Influence of data structure on the estimation of the additive genetic direct and maternal covariance for early growth traits in Nellore cattle

The objective of the present study was to investigate the effect of data structure on estimated genetic parameters and predicted breeding values of direct and maternal genetic effects for weaning weight (WW) and weight gain from birth to weaning (BWG), including or not the genetic covariance between direct and maternal effects. Records of 97,490 Nellore animals born between 1993 and 2006, from the Jacarezinho cattle raising farm, were used. Two different data sets were analyzed: DI_all, which included all available progenies of dams without their own performance; DII_all, which included DI_all + 20% of recorded progenies with maternal phenotypes. Two subsets were obtained from each data set (DI_all and DII_all): DI_1 and DII_1, which included only dams with three or fewer progenies; DI_5 and DII_5, which included only dams with five or more progenies. (Co)variance components and heritabilities were estimated by Bayesian inference through Gibbs sampling using univariate animal models. In general, for the population and traits studied, the proportion of dams with known phenotypic information and the number of progenies per dam influenced direct and maternal heritabilities, as well as the contribution of maternal permanent environmental variance to phenotypic variance. Only small differences were observed in the genetic and environmental parameters when the genetic covariance between direct and maternal effects was set to zero in the data sets studied. Thus, the inclusion or not of the genetic covariance between direct and maternal effects had little effect on the ranking of animals according to their breeding values for WW and BWG. Accurate estimation of genetic correlations between direct and maternal genetic effects depends on the data structure. Thus, this covariance should be set to zero in Nellore data sets in which the proportion of dams with phenotypic information is low, the number of progenies per dam is small, and pedigree relationships are poorly known. (c) 2012 Elsevier B.V. All rights reserved.

Estimation of genetic parameters for milk yield in Murrah buffaloes by Bayesian inference

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Estimation models of variance components for farrowing interval in swine

Este trabalho teve como objetivo principal avaliar a importância da inclusão dos efeitos genético materno, comum de leitegada e de ambiente permanente no modelo de estimação de componentes de variância para a característica intervalo de parto em fêmeas suínas. Foram utilizados dados que consistiam de 1.013 observações de fêmeas Dalland (C-40), registradas em dois rebanhos. As estimativas dos componentes de variância foram realizadas pelo método da máxima verossimilhança restrita livre de derivadas. Foram testados oito modelos, que continham os efeitos fixos (grupos de contemporâneo e covariáveis) e os efeitos genético aditivo direto e residual, mas variavam quanto à inclusão dos efeitos aleatórios genético materno, ambiental comum de leitegada e ambiental permanente. O teste da razão de verossimilhança (LR) indicou a não necessidade da inclusão desses efeitos no modelo. No entanto observou-se que o efeito ambiental permanente causou mudança nas estimativas de herdabilidade, que variaram de 0,00 a 0,03. Conclui-se que os valores de herdabilidade obtidos indicam que esta característica não apresentaria ganho genético como resposta à seleção. O efeito ambiental comum de leitegada e o genético materno não apresentaram influência sobre esta característica. Já o ambiental permanente, mesmo sem ter sido significativo o seu efeito pelo LR, deve ser considerado nos modelos genéticos para essa característica, pois sua presença causou mudança nas estimativas da variância genética aditiva.

Comparison of methodologies for degree-day estimation using numerical methods

O desenvolvimento de projetos relacionados ao desempenho de diversas culturas tem recebido aperfeiçoamento cada vez maior, incorporado a modelos matemáticos sendo indispensável à utilização de equações cada vez mais consistentes que possibilitem previsão e maior aproximação do comportamento real, diminuindo o erro na obtenção das estimativas. Entre as operações unitárias que demandam maior estudo estão aquelas relacionadas com o crescimento da cultura, caracterizadas pela temperatura ideal para o acréscimo de matéria seca. Pelo amplo uso dos métodos matemáticos na representação, análise e obtenção de estimativas de graus-dia, juntamente com a grande importância que a cultura da cana-de-açúcar tem para a economia brasileira, foi realizada uma avaliação dos modelos matemáticos comumente usados e dos métodos numéricos de integração na estimativa da disponibilidade de graus-dia para essa cultura, na região de Botucatu, Estado de São Paulo. Os modelos de integração, com discretização de 6 em 6 h, apresentaram resultados satisfatórios na estimativa de graus-dia. As metodologias tradicionais apresentaram desempenhos satisfatórios quanto à estimativa de grausdia com base na curva de temperatura horária para cada dia e para os agrupamentos de três, sete, 15 e 30 dias. Pelo método numérico de integração, a região de Botucatu, Estado de São Paulo, apresentou disponibilidade térmica anual média de 1.070,6 GD para a cultura da cana-de-açúcar.

Estimation and evaluation of dynamic properties as indicators of changes on soil structure in sugarcane fields of São Paulo State - Brazil

