994 resultados para Beef cattle breeds
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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The presence of Cryptosporidium spp. in a cattle herd registered with an outbreak of diarrhea was investigated and the the molecular subtyping of Cryptosporidium parvum was characterized. Fecal samples from 85 Nellore beef cattle (Bos indicus) were collected and examined with Ziehl-Neelsen modified staining method. Fifty-four cattle (63.52%) had Cryptosporidium spp. oocysts in their feces. Fragments of genes encoding the 18S ribosomal RNA subunit and a 60-kDa glycoprotein (gp60) were amplified by nested PCR accomplished in the 11 most heavily parasitized samples, and the amplicons were sequenced. Eight of the 11 analyzed samples were positive for 18S rRNA sequences and identified monospecific infections with C. parvum. Seven samples were positive for gp60 and identified subtypes IIaA15G2R1 (6/11) and IIaA14G2R1 (1/11). This report is the first for C. parvum subtype IIaA14G2R1 in beef cattle in Brazil.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Until 1990, beef cattle production in Brazil was recognized as an enterprise of low investment, low cost of production, as well as an extensive production system that used large land areas to be economically feasible. The situation changed for the Brazilian beef market when the economy stabilized in 1994 and all sectors involved in the beef supply chain were able to predict their associated costs and profits. During the same period, purchasing power of the Brazilian population grew, and as a consequence, consumers began to demand higher quality beef products. This new scenario in the late 1990s and early 2000s has led to more intensive beef production systems in Brazil as well as the need for a greater understanding of how technologies might be applied. As consequence of this evolution, in the last five years, a necessity to increase beef production has occurred. The quality of Brazilian beef has improved compared with beef produced 15 years ago, but continued improvements are needed to achieve excellence in terms of large-scale production of high quality beef, be sustainable over a long period of time, and increase our contribution to global food security.
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A data set of a commercial Nellore beef cattle selection program was used to compare breeding models that assumed or not markers effects to estimate the breeding values, when a reduced number of animals have phenotypic, genotypic and pedigree information available. This herd complete data set was composed of 83,404 animals measured for weaning weight (WW), post-weaning gain (PWG), scrotal circumference (SC) and muscle score (MS), corresponding to 116,652 animals in the relationship matrix. Single trait analyses were performed by MTDFREML software to estimate fixed and random effects solutions using this complete data. The additive effects estimated were assumed as the reference breeding values for those animals. The individual observed phenotype of each trait was adjusted for fixed and random effects solutions, except for direct additive effects. The adjusted phenotype composed of the additive and residual parts of observed phenotype was used as dependent variable for models' comparison. Among all measured animals of this herd, only 3160 animals were genotyped for 106 SNP markers. Three models were compared in terms of changes on animals' rank, global fit and predictive ability. Model 1 included only polygenic effects, model 2 included only markers effects and model 3 included both polygenic and markers effects. Bayesian inference via Markov chain Monte Carlo methods performed by TM software was used to analyze the data for model comparison. Two different priors were adopted for markers effects in models 2 and 3, the first prior assumed was a uniform distribution (U) and, as a second prior, was assumed that markers effects were distributed as normal (N). Higher rank correlation coefficients were observed for models 3_U and 3_N, indicating a greater similarity of these models animals' rank and the rank based on the reference breeding values. Model 3_N presented a better global fit, as demonstrated by its low DIC. The best models in terms of predictive ability were models 1 and 3_N. Differences due prior assumed to markers effects in models 2 and 3 could be attributed to the better ability of normal prior in handle with collinear effects. The models 2_U and 2_N presented the worst performance, indicating that this small set of markers should not be used to genetically evaluate animals with no data, since its predictive ability is restricted. In conclusion, model 3_N presented a slight superiority when a reduce number of animals have phenotypic, genotypic and pedigree information. It could be attributed to the variation retained by markers and polygenic effects assumed together and the normal prior assumed to markers effects, that deals better with the collinearity between markers. (C) 2012 Elsevier B.V. All rights reserved.
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The objective of this study was to investigate, in a population of crossbred cattle, the obtainment of the non-additive genetic effects for the characteristics weight at 205 and 390 days and scrotal circumference, and to evaluate the consideration of these effects in the prediction of breeding values of sires using different estimation methodologies. In method 1, the data were pre-adjusted for the non-additive effects obtained by least squares means method in a model that considered the direct additive, maternal and non-additive fixed genetic effects, the direct and total maternal heterozygosities, and epistasis. In method 2, the non-additive effects were considered covariates in genetic model. Genetic values for adjusted and non-adjusted data were predicted considering additive direct and maternal effects, and for weight at 205 days, also the permanent environmental effect, as random effects in the model. The breeding values of the categories of sires considered for the weight characteristic at 205 days were organized in files, in order to verify alterations in the magnitude of the predictions and ranking of animals in the two methods of correction data for the non-additives effects. The non-additive effects were not similar in magnitude and direction in the two estimation methods used, nor for the characteristics evaluated. Pearson and Spearman correlations between breeding values were higher than 0.94, and the use of different methods does not imply changes in the selection of animals.
