Digestibilidade e ganhos em peso de ovinos alimentados com diferentes fontes de volumosos e recebendo somatotropina recombinante bovina (rBST)

O objetivo deste trabalho foi avaliar os efeitos da aplicação de 20 mg de somatotropina recombinante bovina (rBST) de liberação lenta, em períodos de 14 e 28 dias, sobre a ingestão de matéria seca, os coeficientes de digestibilidade de matéria seca (MS), fibra em detergente ácido (FDA), proteína bruta (PB) e energia bruta (EB), o balanço de nitrogênio e o ganho de peso diário, em rações à base de silagem de milho, cana-de-açúcar ou bagaço hidrolisado e concentrado. Foi usado um total de 24 borregos mestiços, não-castrados, com média de 4 a 5 meses de idade e 22 ± 2 kg de PV. Não houve efeito da rBST na ingestão de matéria seca, nas digestibilidades de PB e FDA, no balanço de nitrogênio e no ganho de peso diário dos borregos. A digestibilidade da energia bruta foi influenciada pela aplicação de rBST, quando os diferentes volumosos ou períodos pós-aplicação hormonal foram considerados, porém, somente foi observado efeito da ação hormonal sobre a digestibilidade de MS nas dietas à base de silagem de milho.

Signal transduction-related responses to phytohormones and environmental challenges in sugarcane

Background: Sugarcane is an increasingly economically and environmentally important C4 grass, used for the production of sugar and bioethanol, a low-carbon emission fuel. Sugarcane originated from crosses of Saccharum species and is noted for its unique capacity to accumulate high amounts of sucrose in its stems. Environmental stresses limit enormously sugarcane productivity worldwide. To investigate transcriptome changes in response to environmental inputs that alter yield we used cDNA microarrays to profile expression of 1,545 genes in plants submitted to drought, phosphate starvation, herbivory and N-2-fixing endophytic bacteria. We also investigated the response to phytohormones (abscisic acid and methyl jasmonate). The arrayed elements correspond mostly to genes involved in signal transduction, hormone biosynthesis, transcription factors, novel genes and genes corresponding to unknown proteins.Results: Adopting an outliers searching method 179 genes with strikingly different expression levels were identified as differentially expressed in at least one of the treatments analysed. Self Organizing Maps were used to cluster the expression profiles of 695 genes that showed a highly correlated expression pattern among replicates. The expression data for 22 genes was evaluated for 36 experimental data points by quantitative RT-PCR indicating a validation rate of 80.5% using three biological experimental replicates. The SUCAST Database was created that provides public access to the data described in this work, linked to tissue expression profiling and the SUCAST gene category and sequence analysis. The SUCAST database also includes a categorization of the sugarcane kinome based on a phylogenetic grouping that included 182 undefined kinases.Conclusion: An extensive study on the sugarcane transcriptome was performed. Sugarcane genes responsive to phytohormones and to challenges sugarcane commonly deals with in the field were identified. Additionally, the protein kinases were annotated based on a phylogenetic approach. The experimental design and statistical analysis applied proved robust to unravel genes associated with a diverse array of conditions attributing novel functions to previously unknown or undefined genes. The data consolidated in the SUCAST database resource can guide further studies and be useful for the development of improved sugarcane varieties.

Transcription profiling of signal transduction-related genes in sugarcane tissues

A collection of 237,954 sugarcane ESTs was examined in search of signal transduction genes. Over 3,500 components involved in several aspects of signal transduction, transcription, development, cell cycle, stress responses and pathogen interaction were compiled into the Sugarcane Signal Transduction (SUCAST) Catalogue. Sequence comparisons and protein domain analysis revealed 477 receptors, 510 protein kinases, 107 protein phosphatases, 75 small GTPases, 17 G-proteins, 114 calcium and inositol metabolism proteins, and over 600 transcription factors. The elements were distributed into 29 main categories subdivided into 409 sub-categories. Genes with no matches in the public databases and of unknown function were also catalogued. A cDNA microarray was constructed to profile individual variation of plants cultivated in the field and transcript abundance in six plant organs (flowers, roots, leaves, lateral buds, and 1(st) and 4(th) internodes). From 1280 distinct elements analyzed, 217 (17%) presented differential expression in two biological samples of at least one of the tissues tested. A total of 153 genes (12%) presented highly similar expression levels in all tissues. A virtual profile matrix was constructed and the expression profiles were validated by real-time PCR. The expression data presented can aid in assigning function for the sugarcane genes and be useful for promoter characterization of this and other economically important grasses.

