998 resultados para Soil classification


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Heavy metals have been accumulating in Brazilian soils, due to natural processes, such as atmospheric deposition, or human industrial activities. For certain heavy metals, when in high concentrations in the soil, there is no specific extractant to determine the availability of these elements in the soil. The objective of the present study was to evaluate the availability of Cd, Cu, Fe, Mn, Pb and Zn for rice and soybeans, using different chemical extractants. In this study we used seven soil samples with different levels of contamination, in completely randomized experimental design with four replications. We determined the available concentrations of Cd, Cu, Fe, Mn, Pb and Zn extracted by Mehlich-1, HCl 0.1 mol L-1, DTPA, and organic acid extractants and the contents in rice and soybeans, which extracts were analyzed by ICP-OES. It was observed that Mehlich-1, HCl 0.1 mol L-1 and DTPA extractants were effective to assess the availability of Cd, Cu, Pb and Zn for rice and soybeans. However, the same was not observed for the organic acid extractant.

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The aim of the present study was to evaluate water consumption, use efficiency and yield components of sunflower variety Embrapa 122 V/2000 cultivated in two types of soil (Fluvissol and Haplic Luvisol) subjected to increasing doses of cattle manure. The experiment was carried out in a greenhouse at Universidade Estadual da Paraíba. The experimental design was completely randomized in a factorial scheme. The irrigation was performed every other day, replacing the water absorbed by the plants. The water consumption and the use efficiency were evaluated, being the use efficiency determined by the ratio of the total dry mass of sunflower and the amount of water used to produce it in each treatment. Plants were harvested at 95 days after sowing when the following parameters were evaluated: number of seeds per plant, weight of seeds per plant, weight of 1000 seeds and the outer diameter of the capitulum (head). The results showed that the sunflower was positively affected by cattle manure application, increasing the production components and the water use efficiency, regardless of the type of soil. Excepting for the 1000 seeds weight and the water use efficiency, the type of soil affected significantly the water use, the number and weight of seeds per plant. The plants cultivated in Haplic Luvisol had a better performance.

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Forest cover of the Maringá municipality, located in northern Parana State, was mapped in this study. Mapping was carried out by using high-resolution HRC sensor imagery and medium resolution CCD sensor imagery from the CBERS satellite. Images were georeferenced and forest vegetation patches (TOFs - trees outside forests) were classified using two methods of digital classification: reflectance-based or the digital number of each pixel, and object-oriented. The areas of each polygon were calculated, which allowed each polygon to be segregated into size classes. Thematic maps were built from the resulting polygon size classes and summary statistics generated from each size class for each area. It was found that most forest fragments in Maringá were smaller than 500 m². There was also a difference of 58.44% in the amount of vegetation between the high-resolution imagery and medium resolution imagery due to the distinct spatial resolution of the sensors. It was concluded that high-resolution geotechnology is essential to provide reliable information on urban greens and forest cover under highly human-perturbed landscapes.

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The socioeconomic importance of sugar cane in Brazil is unquestionable because it is the raw material for the production of ethanol and sugar. The accurate spatial intervention in the management of the crop, resulting zones of soil management, increases productivity as well as its agricultural yields. The spatial and Person's correlations between sugarcane attributes and physico-chemical attributes of a Typic Tropustalf were studied in the growing season of 2009, in Suzanápolis, State of São Paulo, Brazil (20°28'10'' S lat.; 50°49'20'' W long.), in order to obtain the one that best correlates with agricultural productivity. Thus, the geostatistical grid with 120 sampling points was installed to soil and data collection in a plot of 14.6 ha with second crop sugarcane. Due to their substantial and excellent linear and spatial correlations with the productivity of the sugarcane, the population of plants and the organic matter content of the soil, by evidencing substantial correlations, linear and spatial, with the productivity of sugarcane, were indicators of management zones strongly attached to such productivity.

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Heavy metals can accumulate in soil and cause phytotoxicity in plants with some specific symptoms. The present study evaluated the specific symptoms on rice and soybeans plants caused by excess of heavy metals in soil. Rice and soybean were grown in pots containing soil with different levels of heavy metals. A completely randomized design was used, with four replications, using two crop species and seven sample soils with different contamination levels. Rice and soybean exhibited different responses to the high concentrations of heavy metals in the soil. Rice plants accumulated higher Cu, Mn, Pb and Zn concentrations and were more sensitive to high concentrations of these elements in the soil, absorbing them more easily compared to the soybean plants. However, high available Zn concentrations in the soil caused phytotoxicity symptoms in rice and soybean, mainly chlorosis and inhibited plant growth. Further, high Zn concentrations in the soil reduced the Fe concentration in the shoots of soybean and rice plants to levels considered deficient.

