Overexpression of a tobacco glutathione S-transferase with glutathione peroxidase activity (GST/GPX) in transgenic tobacco (Nicotiana tabacum L.) enhanced seedling growth under a variety of stressful conditions. In addition to increased GST and GPX activity, transgenic GST/GPX-expressing (GST+) seedlings had elevated levels of monodehydroascorbate reductase activity. GST+ seedlings also contained higher levels of glutathione and ascorbate than wild-type seedlings and the glutathione pools were more oxidized. Thermal or salt-stress treatments that inhibited the growth of wild-type seedlings also caused increased levels of lipid peroxidation. These treatments had less effect on the growth of GST+ seedling growth and did not lead to increased lipid peroxidation. Stress-induced damage resulted in reduced metabolic activity in wild-type seedlings while GST+ seedlings maintained metabolic activity levels comparable to seedlings grown under control conditions. These results indicate that overexpression of GST/GPX in transgenic tobacco seedlings provides increased glutathione-dependent peroxide scavenging and alterations in glutathione and ascorbate metabolism that lead to reduced oxidative damage. We conclude that this protective effect is primarily responsible for the ability of GST+ seedlings to maintain growth under stressful conditions.
Plant phenology and yield predictions require precise knowledge of crop-weather relationships. The objective of this research is to identify an inherent biochemical trait that may provide a useful index to link the physical parameters of the environment with the plant biochemistry. We define the term thermal ki11etic wi11dow as the range of plant temperatures at which the apparent Michaelis constant, Km, is at or below 200% of the minimum observed value. For example, the thermal kinetic window of wheat (Triticum aestivum L.) glyoxylate reductase for NADH is between 17.5 and 23°C, and the thermal kinetic window for cotton (Gossypium hirustum L.) is between 23.5 and 32 oc. A linear relationship between the time that foliage temperatures were within their thremal kinetic window and plant biomass production was obtained for both wheat and cotton. Wheat and cotton were within their thermal kinetic windows less than 30% of the season, suggesting that approximately 70% of the growing season is available for increasing crop production either through changes in management practices or genetics. Measurements of foliage temperatures coupled with enzyme kinetics provide a unique description of the biological-physical interactions.
A method for solving boundary value problems (BVPs) is introduced using artificial neural networks (ANNs) for irregular domain boundaries with mixed Dirichlet/Neumann boundary conditions (BCs). The approximate ANN solution automatically satisfies BCs at all stages of training, including before training commences. This method is simpler than other ANN methods for solving BVPs due to its unconstrained nature and because automatic satisfaction of Dirichlet BCs provides a good starting approximate solution for significant portions of the domain. Automatic satisfaction of BCs is accomplished by the introduction of an innovative length factor. Several examples of BVP solution are presented for both linear and nonlinear differential equations in two and three dimensions. Error norms in the approximate solution on the order of 10(-4) to 10(-5) are reported for all example problems.
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