Suckling and allosuckling in river buffalo calves and its relation with weight gain

The aim of the present study was to investigate if river buffalo calves (Bubalus bubalis) have equal access to all cows and if milk is thus equally available to all of them. We recorded suckling/allosuckling behaviour and weight gain (WG) of 29 calves (14 males and 15 females), with special consideration to their sex, birth order (BO) and age. Cows' nursing behaviour and milli production (MP) were also considered. While males tended to be born earlier than females during this study, this was not the trend in the overall herd records. The cows' MP was not effected by the calves' sex. However, bull-calves presented greater mean WG, and mean times spent in individual filial (IF) and in communal nonfilial (CNF) suckling than heifer-calves, which showed greater communal filial (CF) suckling than the former during the first 4 months of life. The WG was associated with IF for bull-calves (r = 0.680 and 0.765, respectively, for the periods from birth to 4th and 8th months of age), and to CNF for heifer-calves (r = 0.628, for the period from birth to 8th month). Results from multiple regression analysis showed independent effects of each suckling category on the calf WG, and such effects were variable according to the calf's sex. BO was negatively correlated to calves' WG (bull-calves: r(s) = - 0.873 and - 0.799, from birth to 4th and gth months, respectively; heifer-calves: r(s) = - 0.531 from birth to 4th month). Specifically for bull-calves, there was a positive correlation between BO and MP (r(s) = 0.528 and 0.633, from birth to 4th and 8th months of age, respectively). The correlation between BO and IF was negative in both sexes, indicating that calves that were born early had more opportunities to suckle individually from their mothers. For heifer-calves, BO was positively correlated with CF (two periods), and negatively with CNF (from birth to 8th month of age), suggesting that heifer-calves were most often accompanied by other calves during suckling when they were born later. The data taken together indicate that sex and/or BO influenced decisively social interactions during suckling, promoting differential development among the calves. In animal husbandry, if a homogenous WG is desired, these factors have to be taken into consideration. (C) 2000 Elsevier B.V. B.V. All rights reserved.

Fatores ambientais e estimativa de herdabilidade para o intervalo desmame-cio de fêmeas suínas

Este trabalho foi realizado com os objetivos de avaliar a influência de fatores ambientais e estimar a herdabilidade para a característica intervalo desmame-cio (IDC) de fêmeas suínas. Para isso, utilizaram-se 1.032 observações de 347 porcas Dalland (C-40), pertencentes a dois rebanhos. No modelo, incluíram-se como aleatórios os efeitos do pai e da mãe da porca e, como fixos, os efeitos do ano de parto, do rebanho e da estação de parição, bem como as co-variáveis idade da porca ao parto, tamanho da leitegada ao nascer e período de lactação. As estimativas dos componentes de variância e do parâmetro genético foram obtidas utilizando-se o aplicativo MTDFREML, que emprega a metodologia da máxima verossimilhança restrita livre de derivadas. A média foi de 5,3 dias, com um coeficiente de variação de 71,44%. O período de lactação teve influência linear sobre o IDC. do mesmo modo, a regressão quadrática do IDC em relação à idade da porca ao parto foi significativa. O pai e a mãe foram importantes fontes de variação no intervalo desmame-cio, que, provavelmente pelo fato de acontecer tardiamente na vida do animal, não foi influenciado pelo rebanho, pelo ano e pela estação. A estimativa de herdabilidade para o primeiro intervalo desmame-cio foi de 0,11, o que indica que esta característica não apresentaria ganho genético satisfatório como resposta à seleção individual.

Efeitos genéticos e não-genéticos sobre o intervalo de parto em fêmeas suínas no Sudeste do Brasil

The effect of environmental and genetic effects on the farrowing interval in Dalland (C-40) sows in the Southeast of Brazil was studied. Data consisting of 1,013 farrowing intervals recorded in two herds were analyzed, using a model that included the sire and the dam as random effects and the year of farrowing, the herd and the farrowing season as fixed effects, plus the covariables sow's age at farrowing, litter size at birth, lactation length and weaning-estrus interval. For the farrowing interval first only, variance components were estimated by REML, with an animal model that included, as fixed effect, a contemporary group and, as random effects, the additive genetic variance and the error. The mean farrowing interval was 140.9+5.7 days, with a 4.0% coefficient of variation. Variance analysis showed no effect of either year, season of farrowing or herd on the farrowing interval. The sire effect was not important for the farrowing interval, but the dam represented an important source of variation. The total number of piglets born and the sow's age at farrowing had no influence on the farrowing interval. The length of lactation exerted an influence on the farrowing interval, accounting for 19.4% of the total variation of this trait. Likewise, the linear regression of the weaning-estrus interval in relation to the farrowing interval was highly significant, accounting for 51.7% of the total variation. The heritability estimate was 0.00, suggesting that no genetic gain can be obtained by selection for a shorter farrowing interval.

