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 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)

Modelos de regressão aleatória na avaliação genética do crescimento de ovinos da raça Santa Inês

Utilizaram-se 17.767 registros de peso de 4.210 cordeiros da raça Santa Inês com o objetivo de comparar modelos de regressão aleatória com diferentes estruturas para modelar a variância residual em estudos genéticos da curva de crescimento. Os efeitos fixos incluídos na análise foram: grupo contemporâneo e idade da ovelha no parto. As regressões fixas e aleatórias foram ajustadas por meio de polinômios de Legendre de ordens 4 e 3, respectivamente. A variância residual foi ajustada por meio de classes heterogêneas e por funções de variância empregando polinômios ordinários e de Legendre de ordens 2 a 8. O modelo considerando homogeneidade de variâncias residuais mostrou-se inadequado. de acordo com os critérios utilizados, a variância residual contendo sete classes heterogêneas proporcionou melhor ajuste, embora um mais parcimonioso, com cinco classes, pudesse ser utilizado sem perdas na qualidade de ajuste da variância nos dados. O ajuste de funções de variância com qualquer ordem foi melhor que o obtido por meio de classes. O polinômio ordinário de ordem 6 proporcionou melhor ajuste entre as estruturas testadas. A modelagem do resíduo interferiu nas estimativas de variâncias e parâmetros genéticos. Além da alteração da classificação dos reprodutores, a magnitude dos valores genéticos preditos apresenta variações significativas, de acordo com o ajuste da variância residual empregado.

Efeito da idade da vaca e da data juliana de nascimento sobre o ganho médio diário de bezerros de corte no período pré-desmame

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Classificação de imagens de ambientes coralinos: uma abordagem empregando uma combinação de classificadores e máquina de vetor de suporte

The use of the maps obtained from remote sensing orbital images submitted to digital processing became fundamental to optimize conservation and monitoring actions of the coral reefs. However, the accuracy reached in the mapping of submerged areas is limited by variation of the water column that degrades the signal received by the orbital sensor and introduces errors in the final result of the classification. The limited capacity of the traditional methods based on conventional statistical techniques to solve the problems related to the inter-classes took the search of alternative strategies in the area of the Computational Intelligence. In this work an ensemble classifiers was built based on the combination of Support Vector Machines and Minimum Distance Classifier with the objective of classifying remotely sensed images of coral reefs ecosystem. The system is composed by three stages, through which the progressive refinement of the classification process happens. The patterns that received an ambiguous classification in a certain stage of the process were revalued in the subsequent stage. The prediction non ambiguous for all the data happened through the reduction or elimination of the false positive. The images were classified into five bottom-types: deep water; under-water corals; inter-tidal corals; algal and sandy bottom. The highest overall accuracy (89%) was obtained from SVM with polynomial kernel. The accuracy of the classified image was compared through the use of error matrix to the results obtained by the application of other classification methods based on a single classifier (neural network and the k-means algorithm). In the final, the comparison of results achieved demonstrated the potential of the ensemble classifiers as a tool of classification of images from submerged areas subject to the noise caused by atmospheric effects and the water column

Exigências de triptofano e padrão de recuperação do desempenho de poedeiras comerciais após alimentação com rações deficientes em triptofano

Este experimento foi conduzido para avaliar as exigências de triptofano e o padrão de recuperação do desempenho de poedeiras alimentadas com rações deficientes em triptofano. Foram utilizadas 160 poedeiras comerciais da linhagem Hisex White distribuídas em um delineamento inteiramente casualizado com cinco níveis de triptofano nas dietas (0,13; 0,15; 0,17; 0,19 e 0,21%), com oito repetições de quatro aves. As poedeiras permaneceram por duas semanas em adaptação (51 a 52 semanas), por seis semanas para avaliação da exigência de triptofano (53 a 58 semanas) e por quatro semanas para determinação do padrão de recuperação do desempenho (59 a 62 semanas). A produção e a massa de ovos foram prejudicadas quando as poedeiras foram alimentadas com rações contendo 0,13% de triptofano, no entanto, o desempenho foi recuperado após uma semana de alimentação com ração contendo 0,21% desse aminoácido. A qualidade interna dos ovos não foi influenciada pelos níveis de triptofano estudados (ingestão de 137,1 a 228,0 mg triptofano/dia). As exigências de triptofano foram estabelecidas entre 161 e 188 mg/dia, dependendo da característica avaliada (produção ou massa de ovos) e do modelo de regressão aplicado (polinomial, exponencial ou segmentado).

