Experience with the Applegate-Nelson-Metzenberg method of mutant enrichment in high sorbose medium

Experience with the Applegate-Nelson-Metzenberg method of mutant enrichment in high sorbose mediu

Mutants with increased sensitivity to caffeine

Mutants with increased sensitivity to caffein

Guanine-requiring mutants

Guanine-requiring mutant

Estimation Of Reference Crop Evapotranspiration Using Fuzzy State Models

Daily evapotranspiration (ET) rates are needed for irrigation scheduling. Owing to the difficulty of obtaining accurate field measurements, ET rates are commonly estimated from weather parameters. A few empirical or semi–empirical methods have been developed for assessing daily reference crop ET, which is converted to actual crop ET using crop coefficients. The FAO Penman–Monteith method, which is now accepted as the standard method for the computation of daily reference ET, is sophisticated. It requires several input parameters, some of which have no actual measurements but are estimated from measured weather parameters. In this study, we examined the suitability of fuzzy logic for estimating daily reference ET with simpler and fewer parameters. Two fuzzy evapotranspiration models, using two or three input parameters, were developed and applied to estimate grass ET. Independent weather parameters from sites representing arid and humid climates were used to test the models. The fuzzy estimated ET values were compared with direct ET measurements from grass–covered weighing lysimeters, and with ET estimations obtained using the FAO Penman–Monteith and the Hargreaves–Samani equations. The estimated ET values from a fuzzy model using three input parameters (Syx = 0.54 mm, r2 = 0.90) were found to be comparable to ET values estimated with the FAO Penman–Monteith equation (Syx = 0.50 mm, r2 = 0.91) and were more accurate than those obtained by the Hargreaves–Samani equation (Syx = 0.66 mm, r2 = 0.53). These results show that fuzzy evapotranspiration models with simpler and fewer input parameters can yield accurate estimation of ET

Hydration dynamics at fluorinated protein surfaces

Water-protein interactions dictate many processes crucial to protein function including folding, dynamics, interactions with other biomolecules, and enzymatic catalysis. Here we examine the effect of surface fluorination on water-protein interactions. Modification of designed coiled-coil proteins by incorporation of 5,5,5-trifluoroleucine or (4S)-2-amino-4-methylhexanoic acid enables systematic examination of the effects of side-chain volume and fluorination on solvation dynamics. Using ultrafast fluorescence spectroscopy, we find that fluorinated side chains exert electrostatic drag on neighboring water molecules, slowing water motion at the protein surface

Optimization Of Fuzzy Evapotranspiration Model Through Neural Training With Input–Output Examples

In a previous study, we demonstrated that fuzzy evapotranspiration (ET) models can achieve accurate estimation of daily ET comparable to the FAO Penman–Monteith equation, and showed the advantages of the fuzzy approach over other methods. The estimation accuracy of the fuzzy models, however, depended on the shape of the membership functions and the control rules built by trial–and–error methods. This paper shows how the trial and error drawback is eliminated with the application of a fuzzy–neural system, which combines the advantages of fuzzy logic (FL) and artificial neural networks (ANN). The strategy consisted of fusing the FL and ANN on a conceptual and structural basis. The neural component provided supervised learning capabilities for optimizing the membership functions and extracting fuzzy rules from a set of input–output examples selected to cover the data hyperspace of the sites evaluated. The model input parameters were solar irradiance, relative humidity, wind speed, and air temperature difference. The optimized model was applied to estimate reference ET using independent climatic data from the sites, and the estimates were compared with direct ET measurements from grass–covered lysimeters and estimations with the FAO Penman–Monteith equation. The model–estimated ET vs. lysimeter–measured ET gave a coefficient of determination (r2) value of 0.88 and a standard error of the estimate (Syx) of 0.48 mm d–1. For the same set of independent data, the FAO Penman–Monteith–estimated ET vs. lysimeter–measured ET gave an r2 value of 0.85 and an Syx value of 0.56 mm d–1. These results show that the optimized fuzzy–neural–model is reasonably accurate, and is comparable to the FAO Penman–Monteith equation. This approach can provide an easy and efficient means of tuning fuzzy ET models

State of Climate 2011 - Global Ocean Phytoplankton

Phytoplankton photosynthesis in the sun lit upper layer of the global ocean is the overwhelmingly dominant source of organic matter that fuels marine ecosystems. Phytoplankton contribute roughly half of the global (land and ocean) net primary production (NPP; gross photosynthesis minus plant respiration) and phytoplankton carbon fixation is the primary conduit through which atmospheric CO2 concentrations interact with the ocean s carbon cycle. Phytoplankton productivity depends on the availability of sunlight, macronutrients (e.g., nitrogen, phosphorous), and micronutrients (e.g., iron), and thus is sensitive to climate-driven changes in the delivery of these resources to the euphotic zon

In vivo Observation of Tree Drought Response with Low-Field NMR and Neutron Imaging

Using a simple low-field NMR system, we monitored water content in a livingtree in a greenhouse over two months. By continuously running thesystem, we observed changes in tree water content on a scale of halfan hour. The data showed a diurnal change in water content consistentboth with previous NMR and biological observations. Neutron imaging experiments showthat our NMR signal is primarily due to water being rapidly transported through the plant, and not to other sources of hydrogen, such as water in cytoplasm, or water in cell walls. After accountingfor the role of temperature in the observed NMR signal, we demonstratea change in the diurnal signal behavior due to simulated drought conditionsfor the tree. These results illustrate the utility of our system toperform noninvasive measurements of tree water content outside of a temperature controlled environment

Pinning/depinning of crack fronts in heterogeneous materials

The fatigue fracture surfaces of a metallic alloy, and the stress corrosion fracture surfaces of glass are investigated as a function of crack velocity. It is shown that in both cases, there are two fracture regimes, which have a well defined self-affine signature. At high enough length scales, the universal roughness index 0.78 is recovered. At smaller length scales, the roughness exponent is close to 0.50. The crossover length $\xi_c$ separating these two regimes strongly depends on the material, and exhibits a power-law decrease with the measured crack velocity $\xi_c \propto v^{-\phi}$, with $\phi \simeq 1$. The exponents $\nu$ and $\beta$ characterising the dependence of $\xi_c$ and $v$ upon the pulling force are shown to be close to $\nu \simeq 2$ and $\beta \simeq 2$.Comment: 4 pages, latex, and 4 encapsulated postscript figure

A microbiological assay for host-specific fungal polyketide toxins

Genetic analysis of biosynthetic pathways for fungal secondary metabolites depends on availability of efficient and dependable assays for the end products. Some fungal plant pathogens produce secondary metabolites called host-specific toxins. Until recently, all bioassays for these toxins required use of whole plants or plant parts (Yoder 1981 In: Toxins in Plant Disease, Durbin ed., pp. 45-78). Since host-specific toxins, by definition, affect only plants that are susceptible to the toxin-producing fungus, other plants, animals and microorganisms are not sensitive and therefore cannot be used in bioassays