70 resultados para fuzzy based evaluation method


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Macroporosity is often used in the determination of soil compaction. Reduced macroporosity can lead to poor drainage, low root aeration and soil degradation. The aim of this study was to develop and test different models to estimate macro and microporosity efficiently, using multiple regression. Ten soils were selected within a large range of textures: sand (Sa) 0.07-0.84; silt 0.03-0.24; clay 0.13-0.78 kg kg-1 and subjected to three compaction levels (three bulk densities, BD). Two models with similar accuracy were selected, with a mean error of about 0.02 m³ m-3 (2 %). The model y = a + b.BD + c.Sa, named model 2, was selected for its simplicity to estimate Macro (Ma), Micro (Mi) or total porosity (TP): Ma = 0.693 - 0.465 BD + 0.212 Sa; Mi = 0.337 + 0.120 BD - 0.294 Sa; TP = 1.030 - 0.345 BD 0.082 Sa; porosity values were expressed in m³ m-3; BD in kg dm-3; and Sa in kg kg-1. The model was tested with 76 datum set of several other authors. An error of about 0.04 m³ m-3 (4 %) was observed. Simulations of variations in BD as a function of Sa are presented for Ma = 0 and Ma = 0.10 (10 %). The macroporosity equation was remodeled to obtain other compaction indexes: a) to simulate maximum bulk density (MBD) as a function of Sa (Equation 11), in agreement with literature data; b) to simulate relative bulk density (RBD) as a function of BD and Sa (Equation 13); c) another model to simulate RBD as a function of Ma and Sa (Equation 16), confirming the independence of this variable in relation to Sa for a fixed value of macroporosity and, also, proving the hypothesis of Hakansson & Lipiec that RBD = 0.87 corresponds approximately to 10 % macroporosity (Ma = 0.10 m³ m-3).

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DRIS, an Diagnosis and Recommendation Integrated System, is a tool to evaluate the nutritional status of plants. Different DRIS formulas have been proposed to improve the efficiency of the crop nutrition diagnoses. The objective of this study was to compare the nutritional diagnosis of the formulas of Beaufils (1973), of Jones (1981) and of Elwali and Gascho (1984), based on the degree of agreement in commercial orchards of Theobrama grandiflorum trees. Leaf samples of 5 to 18 year-old cupuaçu trees were collected from 153 commercial orchards in agroforestry and monoculture systems in the state of Rondonia, Brazil. Bivariate relationships between nutrition concentrations in healthy trees were used to calculate DRIS norms. DRIS indices were calculated based on the different formulas and interpreted by the Potential Fertilizer Response method, in five categories. The DRIS norms, DRIS index calculations and their interpretations were developed using the DRIS Cupuaçu computer program (www.dris.com.br). The different DRIS formulas resulted in similar diagnoses with a degree of agreement of > 90% for the nutrients N, P, K, Ca, and Mg.

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The main objective of this work was to compare two methods to estimate the deposition of pesticide applied by aerial spraying. Hundred and fifty pieces of water sensitive paper were distributed over an area of 50 m length by 75 m width for sampling droplets sprayed by an aircraft calibrated to apply a spray volume of 32 L/ha. The samples were analysed by visual microscopic method using NG 2 Porton graticule and by an image analyser computer program. The results reached by visual microscopic method were the following: volume median diameter, 398±62 mum; number median diameter, 159±22 mum; droplet density, 22.5±7.0 droplets/cm² and estimated deposited volume, 22.2±9.4 L/ha. The respective ones reached with the computer program were: 402±58 mum, 161±32 mum, 21.9±7.5 droplets/cm² and 21.9±9.2 L/ha. Graphs of the spatial distribution of droplet density and deposited spray volume on the area were produced by the computer program.

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The objective of this work was to test a simple method for root hair evaluation of 21 common bean (Phaseolus vulgaris) genotypes, most of them used in breeding programs in Brazil. Hairs of basal and primary roots of 5-day old seedlings, produced on germination paper with no phosphorus addition, were visually evaluated by a rating scale after staining with 0.05% trypan blue. The method reveals variability among the genotypes, and the standard error of the mean is relatively low.

