Economic Analysis of Cellulosic Feedstock for Bioenergy in the Texas Rio Grande Valley

Farm Management,

Can 13C Discrimination in Corn (Zea mays) Grain be Used to Characterize Intra-plant Competition for Water and Nitrogen

It is difficult to quantify the mechanism(s) responsible for competition-induced yield loss using traditional experimental techniques. A technique using yield and 13C discrimination (Δ) for wheat, a C3 plant, has been developed to separate total yield loss (TYL) into yield loss due to N (YLNS) and water (YLWS) stresses. The objective of this research was to determine whether the Δ approach could be used in corn, a C4 plant, to separate TYL into YLNS and yield loss due to a combination of water and light stresses (YLWLS). The field study had a factorial design using five corn densities and five N rates and was conducted in western Nebraska in 1999 and 2000. Relationships for YLNS and YLWLS with TYL were derived from only a portion of the yield and Δ data collected in 1999 and validated based on the remaining data collected in 1999 and 2000. In 1999, 20 to 40% of TYL was due to YLWLS, whereas in 2000, a dry year, YLWLS accounted for 60 to 80% of the TYL. Results from using the Δ-based approach were consistent with analysis of variance results. For example, calculated YLWLS values were related to measured YLWLS by the equation: calculated YLWLS = 19 + 0.91 (measured YLWLS) (r 2 = 0.95; P \u3c 0.01). The Δ approach, based on a plant\u27s physiological response to the environment, can be used to separate and quantify competition-induced YLNS and YLWLS in corn

Economic Analysis of Cellulosic Feedstock for Bioenergy in the Texas Rio Grande Valley

Exam paper (Supplementary) for second semester 201

Structure finding in cosmological simulations: the state of affairs

The ever increasing size and complexity of data coming from simulations of cosmic structure formation demand equally sophisticated tools for their analysis. During the past decade, the art of object finding in these simulations has hence developed into an important discipline itself. A multitude of codes based upon a huge variety of methods and techniques have been spawned yet the question remained as to whether or not they will provide the same (physical) information about the structures of interest. Here we summarize and extent previous work of the `halo finder comparison project': we investigate in detail the (possible) origin of any deviations across finders. To this extent, we decipher and discuss differences in halo-finding methods, clearly separating them from the disparity in definitions of halo properties. We observe that different codes not only find different numbers of objects leading to a scatter of up to 20 per cent in the halo mass and Vmax function, but also that the particulars of those objects that are identified by all finders differ. The strength of the variation, however, depends on the property studied, e.g. the scatter in position, bulk velocity, mass and the peak value of the rotation curve is practically below a few per cent, whereas derived quantities such as spin and shape show larger deviations. Our study indicates that the prime contribution to differences in halo properties across codes stems from the distinct particle collection methods and - to a minor extent - the particular aspects of how the procedure for removing unbound particles is implemented. We close with a discussion of the relevance and implications of the scatter across different codes for other fields such as semi-analytical galaxy formation models, gravitational lensing and observables in general