4 resultados para Dairy cattle Breeding Australia Statistics Data processing

em Repositório Alice (Acesso Livre à Informação Científica da Embrapa / Repository Open Access to Scientific Information from Embrapa)


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ABSTRACT: Ruminal gases, particularly methane, generated during the fermentative process in rumen, represent a partial loss of feed energy and are also pointed to as an important factors in greenhouse effect. This study aimed at quantifying methane (CH 4) emission rates from lactating and dry cows and heifers, 24 month-old in average, on pasture under Southeast Brazil tropical conditions, using the tracer gas technique, sulphur hexafluoride (SF 6), four animals per category, distributed in four blocks. Measurements were performed in February and June, 2002, with Holstein and Brazilian Dairy Crossbred (Holstein ¾ x Gir (Zebu) ¼), maintained on fertilized Tanzania-grass (Panicum maximum Jacq. cv. Tanzania) and fertilized Brachiaria-grass (Brachiaria decumbens cv. Basilisk) pastures. Heifers of both breeds were maintained on unfertilized Brachiaria-grass to simulate conditions of extensive cattle farming systems. CH 4 and SF 6 levels were measured with gas chromatography. Differences in CH4 emissions were measured (p < 0.05) for genetical groups. Holstein produced more methane (299.3g day?1) than the Crossbred (264.2 g day?1). Lactating cows produced more methane (353.8 g day?1) than dry cows (268.8 g day?1) and heifers (222.6 g day?1). Holstein, with greater milk production potential, produced less CH4 (p < 0.05) per unit of dry matter intake (19.1 g kg?1) than the Crossbred (22.0 g kg?1). Methane emission by heifers grazing fertilized pasture (intensive system) was 222.6 g day?1, greater (p < 0.05) than that of heifers on unfertilized pasture (179.2 g day?1). Methane emission varied as function of animal category and management intensity of production system.

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The objective of this study was to evaluate the effects of inclusion or non-inclusion of short lactations and cow (CGG) and/or dam (DGG) genetic group on the genetic evaluation of 305-day milk yield (MY305), age at first calving (AFC), and first calving interval (FCI) of Girolando cows. Covariance components were estimated by the restricted maximum likelihood method in an animal model of single trait analyses. The heritability estimates for MY305, AFC, and FCI ranged from 0.23 to 0.29, 0.40 to 0.44, and 0.13 to 0.14, respectively, when short lactations were not included, and from 0.23 to 0.28, 0.39 to 0.43, and 0.13 to 0.14, respectively, when short lactations were included. The inclusion of short lactations caused little variation in the variance components and heritability estimates of traits, but their non-inclusion resulted in the re-ranking of animals. Models with CGG or DGG fixed effects had higher heritability estimates for all traits compared with models that consider these two effects simultaneously. We recommend using the model with fixed effects of CGG and inclusion of short lactations for the genetic evaluation of Girolando cattle.

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Background: Copy number variations (CNVs) have been shown to account for substantial portions of observed genomic variation and have been associated with qualitative and quantitative traits and the onset of disease in a number of species. Information from high-resolution studies to detect, characterize and estimate population-specific variant frequencies will facilitate the incorporation of CNVs in genomic studies to identify genes affecting traits of importance. Results: Genome-wide CNVs were detected in high-density single nucleotide polymorphism (SNP) genotyping data from 1,717 Nelore (Bos indicus) cattle, and in NGS data from eight key ancestral bulls. A total of 68,007 and 12,786 distinct CNVs were observed, respectively. Cross-comparisons of results obtained for the eight resequenced animals revealed that 92 % of the CNVs were observed in both datasets, while 62 % of all detected CNVs were observed to overlap with previously validated cattle copy number variant regions (CNVRs). Observed CNVs were used for obtaining breed-specific CNV frequencies and identification of CNVRs, which were subsequently used for gene annotation. A total of 688 of the detected CNVRs were observed to overlap with 286 non-redundant QTLs associated with important production traits in cattle. All of 34 CNVs previously reported to be associated with milk production traits in Holsteins were also observed in Nelore cattle. Comparisons of estimated frequencies of these CNVs in the two breeds revealed 14, 13, 6 and 14 regions in high (>20 %), low (<20 %) and divergent (NEL > HOL, NEL < HOL) frequencies, respectively. Conclusions: Obtained results significantly enriched the bovine CNV map and enabled the identification of variants that are potentially associated with traits under selection in Nelore cattle, particularly in genome regions harboring QTLs affecting production traits.