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The objective of this work was to evaluate the production of flour using by-products (cephalothorax) obtained from the shrimp (Litopenaeus vannamei) industry, and to perform a sensory analysis of shrimp flour-based products. Physicochemical and microbiological analyses on fresh cephalothorax and on manufactured flour were performed, as well as the determination of cholesterol content of this flour, and the sensorial evaluation of soup and pastry made with this flour. By the microbiological analyses, no pathogenic microorganism was detected in the samples. Physicochemical analyses of flour showed high levels of protein (50.05%) and minerals (20.97%). Shrimp cephalothorax flour showed high levels of cholesterol. The sensory evaluation indicated a good acceptance of the products, with satisfactory acceptability index (81% for soup, and 83% for pastry), which indicates that shrimp cephalothorax in the form of flour has a potential for developing new products.

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The hydroalcoholic extracts prepared from standard leaves of Maytenus ilicifolia and commercial samples of espinheira-santa were evaluated qualitatively (fingerprinting) and quantitatively. In this paper, fingerprinting chromatogram coupled with Principal Component Analysis (PCA) is described for the metabolomic analysis of standard and commercial espinheira-santa samples. The epicatechin standard was used as an external standard for the development and validation of a quantitative method for the analysis in herbal medicines using a photo diode array detector. This method has been applied for quantification of epicatechin in commercialized herbal medicines sold as espinheira-santa in Brazil and in the standard sample of M. ilicifolia.

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A study was made to evaluate the effect of a castor oil-based detergent on strawberry crops treated with different classes of pesticides, namely deltamethrin, folpet, tebuconazole, abamectin and mancozeb, in a controlled environment. Experimental crops of greenhouse strawberries were cultivated in five different ways with control groups using pesticides and castor oil-based detergent. The results showed that the group 2, which was treated with castor oil-based detergent, presented the lowest amount of pesticide residues and the highest quality of fruit produced.

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In general, laboratory activities are costly in terms of time, space, and money. As such, the ability to provide realistically simulated laboratory data that enables students to practice data analysis techniques as a complementary activity would be expected to reduce these costs while opening up very interesting possibilities. In the present work, a novel methodology is presented for design of analytical chemistry instrumental analysis exercises that can be automatically personalized for each student and the results evaluated immediately. The proposed system provides each student with a different set of experimental data generated randomly while satisfying a set of constraints, rather than using data obtained from actual laboratory work. This allows the instructor to provide students with a set of practical problems to complement their regular laboratory work along with the corresponding feedback provided by the system's automatic evaluation process. To this end, the Goodle Grading Management System (GMS), an innovative web-based educational tool for automating the collection and assessment of practical exercises for engineering and scientific courses, was developed. The proposed methodology takes full advantage of the Goodle GMS fusion code architecture. The design of a particular exercise is provided ad hoc by the instructor and requires basic Matlab knowledge. The system has been employed with satisfactory results in several university courses. To demonstrate the automatic evaluation process, three exercises are presented in detail. The first exercise involves a linear regression analysis of data and the calculation of the quality parameters of an instrumental analysis method. The second and third exercises address two different comparison tests, a comparison test of the mean and a t-paired test.

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The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

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In this study, dispersive liquid-liquid microextraction based on the solidification of floating organic droplets was used for the preconcentration and determination of thorium in the water samples. In this method, acetone and 1-undecanol were used as disperser and extraction solvents, respectively, and the ligand 1-(2-thenoyl)-3,3,3-trifluoracetone reagent (TTA) and Aliquat 336 was used as a chelating agent and an ion-paring reagent, for the extraction of thorium, respectively. Inductively coupled plasma-optical emission spectrometry was applied for the quantitation of the analyte after preconcentration. The effect of various factors, such as the extraction and disperser solvent, sample pH, concentration of TTA and concentration of aliquat336 were investigated. Under the optimum conditions, the calibration graph was linear within the thorium content range of 1.0-250 µg L-1 with a detection limit of 0.2 µg L-1. The method was also successfully applied for the determination of thorium in the different water samples.

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INTRODUCTION: Web-based e-learning is a teaching tool increasingly used in many medical schools and specialist fields, including ophthalmology. AIMS: this pilot study aimed to develop internet-based course-based clinical cases and to evaluate the effectiveness of this method within a graduate medical education group. METHODS: this was an interventional randomized study. First, a website was built using a distance learning platform. Sixteen first-year ophthalmology residents were then divided into two randomized groups: one experimental group, which was submitted to the intervention (use of the e-learning site) and another control group, which was not submitted to the intervention. The students answered a printed clinical case and their scores were compared. RESULTS: there was no statistically significant difference between the groups. CONCLUSION: We were able to successfully develop the e-learning site and the respective clinical cases. Despite the fact that there was no statistically significant difference between the access and the non access group, the study was a pioneer in our department, since a clinical case online program had never previously been developed.

