3 resultados para cross-breeding

em Biblioteca Digital da Produção Intelectual da Universidade de São Paulo


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Surveys were conducted in Brazil, Benin and Tanzania to collect predatory mites as candidates for control of the coconut mite Aceria guerreronis Keifer, a serious pest of coconut fruits. At all locations surveyed, one of the most dominant predators on infested coconut fruits was identified as Neoseiulus baraki Athias-Henriot, based on morphological similarity with regard to taxonomically relevant characters. However, scrutiny of our own and published descriptions suggests that consistent morphological differences may exist between the Benin population and those from the other geographic origins. In this study, we combined three methods to assess whether these populations belong to one species or a few distinct, yet closely related species. First, multivariate analysis of 32 morphological characters showed that the Benin population differed from the other three populations. Second, DNA sequence analysis based on the mitochondrial cytochrome oxidase subunit I (COI) showed the same difference between these populations. Third, cross-breeding between populations was unsuccessful in all combinations. These data provide evidence for the existence of cryptic species. Subsequent morphological research showed that the Benin population can be distinguished from the others by a new character (not included in the multivariate analysis), viz. the number of teeth on the fixed digit of the female chelicera.

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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 general combining ability (GCA), specific combining ability (SCA), and heterosis were studied in a complete diallel cross among fresh market tomato breeding lines with reciprocal excluded. Fifteen genotypes (five parents and ten hybrids) were tested using a randomized complete block design, with three replications, and the experiments were conducted in Itatiba, São Paulo state, Brazil, in 2005/06. The yield components evaluated were fruit yield per plant (FP), fruit number per plant (FN), average fruit weight (FW); cluster number per plant (CN); fruit number per cluster (FC), fruit wall thickness (FT) and number of locules per fruit (NL). Fruit quality components evaluated were total soluble solids (SS); total titratable acidity (TA); SS/TA ratio, fruit length (FL); fruit width (WI); length to width ratio (FL/WI). The data for each trait was first subjected to analysis of variance. Griffing's method 2, model 1 was employed to estimate the general (GCA) and specific (SCA) combining abilities. Parental and hybrid data for each trait were used to estimate of mid-parent heterosis. For plant fruit yield, IAC-2 was the best parental line with the highest GCA followed by IAC-4 and IAC-1 lines. The hybrids IAC-1 x IAC-2, IAC-1 x IAC-4 and IAC-2 x IAC-4 showed the highest effects of SCA. High heterotic responses were found for fruit yield and plant fruit number with values up to 49.72% and 47.19%, respectively. The best hybrids for fruit yield and plant fruit number were IAC-1 x IAC-2, IAC-1 x IAC-4 and IAC-2 x IAC-5, for fruit yield and plant fruit number, the main yield components.