142 resultados para linear-regression
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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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This paper describes the albedo (r) and estimates of net radiation and global solar irradiance for green beans crop (Phaseolus vulgaris L.), cultivated in greenhouse with cover of polyethylene and field conditions, in Botucatu, SP, Brazil (22º 54' S; 48º 27' W; 850 m). The solar global irradiance (Rg) and solar reflected radiation (Rr) were used to estimate the albedo through the ratio between Rr and Rg. The diurnal curves of albedo were obtained for days with clear sky and partially cloudy conditions, for different phenological stages of the crop. The albedo ranged with the solar elevation, the environment and the phenological stages. The cloudiness range have almost no influence on the albedo diurnal amount. The estimation of radiation were made by linear regression, using the global solar irradiance (Rg) and net short-waves radiation (Rc) as independent variables. All estimates of radiation showed better adjustment for specific phenological periods compared to the entire crop growing cycle. The net radiation in the greenhouse has been estimated by the global solar irradiance measured at field conditions.
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The objective of this work was to perform a quantitative analysis of the amino acid composition of soybean seeds as affected by climatic variables during seed filling. Amino acids were determined from seed samples taken at harvest in 31 multi-environment field trials carried out in Argentina. Total amino acids ranged from 31.69 to 49.14%, and total essential and nonessential amino acids varied from 12.83 to 19.02% and from 18.86 to 31.15%, respectively. Variance components expressed as the percentage of total variation showed that the environment was the most important source of variation for all traits, followed by the genotype x environment interaction. Significant explanatory linear regressions were detected for amino acid content regarding: average daily mean air temperature and cumulative solar radiation, during seed filling; precipitation minus potential evapotranspiration, during the whole reproductive period; and the combinations of these climatic variables. Each amino acid behaves differently according to environmental conditions, indicating compensatory effects among them.
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The objective of this work was to develop and validate linear regression models to estimate the production of dry matter by Tanzania grass (Megathyrsus maximus, cultivar Tanzania) as a function of agrometeorological variables. For this purpose, data on the growth of this forage grass from 2000 to 2005, under dry‑field conditions in São Carlos, SP, Brazil, were correlated to the following climatic parameters: minimum and mean temperatures, degree‑days, and potential and actual evapotranspiration. Simple linear regressions were performed between agrometeorological variables (independent) and the dry matter accumulation rate (dependent). The estimates were validated with independent data obtained in São Carlos and Piracicaba, SP, Brazil. The best statistical results in the development and validation of the models were obtained with the agrometeorological parameters that consider thermal and water availability effects together, such as actual evapotranspiration, accumulation of degree‑days corrected by water availability, and the climatic growth index, based on average temperature, solar radiation, and water availability. These variables can be used in simulations and models to predict the production of Tanzania grass.
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The objective of this work was to test long-term trends in the duration of rice development phases in Santa Maria, RS, Brazil. The duration from emergence to V3 (EM-V3), emergence to panicle differentiation (EM-R1), emergence to anthesis (EM-R4), and emergence to all grains with brown hull (EM-R9) was calculated using leaf appearance and developmental models for four rice cultivars (IRGA 421, IRGA 417, EPAGRI 109, and EEA 406), for the period from 1912 to 2011, considering three emergence dates (early, mid, and late). The trend of the time series was tested with the non-parametric Mann-Kendall test, and the magnitude of the trend was estimated with simple linear regression. Rice development has changed over the last ten decades in this location, leading to an anticipation of harvest time of 17 to 31 days, depending on the cultivar maturity group and emergence date, which is related to trends of temperature increase during the growing season. Warmer temperatures over the evaluated time period are responsible for changing rice phenology in this location, since minimum and maximum daily temperature drive the rice developmental models used.
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The objective of this work was to characterize the chemical properties of white oat (Avena sativa) caryopsis and to determine the adaptability and stability of cultivars recommended for cultivation in the state of Rio Grande do Sul, Brazil. The trials were carried out in the 2007, 2008 and 2009 crop seasons, in three municipalities: Augusto Pestana, Capão do Leão, and Passo Fundo. Fifteen cultivars were evaluated in a randomized block design, with four replicates. The contents of protein, lipid, and nitrogen-free extract were evaluated in the caryopsis. Cultivar performances for the measured characters varied according to location and year of cultivation. The cultivar URS Guapa showed high content of nitrogen-free extract and low contents of protein and lipid in the caryopsis. 'FAPA Louise' showed high content of lipid, whereas 'Albasul', 'UPF 15', and 'UPF 18' showed high content of protein and low content of nitrogen-free extract. There is no evidence of an ideal biotype for the evaluated characters, which could simultaneously show high average performance, adaptability to favorable and unfavorable environments, and stability.
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The phyllochron is defined as the time required for the appearance of successive leaves on a plant; this characterises plant growth, development and adaptation to the environment. To check the growth and adaptation in cultivars of strawberry grown intercropped with fig trees, it was estimated the phyllochron in these production systems and in the monocrop. The experiment was conducted in greenhouses at the University of Passo Fundo (28º15'41'' S, 52º24'45'' W and 709 m) from June 8th to September 4th, 2009; this comprised the period of transplant until the 2nd flowering. The cultivars Aromas, Camino Real, Albion, Camarosa and Ventana, which seedlings were originated from the Agrícola LLahuen Nursery in Chile, as well as Festival, Camino Real and Earlibrite, originated from the Viansa S.A. Nursery in Argentina, were grown in white polyethylene bags filled with commercial substrate (Tecnomax®) and evaluated. The treatments were arranged in a randomised block design and four replicates were performed. A linear regression was realized between the leaf number (LN) in the main crown and the accumulated thermal time (ATT). The phyllochron (degree-day leaf-1) was estimated as the inverse of the angular coefficient of the linear regression. The data were submitted to ANOVA, and when significance was observed, the means were compared using the Tukey test (p < 0.05). The mean and standard deviation of phyllochrons of strawberry cultivars intercropped with fig trees varied from 149.35ºC day leaf-1 ± 31.29 in the Albion cultivar to 86.34ºC day leaf-1 ± 34.74 in the Ventana cultivar. Significant differences were observed among cultivars produced in a soilless environment with higher values recorded for Albion (199.96ºC day leaf-1 ± 29.7), which required more degree-days to produce a leaf, while cv. Ventana (85.76ºC day leaf-1 ± 11.51) exhibited a lower phyllochron mean value. Based on these results, Albion requires more degree-days to issue a leaf as compared to cv. Ventana. It was conclude that strawberry cultivars can be grown intercropped with fig trees (cv. Roxo de Valinhos).