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Studies on the use of silicate correctives in agriculture show that they have great potential to improve soil chemical characteristics, however, little information is available on the reactivity rates of their particle-size fractions. This study investigated whether the reactivity rates obtained experimentally could be considered in the calculation of ECC (effective calcium carbonate) for soil liming, promoting adequate development of alfalfa plants. Six treatments were evaluated in the experiment, consisting of two slag types applied in two rates. The experimental ECC was used to calculate one of the rates and the ECC determined in the laboratory was used to calculate the other. Rates of limestone and wollastonite were based on the ECC determined in laboratory. The rates of each soil acidity corretive were calculated to increase the base saturation to 80%. The treatments were applied to a Rhodic Hapludox and an Alfisol Ferrudalfs. The methods for ECC determination established for lime can be applied to steel slag. The application of slag corrected soil acidity with consequent accumulation of Ca, P, and Si in alfalfa, favoring DM production.

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The use of cover crops in no-tillage systems (NTS) can significantly improve the soil's fertility. Thus, a study was performed to evaluate changes in chemical properties of soil caused by cover crops in a no-tillage system. The field experiment consisted of the following crop rotation: cover crops/rice/cover crops/rice. The experimental design was in randomized blocks with three replications. Treatments consisted of four cover crops (Brachiaria brizantha(Hochst. ex A. Rich.) Stapf. cv. Marandu, Brachiaria ruziziensis R. Germ. and C.M. Evrard, Panicum maximum Jacq. cv. Colonião, and Pennisetum glaucum(L.) R. Br. cv. BN-2) and fallow (control treatment). Soil samples were collected at the beginning of the summer crop in Oct 2007, Oct 2008 and Oct 2009 at 0-5 cm soil depth. The use of cover crops provided for a significant increase in the level of nutrients, soil organic matter, cation exchange capacity, and base saturation in the soil. Soil fertility improved from the first to second year with the growing of cover crops. The soil under cover crops P. glaucum, B. ruziziensis, and B. brizantha showed higher fertility than the area under fallow.

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ABSTRACT The objective of this work was to study the distribution of values of the coefficient of variation (CV) in the experiments of papaya crop (Carica papaya L.) by proposing ranges to guide researchers in their evaluation for different characters in the field. The data used in this study were obtained by bibliographical review in Brazilian journals, dissertations and thesis. This study considered the following characters: diameter of the stalk, insertion height of the first fruit, plant height, number of fruits per plant, fruit biomass, fruit length, equatorial diameter of the fruit, pulp thickness, fruit firmness, soluble solids and internal cavity diameter, from which, value ranges were obtained for the CV values for each character, based on the methodology proposed by Garcia, Costa and by the standard classification of Pimentel-Gomes. The results obtained in this study indicated that ranges of CV values were different among various characters, presenting a large variation, which justifies the necessity of using specific evaluation range for each character. In addition, the use of classification ranges obtained from methodology of Costa is recommended.

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ABSTRACT Soybean cultivation is increasing rapidly in the region of Alto Vale do Itajaí, State of Santa Catarina, where there is a predominance of silt soils. The objective of this work was to evaluate the content of primary macronutrients in shoots and shoot and root vegetative growth of soybean (Glicine max L. Merrill) grown in a silt-loam soil under different compactation densities and moisture levels. A randomized block design in a 4x4 factorial arrangement was used, with four compactation densities: 1.00; 1.20; 1.40 and 1.60 Mg m-3, and four soil moisture levels: 0.130; 0.160; 0.190 and 0.220 kg kg-1 and four replications. Each pot consisted of the overlapping of three 150-mm PVC rings, where soil was maintained in the higher and lower part of the pot with a density of 1.00 Mg m-3 and in the intermediate ring, the compactation densities were increased. Values of soil density higher than 120 Mg m-3 negatively affected N, P and K uptake by soybean plants, as well as the plant mass of the shoots and roots. The higher levels of soil moisture reduced the compaction effect and promoted better absorption of P and K.

