53 resultados para ellipse fitting


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The soil P sorption capacity has been studied for many years, but little attention has been paid to the rate of this process, which is relevant in the planning of phosphate fertilization. The purpose of this experiment was to assess kinetics of P sorption in 12 representative soil profiles of the State of Paraíba (Brazil), select the best data fitting among four equations and relate these coefficients to the soil properties. Samples of 12 soils with wide diversity of physical, chemical and mineralogical properties were agitated in a horizontal shaker, with 10 mmo L-1 CaCl2 solution containing 6 and 60 mg L-1 P, for periods of 5, 15, 30, 45, 60, 90, 120, 420, 720, 1,020, and 1,440 min. After each shaking period, the P concentration in the equilibrium solution was measured and three equations were fitted based on the Freundlich equation and one based on the Elovich equation, to determine which soil had the highest sorption rate (kinetics) and which soil properties correlated to this rate. The kinetics of P sorption in soils with high maximum P adsorption capacity (MPAC) was fast for 30 min at the lower initial P concentration (6 mg L-1). No difference was observed between soils at the higher initial P concentration (60 mg L-1). The P adsorption kinetics were positively correlated with clay content, MPAC and the amount of Al extracted with dithionite-citrate-bicarbonate. The data fitted well to Freundlich-based equations equation, whose coefficients can be used to predict P adsorption rates in soils.

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The relationships between nutrient contents and indices of the Diagnosis and Recommendation Integrated System (DRIS) are a useful basis to determine appropriate ranges for the interpretation of leaf nutrient contents. The purpose of this study was to establish Beaufils ranges from statistical models of the relationship between foliar concentrations and DRIS indices, generated by two systems of DRIS norms - the F value and natural logarithm transformation - and assess the nutritional status of cotton plants, based on these Beaufils ranges. Yield data from plots (average acreage 100 ha) and foliar concentrations of macro and micronutrients of cotton (Gossypium hirsutum r. latifolium) plants, in the growing season 2004/2005, were stored in a database. The criterion to define the reference population consisted of plots with above-average yields + 0.5 standard deviation (over 4,575 kg ha-1 seed cotton yield). The best-fitting statistical model of the relationship between foliar nutrient concentrations and DRIS indices was linear, with R² > 0.8090, p < 0.01, except for N, with R² = 0.5987, p < 0.01. The two criteria were effective to diagnose the plant nutritional status. The diagnoses were not random, but based on the effectiveness of the chi-square-tested method. The agreement between the methods to assess the nutritional status was 92.59-100 %, except for S, with 74.07 % agreement.

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Digital information generates the possibility of a high degree of redundancy in the data available for fitting predictive models used for Digital Soil Mapping (DSM). Among these models, the Decision Tree (DT) technique has been increasingly applied due to its capacity of dealing with large datasets. The purpose of this study was to evaluate the impact of the data volume used to generate the DT models on the quality of soil maps. An area of 889.33 km² was chosen in the Northern region of the State of Rio Grande do Sul. The soil-landscape relationship was obtained from reambulation of the studied area and the alignment of the units in the 1:50,000 scale topographic mapping. Six predictive covariates linked to the factors soil formation, relief and organisms, together with data sets of 1, 3, 5, 10, 15, 20 and 25 % of the total data volume, were used to generate the predictive DT models in the data mining program Waikato Environment for Knowledge Analysis (WEKA). In this study, sample densities below 5 % resulted in models with lower power of capturing the complexity of the spatial distribution of the soil in the study area. The relation between the data volume to be handled and the predictive capacity of the models was best for samples between 5 and 15 %. For the models based on these sample densities, the collected field data indicated an accuracy of predictive mapping close to 70 %.

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The S-index was introduced in 2004 in a publication by A.R. Dexter. S was proposed as an indicator of soil physical quality. A critical value delimiting soils with rich and poor physical quality was proposed. At present, Brazil is world leader in citations of Dexter's publication. In this publication the S-theory is mathematically revisited and extended. It is shown that S is mathematically correlated to bulk density and total porosity. As an absolute indicator, the value of S alone has proven to be incapable of predicting soil physical quality. The critical value does not always hold under boundary conditions described in the literature. This is to be expected because S is a static parameter, therefore implicitly unable to describe dynamic processes. As a relative indicator of soil physical quality, the S-index has no additional value over bulk density or total porosity. Therefore, in the opinion of the author, the fact that bulk density or total porosity are much more easily determined than the water retention curve for obtaining S disqualifies S as an advantageous indicator of relative soil physical quality. Among the several equations available for the fitting of water retention curves, the Groenevelt-Grant equation is preferable for use with S since one of its parameters and S are linearly correlated. Since efforts in soil physics research have the purpose of describing dynamic processes, it is the author's opinion that these efforts should shift towards mechanistic soil physics as opposed to the search for empirical correlations like S which, at present, represents far more than its reasonable share of soil physics in Brazil.

