947 resultados para 300602 Tree Improvement (Selection, Breeding and Genetic Engineering)
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Although the citriculture is one of the most important economic activities in Brazil, it is based on a small number of varieties. This fact has contributed for the vulnerability of the culture regarding the phytosanitary problems. A higher number of varieties/genotypes with potential for commercial growing, either for the industry or fresh market, has been one of the main objectives of citrus breeding programs. The genetic breeding of citrus has improved, in the last decades, due to the possibility of an association between biotechnological tools and classical methods of breeding. The use of molecular markers for early selection of zygotic seedlings from controlled crosses resulted in the possibility of selection of a high number of new combination and, as a consequence, the establishment of a great number of hybrids in field experiments. The faster new tools are incorporated in the program, the faster is possibility to reach new genotypes that can be tested as a new variety. Good traits should be kept or incorporate, whereas bad traits have to be excluded or minimized in the new genotype. Scion and rootstock can not be considered separately, and graft compatibility, fruit quality and productivity are essential traits to be evaluated in the last stages of the program. The mapping of QTLs has favored breeding programs of several perennial species and in citrus it was possible to map several characteristics with qualitative and quantitative inheritance. The existence of linkage maps and QTLs already mapped, the development of EST and BAC library and the sequencing of the Citrus complete genome altogether make very demanding and urgent the exploration of such data to launch a wider genetic study of citrus. The rising of information on genome of several organisms has opened new approaches looking for integration between breeding, genetic and genome. Genome assisted selection (GAS) involves more than gene or complete genome sequencing and is becoming an import support in breeding programs of annual and perennial species. An huge information amount can be derivate from genome analysis. The use and benefit of such informations will depend on the genetic basis of the breeding program.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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In Brazil, Eucalyptus grandis Hill ex Maiden is widely used for commercial reforestation, especially for production of pulp, paper and energy. Its genetic variability is being explored in tree improvement programs for over 30 years. The objective of this work was to estimate genetic parameters and compare genetic gains by multi-effects index in a breeding population of E. grandis. Progeny tests were established using open-pollinated seeds from ten provenances ranging from 153 to 160 progenies established in a completely randomized block design in four sites of Sao Paulo State (Anhembi, Avere Itarare e Pratania). At 24 months of age the traits diameter at breast height (DBH), height (ALT) and volume (VOL) were measured. The individual site analyses indicated significant genetic differences among progenies, height genetic variability and the mean progeny heritability (> 0.70). For joint analyses of sites, significant differences in genotype x environmental interaction effects were detected, showing differences of performance of the progenies in different sites. The Itarare site gave high genetic gains, effective size and genetic diversity. The genetic diversity and low effective size are unviable factors; considering that the progeny tests studied should retain adequate levels of genetic variability in order to be transformed in future seedling seed orchards.
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Eucalyptus camaldulensis has great importance in Brazil because of their phenotypic plasticity for different environmental conditions, as soils, altitudes and rainfall. This study is an investigation of a base population of E. camaldulensis from Australia through a progeny test implanted in Selviria, MS. The trial was established in a randomized block design, with 25 families and 60 replications of single tree plots. Genetic parameters for anatomic traits and volume shrinkage were estimated, as well as their correlations with wood basic density. No significant differences among progenies were observed for the traits studied. The additive genetic variation coefficient at individual and among progeny levels ranged from low (0.26%) to high (16.98%). The narrow sense heritability at individual and family means levels also ranged from low (0.01) to high (0.87). This indicates that some traits are under strong genetic control and can be improved by selection. In the present situation, in order to attain the highest genetic gains, the sequential selection among and within progeny would be recommended.
