Planejamento agrícola e implantação de sistema de cultivo de cana-de-açúcar com auxílio de técnicas geoestatísticas

Sugarcane is one of the most important crops of the Brazilian agribusiness and this importance justifies the use of techniques that allow the implementation of cultivation systems capable of reducing the variability of soil characteristics and the establishment of efficient agricultural planning. The aim of the present work was the planning and implementation of cultivation systems for sugarcane using geostatistical techniques, in the Pereira Barreto region, SP. An area of 505 ha was mapped using the global positioning system (GPS) and a Digital Elevation Model was elaborated (MDE). Soil samples were collected for 0-0.25 m depth, in each 7 ha, for their chemical attributes and texture characterization. Data were analyzed by descriptive statistics and geostatistics. The determination of the spatial distribution of soil granulometric and chemical attributes allowed the allocation of the studied sugarcane varieties according to soil fertility and clay content. The kriging maps of soil granulometric and chemical attributes brought useful information to the establishment of production environments with different soil and crop managements. The identification of different environments by means of geostatistical techniques allowed the precise planning of the sugarcane cultivation, as well as the adequacy of fertilization practices and the allocation of suitable sugarcane varieties adapted to the conditions imposed by differences in the soil attributes.

Influência das superfícies geomórficas na distribuição espacial dos atributos do solo em área sob cultivo de cana-de-açúcar

Variations in soil attributes occur based on relief forms and parent material. The objective of this research was to study the influences of geomorphic surfaces on the spatial distribution of soil attributes in a sugarcane cultivation area. First, 530,67 hectares were mapped by using a Global Positioning System. Then, a Digital Elevation Model was developed and geomorphic surfaces were identified and delimited, according to topographic and stratigraphic criteria based on detailed field investigations. Soil samples were collected every 7 ha, at 0.0-0.25 m and 0.80-1.00 m depths, totalizing 134 samples. Texture, Ca, K, Mg, SB, CEC, V%, pH, and OMS analyses were carried out as well as descriptive statistics and geostatistics analysis. It was concluded that the geostatistic techniques and digital elevation model helped to notice that soil attributes presented limits close to the geomorphic surfaces ones.

Variabilidade temporal e mapeamento dos dados climáticos de Botucatu-SP

O trabalho teve objetivo estudar a variabilidade temporal da temperatura do ar, precipitação pluviométrica e umidade relativa do ar na cidade de Botucatu-SP, Brasil, utilizando técnicas geoestatísticas. Os dados de precipitação pluviométrica, temperatura do ar e umidade relativa do ar utilizados no presente estudo são provenientes da Estação Meteorológica da Fazenda Lageado, da Faculdade de Ciências Agronômicas-UNESP. As observações foram realizadas no período de 1988 a 2007, referem-se ao total mensal de precipitação pluvial expressa em altura de lâmina d'água (mm), médias mensais de temperatura em ºC e umidade relativa em %. Os dados foram avaliados por meio da estatística clássica e geoestatística. As variáveis climáticas tiveram sua dependência verificada por variogramas, apresentando dependência temporal maior que 76%. A série temporal de umidade relativa do ar foi a que apresentou maior alcance (8,67 meses) e, conseqüentemente, maior estabilidade climática. O conhecimento da distribuição temporal das variáveis climáticas é importante para o estudo e realização do zoneamento agroclimático, bem como para o dimensionamento do sistema de irrigação das culturas.

Métodos de interpolação para estimar o ph em solo sob dois manejos de café Arábica

There are many methods used to estimate values in places no sampled for construction of contours maps. The aim of this study was to use the methods of interpolation kriging, inverse of the square of the distance and polynomial in the representation of the spatial variability of the pH of the soil in the organic and conventional management in the culture of the coffee plantation. For that, irregular meshes were built for soil sampling in the depth of 0-0,10 meters, totaling 40 points sampling in each area. For gauging of the interpolation methods they were solitary 10% of the total of points, for each area. Initially, the data were appraised through the classic statistics (descriptive and exploratory) and spatial analysis. The method inverse square of the distance and kriging has low error in estimating dados. The method of kriging presented low variation around the average in different managements.

The effects of soil pollution and its relation with morbidity in shoreline areas

Soil and subsoil pollution is not only significant in terms of environmental loss, but also a matter of environmental and public health. Solid, liquid and gaseous residues are the major soil contamination agents. They originate from urban conglomerates and industrial areas in which it is impossible to emphasize the chemical, petrochemical and textile industry; thermoelectric, mining, and ironmaster activities. The contamination process can thus be defined as a compound addition to soil, from what qualitative and or quantitative manners can modify soil's natural characteristics and use, producing baneful and deteriorative effects on human health. Studies have shown that human exposition to high concentration of some heavy metals found on soil can cause serious health problems, such as pulmonary or kidney complications, liver and nervous system harm, allergy, and the chronic exposition that leads to death. The present study searches for the correlation among soil contamination, done through a geochemical baseline survey of an industrial contamination area on the shoreline of Sao Paulo state. The study will be conducted by spatial analysis using Geographical Information Systems for mapping and regression analysis. The used data are 123 soil samples of percentage concentration of heavy metals. They were sampled and spatially distributed by geostatistics methods. To verify if there is a relation between heavy metals soil pollution and morbidity an executed correlation and regression analysis will be done using the pollution registers as the independent variables and morbidity as dependable variables. It is expected, by the end of the study, to identify the areas relation between heavy metals soil pollution and morbidity, moreover to be able to provide assistance in terms of new methodologies that could facilitate soil pollution control programs and public health planning. © 2010 WIT Press.