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This study was conducted with 35 Nellore beef cattle to determine the effect of supplementation of two levels and two copper sources (organic and inorganic) on metabolism of lipids and cholesterol of meat. The five treatments used were: Control: without copper supplementation, 110 or 140: 10 or 40 mg/kg DM (as Cu sulfate), O10 or O40: 10 or 40 mg/kg DM (as Cu proteinate). In general, the copper supplementation changed the fatty acid profile of meat (p < 0.05), with a higher proportion of unsaturated fatty acids and reduction of saturated fatty acids. There was no effect of supplementation on blood cholesterol and triglycerides, however; in general, there was a reduction in cholesterol concentration in the L dorsi (p < 0.05) compared to the control treatment through the reduction (p < 0.05) in the concentrations of GSH and GSH/GSSG ratio. The Cu supplementation did have an influence on metabolism of lipids. The production of healthier meat is beneficial to public health by reducing the risk of cardiovascular disease. (C) 2012 Elsevier Ltd. All rights reserved.
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Validity of comparisons between expected breeding values obtained from best linear unbiased prediction procedures in genetic evaluations is dependent on genetic connectedness among herds. Different cattle breeding programmes have their own particular features that distinguish their database structure and can affect connectedness. Thus, the evolution of these programmes can also alter the connectedness measures. This study analysed the evolution of the genetic connectedness measures among Brazilian Nelore cattle herds from 1999 to 2008, using the French Criterion of Admission to the group of Connected Herds (CACO) method, based on coefficients of determination (CD) of contrasts. Genetic connectedness levels were analysed by using simple and multiple regression analyses on herd descriptors to understand their relationship and their temporal trends from the 19992003 to the 20042008 period. The results showed a high level of genetic connectedness, with CACO estimates higher than 0.4 for the majority of them. Evaluation of the last 5-year period showed only a small increase in average CACO measures compared with the first 5 years, from 0.77 to 0.80. The percentage of herds with CACO estimates lower than 0.7 decreased from 27.5% in the first period to 16.2% in the last one. The connectedness measures were correlated with percentage of progeny from connecting sires, and the artificial insemination spread among Brazilian herds in recent years. But changes in connectedness levels were shown to be more complex, and their complete explanation cannot consider only herd descriptors. They involve more comprehensive changes in the relationship matrix, which can be only fully expressed by the CD of contrasts.
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The study of population structure by pedigree analysis is useful to identify important circumstances that affect the genetic history of populations. The intensive use of a small number of superior individuals may reduce the genetic diversity of populations. This situation is very common for the beef cattle breeds. Therefore, the objectives of the present study were to analyze the pedigree and possible inbreeding depression on traits of economic interest in the Marchigiana and Bonsmara breeds and to test the inclusion of the individual inbreeding coefficient (F-i) or individual increases in inbreeding coefficient (Delta F-i) in the genetic evaluation model for the quantification of inbreeding depression. The complete pedigree file of the Marchigiana breed included 29,411 animals born between 1950 and 2003. For the Bonsmara breed, the pedigree file included 18,695 animals born between 1988 and 2006. Only animals with at least 2 equivalent generations of known pedigree were kept in the analyses of inbreeding effect on birth weight, weaning weight measured at about 205 d, and BW at 14 mo in the Marchigiana breed, and on birth weight, weaning weight, and scro-tal circumference measured at 12 mo in the Bonsmara breed. The degree of pedigree knowledge was greater for Marchigiana than for Bonsmara animals. The average generation interval was 7.02 and 3.19 for the Marchigiana and Bonsmara breed, respectively. The average inbreeding coefficient was 1.33% for Marchigiana and 0.26% for Bonsmara. The number of ancestors explaining 50% of the gene pool and effective population size computed via individual increase in coancestry were 13 and 97.79 for Marchigiana and 41 and 54.57 for Bonsmara, respectively. These estimates indicate reduction in genetic variability in both breeds. Inbreeding depression was observed for most of the growth traits. The model including Delta F-i can be considered more adequate to quantify inbreeding depression. The inclusion of F-i or Delta F-i in the genetic evaluation model may not result in better fit to the data. A genetic evaluation with simultaneous estimation of inbreeding depression can be performed in Marchigiana and Bonsmara breeds, providing additional information to producers and breeders.
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The objectives of the present study were to characterize and define homogenous production environments of composite beef cattle in Brazil in terms of climatic and geographic variables using multivariate exploratory techniques and to use them to assess the presence of G x E for birth weight (BW) and weaning weight (WW). Data from animals born between 1995 and 2008 on 36 farms located in 27 municipalities of the Brazilian states were used. Fifteen years of climate observations (mean minimum and maximum annual temperature and mean annual rainfall) and geographic (latitude, longitude and altitude) data were obtained for each municipality where the farms were located for characterization of the production environments. Hierarchical and nonhierarchical cluster analysis was used to group farms located in regions with similar environmental variables into clusters. Six clusters of farms were formed. The effect of sire-cluster interaction was tested by single-trait analysis using deviance information criterion (DIC). Genetic parameters were estimated by multi-trait analysis considering the same trait to be different in each cluster. According to the values of DIC, the inclusion of sire-cluster effect did not improve the fit of the genetic evaluation model for BW and WW. Estimates of genetic correlations among clusters ranged from -0.02 to 0.92. The low genetic correlation among the most studied regions permits us to suggest that a separate genetic evaluation for some regions should be undertaken. (C) 2012 Elsevier B.V. All rights reserved.