University of Guelph

About: University of Guelph is a education organization based out in Guelph, Ontario, Canada. It is known for research contribution in the topics: Population & Gene. The organization has 26542 authors who have published 50553 publications receiving 1715255 citations. The organization is also known as: U of G & Guelph University.

The Guelph PIXE software package IV

Abstract: Following the introduction of GUPIXWIN in 2005, a number of upgrades have been made in the interests of extending the applicability of the program. Extension of the proton upper energy limit to 5 MeV facilitates the simultaneous use of PIXE with other ion beam analysis techniques. Also, the increased penetration depth enables the complete PIXE analysis of paintings. A second database change is effected in which recently recommended values of L-subshell fluorescence and Coster–Kronig yields are adopted. A Monte Carlo code has been incorporated in the GUPIX package to provide detector efficiency values that are more accurate than those of the previous approximate analytical formula. Silicon escape peak modeling is extended to the back face of silicon drift detectors. An improved description of the attenuation in dura-coated beryllium detector windows is devised. Film thickness determination is enhanced. A new batch mode facility is designed to handle two-detector PIXE, with one detector measuring major elements and the other simultaneously measuring trace elements.

GGEbiplot—A Windows Application for Graphical Analysis of Multienvironment Trial Data and Other Types of Two-Way Data

Abstract: facilitate the application of the GGE biplot methodology in MET data analysis and in analyses of other types Plant breeding trials produce quantities of data and finding the of two-way data, a Windows application, the GGEbiplot useful information within that data has historically been a major challenge of plant breeding. A recently developed graphical data software, was developed. This paper describes the funcsummary, called GGEbiplot, can aid in data exploration. GGEbiplot tions built in this software and exemplifies their use in is a Windows application that performs biplot analysis of two-way MET data analysis. data that assume an entry tester structure. GGEbiplot analyzes the data and outputs the results as an image, and it also produces an WHAT IS A GGE BIPLOT? interactive show of the data. It allows interactive visualization of the biplot from various perspectives. A multienvironment trial data set, The Concept of Biplot in which cultivars are entries and environments are testers, was used The concept of biplot was first proposed by Gabriel to demonstrate the functions of GGEbiplot. These include but are not limited to: (i) ranking the cultivars based on their performance (1971). The main ideas follow. Any two-way table or in any given environment, (ii) ranking the environments based on matrix X that contains n rows and m columns can be the relative performance of any given cultivar, (iii) comparing the regarded as the product of two matrices: A with n rows performance of any pair of cultivars in different environments, (iv) and r columns and B with r rows and m columns. Thereidentifying the best cultivar in each environment, (v) grouping the fore, Matrix X can always be decomposed to its two environments based on the best cultivars, (vi) evaluating the cultivars component matrices, A and B. If r happens to be 2, based on both average yield and stability, (vii) evaluating the environ- Matrix X is referred to as a rank-two matrix. Each row ments based on both discriminating ability and representativeness, in Matrix A has two values, which define a point in a and (viii) visualizing all of these aspects for a subset of the data by two-dimensional plot. Similarly, each column in Matrix removing some of the cultivars or environments. GGEbiplot has been

Decision support system for agrotechnology transfer: DSSAT v3

Abstract: Agricultural decision makers at all levels need an increasing amount of information to better understand the possible outcomes of their decisions to help them develop plans and policies that meet their goals. An international team of scientists developed a decision support system for agrotechnology transfer (DSSAT) to estimate production, resource use, and risks associated with different crop production practices. The DSSAT is a microcomputer software package that contains crop-soil simulation models, data bases for weather, soil, and crops, and strategy evaluation programs integrated with a ‘shell’ program which is the main user interface. In this paper, an overview of the DSSAT is given along with rationale for its design and its main limitations. Concepts for using the DSSAT in spatial decision support systems (for site-specific farming, farm planning, and regional policy) are presented. DSSAT provides a framework for scientific cooperation through research to enhance its capabilities and apply it to research questions. It also has considerable potential to help decision makers by reducing the time and human resources required for analyzing complex alternative decisions.