Análise espacial de nutrientes e produção de alface cultivada em ambiente protegido

The objective of this work was to study spatial variability of some chemical soil attributes and lettuce production (total shoot fresh matter mass - MF; commercial shoot fresh matter mass - MFC; commercial shoot dry matter mass - MCS; and head commercial diameter - DCC) offering subsidies to the protected environment mapping in nutrients management areas in lettuce culture aiming for a higher productivity with application of fertilizers. The experiment was conducted in a protective environment (greenhouse) with lettuce irrigated by drip irrigation and sampling grid with 152 points. The special dependence analysis, determined by the variogram, was obtained with the aid of the GS+ Program. Considering the need for crop nutrients through the map obtained for element P (phosphorus) it was possible to establish two distinct areas for the application of this element in plantation fertilization. Through the lettuce yield maps obtained with MFC and DCC attributes was difficult to establish distinct areas for its management with data observed in only one crop cycle. Krigagem has proved useful for mapping the attributes studied.

Variabilidade espacial de atributos químicos do solo cultivado com café arábica (Coffea arabica L.) sob diferentes manejos

The objective of this work was to assess the spatial variability of the chemical attributes of two coffee areas, managed in conventional and organic crop systems, and to calculate the percent of variation between them. In each area, a 40-point-mesh was sampled at 0-0.10 m and 0.10-0.20 m layers, within the crown projection, for pH, SB, K, P, Ca and Mg analysis. The data were analyzed through descriptive statistics and geostatistics. From the soil chemical attributes map, the percent of variation between the systems' chemical attributes was determined by GIS algebraic operations. The results show that the soil chemical attributes present a spatial dependence in both systems and layers. Analysis of the soil chemical attributes showed less spatial variability in the organic system, in relation to the conventional, indicating homogeneous zones for different fertilizer applications. The percent of variation of the chemical attributes in the conventional system, in relation to the organic, at 0-0.10 m and 0.10-0.20m layers are 54.80% and 35.61%, respectively.

Delimitação do Embasamento da Bacia de Taubat

The aim of this study is to define the basement map of the Taubaté Basin applying geostatistics to seismic, gravimetric and deep wells data. The study consisted of the interpretation of eleven seismic sections obtained in the central and northeastern portions of the basin. The altitude of the basement and the distribution of faults was determined based on these sections. New information was obtained from 79 wells located mainly in the regions of São José dos Campos and Jacareí. The method of kriging with an external drift was applied, using seismic and well data as the main variables and the gravimetric map as the secondary variable. The basement contour map obtained has a strong correlation with the main faults. It was possible to obtain a better resolution in the region of São José dos Campos and in the northeast area, where the vast majority of wells are located.

Modelo agrometeorológico na estimativa da produtividade de duas variedades de café arábica considerando a variabilidade espacial

The purpose of this study was to estimate the varieties of coffee Arabic Catucáand Catuaí productivity, in Zona da Mata, Minas Gerais, through agrometeorological mathematical models, considering the spatial variability of productivity in the area. The samplings were georrefered building an irregular grid, totalizing 50 samplings per area. After that, geostatic analysis was made to quantify spatial dependence degree of the real values and the estimated productivity. According to the classification, the models superestimated the productivity for the two varieties.

Suscetibilidade magnética na identificação de compartimentos da paisagem em uma vertente

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Variabilidade espacial na produção da alface em ambiente protegido

Este artigo mostra a dinâmica da água após ser aplicada sobre a superfície de um solo cultivado com alface, num sistema fechado de um ambiente protegido. A aplicação de água se deu por meio de um sistema de irrigação por gotejamento, com o CUD ( Coeficiente de Uniformidade de Distribuição ) igual a 97,06 %, o que garantiu uma ótima uniformidade de distribuição, desconsiderando como possíveis causas das variações de umidade do solo, a aplicação de lâminas variadas. Fazendo uso de técnicas de geoestatística, interpolando sessenta pontos amostrais de evaporação, umidade do solo e produtividade da alface, com as mesmas sessenta coordenadas para os três atributos, verificou-se que a umidade do solo, mesmo momentos após a irrigação, não permanece uniforme ao longo do sistema de irrigação, constatando-se que a evaporação local exerce influência de forma predominante sobre a dinâmica da água na superfície do solo. Concluiu-se que as regiões no interior da estufa de maiores evaporações, foram as de maiores variações de umidade do solo e na produção de massa verde da alface.

