96 resultados para nonlinear least-square fit


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Soil water availability to plants is affected by soil compaction and other variables. The Least Limiting Water Range (LLWR) comprises soil physical variables affecting root growth and soil water availability, and can be managed by either mechanical or biological methods. There is evidence that effects of crop rotations could last longer than chiseling, so the objective of this study was to assess the effect of soil chiseling or growing cover crops under no-till (NT) on the LLWR. Crop rotations involving triticale (X Triticosecale) and sunflower (Helianthus annuus) in the fall-winter associated with millet (Pennisetum glaucum), sorghum (Sorghum bicolor) and sunn hemp (Crotalaria juncea) as cover crops preceding soybean (Glycine max) were repeated for three consecutive years. In the treatment with chiseling (performed only in the first year), the area was left fallow between the fall-winter and summer crops. The experiment was carried out in Botucatu, São Paulo State, Brazil, from 2003 to 2006 on a Typic Rhodudalf. The LLWR was determined in soil samples taken from the layers 0-20 cm and 20- 40 cm, after chemical desiccation of the cover crops in December of the first and third year of the experiment. Chiseling decreases soil bulk density in the 0-20 cm soil layer, increasing the LLWR magnitude by lowering the soil water content at which penetration resistance reaches 2.0 MPa; this effect is present up to the third year after chiseling and can reach to a depth of 0.40 m. Crop rotations involving sunflower + sunn hemp, triticale + millet and triticale + sunn hemp for three years prevented soil bulk density from exceeding the critical soil bulk density in the 0- 0.20 m layer. This effect was observed to a depth of 0.40 m after three years of chiseling under crop rotations involving forage sorghum. Hence, chiseling and some crop rotations under no tillage are effective in increasing soil quality assessed by the LLWR.

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The agricultural potential of Latosols of the Brazilian Cerrado region is high, but when intensively cultivated under inappropriate management systems, the porosity can be seriously reduced, leading to rapid soil degradation. Consequently, accelerated erosion and sedimentation of springs and creeks have been observed. Therefore, the objective of this study was to evaluate structural changes of Latosols in Rio Verde, Goiás, based on the Least Limiting Water Range (LLWR), and relationships between LLWR and other physical properties. Soil samples were collected from the B horizons of five oxidic Latosols representing the textural variability of the Latosols of the Cerrado biome. LLWR and other soil physical properties were determined at various soil compaction degrees induced by uniaxial compression. Soil compaction caused effects varying from enhanced plant growth due to higher water retention, to severe restriction of edaphic functions. Also, inverse relationships were observed between clay content and bulk density values (Bd) under different structural conditions. Bd values corresponding to critical soil macroporosity (BdcMAC) were more restrictive to a sustainable use of the studied Latosols than the critical Bd corresponding to LLWR (BdcLLWR). The high tolerable compression potential of these oxidic Latosols was related to the high aeration porosity associated to the granular structure.

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In the south-central region of Brazil, there is a trend toward reducing the sugarcane inter-harvest period and increasing traffic of heavy harvesting machinery on soil with high water content, which may intensify the compaction process. In this study, we assessed the structural changes of a distroferric Red Latosol (Oxisol) by monitoring soil water content as a function of the Least Limiting Water Range (LLWR) and quantified its effects on the crop yield and industrial quality of the first ratoon crop of sugarcane cultivars with different maturation cycles. Three cultivars (RB 83-5054, RB 84-5210 and RB 86-7515) were subjected to four levels of soil compaction brought about by a differing number of passes of a farm tractor (T0 = soil not trafficked, T2 = 2 passes, T10 = 10 passes, and T20 = 20 passes of the tractor in the same place) in a 3 × 4 factorial arrangement with three replications. The deleterious effects on the soil structure from the farm machinery traffic were limited to the surface layer (0-10 cm) of the inter-row area of the ratoon crop. The LLWR dropped to nearly zero after 20 tractor passes between the cane rows. We detected differences among the cultivars studied; cultivar RB 86-7515 stood out for its industrial processing quality, regardless of the level of soil compaction. Monitoring of soil moisture in the crop showed exposure to water stress conditions, although soil compaction did not affect the production variables of the sugarcane cultivars. We thus conclude that the absence of traffic on the plant row maintained suitable soil conditions for plant development and may have offset the harmful effects of soil compaction shown by the high values for bulk density between the rows of the sugarcane cultivars.