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ABSTRACT Quantitative assessment of soil physical quality is of great importance for eco-environmental pollution and soil quality studies. In this paper, based on the S-theory, data from 16 collection sites in the Haihe River Basin in northern China were used, and the effects of soil particle size distribution and bulk density on three important indices of theS-theory were investigated on a regional scale. The relationships between unsaturated hydraulic conductivityKi at the inflection point and S values (S/hi) were also studied using two different types of fitting equations. The results showed that the polynomial equation was better than the linear equation for describing the relationships between -log Ki and -logS, and -log Kiand -log (S/hi)2; and clay content was the most important factor affecting the soil physical quality index (S). The variation in the S index according to soil clay content was able to be fitted using a double-linear-line approach, with decrease in the S index being much faster for clay content less than 20 %. In contrast, the bulk density index was found to be less important than clay content. The average S index was 0.077, indicating that soil physical quality in the Haihe River Basin was good.

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ABSTRACT Intrinsic equilibrium constants of 17 representative Brazilian Oxisols were estimated from potentiometric titration measuring the adsorption of H+ and OH− on amphoteric surfaces in suspensions of varying ionic strength. Equilibrium constants were fitted to two surface complexation models: diffuse layer and constant capacitance. The former was fitted by calculating total site concentration from curve fitting estimates and pH-extrapolation of the intrinsic equilibrium constants to the PZNPC (hand calculation), considering one and two reactive sites, and by the FITEQL software. The latter was fitted only by FITEQL, with one reactive site. Soil chemical and physical properties were correlated to the intrinsic equilibrium constants. Both surface complexation models satisfactorily fit our experimental data, but for results at low ionic strength, optimization did not converge in FITEQL. Data were incorporated in Visual MINTEQ and they provide a modeling system that can predict protonation-dissociation reactions in the soil surface under changing environmental conditions.

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ABSTRACT Diffuse reflectance spectroscopy (DRS) is a fast and cheap alternative for soil clay, but needs further investigation to assess the scope of application. The purpose of the study was to develop a linear regression model to predict clay content from DRS data, to classify the soils into three textural classes, similar to those defined by a regulation of the Brazilian Ministry of Agriculture, Livestock and Food Supply. The DRS data of 412 soil samples, from the 0.0-0.5 m layer, from different locations in the state of Rio Grande do Sul, Brazil, were measured at wavelengths of 350 to 2,500 nm in the laboratory. The fitting of the linear regression model developed to predict soil clay content from the DRS data was based on a R2 value of 0.74 and 0.75, with a RMSE of 7.82 and 8.51 % for the calibration and validation sets, respectively. Soil texture classification had an overall accuracy of 79.0 % (calibration) and 80.9 % (validation). The heterogeneity of soil samples affected the performance of the prediction models. Future studies should consider a previous classification of soil samples in different groups by soil type, parent material and/or sampling region.

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Dados hiperespectrais coletados no Brasil pelo sensor AVIRIS (Airborne Visible/Infrared Imaging Spectrometer) foram utilizados para a caracterização espectral de uma típica cena agropastoril e para testar o uso da técnica Spectral Feature Fitting (SFF) na identificação de minerais argilosos na imagem. Utilizou-se um modelo linear de mistura espectral, usando como membros de referência a vegetação verde e seca, a água, e os solos Nitossolo Vermelho, Latossolo Vermelho e Neossolo Quartzarênico órtico. Na identificação dos minerais, foram selecionados espectros de referência da biblioteca espectral do JPL/NASA. Os espectros dos pixels e das referências foram normalizados pelo método do contínuo espectral, entre 2.100 e 2.330 nm, e depois comparados quanto à similaridade com o uso da técnica SFF. A caulinita predomina na cena, cuja identificação remota é dependente do tipo de solo e das proporções dos componentes da cena no interior do pixels. Os melhores resultados foram obtidos em solos de reflectância intermediária a alta e em pixels com valor de abundância da fração solo superior a 70%. Isto ocorreu devido, respectivamente, à menor quantidade de substâncias opacas nestes solos e à redução nos pixels dos efeitos espectrais da lignina-celulose. Estes fatores tendem a mascarar as bandas de absorção das argilas.