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Urban regeneration is more and more a “universal issue” and a crucial factor in the new trends of urban planning. It is no longer only an area of study and research; it became part of new urban and housing policies. Urban regeneration involves complex decisions as a consequence of the multiple dimensions of the problems that include special technical requirements, safety concerns, socio-economic, environmental, aesthetic, and political impacts, among others. This multi-dimensional nature of urban regeneration projects and their large capital investments justify the development and use of state-of-the-art decision support methodologies to assist decision makers. This research focuses on the development of a multi-attribute approach for the evaluation of building conservation status in urban regeneration projects, thus supporting decision makers in their analysis of the problem and in the definition of strategies and priorities of intervention. The methods presented can be embedded into a Geographical Information System for visualization of results. A real-world case study was used to test the methodology, whose results are also presented.

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Low noise surfaces have been increasingly considered as a viable and cost-effective alternative to acoustical barriers. However, road planners and administrators frequently lack information on the correlation between the type of road surface and the resulting noise emission profile. To address this problem, a method to identify and classify different types of road pavements was developed, whereby near field road noise is analyzed using statistical learning methods. The vehicle rolling sound signal near the tires and close to the road surface was acquired by two microphones in a special arrangement which implements the Close-Proximity method. A set of features, characterizing the properties of the road pavement, was extracted from the corresponding sound profiles. A feature selection method was used to automatically select those that are most relevant in predicting the type of pavement, while reducing the computational cost. A set of different types of road pavement segments were tested and the performance of the classifier was evaluated. Results of pavement classification performed during a road journey are presented on a map, together with geographical data. This procedure leads to a considerable improvement in the quality of road pavement noise data, thereby increasing the accuracy of road traffic noise prediction models.

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INTRODUCTION: The correct identification of the underlying cause of death and its precise assignment to a code from the International Classification of Diseases are important issues to achieve accurate and universally comparable mortality statistics These factors, among other ones, led to the development of computer software programs in order to automatically identify the underlying cause of death. OBJECTIVE: This work was conceived to compare the underlying causes of death processed respectively by the Automated Classification of Medical Entities (ACME) and the "Sistema de Seleção de Causa Básica de Morte" (SCB) programs. MATERIAL AND METHOD: The comparative evaluation of the underlying causes of death processed respectively by ACME and SCB systems was performed using the input data file for the ACME system that included deaths which occurred in the State of S. Paulo from June to December 1993, totalling 129,104 records of the corresponding death certificates. The differences between underlying causes selected by ACME and SCB systems verified in the month of June, when considered as SCB errors, were used to correct and improve SCB processing logic and its decision tables. RESULTS: The processing of the underlying causes of death by the ACME and SCB systems resulted in 3,278 differences, that were analysed and ascribed to lack of answer to dialogue boxes during processing, to deaths due to human immunodeficiency virus [HIV] disease for which there was no specific provision in any of the systems, to coding and/or keying errors and to actual problems. The detailed analysis of these latter disclosed that the majority of the underlying causes of death processed by the SCB system were correct and that different interpretations were given to the mortality coding rules by each system, that some particular problems could not be explained with the available documentation and that a smaller proportion of problems were identified as SCB errors. CONCLUSION: These results, disclosing a very low and insignificant number of actual problems, guarantees the use of the version of the SCB system for the Ninth Revision of the International Classification of Diseases and assures the continuity of the work which is being undertaken for the Tenth Revision version.

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O documento em anexo encontra-se na versão post-print (versão corrigida pelo editor).

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This paper presents an integrated system for vehicle classification. This system aims to classify vehicles using different approaches: 1) based on the height of the first axle and_the number of axles; 2) based on volumetric measurements and; 3) based on features extracted from the captured image of the vehicle. The system uses a laser sensor for measurements and a set of image analysis algorithms to compute some visual features. By combining different classification methods, it is shown that the system improves its accuracy and robustness, enabling its usage in more difficult environments satisfying the proposed requirements established by the Portuguese motorway contractor BRISA.

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In music genre classification, most approaches rely on statistical characteristics of low-level features computed on short audio frames. In these methods, it is implicitly considered that frames carry equally relevant information loads and that either individual frames, or distributions thereof, somehow capture the specificities of each genre. In this paper we study the representation space defined by short-term audio features with respect to class boundaries, and compare different processing techniques to partition this space. These partitions are evaluated in terms of accuracy on two genre classification tasks, with several types of classifiers. Experiments show that a randomized and unsupervised partition of the space, used in conjunction with a Markov Model classifier lead to accuracies comparable to the state of the art. We also show that unsupervised partitions of the space tend to create less hubs.