19 resultados para progresso genético


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RESUMO:Com o objetivo de avaliar o comportamento agronômico de genótipos de girassol no Cerrado do Distrito Federal, foram conduzidos ensaios na safrinha dos anos de 2014 e 2015, na estação experimental da Embrapa Cerrados, Planaltina, DF. O delineamento experimental foi de blocos ao acaso com quatro repetições, e foram avaliados 12 genótipos de girassol: HLA 2015, NTC 90, SYN 065, M734, BRS G44, HLA 2014, BRS G45, BRS G43, HLA 2013, HLA 2017, BRS G46, HLA 2016. As características avaliadas foram rendimento de grãos, tamanho do capitulo, peso de mil aquênios, altura de plantas e dias de floração inicial. Diferenças significativas foram encontradas para as características avaliadas. Os genótipos que se destacaram em relação ao rendimento de grãos foram HLA 2014 (3.161 kg ha-1) e a testemunha M743 (3.212 kg ha-1). Além disso, o ensaio do ano 2014 apresentou uma média de rendimento maior (2.829 kg ha-1) e mais precoces (63,10 dias) em relação a 2015. O trabalho permitiu a identificação de materiais promissores para exploração em programas de melhoramento genético. ABSTRACT: Aiming the evaluation on agronomic behavior of sunflower genotypes in the Brazilian savannah, experiments were carried on in the second crop of 2014 and 2015 at Centro de Pesquisa Agropecuária dos Cerrados (Embrapa), Planaltina, DF. A complete randomized block design was used with four replications and 12 genotypes of sunflower were analyzed: HLA 2015, NTC 90, SYN 065, M734, BRS G44, HLA 2014, BRS G45, BRS G43, HLA 2013, HLA 2017, BRS G46, HLA 2016.The evaluated characteristics were grain yield, head, weight thousand achenes, plant height, and flowering time. Significant differences were found in all evaluated characteristics. The genotypes that stood out in seed yield were HLA 2014 (3161 kg ha-1) and M743 (3212 kg ha-1). Besides, the 2014 experiment presented a seed yield average higher (2829 kg ha-1), and earlier flowering (63,10 days) when compared to 2015 experiment. This study allowed the identification of promising materials to explore in breeding programs.

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Abstract: Selection among broilers for performance traits is resulting in locomotion problems and bone disorders, once skeletal structure is not strong enough to support body weight in broilers with high growth rates. In this study, genetic parameters were estimated for body weight at 42 days of age (BW42), and tibia traits (length, width, and weight) in a population of broiler chickens. Quantitative trait loci (QTL) were identified for tibia traits to expand our knowledge of the genetic architecture of the broiler population. Genetic correlations ranged from 0.56 +/- 0.18 (between tibia length and BW42) to 0.89 +/- 0.06 (between tibia width and weight), suggesting that these traits are either controlled by pleiotropic genes or by genes that are in linkage disequilibrium. For QTL mapping, the genome was scanned with 127 microsatellites, representing a coverage of 2630 cM. Eight QTL were mapped on Gallus gallus chromosomes (GGA): GGA1, GGA4, GGA6, GGA13, and GGA24. The QTL regions for tibia length and weight were mapped on GGA1, between LEI0079 and MCW145 markers. The gene DACH1 is located in this region; this gene acts to form the apical ectodermal ridge, responsible for limb development. Body weight at 42 days of age was included in the model as a covariate for selection effect of bone traits. Two QTL were found for tibia weight on GGA2 and GGA4, and one for tibia width on GGA3. Information originating from these QTL will assist in the search for candidate genes for these bone traits in future studies.

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The GxE interaction only became widely discussed from evolutionary studies and evaluations of the causes of behavioral changes of species cultivated in environments. In the last 60 years, several methodologies for the study of adaptability and stability of genotypes in multiple environments trials were developed in order to assist the breeder's choice regarding which genotypes are more stable and which are the most suitable for the crops in the most diverse environments. The methods that use linear regression analysis were the first to be used in a general way by breeders, followed by multivariate analysis methods and mixed models. The need to identify the genetic and environmental causes that are behind the GxE interaction led to the development of new models that include the use of covariates and which can also include both multivariate methods and mixed modeling. However, further studies are needed to identify the causes of GxE interaction as well as for the more accurate measurement of its effects on phenotypic expression of varieties in competition trials carried out in genetic breeding programs.

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The purpose of this study was to identify parents and obtain segregating populations of cowpea (Vigna unguiculata L. Walp.) with the potential for tolerance to water deficit. A full diallel was performed with six cowpea genotypes, and two experiments were conducted in Teresina, PI, Brazil in 2011 to evaluate 30 F2 populations and their parents, one under water deficit and the other under full irrigation.