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Lentil is a self-pollinating diploid (2n = 14 chromosomes) annual cool season legume crop that is produced throughout the world and is highly valued as a high protein food. Several abiotic stresses are important to lentil yields world wide and include drought, heat, salt susceptibility and iron deficiency. The biotic stresses are numerous and include: susceptibility to Ascochyta blight, caused by Ascochyta lentis; Anthracnose, caused by Colletotrichum truncatum; Fusarium wilt, caused by Fusarium oxysporum; Sclerotinia white mold, caused by Sclerotinia sclerotiorum; rust, caused by Uromyces fabae; and numerous aphid transmitted viruses. Lentil is also highly susceptible to several species of Orabanche prevalent in the Mediterranean region, for which there does not appear to be much resistance in the germplasm. Plant breeders and geneticists have addressed these stresses by identifying resistant/tolerant germplasm, determining the genetics involved and the genetic map positions of the resistant genes. To this end progress has been made in mapping the lentil genome and several genetic maps are available that eventually will lead to the development of a consensus map for lentil. Marker density has been limited in the published genetic maps and there is a distinct lack of co-dominant markers that would facilitate comparisons of the available genetic maps and efficient identification of markers closely linked to genes of interest. Molecular breeding of lentil for disease resistance genes using marker assisted selection, particularly for resistance to Ascochyta blight and Anthracnose, is underway in Australia and Canada and promising results have been obtained. Comparative genomics and synteny analyses with closely related legumes promises to further advance the knowledge of the lentil genome and provide lentil breeders with additional genes and selectable markers for use in marker assisted selection. Genomic tools such as macro and micro arrays, reverse genetics and genetic transformation are emerging technologies that may eventually be available for use in lentil crop improvement.
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The aim of the present study was to evaluate the genetic correlations among real-time ultrasound carcass, BW, and scrotal circumference (SC) traits in Nelore cattle. Carcass traits, measured by real-time ultrasound of the live animal, were recorded from 2002 to 2004 on 10 farms across 6 Brazilian states on 2,590 males and females ranging in age from 450 to 599 d. Ultrasound records of LM area (LMA) and backfat thickness (BF) were obtained from cross-sectional images between the 12th and 13th ribs, and rump fat thickness (RF) was measured between the hook and pin bones over the junction between gluteus medius and biceps femoris muscles. Also, BW (n = 22,778) and SC ( n = 5,695) were recorded on animals born between 1998 and 2003. The BW traits were 120, 210, 365, 450, and 550-d standardized BW (W120, W210, W365, W450, and W550), plus BW (WS) and hip height (HH) on the ultrasound scanning date. The SC traits were 365-, 450-, and 550-d standardized SC (SC365, SC450, and SC550). For the BW and SC traits, the database used was from the Nelore Breeding Program-Nelore Brazil. The genetic parameters were estimated with multivariate animal models and REML. Estimated genetic correlations between LMA and other traits were 0.06 (BF), -0.04 ( RF), 0.05 (HH), 0.58 (WS), 0.53 (W120), 0.62 (W210), 0.67 (W365), 0.64 ( W450 and W550), 0.28 (SC365), 0.24 (SC450), and 0.00 ( SC550). Estimated genetic correlations between BF and with other traits were 0.74 ( RF), -0.32 (HH), 0.19 (WS), -0.03 (W120), -0.10 (W210), 0.04 (W365), 0.01 (W450), 0.06 ( W550), 0.17 (SC365 and SC450), and -0.19 (SC550). Estimated genetic correlations between RF and other traits were -0.41 (HH), -0.09 (WS), -0.13 ( W120), -0.09 ( W210), -0.01 ( W365), 0.02 (W450), 0.03 (W550), 0.05 ( SC365), 0.11 ( SC450), and -0.18 (SC550). These estimates indicate that selection for carcass traits measured by real-time ultrasound should not cause antagonism in the genetic improvement of SC and BW traits. Also, selection to increase HH might decrease subcutaneous fat as correlated response. Therefore, to obtain animals suited to specific tropical production systems, carcass, BW, and SC traits should be considered in selection programs.
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P>Age at first calving (AFC) measures the entry of heifers into the beef cattle production system. This trait can be used as a selection criterion for earlier reproductive performance. Using data from Nelore cattle participating in the `Program for Genetic Improvement of the Nelore Breed` (PMGRN-Nelore Brazil), bi-trait analyses were performed using the restricted maximum likelihood method, based on an AFC animal model and the following traits: female body weight adjusted to 365 (BW365) and 450 (BW450) days of age, and male scrotal circumference adjusted to 365 (SC365), 450 (SC450), 550 (SC550) and 730 (SC730) days of age. The heritability estimates for AFC ranged from 0.02 +/- 0.02 to 0.04 +/- 0.02. The estimates of additive direct heritabilities (with standard error) for BW365, BW450, SC365, SC450, SC550 and SC730 were 0.36 +/- 0.07, 0.38 +/- 0.07, 0.48 +/- 0.07, 0.65 +/- 0.07, 0.64 +/- 0.07 and 0.42 +/- 0.07, respectively, and the genetic correlations with AFC were -0.38, -0.33, 0.10, -0.13, -0.13 and 0.06, respectively. In the herds studied, selection for SC365, SC450, SC550 or SC730 should not cause genetic changes in AFC. Selection based on BW365 or BW450 would favor smaller AFC breeding values. However, the low magnitude of direct heritability estimates for AFC in these farms indicates that changes in phenotypical expression depend mostly on non-genetic factors.
