2 resultados para creating environments for interaction
Resumo:
In this study, we investigated the different responses of Spondias tuberosa (umbu) trees, which grow in two different ecological life zones in northeast Brazil: tropical wet and tropical arid ecosystems. We evaluated the responses of plants grown under humid and dry conditions by measuring the photosynthesis, water status, fluorescence parameters, carbon isotopes and antioxidant system activity. The higher net photosynthesis values were recorded contemporaneously with the lower VPD values. The highest internal-to-ambient CO2 concentration and the absence of typical changes in the fluorescence parameters suggested an onset of a nonstomatal limitation in the photosynthesis. Our results showed that umbu plants can adjust their antioxidant activity during the dry season as a defensive strategy against the deleterious effects of water stress. This evidence is supported by the observed modifications in the pigment concentrations, increased accumulation of hydrogen peroxide and malondialdehyde, high levels of electrolyte leakage, increased antioxidant activity, and decreased carbon isotope discrimination in the umbu trees during the dry season. Supported by multivariate analysis of variance, significantly effect of interaction between categorical months of collect and location predicts a strong ?dry season effect? on our dataset. Taken together, our data show that umbu trees grown in a wet tropical environment are more susceptible to drought, as compared with their tropical arid counterparts.
Resumo:
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.