Is there any influence of breastfeeding on the cerebral blood flow? A review of 256 healthy newborns
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OBJECTIVE: To investigate whether breastfeeding influence the cerebral blood-flow velocity. MATERIALS AND METHODS: The present study included 256 healthy term neonates, all of them with appropriate weight for gestational age, 50.8% being female. Pulsatility index, resistance index and mean velocity were measured during breastfeeding or resting in the anterior cerebral artery, in the left middle cerebral artery, and in the right middle cerebral artery of the neonates between their first 10 and 48 hours of life. The data were analyzed by means of a paired t-test, Brieger's f-test for analysis of variance and linear regression, with p < 0.01 being accepted as statistically significant. RESULTS: Mean resistance index decreased as the mean velocity increased significantly during breastfeeding. Pulsatility index values decreased as much as the resistance index, but in the right middle cerebral artery it was not statistically significant. CONCLUSION: Breastfeeding influences the cerebral blood flow velocities.
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The least square method is analyzed. The basic aspects of the method are discussed. Emphasis is given in procedures that allow a simple memorization of the basic equations associated with the linear and non linear least square method, polinomial regression and multilinear method.
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The present paper aims to bring under discussion some theoretical and practical aspects about the proposition, validation and analysis of QSAR models based on multiple linear regression. A comprehensive approach for the derivation of extrathermodynamic equations is reviewed. Some examples of QSAR models published in the literature are analyzed and criticized.
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Genetic algorithm was used for variable selection in simultaneous determination of mixtures of glucose, maltose and fructose by mid infrared spectroscopy. Different models, using partial least squares (PLS) and multiple linear regression (MLR) with and without data pre-processing, were used. Based on the results obtained, it was verified that a simpler model (multiple linear regression with variable selection by genetic algorithm) produces results comparable to more complex methods (partial least squares). The relative errors obtained for the best model was around 3% for the sugar determination, which is acceptable for this kind of determination.
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The aim of this investigation is to study how Zr/Ti-PILC adsorbs metals. The physico-chemical proprieties of Zr/Ti-PILC have been optimized with pillarization processes and Cu(II), Ni(II) and Co(II) adsorption from aqueous solution has been carried out, with maximum adsorption values of 8.85, 8.30 and 7.78 x10-1 mmol g-1, respectively. The Langmuir, Freundlich and Temkin adsorption isotherm models have been applied to fit the experimental data with a linear regression process. The energetic effect caused by metal interaction was determined through calorimetric titration at the solid-liquid interface and gave a net thermal effect that enabled the calculation of the exothermic values and the equilibrium constant.
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Genetic algorithm and multiple linear regression (GA-MLR), partial least square (GA-PLS), kernel PLS (GA-KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between retention index (RI) and descriptors for 116 diverse compounds in essential oils of six Stachys species. The correlation coefficient LGO-CV (Q²) between experimental and predicted RI for test set by GA-MLR, GA-PLS, GA-KPLS and L-M ANN was 0.886, 0.912, 0.937 and 0.964, respectively. This is the first research on the QSRR of the essential oil compounds against the RI using the GA-KPLS and L-M ANN.
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Ten common doubts of chemistry students and professionals about their statistical applications are discussed. The use of the N-1 denominator instead of N is described for the standard deviation. The statistical meaning of the denominators of the root mean square error of calibration (RMSEC) and root mean square error of validation (RMSEV) are given for researchers using multivariate calibration methods. The reason why scientists and engineers use the average instead of the median is explained. Several problematic aspects about regression and correlation are treated. The popular use of triplicate experiments in teaching and research laboratories is seen to have its origin in statistical confidence intervals. Nonparametric statistics and bootstrapping methods round out the discussion.
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Glycerol, a co-product of biodiesel production, was used as a carbon source for the kinetics studies and production of biosurfactants by P. aeruginosa MSIC02. The highest fermentative parameters (Y PX = 3.04 g g-1; Y PS = 0.189 g g-1, P B = 31.94 mg L-1 h-1 and P X = 10.5 mg L-1 h-1) were obtained at concentrations of 0.4% (w/v) NaNO3 and 2% (w/v) glycerol. The rhamnolipid exhibited 80% of emulsification on kerosene, surface tension of 32.5 mN m-1, CMC = 28.2 mg L-1, C20 (concentration of surfactant in the bulk phase that produces a reduction of 20 dyn/cm in the surface tension of the solvent) = 0.99 mg L-1, Γm (surface concentration excess) = 2.4 x 10-26 mol Å-2 and S (surface area) = 70.4 Ų molecule-1 with solutions containing 10% NaCl. A mathematical model based on logistic equation was considered to representing the process. Model parameters were estimated by non-linear regression method. This approach was able to give a good description of the process.