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Visible and near infrared (vis-NIR) spectroscopy is widely used to detect soil properties. The objective of this study is to evaluate the combined effect of moisture content (MC) and the modeling algorithm on prediction of soil organic carbon (SOC) and pH. Partial least squares (PLS) and the Artificial neural network (ANN) for modeling of SOC and pH at different MC levels were compared in terms of efficiency in prediction of regression. A total of 270 soil samples were used. Before spectral measurement, dry soil samples were weighed to determine the amount of water to be added by weight to achieve the specified gravimetric MC levels of 5, 10, 15, 20, and 25 %. A fiber-optic vis-NIR spectrophotometer (350-2500 nm) was used to measure spectra of soil samples in the diffuse reflectance mode. Spectra preprocessing and PLS regression were carried using Unscrambler® software. Statistica® software was used for ANN modeling. The best prediction result for SOC was obtained using the ANN (RMSEP = 0.82 % and RPD = 4.23) for soil samples with 25 % MC. The best prediction results for pH were obtained with PLS for dry soil samples (RMSEP = 0.65 % and RPD = 1.68) and soil samples with 10 % MC (RMSEP = 0.61 % and RPD = 1.71). Whereas the ANN showed better performance for SOC prediction at all MC levels, PLS showed better predictive accuracy of pH at all MC levels except for 25 % MC. Therefore, based on the data set used in the current study, the ANN is recommended for the analyses of SOC at all MC levels, whereas PLS is recommended for the analysis of pH at MC levels below 20 %.

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As opposed to objective definitions in soil physics, the subjective term “soil physical quality” is increasingly found in publications in the soil physics area. A supposed indicator of soil physical quality that has been the focus of attention, especially in the Brazilian literature, is the Least Limiting Water Range (RLL), translated in Portuguese as "Intervalo Hídrico Ótimo" or IHO. In this paper the four limiting water contents that define RLLare discussed in the light of objectively determinable soil physical properties, pointing to inconsistencies in the RLLdefinition and calculation. It also discusses the interpretation of RLL as an indicator of crop productivity or soil physical quality, showing its inability to consider common phenological and pedological boundary conditions. It is shown that so-called “critical densities” found by the RLL through a commonly applied calculation method are questionable. Considering the availability of robust models for agronomy, ecology, hydrology, meteorology and other related areas, the attractiveness of RLL as an indicator to Brazilian soil physicists is not related to its (never proven) effectiveness, but rather to the simplicity with which it is dealt. Determining the respective limiting contents in a simplified manner, relegating the study or concern on the actual functioning of the system to a lower priority, goes against scientific construction and systemic understanding. This study suggests a realignment of the research in soil physics in Brazil with scientific precepts, towards mechanistic soil physics, to replace the currently predominant search for empirical correlations below the state of the art of soil physics.

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ABSTRACT The expansion of the sugarcane industry in Brazil has intensified the mechanization of agriculture and caused effects on the soil physical quality. The purpose of this study was to evaluate the limiting water range and soil bearing capacity of a Latossolo Vermelho distroférrico típico (Rhodic Hapludox) under the influence of different tractor-trailers used in mechanical sugarcane harvesting. The experiment was arranged in a randomized block design with five replications. The treatments consisted of green sugarcane harvesting with: harvester without trailer (T1); harvester with two trailers with a capacity of 10 Mg each (T2); harvester with trailer with a capacity of 20 Mg (T3) and harvester and truck with trailer with a capacity of 20 Mg (10 Mg per compartment) (T4). The least limiting water range and soil bearing capacity were evaluated. The transport equipment to remove the harvested sugarcane from the field (trailer) at harvest decreased the least limiting water range, reducing the structural soil quality. The truck trailer caused the greatest impact on the soil physical properties studied. The soil load bearing capacity was unaffected by the treatments, since the pressure of the harvester (T1) exceeded the pre-consolidation pressure of the soil.

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This paper focused on four alternatives of analysis of experiments in square lattice as far as the estimation of variance components and some genetic parameters are concerned: 1) intra-block analysis with adjusted treatment and blocks within unadjusted repetitions; 2) lattice analysis as complete randomized blocks; 3) intrablock analysis with unadjusted treatment and blocks within adjusted repetitions; 4) lattice analysis as complete randomized blocks, by utilizing the adjusted means of treatments, obtained from the analysis with recovery of interblock information, having as mean square of the error the mean effective variance of this same analysis with recovery of inter-block information. For the four alternatives of analysis, the estimators and estimates were obtained for the variance components and heritability coefficients. The classification of material was also studied. The present study suggests that for each experiment and depending of the objectives of the analysis, one should observe which alternative of analysis is preferable, mainly in cases where a negative estimate is obtained for the variance component due to effects of blocks within adjusted repetitions.

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The research aimed to evaluate machine traffic effect on soil compaction and the least limiting water range related to soybean cultivar yields, during two years, in a Haplustox soil. The six treatments were related to tractor (11 Mg weight) passes by the same place: T0, no compaction; and T1*, 1; T1, 1; T2, 2; T4, 4 and T6, 6. In the treatment T1*, the compaction occurred when soil was dried, in 2003/2004, and with a 4 Mg tractor in 2004/2005. Soybean yield was evaluated in relation to soil compaction during two agricultural years in completely randomized design (compaction levels); however, in the second year, there was a factorial scheme (compaction levels, with and without irrigation), with four replicates represented by 9 m² plots. In the first year, soybean [Glycine max (L.) Merr.] cultivar IAC Foscarim 31 was cultivated without irrigation; and in the second year, IAC Foscarim 31 and MG/BR 46 (Conquista) cultivars were cultivated with and without irrigation. Machine traffic causes compaction and reduces soybean yield for soil penetration resistance between 1.64 to 2.35 MPa, and bulk density between 1.50 to 1.53 Mg m-3. Soil bulk density from which soybean cultivar yields decrease is lower than the critical one reached at least limiting water range (LLWR =/ 0).