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Crop modelling has evolved over the last 30 or so years in concert with advances in crop physiology, crop ecology and computing technology. Having reached a respectable degree of acceptance, it is appropriate to review briefly the course of developments in crop modelling and to project what might be major contributions of crop modelling in the future. Two major opportunities are envisioned for increased modelling activity in the future. One opportunity is in a continuing central, heuristic role to support scientific investigation, to facilitate decision making by crop managers, and to aid in education. Heuristic activities will also extend to the broader system-level issues of environmental and ecological aspects of crop production. The second opportunity is projected as a prime contributor in understanding and advancing the genetic regulation of plant performance and plant improvement. Physiological dissection and modelling of traits provides an avenue by which crop modelling could contribute to enhancing integration of molecular genetic technologies in crop improvement. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.
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The objective of this study was to assess the impact of genetic breeding on grain yield, and to identify the physiological traits associated to the increment in yield and their related growth processes, for wheat cultivars grown in Southern Brazil, in the past five decades. Seven wheat cultivars released between 1940 and 1992, were compared for physiological aspects associated with grain yield. Grain yield, biological yield, biomass partitioning, harvest index and grain yield components were also determined. The number of grains per square meter was more affected by plant breeding and was better correlated with grain yield (r = 0.94, p<0.01) than with grain weight (r = -0.39ns). The higher number of grains per square meter was better correlated with the number of grains per spike in the modern cultivars than in the older ones. The genetic gain in grain yield was 44.9 kg ha-1 per year, reflecting important efforts of the breeding programs carried out in Southern Brazil. Grain yield changes, during the period of study, were better associated with biomass production (r = 0.78, p<0.01) than with harvest index (r = 0.65, p<0.01).
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The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.
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The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Restricted breeding seasons in beef cattle lead to censoring of reproductive data. In this paper, age at first conception (AFC) of Nellore females exposed to the sires for the first time between 11 and 16 months of age, was studied aiming to verify the possibility of genetically advance sexual precocity using a survival model. The final data set contained 6699 records of AFC in days. Records of females that did not calve in the next year following exposure to the sire were considered censored (77.5% of total). The model used was a Weibull mixed survival model including effects of contemporary groups, period (fixed) and animal (random). The effect of the contemporary groups on AFC was important (p < 0.01). Heritabilities were 0.51 and 0.76 in logarithmic and original scales respectively. Results indicate that it is possible to genetically advance sexual precocity, using the outcome of survival analysis of AFC as selection criterion. They also suggest that improvements of the environment could advance sexual precocity too, thus an adequate pregnancy rate for farmers could quickly be achieved.
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The objective of this work was to study the effect of selective thinning on the estimates of genetic parameters in progenies of Pinus caribaea var. hondurensis. The progeny test was installed in June 1986, following a 10 × 10, triple square lattice design, containing ten trees in linear plots in 3.0 × 3.0m spacing. Twelve years after the planting, a selective thinning based on Multi-effect index (selection for DBH) was performed, leaving six trees per plot. The assessments were done in four situations: A (before thinning); B (among thinned trees); C (among remnant trees at 13 years of age) and D (two years after the thinning). The following traits were analyzed: total height (H), diameter at breast height (DBH), volume (VOL), stem form (FOR), foxtail (FT), wood density at 1.3 m (WD1) and wood density at the half height (WD2). The thinning led to increase in the estimates of variability among progenies for VOL and decrease for ALT and DBH. There was a high and positive genetic correlation among the growth traits, mainly between DBH and VOL. The latter remained unchanged after thinning. The narrow-sense heritabilities at the individual level, showed a slight increase while at the family mean level had a reduction with the thinning. The estimates of breeding values increased with the thinning. This may lead to an easier identification of the best progenies in further selection.