The indiscriminate management and use of soils without moisture control has changed the structure of it due to the increment of the traffic by agricultural machines through the years, causing in consequence, a soil compaction and yield reduction in the areas of intensive traffic. The purpose of this work was to estimate and to evaluate the performance of preconsolidation pressure of the soil and shear stress as indicators of changes on soil structure in fields cropped with sugarcane, as well as the impact of management processes in an Eutrorthox soil structure located in São Paulo State. The experimental field was located in Piracicaba's rural area (São Paulo State, Brazil) and has been cropped with sugarcane, in the second harvest cycle. The soil was classified by Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA) [Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), 1999. Centro Nacional de Pesquisa de Solos. Sistema Brasileiro de Classificao de Solos, Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), Brasilia, 412 pp.] as an Eutrorthox. Undisturbed samples were collected and georeferenced in a grid of 60 m x 60 m from two depths: 0-0.10 m (superficial layer - SL) and in the layer of greatest mechanical resistance (LGMR), previously identified by cone index (CI). The investigated variables were pressure preconsolidation (sigma(p)), apparent cohesion (c) and internal friction angle (phi). The conclusions from the results were that the SLSC was predicted satisfactorily from up as a function of soil moisture; thus, decisions about machinery size and loading (contact pressures) can be taken. Apparent cohesion (c), internal friction angle (phi) and the Coulomb equation were significantly altered by traffic intensity. The sigma(p), c and phi maps were shown to be important tools to localize and visualize soil compaction and mechanical resistance zones. They constitute a valuable resource to evaluate the traffic impact in areas cropped with sugarcane in State of São Paulo, Brazil. (C) 2008 Elsevier B.V. All rights reserved.

Step Counting and Energy Expenditure Estimation in Patients With Chronic Obstructive Pulmonary Disease and Healthy Elderly: Accuracy of 2 Motion Sensors

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Estimation of Maximal Work Rate Based on the 6-Minute Walk Test and Fat-Free Mass in Chronic Obstructive Pulmonary Disease

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Tungsten permanent chemical modifier for fast estimation of Se contents in soil by graphite furnace atomic absorption spectrometry

A tungsten carbide coating on the integrated platform of a transversely heated graphite atomizer was used as a modifier for the direct determination of Se in soil extracts by graphite furnace atomic absorption spectrometry. Diethylenetriaminepentaacetic acid (0.0050 mol L-1) plus ammonium hydrogencarbonate (1.0 mol L-1) extracted predominantly available inorganic selenate from soil. The formation of a large amount of carbonaceous residue inside the atomizer was avoided with a first pyrolysis step at 600 degreesC assisted by air during 30 s. For 20 muL of soil extracts delivered to the atomizer and calibration by matrix matching, an analytical curve (10.0-100 mug of L-1) with good linear correlation (r = 0.999) between integrated absorbance and analyte concentration was established. The characteristic mass was similar to63 pg of Se, and the lifetime of the tube was similar to750 firings. The limit of detection was 1.6 mug L-1, and the relative standard deviations (n = 12) were typically <4% for a soil extract containing 50 mug of L-1. The accuracy of the determination of Se was checked for soil samples by means of addition/recovery tests. Recovery data of Se added to four enriched soil samples varied from 80 to 90% and indicated an accurate method.

A neural network approach for robust nonlinear parameter estimation in presence of unknown-but-bounded errors

Systems based on artificial neural networks have high computational rates due to the use of a massive number of simple processing elements and the high degree of connectivity between these elements. This paper presents a novel approach to solve robust parameter estimation problem for nonlinear model with unknown-but-bounded errors and uncertainties. More specifically, a modified Hopfield network is developed and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the network convergence to the equilibrium points. A solution for the robust estimation problem with unknown-but-bounded error corresponds to an equilibrium point of the network. Simulation results are presented as an illustration of the proposed approach. Copyright (C) 2000 IFAC.

Using neural networks for estimation of aquifer dynamical behavior

The systems of water distribution from groundwater wells can be monitored using the changes observed on its dynamical behavior. In this paper, artificial neural networks are used to estimate the depth of the dynamical water level of groundwater wells in relation to water flow, operation time and rest time. Simulation results are presented to demonstrate the validity of the proposed approach. These results have shown that artificial neural networks can be effectively used for the identification and estimation of parameters related to systems of water distribution.

Neural network based estimation of torque in induction motors for real-time applications

Induction motors are largely used in several industry sectors. The selection of an induction motor has still been inaccurate because in most of the cases the load behavior in its shaft is completely unknown. The proposal of this article is to use artificial neural networks for torque estimation with the purpose of best selecting the induction motors rather than conventional methods, which use classical identification techniques and mechanical load modeling. Since proposed approach estimates the torque behavior from the transient to the steady state, one of its main contributions is the potential to also be implemented in control schemes for real-time applications. Simulation results are also presented to validate the proposed approach.

A novel approach to robust parameter estimation using neurofuzzy systems

A novel approach for solving robust parameter estimation problems is presented for processes with unknown-but-bounded errors and uncertainties. An artificial neural network is developed to calculate a membership set for model parameters. Techniques of fuzzy logic control lead the network to its equilibrium points. Simulated examples are presented as an illustration of the proposed technique. The result represent a significant improvement over previously proposed methods. (C) 1999 IMACS/Elsevier B.V. B.V. All rights reserved.

Stratified Sampling Applied to Estimation of the Volumetric Fraction of Alumina in Cast Metal Matrix Composites

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Unscented Kalman Filter Applied to the Spacecraft Attitude Estimation with Euler Angles

The aim of this work is to test an algorithm to estimate, in real time, the attitude of an artificial satellite using real data supplied by attitude sensors that are on board of the CBERS-2 satellite (China Brazil Earth Resources Satellite). The real-time estimator used in this work for attitude determination is the Unscented Kalman Filter. This filter is a new alternative to the extended Kalman filter usually applied to the estimation and control problems of attitude and orbit. This algorithm is capable of carrying out estimation of the states of nonlinear systems, without the necessity of linearization of the nonlinear functions present in the model. This estimation is possible due to a transformation that generates a set of vectors that, suffering a nonlinear transformation, preserves the same mean and covariance of the random variables before the transformation. The performance will be evaluated and analyzed through the comparison between the Unscented Kalman filter and the extended Kalman filter results, by using real onboard data.

Fault section estimation in electric power systems using an optimization immune algorithm

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)