943 resultados para RESPONSE-SURFACE METHODOLOGY


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The use of sewage sludge in Brazilian agriculture was regulated by the resolution no. 375 Conama, in 2006. However, there is a lack of research to adequate the mineral N and P fertilizer doses to be applied in agricultural fields treated with this residue. In a field experiment, the effects of application rates of sewage sludge and mineral N and P fertilizers on the productivity and technical characteristics of the cane-plant and first ratoon (residual effect) crops were evaluated. Four doses of sewage sludge (0, 3.6, 7.2 and 10.8 t ha-1, dry base), of N (0, 30, 60 and 90 kg ha-1) and of P2O5 (0, 60, 120 and 180 kg ha-1) were combined in a factorial and laid out on randomized block design, a with two replications. To evaluate the residual effect of the sludge, 120 kg ha-1 N and 140 kg ha-1 of K2O were applied in all plots. Sludge application at cane planting, with or without N and/or P fertilizer increased the stalk yield from 84 up to 118 t ha-1, with no alteration in the sugarcane quality, compared with the application of NPK fertilizer alone, resulting in a stalk yield of 91 t ha-1. The study of the response surface for stalk yield on lowfertility soil was the basis for a recommendation of mineral N and P fertilizer doses for sugarcane implantation as related to sewage sludge application rates. It was also concluded that a sludge application of 10.8 t ha-1, which is the sludge dose established based on the N criterion according to the resolution Conama nº 375, could a) reduce the use of mineral N by 100 % and of P2O5 by 30 %, with increments of 22 % in stalk yield, as a direct effect of sludge application to cane plant crop, and b) increase the stalk yield in the second harvest (first ratoon) by up to 12 % and sugar yield by up to 11 %, by the residual effect of sludge application to sugar cane.

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The objective of this work was to evaluate the application of the spectral-temporal response surface (STRS) classification method on Moderate Resolution Imaging Spectroradiometer (MODIS, 250 m) sensor images in order to estimate soybean areas in Mato Grosso state, Brazil. The classification was carried out using the maximum likelihood algorithm (MLA) adapted to the STRS method. Thirty segments of 30x30 km were chosen along the main agricultural regions of Mato Grosso state, using data from the summer season of 2005/2006 (from October to March), and were mapped based on fieldwork data, TM/Landsat-5 and CCD/CBERS-2 images. Five thematic classes were considered: Soybean, Forest, Cerrado, Pasture and Bare Soil. The classification by the STRS method was done over an area intersected with a subset of 30x30-km segments. In regions with soybean predominance, STRS classification overestimated in 21.31% of the reference values. In regions where soybean fields were less prevalent, the classifier overestimated 132.37% in the acreage of the reference. The overall classification accuracy was 80%. MODIS sensor images and the STRS algorithm showed to be promising for the classification of soybean areas in regions with the predominance of large farms. However, the results for fragmented areas and smaller farms were less efficient, overestimating soybean areas.

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Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

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This paper describes a simple and rapid spectrophotometric method for quantitative determination of sildenafil citrate based on its reaction with p-chloranil accelerated by hydrogen peroxide, producing a stable purple compound (λmax= 535 nm). In the absence of peroxide this reaction is very slow. The experimental conditions were optimized by using response surface methodologies. Beer's law is obeyed in a concentration range of 8.52 x 10-5 - 1.70 x 10-3 mol L-1 (r = 0.999). The detection limit was 1.96 x 10-5 mol L-1. The method was successfully applied for the determination of sildenafil citrate in medicines with good accuracy and precision.

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This work optimized the HPLC conditions for the simultaneous determination of luteolin, apigenin, myricetin, quercetin and kaempferol in aglycone form, as well defined the best conditions for hydrolysis/extraction of these flavonoids in fruits, using the statistical central composite design and response surface analysis. A reverse phase method was developed using a gradient of methanol/water acidified with 0.3% formic acid as mobile phase and a photodiode array detector. The samples were extracted with methanol/water (50:50 v/v) at 90 ºC. The optimum time and HCl concentration varied for the different fruits investigated, demonstrating the necessity of optimizing these conditions for each fruit analyzed. Good recovery (87.1 to 96.3%), repeatability and linearity were obtained.

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The aim of this study was to validate a method for the determination of acethaldehyde, methanol, ethanol, acetone and isopropanol employing solid-phase microextraction associated to gas chromatography with flame ionization detection. The operational conditions of SPME were optimized by response surface analysis. The calibration curves for all compounds were linear with r² > 0.9973. Accuracy (89.1-109.0%), intra-assay precision (1.8-8.5%) and inter-assay precision (2.2-8.2%) were acceptable. The quantification limit was 50 µg/mL. The method was applied to the meaurement of ethanol in blood and oral fluid of a group of volunteers. Oral fluid ethanol concentrations were not directly correlated with blood concentrations.