Estimativa de ganho genético a partir de diferenciais de seleção e parâmetros populacionais em um rebanho Caracu

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Equações de predição da composição química corporal a partir do corte da 9-10-11ª costelas de bovinos castrados Nelore

Objetivou-se obter equações de regressão linear simples para estimativa da composição química corporal de novilhos Nelore a partir da composição química do corte da 9-10-11ª costelas. Foram utilizados 27 bovinos em confinamento, com 21 a 31 meses de idade e 338,0 a 503,6 kg de peso corporal. do total, foram abatidos seis animais (referência) ao início do experimento para estimativa da composição química corporal. A composição química em água, proteína, EE e cinzas foi determinada no corte da 9-10-11ª costelas e nos tecidos corporais. As equações de regressão para estimativa do peso de corpo vazio (PCVZ) a partir dos pesos de jejum (PV) e carcaça quente (PCQ) foram PCVZ = 0,8726 PV - 2,7399 e PCVZ = 1,5350 PCQ + 13,598 (R² = 0,98). O ganho de 1 kg de PCVZ correspondeu a aproximadamente 1,15 kg de PV. A porcentagem de água no corpo vazio (CVz) esteve altamente correlacionada às porcentagens de água (R² = 0,98) e EE (R² = 0,91) no corte das costelas. A equação mais indicada foi a desenvolvida a partir da porcentagem de água no corte das costelas (Sx, y = 0,46). Verificou-se alta correlação entre a porcentagem de EE no CVz e a porcentagem de EE (R² = 0,95) no corte das costelas, portanto, a equação %EE CVz = 0,9662%EE costelas + 1,5294 pode ser utilizada para estimativa da composição do CVz em EE. O mesmo ocorreu para a porcentagem de cinzas, sendo recomendada a equação %MM CVz = 0,5915%MM costelas + 0,7619 (R² = 0,88). A composição química percentual em água, EE e minerais no corte das 9-10-11ª costelas permitiu estimar com acuidade a composição do corpo vazio.

Prediction equations to estimate the demand of energy and crude protein for maintenance, gain and egg production for laying Japanese quails

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Prediction of intake and average daily gain by different feeding systems for goats

A main purpose of a mathematical nutrition model (a.k.a., feeding systems) is to provide a mathematical approach for determining the amount and composition of the diet necessary for a certain level of animal productive performance. Therefore, feeding systems should be able to predict voluntary feed intake and to partition nutrients into different productive functions and performances. In the last decades, several feeding systems for goats have been developed. The objective of this paper is to compare and evaluate the main goat feeding systems (AFRC, CSIRO, NRC, and SRNS), using data of individual growing goat kids from seven studies conducted in Brazil. The feeding systems were evaluated by regressing the residuals (observed minus predicted) on the predicted values centered on their means. The comparisons showed that these systems differ in their approach for estimating dry matter intake (DMI) and energy requirements for growing goats. The AFRC system was the most accurate for predicting DMI (mean bias = 91 g/d, P < 0.001; linear bias 0.874). The average ADG accounted for a large part of the bias in the prediction of DMI by CSIRO, NRC, and, mainly, AFRC systems. The CSIRO model gave the most accurate predictions of ADG when observed DMI was used as input in the models (mean bias 12 g/d, P < 0.001; linear bias -0.229). while the AFRC was the most accurate when predicted DMI was used (mean bias 8g/d. P > 0.1; linear bias -0.347). (C) 2011 Elsevier B.V. All rights reserved.

Genetic parameters and relationships of heifer pregnancy and age at first calving with weight gain, yearling and mature weight in Nelore cattle