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Aluminum (Al) toxicity is a major factor limiting barley growth in acid soils, and genotypes with adequate level of tolerance are needed for improving barley adaptation in Brazil. To study the inheritance of Al tolerance in Brazilian barleys, cultivars Antarctica 1, BR 1 and FM 404 were crossed to sensitive Kearney and PFC 8026, and intercrossed. Parental, F1, F2 and F6 generations were grown in nutrient solution containing 0.03, 0.05 and 0.07 mM of Al and classified for tolerance by the root tip hematoxylin staining assay. Tolerant by sensitive F2 progenies segregated three tolerant to one sensitive, fitting the 3:1 ratio expected for a single gene. The F6 populations segregated one tolerant to one sensitive also fitting a monogenic ratio. The F2 seedlings from crosses among tolerant genotypes scored the same as the parents. Since the population size used would allow detection of recombination as low as 7%, the complete absence of Al sensitive recombinants suggests that tolerance in these cultivars is most probably, controlled by the same gene. Thus, the potential for improving Al tolerance through recombination of these genotypes is very low and different gene sources should be evaluated.

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The objective of this work was to evaluate a generalized response function to the atmospheric CO2 concentration [f(CO2)] by the radiation use efficiency (RUE) in rice. Experimental data on RUE at different CO2 concentrations were collected from rice trials performed in several locations around the world. RUE data were then normalized, so that all RUE at current CO2 concentration were equal to 1. The response function was obtained by fitting normalized RUE versus CO2 concentration to a Morgan-Mercer-Flodin (MMF) function, and by using Marquardt's method to estimate the model coefficients. Goodness of fit was measured by the standard deviation of the estimated coefficients, the coefficient of determination (R²), and the root mean square error (RMSE). The f(CO2) describes a nonlinear sigmoidal response of RUE in rice, in function of the atmospheric CO2 concentration, which has an ecophysiological background, and, therefore, renders a robust function that can be easily coupled to rice simulation models, besides covering the range of CO2 emissions for the next generation of climate scenarios for the 21st century.

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The FTIR spectroscopy has been used to quantify the secondary structures of proteins, using amide I band (1600 - 1700 cm-1). The resolution enhancement methods have been used to resolve the individual components of this band that correlate to the secondary structure. In this paper we discuss the methods of derivative, Fourier deconvolution and fitting with simulated spectra. The results shows that they have serious problems and can be used only as a qualitative or semiquatitative method.

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Acid base properties of mixed species of the microalgae Spirulina were studied by potentiometric titration in medium of 0.01 and 0.10 mols L-1 NaNO3 at 25.0±0.10 C using modified Gran functions or nonlinear regression techniques for data fitting. The discrete site distribution model was used, permitting the characterization of five classes of ionizable sites in both ionic media. This fact suggests that the chemical heterogeneity of the ionizable sites on the cell surface plays a major role on the acid-base properties of the suspension in comparison to electrostatic effects due to charge-charge interactions. The total of ionizable sites were 1.75±0.10 and 1.86±0.20 mmolsg-1 in ionic media of 0.01 and 0.10 mols L-1 NaNO3, respectively. A major contribution of carboxylic groups was observed with an average 34 and 22% of ionizable sites being titrated with conditional pcKa of 4.0 and 5.4, respectively. The remaining 44% of ionizable sites were divided in three classes with averaged conditional pcKa of 6.9, 8.7 and 10.12, which may be assigned respectively to imidazolic, aminic, and phenolic functionalities.

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The present work purposes the development of an analytical method for amitriptyline determination in pharmaceutical formulations using FIA system. It was based on interaction of amitriplyline with sodium lauryl sulphate in acid medium (pH 2.5) resulting in the ion-pair formation turbidimetrically detected at 410 nm. The fitting regression equation for range curve from 2.0 x 10-3 up to 3.2 x 10-3 mol L-1 was found to be analytical signal = -2.7417 + 0.1538 [amitriptyline] (r = 0.99991) with a detection limit of 1.8 x 10-3 mol L-1. The precision assessed as relative standard deviation (n = 10) was found to be 2.40 and 1.94%, for the respective concentration of amitriplyline 2.0 x 10-3 and 3.2 x 10-3 mol L-1 and the sample throughout was 60 h-1. The accuracy of method was successfully assessed in pharmaceutical formulation after comparison with a reference analytical method.

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The barometric equation is revisited. Restrictions imposed for its derivation are investigated. Results are discussed and related to simple themes of ordinary life. The theoretical models fit to experimental data. Correction for temperature effect improves the fitting in comparison to the barometric formula. The scope for application of the model is discussed.

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Electron paramagnetic resonance (EPR) spectroscopy was used to study the main structural accommodations of spin labels in bilayers of saturated phosphatidylcholines with acyl chain lengths ranging from 16 to 22 carbon atoms. EPR spectra allowed the identification of two distinct spectral components in thermodynamic equilibrium at temperatures below and above the main phase transition. An accurate analysis of EPR spectra, using two fitting programs, enabled determination of the thermodynamic profile for these major probe accommodations. Focusing the analysis on two-component EPR spectra of a spin-labeled lipid, the influence of 40 mol % cholesterol in DPPC was studied.