Random regression models to estimate genetic parameters for test-day milk yield in Brazilian Murrah buffaloes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Random regression models to estimate test-day milk yield genetic parameters Holstein cows in Southeastern Brazil

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

Modeling of average growth curve in Santa Ines sheep using random regression models

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle

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

Genetic parameters for test-day yield of milk, fat and protein in buffaloes estimated by random regression models

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

Extraction of Building Roof Contours From LiDAR Data Using a Markov-Random-Field-Based Approach

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

Stretched-exponential behavior and random walks on diluted hypercubic lattices

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

Stochastic dynamics in exotic and native blowflies: an analysis combining laboratory experiments and a two-patch metapopulation model

In this study we explored the stochastic population dynamics of three exotic blowfly species, Chrysomya albiceps, Chrysomya megacephala and Chrysomya putoria, and two native species, Cochliomyia macellaria and Lucilia eximia, by combining a density-dependent growth model with a two-patch metapopulation model. Stochastic fecundity, survival and migration were investigated by permitting random variations between predetermined demographic boundary values based on experimental data. Lucilia eximia and Chrysomya albiceps were the species most susceptible to the risk of local extinction. Cochliomyia macellaria, C. megacephala and C. putoria exhibited lower risks of extinction when compared to the other species. The simultaneous analysis of stochastic fecundity and survival revealed an increase in the extinction risk for all species. When stochastic fecundity, survival and migration were simulated together, the coupled populations were synchronized in the five species. These results are discussed, emphasizing biological invasion and interspecific interaction dynamics.

A model for the plankton system of the Broa reservoir, Sao Carlos, Brazil

In this paper a model, called ELLOBO running in STELLA II, was set to describe the plankton system of the Broa reservoir (SP). The three state variables of the model are: phytoplankton, zooplankton, and the fish Astyanax fasciatus. The forcing variables are: temperature, nitrate, phosphorus and solar radiation. The model did not consider the cycling of nutrients inside the reservoir. The results show that: temperature is the principal forcing variable in the phytoplankton dynamic and in the subsequent evolution of the whole system. The zooplankton predation was described by Odum's equation, and there is a strong random component in zooplankton grazing, which was essential for the model, because zooplankton estimates have high variance. One must collect data in a short space of time (maybe daily) to better explain the zooplankton and phytoplankton variation. Validation was performed using simple statistics (arithmetic mean, standard deviation) and the results show concordance between observed and simulated values. Overhead was used to calibrate some parameters and to validate the model. The highest overhead value (5%) imply in the better accordance between estimated and;observed state variables values. We believe this approach in Broa reservoir will provide an useful tool for future research and it could be used comparatively in other continental aquatic ecosystems. (C) 2000 Elsevier B.V. B.V. All rights reserved.

Exploring community assembly through an individual-based model for trophic interactions

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Interactions of mast cell degranulating peptides with model membranes: A comparative biophysical study

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Efficiency of ethanol conversion induced by controlled modification of pore structure and acidic properties of alumina catalysts

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Analysis of beef cattle longitudinal data applying a nonlinear model

The objective of this work was to evaluate the Nelore beef cattle, growth curve parameters using the Von Bertalanffy function in a nested Bayesian procedure that allowed estimation of the joint posterior distribution of growth curve parameters, their (co)variance components, and the environmental and additive genetic components affecting them. A hierarchical model was applied; each individual had a growth trajectory described by the nonlinear function, and each parameter of this function was considered to be affected by genetic and environmental effects that were described by an animal model. Random samples of the posterior distributions were drawn using Gibbs sampling and Metropolis-Hastings algorithms. The data set consisted of a total of 145,961 BW recorded from 15,386 animals. Even though the curve parameters were estimated for animals with few records, given that the information from related animals and the structure of systematic effects were considered in the curve fitting, all mature BW predicted were suitable. A large additive genetic variance for mature BW was observed. The parameter a of growth curves, which represents asymptotic adult BW, could be used as a selection criterion to control increases in adult BW when selecting for growth rate. The effect of maternal environment on growth was carried through to maturity and should be considered when evaluating adult BW. Other growth curve parameters showed small additive genetic and maternal effects. Mature BW and parameter k, related to the slope of the curve, presented a large, positive genetic correlation. The results indicated that selection for growth rate would increase adult BW without substantially changing the shape of the growth curve. Selection to change the slope of the growth curve without modifying adult BW would be inefficient because their genetic correlation is large. However, adult BW could be considered in a selection index with its corresponding economic weight to improve the overall efficiency of beef cattle production.

Small-angle X-ray scattering and nitrogen adsorption study of the nanoporosity elimination in TEOS sonohydrolysis-derived xerogels

Small-angle X-ray scattering (SAXS) and nitrogen adsorption techniques were used to study the temperature and time structural evolution of the nanoporosity in silica xerogels prepared from acid- and ultrasound-catalyzed hydrolysis of tetraetboxysilane (TEOS). Silica xerogels present a structure of nanopores of fully random shape, size, and distribution, which can be described by an exponential correlation function gamma(r) = exp (-r/a), where a is the correlation distance, as predicted by the Debye, Anderson, and Brumberger (DAB) model. The mean pore size was evaluated as about 1.25 nm from SAXS and about 1.9 nm from nitrogen adsorption. The nanopore elimination in TEOS sonohydrolysis-derived silica xerogels is readily accelerated at temperatures around 900 degrees C probably by the action of a viscous flow mechanism. The nanopore elimination process takes place in such a way that the pore volume fraction and the specific surface are reduced while the mean pore size remains constant. (c) 2005 WILEY-VCH Verlag GmbH S Co. KGaA, Weinheim.

Buffalos milk yield analysis using random regression models

Data comprising 1,719 milk yield records from 357 females (predominantly Murrah breed), daughters of 110 sires, with births from 1974 to 2004, obtained from the Programa de Melhoramento Genetic de Bubalinos (PROMEBUL) and from records of EMBRAPA Amazonia Oriental - EAO herd, located in Belem, Para, Brazil, were used to compare random regression models for estimating variance components and predicting breeding values of the sires. The data were analyzed by different models using the Legendre's polynomial functions from second to fourth orders. The random regression models included the effects of herd-year, month of parity date of the control; regression coefficients for age of females (in order to describe the fixed part of the lactation curve) and random regression coefficients related to the direct genetic and permanent environment effects. The comparisons among the models were based on the Akaike Infromation Criterion. The random effects regression model using third order Legendre's polynomials with four classes of the environmental effect were the one that best described the additive genetic variation in milk yield. The heritability estimates varied from 0.08 to 0.40. The genetic correlation between milk yields in younger ages was close to the unit, but in older ages it was low.