemes, was very promising to determine the locations of these additional points for all physical and chemical soil properties, enhancing the accuracy of kriging estimates of the physical-chemical properties.