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A statistical mixture-design technique was used to study the effects of different solvents and their mixtures on the yield, total polyphenol content, and antioxidant capacity of the crude extracts from the bark of Schinus terebinthifolius Raddi (Anacardiaceae). The experimental results and their response-surface models showed that ternary mixtures with equal portions of all the three solvents (water, ethanol and acetone) were better than the binary mixtures in generating crude extracts with the highest yield (22.04 ± 0.48%), total polyphenol content (29.39 ± 0.39%), and antioxidant capacity (6.38 ± 0.21). An analytical method was developed and validated for the determination of total polyphenols in the extracts. Optimal conditions for the various parameters in this analytical method, namely, the time for the chromophoric reaction to stabilize, wavelength of the absorption maxima to be monitored, the reference standard and the concentration of sodium carbonate were determined to be 5 min, 780 nm, pyrogallol, and 14.06% w v-1, respectively. UV-Vis spectrophotometric monitoring of the reaction under these conditions proved the method to be linear, specific, precise, accurate, reproducible, robust, and easy to perform.

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The objective of this manuscript is to describe a practical experiment that can be employed for teaching concepts related to design of experiments using Matlab or Octave computing environment to beginners, undergraduate and graduate students. The classical experiment for determination of Fe (II) using o-phenanthroline was selected because it is easy to understand, and all the required materials are readily available in most analytical laboratories. The approach used in this tutorial is divided in two steps: first, the students are introduced to the concept of multivariate effects, how to calculate and interpret them, and the construction and evaluation of a linear model to describe the experimental domain by using a 2³ factorial design. Second, an extension of the factorial design by adding axial points is described, thereby, providing a central composite design. The quadratic model is then introduced and used to build the response surface.

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In this work, Doehlert experimental design was used to optimize the Transesterification Double Step Process (TDSP) method of methyl soybean oil biodiesel production which starts with a basic catalysis followed by an acidic catalysis. The conversion values were calculated from NMR spectra. Response surface was used to show the results of the interactions between the variables. This experimental design evaluated variables like catalyst and alcohol amount for the basic catalysis and time and temperature for the acidic catalysis. According to results obtained after Doehlert design application the alcohol amount was the main factor that influenced on the basic catalysis but for the acidic catalysis both time and temperature are important and their effects are opposite. It resulted on excellent conversions for both steps obtaining for the basic catalysis about 100% when was used like optimal conditions catalyst amount equal to 0.40 g and volume of methanol equal to 60 mL and for the acidic catalysis about 99% when was used like optimal conditions temperature of 65 °C and 90 minutes for reaction time.

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ABSTRACT In the present study, the influence of temperature (15, 20, 25, 30 and 35°C) and leaf wetness period (6, 12, 24 and 48 hours) on the severity of Cercospora leaf spot of beet, caused by Cercospora beticola, was studied under controlled conditions. Lesion density was influenced by temperature and leaf wetness duration (P<0.05). Data were subjected to nonlinear regression analysis. The generalized beta function was used for fitting the disease severity and temperature data, while a logistic function was chosen to represent the effect of leaf wetness on the severity of Cercospora leaf spot. The response surface resultant of the product of the two functions was expressed as ES = 0.0001105 * (((x-8)2.294387) * ((36-x)0.955017)) * (0.39219/(1+25.93072 * exp (-0.16704*y))), where: ES represents the estimated severity value (0.1); x, the temperature (ºC) and y, the leaf wetness duration (hours). This model should be validated under field conditions to assess its use as a computational forecast system for Cercospora leaf spot of beet.

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ABSTRACT In the present study, onion plants were tested under controlled conditions for the development of a climate model based on the influence of temperature (10, 15, 20 and 25°C) and leaf wetness duration (6, 12, 24 and 48 hours) on the severity of Botrytis leaf blight of onion caused by Botrytis squamosa. The relative lesion density was influenced by temperature and leaf wetness duration (P <0.05). The disease was most severe at 20°C. Data were subjected to nonlinear regression analysis. Beta generalized function was used to adjust severity and temperature data, while a logistic function was chosen to represent the effect of leaf wetness on the severity of Botrytis leaf blight. The response surface obtained by the product of two functions was expressed as ES = 0.008192 * (((x-5)1.01089) * ((30-x)1.19052)) * (0.33859/(1+3.77989 * exp (-0.10923*y))), where ES represents the estimated severity value (0.1); x, the temperature (°C); and y, the leaf wetness (in hours). This climate model should be validated under field conditions to verify its use as a computational system for the forecasting of Botrytis leaf blight in onion.