Espacialização das estimativas de contaminação de águas subterrâneas por Tebuthiuron

Improper use of pesticides can lead to significant environmental impacts such as, contamination of environmental compartments, being the aquatic compartments the most vulnerable. In this context, the spatialization of pesticides concentrations estimative in groundwater provides important insights for decision making in managing and monitoring pesticides use. This study aimed to spatialize estimatives of groundwater contamination by Tebuthiuron, from different irrigation depths in the Rio Pardo basin, Pardinho-SP, Brazil. The simulations were performed using the ARAquá computer system, considering 0mm, 200 mm and 400 mm annual irrigation depths. Geostatistical techniques were used to obtain the spatial distribution of the simulated estimative. Tebuthiuron maps estimating concentration in groundwater were obtained by Kriging interpolation method, and indicated the areas with high potential for groundwater contamination. Considering all the simulations, it was concluded that there was no risk of groundwater contamination by Tebuthiuron in the study area.

Submerged macrophytes height estimation by echosounder data sample

Traditional methods of submerged aquatic vegetation (SAV) survey last long and then, they are high cost. Optical remote sensing is an alternative, but it has some limitations in the aquatic environment. The use of echosounder techniques is efficient to detect submerged targets. Therefore, the aim of this study is to evaluate different kinds of interpolation approach applied on SAV sample data collected by echosounder. This study case was performed in a region of Uberaba River - Brazil. The interpolation methods evaluated in this work follow: Nearest Neighbor, Weighted Average, Triangular Irregular Network (TIN) and ordinary kriging. Better results were carried out with kriging interpolation. Thus, it is recommend the use of geostatistics for spatial inference of SAV from sample data surveyed with echosounder techniques. © 2012 IEEE.

Delineation of specific management areas for coffee cultivation based on the soil-relief relationship and numerical classification

Predicting and mapping productivity areas allows crop producers to improve their planning of agricultural activities. The primary aims of this work were the identification and mapping of specific management areas allowing coffee bean quality to be predicted from soil attributes and their relationships to relief. The study area was located in the Southeast of the Minas Gerais state, Brazil. A grid containing a total of 145 uniformly spaced nodes 50 m apart was established over an area of 31. 7 ha from which samples were collected at depths of 0. 00-0. 20 m in order to determine physical and chemical attributes of the soil. These data were analysed in conjunction with plant attributes including production, proportion of beans retained by different sieves and drink quality. The results of principal component analysis (PCA) in combination with geostatistical data showed the attributes clay content and available iron to be the best choices for identifying four crop production environments. Environment A, which exhibited high clay and available iron contents, and low pH and base saturation, was that providing the highest yield (30. 4l ha-1) and best coffee beverage quality (61 sacks ha-1). Based on the results, we believe that multivariate analysis, geostatistics and the soil-relief relationships contained in the digital elevation model (DEM) can be effectively used in combination for the hybrid mapping of areas of varying suitability for coffee production. © 2012 Springer Science+Business Media New York.

Quantification of uncertainties associated with space-time estimates of short-term soil CO2 emissions in a sugar cane area

The characterization of soil CO2 emissions (FCO2) is important for the study of the global carbon cycle. This phenomenon presents great variability in space and time, a characteristic that makes attempts at modeling and forecasting FCO2 challenging. Although spatial estimates have been performed in several studies, the association of these estimates with the uncertainties inherent in the estimation procedures is not considered. This study aimed to evaluate the local, spatial, local-temporal and spatial-temporal uncertainties of short-term FCO2 after harvest period in a sugar cane area. The FCO2 was featured in a sampling grid of 60m×60m containing 127 points with minimum separation distances from 0.5 to 10m between points. The FCO2 was evaluated 7 times within a total period of 10 days. The variability of FCO2 was described by descriptive statistics and variogram modeling. To calculate the uncertainties, 300 realizations made by sequential Gaussian simulation were considered. Local uncertainties were evaluated using the probability values exceeding certain critical thresholds, while the spatial uncertainties considering the probability of regions with high probability values together exceed the adopted limits. Using the daily uncertainties, the local-spatial and spatial-temporal uncertainty (Ftemp) was obtained. The daily and mean emissions showed a variability structure that was described by spherical and Gaussian models. The differences between the daily maps were related to variations in the magnitude of FCO2, covering mean values ranging from 1.28±0.11μmolm-2s-1 (F197) to 1.82±0.07μmolm-2s-1 (F195). The Ftemp showed low spatial uncertainty coupled with high local uncertainty estimates. The average emission showed great spatial uncertainty of the simulated values. The evaluation of uncertainties associated with the knowledge of temporal and spatial variability is an important tool for understanding many phenomena over time, such as the quantification of greenhouse gases or the identification of areas with high crop productivity. © 2013 Elsevier B.V.