The objectives of the current study were to investigate the additive genetic associations between heifer pregnancy at 16 months of age (HP16) and age at first calving (AFC) with weight gain from birth to weaning (WG), yearling weight (YW) and mature weight (MW), in order to verify the possibility of using the traits measured directly in females as selection criteria for the genetic improvement of sexual precocity in Nelore cattle. (Co)variance components were estimated by Bayesian inference using a linear animal model for AFC, WG, YW and MW and a nonlinear (threshold) animal model for HP16. The posterior means of direct heritability estimates were: 0.45 +/- 0.02; 0.10 +/- 0.01; 023 +/- 0.02; 0.36 +/- 0.01 and 0.39 +/- 0.04, for HP16, AFC, WG, YW and MW, respectively. Maternal heritability estimate for WG was 0.07 +/- 0.01. Genetic correlations estimated between HP16 and WG, YW and MW were 0.19 +/- 0.04; 0.25 +/- 0.06 and 0.14 +/- 0.05, respectively. The genetic correlations of AFC with WG, YW and MW were low to moderate and negative, with values of -0.18 +/- 0.06; -0.22 +/- 0.05 and -0.12 +/- 0.05, respectively. The high heritability estimated for HP16 suggests that this trait seem to be a better selection criterion for females sexual precocity than AFC. Long-term selection for animals that are heavier at young ages tends to improve the heifers sexual precocity evaluated by HP16 or AFC. Predicted breeding values for HP16 can be used to select bulls and it can lead to an improvement in sexual precocity. The inclusion of HP16 in a selection index will result in small or no response for females mature weight. (C) 2011 Elsevier B.V. All rights reserved.

Environmental and genetic factors affecting the weaning-estrus interval in sows

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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)

Lógica Fuzzy para Controle de pH em um Processo Petrolífero

This work proposes the design, the performance evaluation and a methodology for tuning the initial MFs parameters of output of a function based Takagi-Sugeno-Kang Fuzzy-PI controller to neutralize the pH in a stirred-tank reactor. The controller is designed to perform pH neutralization of industrial plants, mainly in units found in oil refineries where it is strongly required to mitigate uncertainties and nonlinearities. In addition, it adjusts the changes in pH regulating process, avoiding or reducing the need for retuning to maintain the desired performance. Based on the Hammerstein model, the system emulates a real plant that fits the changes in pH neutralization process of avoiding or reducing the need to retune. The controller performance is evaluated by overshoots, stabilization times, indices Integral of the Absolute Error (IAE) and Integral of the Absolute Value of the Error-weighted Time (ITAE), and using a metric developed by that takes into account both the error information and the control signal. The Fuzzy-PI controller is compared with PI and gain schedule PI controllers previously used in the testing plant, whose results can be found in the literature.

Estudo avaliativo de um algoritmo genético auto-organizável e multiobjetivo utilizando aprendizado de máquina para aplicações de telecomunicações

This paper presents an evaluative study about the effects of using a machine learning technique on the main features of a self-organizing and multiobjective genetic algorithm (GA). A typical GA can be seen as a search technique which is usually applied in problems involving no polynomial complexity. Originally, these algorithms were designed to create methods that seek acceptable solutions to problems where the global optimum is inaccessible or difficult to obtain. At first, the GAs considered only one evaluation function and a single objective optimization. Today, however, implementations that consider several optimization objectives simultaneously (multiobjective algorithms) are common, besides allowing the change of many components of the algorithm dynamically (self-organizing algorithms). At the same time, they are also common combinations of GAs with machine learning techniques to improve some of its characteristics of performance and use. In this work, a GA with a machine learning technique was analyzed and applied in a antenna design. We used a variant of bicubic interpolation technique, called 2D Spline, as machine learning technique to estimate the behavior of a dynamic fitness function, based on the knowledge obtained from a set of laboratory experiments. This fitness function is also called evaluation function and, it is responsible for determining the fitness degree of a candidate solution (individual), in relation to others in the same population. The algorithm can be applied in many areas, including in the field of telecommunications, as projects of antennas and frequency selective surfaces. In this particular work, the presented algorithm was developed to optimize the design of a microstrip antenna, usually used in wireless communication systems for application in Ultra-Wideband (UWB). The algorithm allowed the optimization of two variables of geometry antenna - the length (Ls) and width (Ws) a slit in the ground plane with respect to three objectives: radiated signal bandwidth, return loss and central frequency deviation. These two dimensions (Ws and Ls) are used as variables in three different interpolation functions, one Spline for each optimization objective, to compose a multiobjective and aggregate fitness function. The final result proposed by the algorithm was compared with the simulation program result and the measured result of a physical prototype of the antenna built in the laboratory. In the present study, the algorithm was analyzed with respect to their success degree in relation to four important characteristics of a self-organizing multiobjective GA: performance, flexibility, scalability and accuracy. At the end of the study, it was observed a time increase in algorithm execution in comparison to a common GA, due to the time required for the machine learning process. On the plus side, we notice a sensitive gain with respect to flexibility and accuracy of results, and a prosperous path that indicates directions to the algorithm to allow the optimization problems with "η" variables