Estimates of genetic parameters for scrotal circumference using random regression models in Nelore cattle

A total of 15,901 scrotal circumference (SC) records from 5300 Nelore bulls, ranging from 229 to 560 days of age, were used with the objective of estimating (co)variance functions for SC, using random regression models. Models included the fixed effects of contemporary group and age of dam at calving as covariable (linear and quadratic effects). To model the population mean trend, a third order Legendre polynomial on animal age was utilized. The direct additive genetic and animal permanent environmental random effects were modeled by Legendre polynomials on animal age, with orders of fit ranging from 1 to 5. Residual variances were modeled considering 1 (homogeneity of variance) or 4 age classes. Results obtained with the random regression models were compared to multi-trait analysis. (Co)variance estimates using multi-trait and random regression models were similar. The model considering a third- and fifth-order Legendre polynomials for additive genetic and animal permanent environmental effects, respectively, was the most adequate to model changes in variance of SC with age. Heritability estimates for SC ranged from 0.24 (229 days of age) to 0.47 (300 days of age), remained almost constant until 500 days of age (0.52), decreasing thereafter (0.44). In general, the genetic correlations between measures of scrotal circumference obtained from 229 to 560 days of age decreased with increasing distance between ages. For genetic evaluation scrotal circumference could be measured between 400 and 500 days of age. (C) 2010 Elsevier B.V. All rights reserved.

Random regression analyses using B-splines functions to model growth from birth to adult age in Canchim cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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)

Variance component estimates applying random regression models for test-day milk yield in Caracu heifers (Bos taurus Artiodactyla, Bovidae)

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)

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Random regression models using different functions to model test-day milk yield of Brazilian Holstein cows

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

Milk yield persistency in Brazilian Gyr cattle based on a random regression model

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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)

Determination of fiber length and juvenile and mature wood zones from Hevea brasiliensis trees grown in Brazil

The aim of this study was to verify the average fiber length and the juvenile and mature wood zones from Hevea brasiliensis proveniences from a reforestation area in São Paulo, Brazil. For this purpose, five Hevea brasiliensis trees were randomly collected from a 50-year-old plantation, located in Balsamo, São Paulo, Brazil. The trees were cut and five flat sawn boards were obtained. The juvenile and mature wood zones were determined by fiber length measurement from the pith to the bark. The results showed that: (a) the juvenile wood of this species occurred approx. between 40 and 55 mm, from the pith, and from this point forward, the mature wood zone was found; (b) there was a significant difference between the average fiber length of juvenile wood (1.26 mm) and mature wood (1.51 mm).

Aplicação de técnicas de aprendizado de máquina no reconhecimento de classes estruturais de proteínas

Nowadays, classifying proteins in structural classes, which concerns the inference of patterns in their 3D conformation, is one of the most important open problems in Molecular Biology. The main reason for this is that the function of a protein is intrinsically related to its spatial conformation. However, such conformations are very difficult to be obtained experimentally in laboratory. Thus, this problem has drawn the attention of many researchers in Bioinformatics. Considering the great difference between the number of protein sequences already known and the number of three-dimensional structures determined experimentally, the demand of automated techniques for structural classification of proteins is very high. In this context, computational tools, especially Machine Learning (ML) techniques, have become essential to deal with this problem. In this work, ML techniques are used in the recognition of protein structural classes: Decision Trees, k-Nearest Neighbor, Naive Bayes, Support Vector Machine and Neural Networks. These methods have been chosen because they represent different paradigms of learning and have been widely used in the Bioinfornmatics literature. Aiming to obtain an improvment in the performance of these techniques (individual classifiers), homogeneous (Bagging and Boosting) and heterogeneous (Voting, Stacking and StackingC) multiclassification systems are used. Moreover, since the protein database used in this work presents the problem of imbalanced classes, artificial techniques for class balance (Undersampling Random, Tomek Links, CNN, NCL and OSS) are used to minimize such a problem. In order to evaluate the ML methods, a cross-validation procedure is applied, where the accuracy of the classifiers is measured using the mean of classification error rate, on independent test sets. These means are compared, two by two, by the hypothesis test aiming to evaluate if there is, statistically, a significant difference between them. With respect to the results obtained with the individual classifiers, Support Vector Machine presented the best accuracy. In terms of the multi-classification systems (homogeneous and heterogeneous), they showed, in general, a superior or similar performance when compared to the one achieved by the individual classifiers used - especially Boosting with Decision Tree and the StackingC with Linear Regression as meta classifier. The Voting method, despite of its simplicity, has shown to be adequate for solving the problem presented in this work. The techniques for class balance, on the other hand, have not produced a significant improvement in the global classification error. Nevertheless, the use of such techniques did improve the classification error for the minority class. In this context, the NCL technique has shown to be more appropriated

Produção da figueira submetida a diferentes épocas de poda e irrigação

O trabalho teve como objetivo avaliar diferentes épocas de poda, correspondentes aos meses de julho, agosto, setembro e outubro dos anos de 2004/05 e 2005/06, com e sem o uso de irrigação, em figueira 'Roxo de Valinhos', no município de Botucatu-SP. Para atingir tal objetivo, adotou-se o delineamento experimental em parcelas subdivididas, com 5 repetições em blocos, onde as parcelas corresponderam aos tratamentos com e sem irrigação, e as subparcelas foram constituídas pelas podas realizadas nos quatro meses do ano. Foram avaliadas características de produção e alguns atributos de qualidade, que serviram para indicar a necessidade do uso de irrigação. Os resultados obtidos permitiram concluir que, na avaliação do desdobramento da interação entre épocas de poda e irrigação complementar, o mês de agosto, com o uso de irrigação complementar, foi o mais favorável para a realização da poda da figueira, proporcionando as maiores produções médias verificadas no ensaio, tanto no ciclo agrícola de 2004/05 (3.513,8 g planta-1), quanto em 2005/06 (4.110,7 g planta-1). em condições não-irrigadas, não houve diferença estatística entre os meses de julho, agosto e setembro de 2004/05 e entre julho e agosto de 2005/06.

Carbon-13 turnover in 'roxo de valinhos' fig trees

The aim of this study was to assess carbon-13 turnover in different organs of the fig tree, 'Roxo de Valinhos' cultivar. The experiment was carried out in an orchard at School of Agronomical Sciences, FCA/UNESP, Botucatu Campus, State of São Paulo, Brazil. The main photosynthetically active leaf was previously determined based on gas exchanges by means of an open portable photosynthesis system, IRGA. That leaf was placed in a chamber where the enriched gas injection occurred. The leaf enrichment time was 30 minutes. Treatments were constituted of seven fig trees removed from the soil after: 6; 24; 48; 72; 120; 168 and 360 hours of enrichment using (13)C, and their parts were sectioned into: apical bud, young leaves, adult leaves (photosynthetically active), lateral sprouts, fruits, and branch. The results allowed the establishment of the carbon-13 metabolism sequence in the studied parts: Young leaves > Fruits > Sprouts > Adult leaves > Apical bud > branch > Labeled leaf. 'Roxo de Valinhos' fig trees, had (13)C turnover of 24 hours and carbon-13 half-time shorter than 11 hours.