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The objective of this study was to improve the simulation of node number in soybean cultivars with determinate stem habits. A nonlinear model considering two approaches to input daily air temperature data (daily mean temperature and daily minimum/maximum air temperatures) was used. The node number on the main stem data of ten soybean cultivars was collected in a three-year field experiment (from 2004/2005 to 2006/2007) at Santa Maria, RS, Brazil. Node number was simulated using the Soydev model, which has a nonlinear temperature response function [f(T)]. The f(T) was calculated using two methods: using daily mean air temperature calculated as the arithmetic average among daily minimum and maximum air temperatures (Soydev tmean); and calculating an f(T) using minimum air temperature and other using maximum air temperature and then averaging the two f(T)s (Soydev tmm). Root mean square error (RMSE) and deviations (simulated minus observed) were used as statistics to evaluate the performance of the two versions of Soydev. Simulations of node number in soybean were better with the Soydev tmm version, with a 0.5 to 1.4 node RMSE. Node number can be simulated for several soybean cultivars using only one set of model coefficients, with a 0.8 to 2.4 node RMSE.

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The objective of this work was to estimate the stability and adaptability of pod and seed yield in runner peanut genotypes based on the nonlinear regression and AMMI analysis. Yield data from 11 trials, distributed in six environments and three harvests, carried out in the Northeast region of Brazil during the rainy season were used. Significant effects of genotypes (G), environments (E), and GE interactions were detected in the analysis, indicating different behaviors among genotypes in favorable and unfavorable environmental conditions. The genotypes BRS Pérola Branca and LViPE‑06 are more stable and adapted to the semiarid environment, whereas LGoPE‑06 is a promising material for pod production, despite being highly dependent on favorable environments.

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Adsorption of Cu(II), Ni(II), Pb(II) and Zn(II) ions from aqueous solutions by N-(3,4-dihydroxybenzyl) chitosan have been carried out. The Langmuir (L), Freundlich (F), Langmuir - Freundlich (LF), Redlich-Peterson (RP) and Tóth (T) adsorption isotherms models have been applied to fit the experimental data. Nonlinear regression computational program "Enzefitte", which is a library of the more commonly used adsorption isotherm equations for obtaining tabular outuput suitable for plotting theoretical of fitted isotherms, has been used to estimate the adsorption parameters. These parameters were used to calculate the amount adsorbed q calc., a function of concentration (C).

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The objective of this work was to accomplish the simultaneous determination of some chemical elements by Energy Dispersive X-ray Fluorescence (EDXRF) Spectroscopy through multivariate calibration in several sample types. The multivariate calibration models were: Back Propagation neural network, Levemberg-Marquardt neural network and Radial Basis Function neural network, fuzzy modeling and Partial Least Squares Regression. The samples were soil standards, plant standards, and mixtures of lead and sulfur salts diluted in silica. The smallest Root Mean Square errors (RMS) were obtained with Back Propagation neural networks, which solved main EDXRF problems in a better way.

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A new procedure to find the limiting range of the photomultiplier linear response of a low-cost, digital oscilloscope-based time-resolved laser-induced luminescence spectrometer (TRLS), is presented. A systematic investigation on the instrument response function with different signal input terminations, and the relationship between the luminescence intensity reaching the photomultiplier and the measured decay time are described. These investigations establish that setting the maximum intensity of the luminescence signal below 0.3V guarantees, for signal input terminations equal or higher than 99.7 ohm, a linear photomultiplier response.

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The moisture sorption isotherms of Chilean papaya were determined at 5, 20, and 45 ºC, over a relative humidity range of 10-95%. The GAB, BET, Oswin, Halsey, Henderson, Smith, Caurie and Iglesias-Chirife models were applied to the sorption experimental data. The goodness of fit of the mathematical models was statistically evaluated by means of the determination coefficient, mean relative percentage deviation, sum square error, root-mean-square error, and chi-square values. The GAB, Oswin and Halsey models were found to be the most suitable for the description of the sorption data. The sorption heats calculated using the Clausius-Clapeyron equation were 57.35 and 59.98 kJ·mol-1, for adsorption and desorption isotherms, respectively.

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An analytical method for the determination of the anti-inflammatory drug 5-aminosalicylic acid (5-ASA) in pharmaceutical formulations using square wave voltammetry at pencil graphite electrodes was developed. After the optimization of the experimental conditions, calibration curves were obtained in the linear concentration range from 9.78 × 10-7 to 7.25 × 10-5 mol L-1 resulting in a limit of detection of 2.12 ± 0.05 x 10-8 mol L-1. Statistical tests showed that the concentrations of 5-ASA in commercial tablets and enemas obtained with the proposed voltammetric method agreed with HPLC values at a 95% confidence level.