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The feasibility of using augmented block designs and spatial analysis methods for early stage selection in eucalyptus breeding programs was tested. A total of 113 half-sib progenies of Eucalyptus urophylla and eight clones were evaluated in an 11 x 11 triple lattice experiment at two locations: Posto da Mata (Bahia, Brazil) and São Mateus (Minas Gerais, Brazil). Four checks were randomly allocated within each block. Plots consisted of 15 m long rows containing 6 plants spaced 3 m apart. The girth at breast height (cm/plant) was evaluated at 19 and 26 months of age. Variance analyses were performed according to the following methods: lattice design, randomized complete block design, augmented block design, Papadakis method, moving means method, and check plots. Comparisons among different methods were based on the magnitude of experimental errors and precision of the estimates of genetic and phenotypic parameters. General results indicated that augmented block design is useful to evaluate progenies and clones in early selection in eucalyptus breeding programs using moderate and low selection intensities. However, this design is not suitable for estimating genetic and phenotypic parameters due to its low precision. Check plots, nearest neighbour, Papadakis (1937), and moving means methods were efficient in removing the heterogeneity within blocks. These efficiencies were compared to that in lattice analysis for estimation of genetic and phenotypic parameters.

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In order to verify Point-Centered Quarter Method (PCQM) accuracy and efficiency, using different numbers of individuals by per sampled area, in 28 quarter points in an Araucaria forest, southern Paraná, Brazil. Three variations of the PCQM were used for comparison associated to the number of sampled individual trees: standard PCQM (SD-PCQM), with four sampled individuals by point (one in each quarter), second measured (VAR1-PCQM), with eight sampled individuals by point (two in each quarter), and third measuring (VAR2-PCQM), with 16 sampled individuals by points (four in each quarter). Thirty-one species of trees were recorded by the SD-PCQM method, 48 by VAR1-PCQM and 60 by VAR2-PCQM. The level of exhaustiveness of the vegetation census and diversity index showed an increasing number of individuals considered by quadrant, indicating that VAR2-PCQM was the most accurate and efficient method when compared with VAR1-PCQM and SD-PCQM.

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The destruction of the cotton crop residues (cotton stalks) is a mandatory procedure in Brazil for prophylactic issues, but is a subject unexplored by the research and there are few studies that deal with this issue. However, this is not encouraged in recent decades, studies aimed at developing and evaluating equipment for this purpose. The present study had the objective to evaluate six methods for mechanical destruction of cotton crop residues. Each method was defined based on the principle of operation of the active parts of the equipment, which were tested in medium texture soil and in a clayey one. The variables used to evaluate the efficiency of the equipment were the regrowth rate, the theoretical field capacity and energy demand. The equipment with convergent concave disks (DCC) and flat cutters discs from manufacturer A (CPS-a) showed the best results in cotton stalks destruction in both soil types. The harrow disc (GPD) was efficient only in clay soil. It was concluded that the equipment with convergent concave disks, among those tested, was the most efficient to destroy cotton stalks, regardless of soil type, and that the harrow disc was not included among the best performers.

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Clustering soil and crop data can be used as a basis for the definition of management zones because the data are grouped into clusters based on the similar interaction of these variables. Therefore, the objective of this study was to identify management zones using fuzzy c-means clustering analysis based on the spatial and temporal variability of soil attributes and corn yield. The study site (18 by 250-m in size) was located in Jaboticabal, São Paulo/Brazil. Corn yield was measured in one hundred 4.5 by 10-m cells along four parallel transects (25 observations per transect) over five growing seasons between 2001 and 2010. Soil chemical and physical attributes were measured. SAS procedure MIXED was used to identify which variable(s) most influenced the spatial variability of corn yield over the five study years. Basis saturation (BS) was the variable that better related to corn yield, thus, semivariograms models were fitted for BS and corn yield and then, data values were krigged. Management Zone Analyst software was used to carry out the fuzzy c-means clustering algorithm. The optimum number of management zones can change over time, as well as the degree of agreement between the BS and corn yield management zone maps. Thus, it is very important take into account the temporal variability of crop yield and soil attributes to delineate management zones accurately.