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ABSTRACT2-Phenylethanol (PE) is an aromatic alcohol with a characteristic odor of roses, widely used in food industry to modify certain aroma compositions in formulations with fruit, jam, pudding, and chewing gums, and also in cosmetic and fragrance industry. This compound occurs naturally in low concentrations in some essential oils from flowers and plants. An alternative to plants extraction are biotechnological processes. This study evaluated 2-phenylethanol’s production in cultivation of Saccharomyces cerevisiae in cassava wastewater originated from starch industry. The substrate was supplemented with glucose and L-phenylalanine in order to obtain higher 2-phenylethanol concentrations and better efficiency in glucose/2-phenylethanol conversion. It was performed using Rotatable Center Composite Design and response surface analysis. Cultures were performed under aerobic conditions in a batch system in Erlenmeyer flasks containing 50 mL of medium in shaker at 150 rpm and 24 ± 1 ºC. The highest PE values ​​were obtained with supplementation of 20.0 g.L-1 of glucose and 5.5 g.L-1 of L-phenylalanine, which has been experimentally validated, obtaining a PE production of 1.33 g.L-1 and PE/glucose yield factor of 0.070 g.g-1, equivalent to 74.3 and 89.7% ​​of desirability values according to the validated model.

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The weed Borreria densiflora is a management issue in soybean and sugarcane crops from North and Northeastern Brazil. Knowledge upon chemical control of B. densiflora contributes to the integrated management of this weed species, especially when active ingredient options become reduced due to the selection of herbicide resistant or tolerant weed species. Experiments in pre- and post-emergence of B. densiflora were conducted in greenhouse, in a randomized block design and four replications. In pre-emergence, the dose-response curve methodology was used and 7 herbicides were tested. In post-emergence, 9 herbicides at the recommended rate and 4 herbicide mixtures were tested. For pre and post-emergence conditions, evaluations were conducted at 60 and 21 days after treatment (DAT), respectively, and the variables analyzed were weed control and dry weight (%). The results showed options of pre-emergent herbicides that can be used for controlling B. densiflora, especially in sugarcane, where chemical weed control is mainly based on pre-emergent applications. In the current glyphosate resistance scenario, one should consider the use of pre-emergent herbicides within an integrated management of B. densiflora. For satisfactory post-emergence control, B. densiflora plants should be sprayed at the phenological stage of up to three pairs of leaves. Herbicide mixtures have been and will continue to be an important tool in chemical weed management, broadening the spectrum of weed control, while diversifying herbicide mechanisms of action, which helps to prevent or delay the appearance of herbicide resistance.

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The objective of this work was to develop a recommendation for the chemical peeling of pequi fruit and characterize the flour obtained from the external mesocarp of "Pequizeiro", pequi tree (Caryocar brasiliense Camb.). The technology applied to obtain the external mesocarp pequi flour included the epicarp removal with NaOH solution. The Response Surface Method was used to optimize the chemical peeling process by applying the Central Composite Rotatable Design, with eleven trials including three replicates at the central point, varying the NaOH aqueous solution concentration and fruit immersion time. The mass loss was evaluated through the analysis of variance and using bi and three dimensional graphs. The chemical characteristics of the external mesocarp pequi flour evaluated were: moisture content, ashes, proteins, lipids, total carbohydrates, dietary fiber, and some minerals. The best combination for an efficient removal of the fruit peel with the lowest mass loss was reached with 7.05 minutes of immersion in a 5.08 g.L-1 NaOH aqueous solution. This study indicated that the external mesocarp pequi flour is a food source rich in dietary fiber, carbohydrates, ashes, magnesium, calcium, manganese, and copper, but it is poor in lipids, zinc, and iron.

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Docosahexaenoic acid is an essential polyunsaturated fatty acid with important metabolic activities. Its conjugated double bonds make it susceptible to decomposition. Its stability may be improved through fatty acid entrapment with a spray-drying technique; however, the many parameters involved in this technique must be considered to avoid affecting the final product quality. Therefore, this study aimed to evaluate the entrapment conditions and yields of fish oil enriched with docosahexaenoic acid ethyl ester. Microcapsules were obtained from Acacia gum using a spray-drying technique. The experimental samples were analyzed by chromatography and delineated by Statistica software, which found the following optimum entrapment conditions: an inlet temperature of 188 °C; 30% core material; an N2 flow rate of 55 mm; and a pump flow rate of 12.5 mL/minute. These conditions provided a 66% yield of docosahexaenoic acid ethyl ester in the oil, corresponding to 19.8% of entrapped docosahexaenoic acid ethyl ester (w/w). This result was considered significant since 30% corresponded to wall material.