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

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Metodologia estatística na solução do problema do caixeiro viajante e na avaliação de algoritmos : um estudo aplicado à transgenética computacional

The problems of combinatory optimization have involved a large number of researchers in search of approximative solutions for them, since it is generally accepted that they are unsolvable in polynomial time. Initially, these solutions were focused on heuristics. Currently, metaheuristics are used more for this task, especially those based on evolutionary algorithms. The two main contributions of this work are: the creation of what is called an -Operon- heuristic, for the construction of the information chains necessary for the implementation of transgenetic (evolutionary) algorithms, mainly using statistical methodology - the Cluster Analysis and the Principal Component Analysis; and the utilization of statistical analyses that are adequate for the evaluation of the performance of the algorithms that are developed to solve these problems. The aim of the Operon is to construct good quality dynamic information chains to promote an -intelligent- search in the space of solutions. The Traveling Salesman Problem (TSP) is intended for applications based on a transgenetic algorithmic known as ProtoG. A strategy is also proposed for the renovation of part of the chromosome population indicated by adopting a minimum limit in the coefficient of variation of the adequation function of the individuals, with calculations based on the population. Statistical methodology is used for the evaluation of the performance of four algorithms, as follows: the proposed ProtoG, two memetic algorithms and a Simulated Annealing algorithm. Three performance analyses of these algorithms are proposed. The first is accomplished through the Logistic Regression, based on the probability of finding an optimal solution for a TSP instance by the algorithm being tested. The second is accomplished through Survival Analysis, based on a probability of the time observed for its execution until an optimal solution is achieved. The third is accomplished by means of a non-parametric Analysis of Variance, considering the Percent Error of the Solution (PES) obtained by the percentage in which the solution found exceeds the best solution available in the literature. Six experiments have been conducted applied to sixty-one instances of Euclidean TSP with sizes of up to 1,655 cities. The first two experiments deal with the adjustments of four parameters used in the ProtoG algorithm in an attempt to improve its performance. The last four have been undertaken to evaluate the performance of the ProtoG in comparison to the three algorithms adopted. For these sixty-one instances, it has been concluded on the grounds of statistical tests that there is evidence that the ProtoG performs better than these three algorithms in fifty instances. In addition, for the thirty-six instances considered in the last three trials in which the performance of the algorithms was evaluated through PES, it was observed that the PES average obtained with the ProtoG was less than 1% in almost half of these instances, having reached the greatest average for one instance of 1,173 cities, with an PES average equal to 3.52%. Therefore, the ProtoG can be considered a competitive algorithm for solving the TSP, since it is not rare in the literature find PESs averages greater than 10% to be reported for instances of this size.

Animal performance and carcass characteristics of Nellore young bulls fed coated or uncoated urea slaughtered at different weights

The objective of this study was to evaluate animal performance and carcass characteristics of 64 Nellore young bulls at 22 months of age finished in a feedlot and slaughtered at five body weights (350; 455; 485; 555 and 580 kg) fed diets containing coated or uncoated urea. The experimental design adopted was completely randomized, set in a 4 × 2 factorial arrangement, and for the variables assessed in the control animals, it was 5 × 2. No effect of interaction between slaughter weights and diets were observed, so the variables were analyzed separately, compared by polynomial contrasts and by the F test, respectively. The time animals remained in the feedlot to reach slaughter weights was 66, 88, 145 and 194 days. Average daily gain (ADG) showed quadratic behavior, with a maximum of 1.44 kg/day with animals of 491.7 kg. Dry matter intake (DMI) (kg/day) was similar in all the treatments, but it decreased linearly as body weight increased. The bionutritional efficiency worsened linearly as body weight rose. The elevation in slaughter weight resulted in linear decrease in the percentage of beef round and increase in forequarter. Backfat thickness and rib eye area of the longissimus increased linearly and the percentages of muscle and protein in the carcass reduced and those of fat and ether extract increased linearly as body weight increased. Average daily gain, DMI, feed efficiency and carcass characteristics were not affected by diets containing coated or uncoated urea. However, animals fed coated urea presenter better crude fiber and neutral detergent fiber intake.

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)

Genetic parameter estimates for live weight and daily live weight gain obtained for Nellore bulls in a test station using different models

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)

Produção de β-ecdisona em Pfaffia glomerata (Spreng.) Pedersen em função da adubação orgânica em 6 épocas de crescimento

O trabalho teve como objetivo verificar a influência da adubação orgânica em 6 épocas de crescimento na produção de β-ecdisona por plantas de Pfaffia glomerata. O experimento foi conduzido na Fazenda Santo Antonio do Araquá, distrito de Catâneo Ângelo, município de São Manuel, São Paulo, Brasil. Utilizou-se o delineamento de blocos ao acaso, num esquema fatorial 5x6, com quatro repetições, considerando-se 8 plantas úteis por parcela. Os blocos foram constituídos de 6 épocas de crescimento (60, 120, 180, 240, 300 e 360 dias após a germinação) e de 5 doses de esterco de galinha curtido [testemunha (sem adubação), 15, 30, 45 e 60 t ha-1]. Após cada colheita, as raízes das plantas foram secas em estufa com circulação de ar forçada a 40ºC e pesadas para posterior extração do β-ecdisona, seguindo metodologia desenvolvida por Magalhães (2000). Os resultados foram submetidos à análise de variância e ao teste de separação de médias de Scott Knott, todos a 5% de probabilidade. Quando ocorreu interação os resultados foram avaliados usando-se análise de regressão polinominal. O teor de β-ecdisona não foi influenciado pelas doses de adubo e nem pela época do crescimento das plantas. Porém a quantidade total de β-ecdisona por raiz foi influenciada pela época de crescimento, sendo que aos 360 dias após a emergência ocorreu uma maior quantidade do princípio ativo em todos os tratamentos. Apesar de não diferir estatisticamente dos demais tratamentos, aos 360 dias após a emergência das plantas, o tratamento 30 t ha-1 foi o que proporcionou maior quantidade de β-ecdisona.